measuring creativity

MEASURING CREATIVITY Proceedings for the conference, “Can creativity be measured?” Brussels, May 28-29, 2009 Edited by Ernesto Villalba

EUR 24033 EN

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Table of Contents Preface.................................................................................................. V Foreword...........................................................................................................................VII Summary............................................................................................................................IX Acknowledgements.......................................................................................................XI President Barroso’s message to the conference ‘Can creativity be measured?’..............................................................................XII Opening speech from the Director-General of the Joint Research Centre, Dr Roland Schenkel..........................................XIV Introductory speech by Jordi Curell Gotor.........................................................XVII Editor’s note..................................................................................................................... XX Organisation of the volume.....................................................................................XXII

Introduction..........................................................................................1 1. Is it really possible to measure creativity?........................................................ 3

Exploring measures at the aggregate level..................................... 15 2. How about composite indicators?....................................................................17

Innovation and creativity................................................................... 25 3. Measuring innovation: the European Innovation Scoreboard...............27 4. Design, Creativity and Innovation: a scoreboard approach ....................41 5. Measuring creativity and innovation based on knowledge capital investment ..........................................................................83 6. Design and construction of the Hong Kong Creativity Index.................91 7. Is it possible to measure scientific creativity? Some first elements of reflection.................................................................... 103

The creative class and entrepreneurship......................................... 113 8. The regional dimension of creativity and innovation............................. 115 9. Linking creativity and entrepreneurship: a description of the joint OECD/Eurostat Entrepreneurship Indicators programme..................... 149 10. Creativity at work in the European Union................................................... 157

Openness and culture....................................................................... 183 11. Tolerance, heterogeneity, creativity, and economic growth................ 185 12. KEA briefing: towards a European creativity index .................................. 191 III


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13. The Roles of Creative Industries in Regional Innovation and Knowledge Transfer — The Case of Austria................................................ 207 14. Contribution of leisure to creativity and innovation of a region......... 221

Exploring measures at the individual level................................... 237 15. Creativity and key competences..................................................................... 239

General Measurement approaches................................................. 243 16. Creativity and personality................................................................................. 245 17. Fostering and measuring creativity and innovation: individuals, organisations and products...................................................... 257 18. Creation in science, art and everyday life: ideas on creativityand its varying conceptions........................................................... 279

Creativity, measurement and education....................................... 303 19. Researching, measuring and teaching creativity and innovation: a strategy for the future..................................................... 305 20. Creative Learning Assessment (CLA): a framework for developing and assessing children’s creative learning........................... 315 21. Promoting creativity in education and the role of measurement...... 327 22. The role of education in promoting creativity: potential barriers and enabling factors........................................................ 337 23. ICT as a driver for creative learning and innovative teaching.............. 345 24. Proposing measures to promote the education of creative and collaborative knowledge-builders ................................. 369

Concluding remarks........................................................................ 391 25. Parsimonious creativity and its measurement........................................... 393 26. A systems perspective on creativity and its implications for measurement......................................................................... 407 27. Closing speech to the conference ‘Can creativity be measured?’........................................................................... 415 28. Concluding remarks............................................................................................ 419 29. Creativity measurement in the European Policy context...................... 421

Annexes............................................................................................ 423 Index................................................................................................. 461

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Preface


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Foreword

Roland Schenkel

Odile Quintin

Dear Reader, The present volume represents an interesting output from the European Year of Creativity and Innovation. It collects key contributions to the conference “Can creativity be measured?”, held in Brussels on May 28 and 29 2009. Around 200 participants and 40 international speakers attended the event. You will find here a mixture of what is available in the field of creativity measurement in different academic communities. Why should we measure creativity? Measurement can be used for the analysis of policies impacting on creativity. Measurement can allow progress to be monitored over time, e.g. in students’ achievements. Finally measurement also allows country comparison, peer review and policy learning in issues such as how education systems can enhance creativity or the relation between creativity and competitiveness at the country or company level. To meet the challenge of this conference, DG EAC teamed up with the Joint Research Centre (JRC). Several EU policies are related to creativity, such as innovation and entrepreneurship, and several colleagues of different European Commission services joined us and the international experts to make this event a success, sharing with us their experiences and insights. During the conference disciplinary boundaries were crossed and an interesting confrontation took place between those studying creativity for the purpose of increasing individual efficiency, those linking it to competitiveness at the country level, and those aiming to understand the role that education systems can play in fostering it. VII


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We are aware that developing measures of creativity for policy is a long-term challenge. We are still far from a clear, uncontroversial measure of creativity, but we have started the journey and it is clear that creativity can, in fact, be measured, both at the societal and at the individual level. We hope that you will enjoy the reading.

Roland Schenkel

Odile Quintin

DG Joint Research Center

DG Education and Culture


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Summary This book collects together contributions from the conference that took place in Brussels on 28 and 29 May 2009 : ‘Can creativity be measured?’ organised by the Directorate-General for Education and Culture (Education and Culture DG) together with the Centre for Research on Lifelong Learning (CRELL) of the Joint Research Centre (JRC). The book provides an overview of two main approaches to the measurement of creativity. Firstly, aggregate level approaches, where different existing statistical indicators can be used as pointers of creativity in a region or a nation. Secondly, it explores some aspects in the measurement of creativity at the individual level. If we want to foster creativity we need to measure it. Without adequate tools to monitor whether or not the policies in place are actually raising the capacity to be creative, there is no way to know that the policies are being effective. The main conclusion of the conference was that, despite its complexity, creativity can be measured. Still, further work is needed to ascertain what aspects of creativity should be measured and for what purpose. The conference constituted the first step in the challenge of measuring creativity in an international, comparative way. The next step would be to build consensus in a common approach to measurement and thus define with all relevant stakeholders’ involvement what the universal, necessary characteristics of creativity are. The present publication contains some proposals for discussion. The European Year of Creativity and Innovation is providing a perfect platform for building this consensus. The challenge of measuring creativity requires clear political will and leadership. It is, necessarily, a long-term, difficult challenge, but there are some reasons for optimism. Firstly, the field of creativity has more than 50 years of history and ‘confluence approaches’ are providing some degree of consensus in the measurement of creativity characteristics. Secondly, there is more and more evidence of the importance of creativity for economic and social success and, thus, the need for politicians to address the issue of creativity and its measurement. Thirdly, the European Year of Creativity and Innovation has been instrumental in the promotion and awareness of the importance of creativity on both economic and social grounds. This provides a window of opportunity to establish a clear political and research agenda on creativity for the coming years. Finally, Europe has a privileged position for building upon its creative capacity; because of the enormous heterogeneity of Europe, there is a tremendous potential for the exchanging of ideas and enhancing possibilities for creative accomplishments. IX


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Acknowledgements Many people have been involved in the preparation of the conference and this manuscript in different ways. Cristina Marcone was the organising force in the Directorate-General for Education and Culture and made the conference the success it was. At Education and Culture DG, we had administrative support from Kirsten MuellerDemos, Mikael Le-Bourhis and Marie-Catherine Guillaumet. The coordinating team of the European Year of Creativity and Innovation, especially Maruja Gutierrez Diaz and Roger O’Keeffee, were always helpful and willing to give support and help, providing valuable ideas and sharing their insights with us. At the JRC Silvia Loffelholz, Eleonora Beghetto, Kornelia Kozovska and Rossana Rosati helped in the arrangement of expert invitations and administrative issues. Angela Pereira helped in the creation of the web page and the blog. Friedrich Scheuermann provided advice and his experience in many organisational and content-related issues. Teamwork provided the logistics and professional help in the organisation of the conference. Monika Walter from Publications Office was fundamental in assisting in the production of this volume. Anders Hingel, Andrea Saltelli and Michela Nardo were crucial in providing useful inputs to the manuscript and support in the whole implementation of the project.

Disclaimer This document does not represent the point of view of the European Commission. The interpretations and opinions contained in it are solely those of the authors.

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President Barroso’s message to the conference ‘Can creativity be measured?’ Directorate-General for Education and Culture Auditorium, Brussels, 28 and 29 May 2009

José Manuel Barroso Ladies and Gentlemen, Creativity is a crucial component of our capacity to innovate. And innovation is a key factor not just to become more competitive but also to improve our quality of life and the sustainability of our development. The progress of societies depends on innovation and creative people: these two elements contribute to collective and individual well-being, ensure long and sustainable economic growth and can provide new answers to the current financial, economic and social crisis. If we just consider societal and environmental challenges such as climate change or ageing society, we clearly see how innovation can and must play a key role. The year 2009 is the European Year of Creativity and Innovation. The main aim of this year is to promote the importance of creativity for innovation and for the development of personal, social and economic competences. We need to create a flexible environment to empower people to continuously learn and adapt to change, to provide them, from early childhood to maturity, with the skills needed to cope with the different, to develop their talent, and transform their ideas into social and economic value. I am confident that Europe is in a strong position to overcome the current difficulties. It has a long creative history of innovation and inventions, a cultural diversity that allowed all of us to live and work together according to common principles and rules. All this makes Europe a place with a great creative potential. It is essential that governments and civil society understand and actively promote creativity and support innovation, especially providing high quality education for all. XII


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We want to respond to this challenge. In fact, education and training are the prerequisites for the promotion of growth and jobs, for stimulating the potential of small and medium-sized enterprises in all sectors, including culture; but they are also essential to create a more sustainable world, in which growth, environment and social dimensions go hand in hand. Today’s conference demonstrates that creativity is at the core of any innovation. But creativity is a complex construct and requires to be studied properly if we want to develop and implement effective policies. With this conference, the Directorate-General for Education and Culture and the Joint Research Centre took up the challenge to verify the feasibility of measuring creativity at a regional, national and individual level. And I am glad that many services of the Commission, experts, country officials, members from international organisations and practitioners are coming to work together on this issue. This is the only way to find an adequate solution to such an important challenge, drawing from the different expertise working together towards a common purpose. I wish you a fruitful and lively conference and all the success in this new undertaking, making sure I will be informed on the conclusions of the debate and its following steps. And, as well, let me encourage you to be as creative as you can.

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Opening speech from the Director-General of the Joint Research Center, Dr Roland Schenkel Dear friends and colleagues, There are many good reasons why creativity is high on the political agenda and why this workshop is timely: It is easy to realise the importance of creativity in addressing the present economic crisis. We need creative solutions in a diverse set of sectors: financial management at macro- and micro-level, creating new or improved competitive advantages in order to make up for lost markets and to increase employment. Creativity lies at the centre of the knowledge triangle of research, education and innovation established by our Lisbon strategy. Culture and art cannot flourish without creativity. In the social and political realm, creativity needs to be fostered by our educational and training systems that endow our societies with active and prepared citizens. Today’s knowledge societies compete for the best and most creative brains available worldwide. In short, it is easy to agree on the importance of creativity. So in order to establish polices that promote creativity, it is necessary to establish in a scientifically sound way how creativity can be measured in relation to the different vertices of the knowledge triangle: yy How is creativity supporting innovation? yy How is creativity used in the research process? yy How can creativity-related skill be taught and promoted in our education system? To answer these questions, Europe needs quality measures of creativity that grasp the complexity of the phenomenon — these measures need to be developed in a European context, to allow monitoring of progress and policy learning among countries and society at large. For this reason the JRC and Education and Culture DG have organised this event in the framework of the activities of CRELL, the Center for Research on Lifelong Learning, based on Indicators and Benchmarks, which our two services jointly operate.

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CRELL was created in 2005 following a council conclusion to increase the Commission’s research capacity in terms of the development of new indicators in the field of education and training. In this short period it has provided more and more scientific and technical support for knowledge-based policies in education and training. CRELL is a clear example of the strengths of the collaboration between research and policy. The European Commission is committed to evidence-based policy. I am particularly pleased that this conference, and this brave attempt to investigate such a complex concept as creativity, takes place in the European Year of Creativity and Innovation Mrs Quintin and I are not alone in this undertaking: several services of the European Commission such as the Directorates-General for Enterprise and Industry, Research, Eurostat and Regional Policy, are here today, joining forces with us to provide their expertise and initiatives related to the measurement of aspects of creativity. The present undertaking is a long-term challenge that can only be achieved by drawing from different expertise. My colleagues from the Directorate-General for Enterprise and Industry (Enterprise and Industry DG) — working in cooperation with other services including the JRC — have been successful, in providing a sound measure of technological innovation in Europe. The European Innovation Scoreboard, which is published every year, has drawn on the expertise of the JRC in applied statistics and composite indicators. Later this year a new version of the regional innovation scoreboard will be produced under the responsibility of Enterprise and Industry DG, also with the support of the JRC applied statisticians. Other strands of Commission research may have a bearing on our new undertaking: yy The Directorate-General for Research (Research DG) has a long history of the use of indicators for monitoring purposes in the area of science and technology: an example is the publication of the research ‘Key Figures’ earlier this year. yy Regional Policy DG is developing more and more the capacity to bring together regions and learn from each other through the use of indicators. It develops together with JRC a regional competitiveness index with an innovation component. yy Eurostat, the European Statistical Office, makes all these indicators possible. yy JRC has made considerable progress in cooperation with international organisations such as the Organisation for Economic Cooperation and Development XV


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(OECD), the United Nations (UN) and the World Bank, to develop metrics based on composite indicators for policy assessment in the field of knowledge-based economy, governance, environmental performance and others. From our experience in developing complex measures for policymaking using indicators, we know that it is necessary to create consensus and take into account stakeholders’ opinions and views. Therefore, the JRC has established a ‘virtual’ forum to start the debate on how to achieve a measure of creativity that can be used across cultures. We invite all present to accept this challenge and enter this debate through our website. I am confident that JRC will learn from this challenging undertaking and that the Commission will succeed in setting the standard in creativity measurement. I wish you success in your work during these two days.

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Introductory speech by Jordi Curell Gotor Directorate-General for Education and Culture When we were preparing this conference, together with CRELL, we thought we were bold to dare to address the topic of ‘Can creativity be measured?’ Honestly, we only expected a handful of experts to accompany us on this long journey towards the establishment of indicators on creativity. I am therefore particularly pleased to see so many of us gathered together here for this conference, which is one of the events of the European Year for Creativity and Innovation. The success of the conference is undeniable; we have even had to provide a listening room for those who haven’t found a place in the auditorium. I was therefore thinking why there were so many of us here today? And I think it’s because we can possibly agree on three things: yy First, we all agree innovation in Europe is essential. yy Innovation has been very high in the European agenda in the last decade. It has a prominent place in the Lisbon strategy. And it has been addressed in its multifaceted aspects. Most particularly by the directorates-general responsible for the knowledge triangle. yy Enterprise and Idustry DG has launched the EU broad innovation strategy. Research DG has been active in promoting innovation in research. We, Education and Culture DG have been promoting in education and training. Let me mention a few of these initiatives: The European Institute of Innovation and Technology (EIT) has to feature high on any ranking of innovation-related activities. By bringing together higher education institutions, research organisations and business-innovation, the EIT aims at boosting EU’s capacity to transform education and research into tangible commercial innovation opportunities. In the short time since its creation, it has made progress and has already been able to launch the first call for Knowledge and Innovation Communities (KICs) — highly integrated partnerships aimed at establishing and innovation chain, from innovation to economic impact. The first KICs will operate in the areas of climate change and mitigation, sustainable energy and the future of information and communication technology.

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I will also refer to skills and competences. We know that pre- or post-crisis, we cannot compete in the global economy on cost: we can only stay competitive by investing in our people and their capacity to innovate. The implementation of the key transversal competences has a key role to play. Its unique combination of solid basic skills such as literacy, numeracy, and information and computing technology (ICT) and traversal soft ones, social, communicative, entrepreneurship creativity and motivation, offers the opportunity to equip our fellow citizens with the right tools to face an increasingly rapidly evolving world. And this in all segments of the labour market, both at the top end, where high skills are required and at the other end, where low-skilled jobs need to be filled. And the importance of innovation and creativity in education and training systems has become even clearer earlier this month, when the Council adopted the new strategic framework for cooperation in education and training 2020. Four strategic objectives have been identified for the education and training systems to achieve in these next 10 years. Alongside more traditional ones such as making lifelong learning and mobility a reality, improving the quality and efficiency of education and training, and promoting equity social cohesion and active citizenship; we find another one: enhancing creativity and innovation, including entrepreneurship, at all levels of education and training. We need to ensure that education systems develop creativity and education, and we need innovation in reforming education systems. The second point where I think we could all agree is that creativity constitutes a prime source of innovation. Or, to put it differently, that creativity is the mother of innovation. Creativity, like innovation, is about making new connections. The essential difference is that innovation goes beyond creativity to show economic viability, turning creative ideas into products or services. But I would dare to say that without creativity there is no innovation The third point where we definitely agree is on the importance of measuring creativity. As it is often said, what is not measured is at risk of not being done. We are all committed to evidence-based policy and therefore we are committed to coming up with the tools which will allow us to measure the progress (or the lack of progress) towards achieving this objective of enhancing creativity. And that is why this conference is an important and challenging one: we understand measuring is a comparison of an unknown quantity to a known and ‘canonised’ unit. This activity, measuring, is particularly difficult when we are dealing with creativity. The essence of creativity is to produce something that has not existed before, so the biggest problem is comparison, which is why it is difficult to quantify. XVIII


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And that is precisely the aim of this conference: to advance in the understanding of different ways of measuring creativity and assess the feasibility of measuring creativity in an international comparative manner. We expect two outcomes: one, in the more or less short-term, to propose a feasible measure of creativity using existing statistical sources; and two, in a more long-term perspective, we aim to identify the necessary steps to conduct a large-scale survey to measure individual creativity. After presenting different Commission initiatives on indicators and its relationship to creativity, the conference will look into creativity indicators at the aggregate level to continue with the possible approaches to measuring creativity at the individual level. Participants from very different backgrounds are gathered here together. Academics, researchers, national and European officials. People coming from the three sides of the knowledge triangle as well as people bringing in other dimensions — cultural and regional. And people coming from Europe and beyond. This is the strength of this event. And it is not by chance that it is one of the events that takes place during de European Year for Creativity and Innovation. The year aims at changing certain attitudes towards the positive direction, by: raising public awareness; providing information on good practices; and stimulating policy debate and research. That is exactly what this conference is about. I would like to thank all the speakers and participants. And more particularly the JRC and its Director-General, Mr Schenkel, who has played a major role, together with the Education and Culture DG, in organising this event. I wish you a creative two days at this conference which is only a milestone, albeit an important one, on the long road to effectively measuring creativity.

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Editor’s note The job of an editor has a feeling of a censor and a critic. As a censor, the editor can suggest changes to a paper, the deletion of a part or even the rejection of a contribution all together. As the critic, one can comment on other people’s work and establish a dialogue with the author that might lead to the modification of the article. I, however, have purposefully decided to leave the door relatively ‘open’, not censuring or arguing with the authors’ views too much, in order to allow for different views. The volume is therefore, heterogeneous. As if it were a metaphor of creativity, our search for a solution to the challenge of measuring creativity needs of high level of tolerance, openness and a preference for heterogeneity. This publication brings together different perspectives related to the measurement of creativity. Some articles present concrete examples of already established measures, other articles present tools that are being developed and others are more speculative and present ideas to take forward. All point towards the issue of measuring specific aspects of society or individuals in relation to creativity. All of them together show the complexity of the field and indicate possible ways to be used for measuring specific aspects related to creativity. This complexity and heterogeneity should not set us back in the challenge. The attempt of understanding better what creativity is and how it could be promoted further requires that we are able to monitor the effectiveness of the policies in place. To this end, it is necessary to have adequate tools for measurement, stable over time and comparable across countries. It is the role of the stakeholders, future users of a measurement of creativity, to decide which of the plethora of approaches presented here is the most adequate for their interests, and what way to take in order to conquest the challenge. Measuring creativity is surely a difficult task, even more so if it has to be done in an international, comparative way; but ‘difficult’ is not synonymous with ‘impossible’. There are more than 50 years of research in creativity that have shown the way, it is time to ‘stand on shoulders of giants’ and take a step further to make creativity a central aspect of the educational systems in Europe. The present book collects most of the presentations to the conference and has some additions from people who could not participate. The book will be complemented by a special issue of the Creativity Research Journal, ready for the beginXX


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ning of 2010, which will be more academically oriented and contain contributions from other authors. I have enjoyed tremendously the editing of this volume and the preparation of the conference and I am glad that so many renowned experts in the area have contributed to this publication. It is on their shoulders that we rest to make this challenge achievable. I hope you enjoy the reading. Ispra, September 2009 Ernesto Villalba

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Organisation of the volume The present book reflects the structure of the two days’ conference. In order to make the life of the reader easier, the book is divided into sections and subsections that permit better navigation through the publication. After a short introduction that gives a general overview of the whole publication, the book is divided into three main sections. The first section deals with approaches related to the measurement of creativity at the aggregate level. It is divided into three subsections dealing with: measurement of innovation, the creative class and entrepreneurship and with measures related to openness, cultural industries and leisure. The second part of the book provides approaches related to the measurement of creativity at the individual level. This is divided into two subsections. The first subsection presents general approaches that have been used or that are being developed for measuring of creativity in individuals. Some of the authors of this subsection will be contributing with more extended and academic articles to the special issue of the Creativity Research Journal, available at the beginning of 2010. The second subsection delves into the measurement aspect of creativity specifically related to education and training. The third section of the book ‘Concluding remarks’ presents contributions from scholars and policymakers on their views to go forward. The first section starts with an article by Andrea Saltelli and Ernesto Villalba, from the Directorate-General Joint Research Center (JRC) presenting the different steps to be taken to create complex measures using composite indicators. This constitutes an essential guide if an aggregate measure of creativity is to be developed. Then, a series of articles related to the measurement of innovation are presented. Hugo Hollanders, from UNU-MERIT, Maastricht University, presents the European Innovation Scoreboard (EIS), constructed for the Directorate-General for Enterprise and Industry of the European Commission. The EIS has been instrumental in creating policy debate in the last years on innovation policies in Europe. Building on a similar approach, the fourth chapter, by Hugo Hollanders and Adriana van Cruisen, presents a recently developed tool to monitor aspects of creativity, design and innovation. The next chapter presents a new, different approach to the measurement of creativity that is being developed in the UK by the Office for National Statistics (ONS) in collaboration with the University of Warwick and Imperial College London. John Bacon-Shone and Desmond Hui present, afterwards, the Hong Kong creativity index, addressing the difficulties in constructing such a composite indicator. The section closes with some reflections from Johan

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Stierna, from the Directorate-General for Research on some specific indicators related to scientific creativity. The next subsection within the aggregate measurement approaches relates to aspects of the creative class and entrepreneurs. Lewis Dijkstra presents specific indicators used by Regional Policy DG in the sixth progress report on economic and social cohesion, including an indicator on core creative class. Manfred Schiemann presents the Entrepreneurial Indicator Program, developed by the OECD and Eurostat to capture entrepreneurial activity in advanced economies. The subsections close with Edward Lorenz and Bengt-Aake Lundval’s article on an alternative method to measure the creative class. The third and last subsection for this part relates to measurement of openness and cultural aspects at an aggregate level. Tiemann and his group at the Elon University, US, present their measurement of heterogeneity and how it relates to creativity within the framework a social capital approach. Philip Kern and Jan Runge, from the KEA European Affairs present an index developed for the Directorate-General for Education and Culture of the European Commission specifically capturing cultural aspects related to creativity. Simone Kimpeler and Peter Georgieff from the Fraunhofer Institute Systems and Innovation Research argue on the importance of creative industries in Austria for the development of innovation and creativity. The subsection closes with an article by Manuel Cuenca Cabeza and his team, presented by Cristina Ortega at the conference that brings in the importance of leisure and its measurement for creativity and innovation. The second part of the book aims to present different approaches to the measurement of creativity at the individual level and starts with the introductory speech made by Hélène Clark, director of Directorate B at the Education and Culture DG of the European Commission linking creativity to the key competences for lifelong learning adopted by the Council. The subsection on general measurement approaches begins with the article by Rosa Aurora Chávez-Eakle, director of the Washington International Centre for Creativity. She gives an overview of different tools that have been used to measure creative personality. David Cropley, from the University of South Australia, presents a new tool to measure creativity for innovation in organisations. The following chapter, written by Yrjö-Paavo Häyrynen from the University of Joensuul and visiting professor at Helsinki University, presents an overview of the research on creativity measurement, with special emphasis on a European perspective. Petra Mª Pérez Alonso-Geta, from the University of Valencia, shows the development of a new tool base on a meta-analysis of creative studies. XXIII


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The following subsection is centred on education and the measurement of creativity in educational contexts. Sue Ellis shows the Creative Learning Assessment developed by the Center for Literacy in Primary Education in the UK that has been successfully implemented in some schools in inner city London. Marilyn Fryer, from The Creativity Center in the UK, argues on how teachers’ attitudes and their perceptions of creativity are linked to their preferred ways of teaching and assessment. Pasi Sahlberg, from the European Training Foundation, presents some barriers and enablers for the promotion of creativity in education. The role of ICT for creativity in education is outline in the article of Anusca Ferrari, Romina Cacha and Yves Punie, from the Institute of Prospective Technological Studies (IPTS) of the Joint Research Center. And finally, François Taddei and Livio Riboli Sasco, from the Centre de Recherches Interdisciplinaires in France, advocate for the promotion of creativity in education through knowledge-sharing. The last section of the book, Concluding remarks, starts with the contribution of Mark Runco, recently appointed E. Paul Torrance Endowed Professor of Creative Studies and Gifted Education at the University of Georgia, Athens, US. Professor Runco presents his view on parsimonious creativity, addressing some tactics to tackle the challenge of measuring it. This is followed by an article by Mihaly Csikzentmihalyi, Distinguished Professor of Psychology in the School of Behavioural and Organisational Sciences at Claremont Graduate University and Co-Director of the Quality of Life Research Center, where he presents his systems model of creativity and outlines some steps to be taken if Europe is serious about measuring creativity. These two more academic articles are followed by Hélène Clark and Andrea Saltelli’s closing speeches presented at the conference. Finally, Anders Hingel, head of Unit of Analysis and Studies at Education and Culture DG, main co-organisers of the conference with CRELL, presents his views on the conference and the future of measuring creativity in Europe. The volume is closed with some annexes related to the conference in order to provide more information for those that could not attend.

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Introduction


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Is it really possible to measure creativity?

1. Is it really possible to measure creativity? A first proposal for debate

Ernesto Villalba (Center for Research on Lifelong Learning (CRELL) Directorate-General Joint Research Center, European Commission) There is nothing like a dream to create a future. Victor Hugo

Introduction This chapter summarises the main points considered at the conference ‘Can creativity be measured?’ organised by the Directorate-General for Education and Culture (Education and Culture DG) together with the Centre for Research on Lifelong Learning (CRELL) of the Directorate-General Joint Research Centre of the European Commission (JRC) that took place in Brussels on 28 and 29 May 2009. The conference was organised within the activities of the 2009 European Year of Creativity and Innovation. The Year aims to raise awareness of the importance of creativity and innovation for personal, social and economic development; to disseminate good practices; to stimulate education and research, and to promote policy debate on related issues. Within this framework, the conference was set up to stimulate debate around the scientific measurement of creativity. The conference had around 200 participants and almost 40 speakers and panellists. The aim of the conference was to advance the understanding of different ways of measuring creativity and to assess the feasibility of measuring creativity in an international, comparative manner. The intended outcomes of the conference were twofold: firstly, a short-term objective was to provide a list of a limited number of indicators, at national or regional level, covering the various dimensions of creativity (derived from 3


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Ernesto Villalba

existing statistical sources); secondly, in a more long-term perspective, the conference aimed to identify the available tools and necessary steps to be made to conduct a large-scale survey to measure individual creativity.

Towards a working definition of creativity The conference purposefully did not provide a definition of creativity. Since the ultimate objective of the conference was to study the possibilities available for measuring creativity, providing a definition of the phenomena would have restricted the views and approaches. By trying to look at a plethora of approaches to creativity and extracting common elements in all of them, it should be possible to establish a preliminary, working definition of creativity that will permit to go forward and that will describe the essential elements of a measurement model. The approach is ‘inductive’ in the sense that it is expected that a definition will ‘emerge’ from the different approaches. The focus here is on creativity as a human and social characteristic. It occurs in all the different areas of human activity, and across content domains, that is to say it is not restricted to arts but occurs in all domains of human activity. This is, thus, a universal, democratic understanding of creativity. It is universal because it maintains that there are some necessary characteristics in creativity common across all creative actions and democratic because it maintains that everyone has the potential to be creative. The definition points towards an everyday or ‘little c’ creativity. The type of creativity that makes people adapt to the constantly changing environment, reformulate problems, and take risks to try new approaches to problems. The defining characteristics of originality and adequacy to the situation require a point of reference. Csikszentmihalyi (1996, 27) has shown that ‘big C’ creativity, ‘the kind that changes some aspects of the culture, is never only in the mind of a person’. For him, creativity can be observed only in the ‘interrelations of a system made up of three main parts’: domain, field and person (ibid). The domain refers to the cultural system, which consists of a system of symbolic rules and procedures. The field includes all the gatekeepers of a given domain. The field determines what products are regarded as creative. Finally, the person is the actor in the system that actually uses the symbols in a giving domain and which ideas and products are chosen as innovative. The application of Csikzentmihalyi’s thesis to a working definition of ‘little “c” creativity’ is not straight forward. But it is clear that creativity, even the ‘little “c”’, requires a complex combination of factors to appear that relate to the field, the domain and the person. Originality and adequacy will depend on the reference taken (the person, the peers in a domain, the whole history of a field …). 4


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Can creativity be measured? Aggregate and individual level approaches Thus, the question ‘Can creativity be measured?’ purposefully general, is instrumental in looking for a common understanding of what creativity is, what components and aspects of it can be measured and how. This question constitutes a first step, and needs the political will and adequate infrastructure to be taken further. In terms of creativity measurement, one can distinguish between two general and rather different approaches: psychological and aggregate-level approaches (see Villalba, 2008 for further explanation). While the psychological approach is based in the, more or less, traditional psychometric models interested in individual level characteristics, the aggregate approach comes from a different set of disciplines interested in creative aspects of society. This paper will briefly discuss the two approaches: at aggregate and individual levels. Before looking into how to measure creativity, it is necessary to touch upon the reasons on the relevance of measuring creativity for policy purposes

Why should creativity be measured? At least since the relaunch of the Lisbon strategy in 2005, innovation has been one of the main pillars of cooperation in Europe. The Communication of March 2008 (European Commission, 2008a, 2) puts it simply: ‘Europe needs to boost its capacity for creativity and innovation for both social and economic reasons.’ The decision of the European Council in establishing 2009 as the European Year of Creativity and Innovation put the emphasis to the fore. Innovation is defined by the Oslo manual as: ‘The implementation of a new significantly improved product (good or service), or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations’ (OECD and Eurostat 2005, 146). As such, any innovation requires of some short of creativity. There can be creativity without innovation, but innovation cannot appear if there is no creative generation at some point. In general terms, creativity is seen as a precondition to innovation. The first step into any innovation is a creative idea, even if the idea is to copy someone’s idea into your organisation. Another reason for the importance of creativity comes from education. It is usually argued that educational systems are not providing young people with the tools to adapt adequately to the knowledge-based economy. As Sir Ken Robinson (June, 2006) has pointed out, “We are educating children for jobs that do not exist yet, using 5


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technologies that have not been invented yet, in order to solve problems that haven’t even been identified yet.” He maintains that creativity is as important in education as literacy and should be treated with the same status. As Sternberg (2006), Robinson expressed that creative potentials might be suppressed in children, because of society and educational systems that tend to encourage conformity. Thus, educational systems have to change in order to be more proactive in the promotion of creativity. Education needs to accommodate to the new demands of a society that requires flexible workers, lifelong learners ready to adapt to a constantly changing environment. It is not only necessary to discover the talents of each individual and to get each individual to the maximum of his or her capacity, it is also necessary to give young people the adequate set of tools to exercise creativity. In addition, R. Florida (2002a) has postulated that creativity is the new source of wealth. He has been instrumental in the promotion of creativity. For him, there is a paradigm shift in lifestyle from the old economy to a new economy driven by creative individuals. For him, economic growth is determined by the capacity of an area to attract talented individuals. “Places,” he says, “create the ecosystem for creativity to be nurtured; such places are characterised by three Ts: Technology, Tolerance and Talent” (Florida, 2002a, 2002b, 2002c, 2004). The importance of measuring comes from the necessity to provide adequate policies for the promotion of creativity for the reasons stated above. The challenge of measuring creativity adequately is at the core of being able to take adequate decisions and propose initiatives. It is not enough to put in place policies for the promotion of creativity, it is also necessary to monitor if the policies in place are or not being effective. The following section will explore the measurement of creativity at an aggregate level. That is to say, the characteristics of society associated with creativity. Later on, the focus will be in measurement approaches that point out to individual level creativity.

How to measure creativity in society: measuring creativity at the aggregate level The different initiatives that exist to measure creativity at the aggregate level are, indeed, not measuring creativity levels per se. They are measuring the contextual characteristics that could be associated with creativity, or the different aspects in society that can be regarded as the output of a creative process (such an innovation). The different sets of indicators, therefore, constitute pointers of aspects that can be related to creativity. 6


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Different existing initiatives related to different measurements, such as innovation or entrepreneurship, have several indicators in common, and could be unified into a composite index on creativity. To find the most adequate set of indicators for creativity will require further analysis of the relationships between variables and a wide debate on the importance of each indicator for the relevant stakeholders. One clear agreement in terms of pointers of creativity refers to innovation. Innovation is without doubt connected to creativity. Indicators on innovation can be regarded as pointers to assess the capacity of a region or a nation to deliver creative products. In this way, determinants associated with innovation (such as the European Innovation Scoreboard (EIS) enablers or firm activities) could be seen as contributors to the creative capacity of a place. The different indicators on innovation show the tendency of a place to produce valuable economic outcomes derived from its creative capacity. From EIS, mainly the ‘throughputs’, innovators and some of the indicators of economic effects could be regarded as those specifically pointing to the creative products (See Chapters 4 and 13). This could be regarded as a set of indicators pointing to creative performance of a region. It refers to the indicators that are showing evidence of creative behaviour. At the moment, it is mainly possible to find indicators used in innovation indexes that pertain to creative products, processes or organisational innovations (see Chapters 3 and 4). In addition, entrepreneurship performance could be used as an extra pointer of the creative capacity of a region or a nation (see Chapter 9). Inclusion of measures on knowledge capital outcomes (See Chapter 5) and of cultural production (see Chapter 12) might provide also alternative, valuable measures. The Hong Kong creativity Index (see Chapter 6), for example, uses among others, the per capita production of newspapers, books, music and films. Other important creative outcomes that could be possible to grasp refer to the number of publications or the ‘normalised citation impact’ that have been used to measure quality of research activities in university (see Chapter 7). In addition, ideally, the set of indicators on products would also have aspects related to social innovation and innovation in the public sector. In these areas, however, there is a need to further develop an adequate set of indicators and methodologies to collect them. The output indicators referred above are the consequence of a milieu that encourages and enables creativity. This environment that encourages creativity requires of tolerance (Florida, 2002a, 2002b), heterogeneity (see Chapter 11), having adequate cultural amenities (Chapter 12) and should provide a good array of leisure possibilities (see Chapter 14). In addition, technology plays a crucial role as a tool to improve creative performance (see Chapter 23). Relating specifically to science and technology indicators, the web-based hyperlinks between universities, and the share of doctoral 7


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candidates with citizenship from another country, might provide useful measures of heterogeneity (see Chapter 7). The so-called creative industries, might play a crucial role, not only in producing creative outputs, but in acting as a catalysts for creativity in the economy, and hence, innovation, in a region or nation (see Chapter 13). The chapters referred above, provide different sets of interesting indicators to use in the development of indexes to capture the creative environment. A different set of indicators would refer to the people and mainly to those who are participating in jobs that allows them to use their creative potential. Florida uses the creative class indicator (see, for example, Chapter 8) to capture the ‘talent’ of a region. Within the creative class, human resource in science and technology indicators could be included (see Chapter 7). Considering only the percentage of the population in the creative class, however, might be misleading and not adequate for cross-national comparisons, as Lorenz and Lundval have shown in Chapter 10. Measurements more specifically related to work organisation and tasks at work might prove more adequate to capture actual possibilities to perform creative activities at work. In addition, in close connection to indicators on people are indicators referring to the level of education of a population. These measures, traditionally associated with human capital, show the level of skills of the population, but would have to be developed further if we want to really assess creative capacity. It is, thus, interesting to explore further the role of education in creativity.

The role of education Education plays a crucial role in relation to creativity. Firstly, education gives the opportunity to discover and enhance people’s talents. It should also provide the basis to place the seed in individuals that will encourage them to be more creative, take risk and be lifelong learners, constantly updating their knowledge and skills. Education plays also an important role in the update and maintenance of adequate levels of skills and knowledge in the workforce. Indicators that can point to the enhancing capacity of education and training systems towards creativity, however, might not be easy to find. So far, the indicators referred to above on ‘people’, such as the creative class, only provide complementary information to the traditional human capital indicators (e.g. educational attainment of the population). At regional and national levels, it is difficult to find indicators that say more about the creative capacity of a country than the educational attainment of a population. A focus on artistic education might be a possible approach (see Chapters 4 and 12) but this will provide only a partial view of creativity associated with the arts. 8


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The Program for International Student Assessment (PISA) of the OECD could also provide some information on the creative capacity of 14-year olds. At high levels of performance (levels 5 or 6 in PISA), the test items usually require sophisticated ways of providing an adequate answer to complex problems. Some of these items might require high levels of creativity. However, this short of indicators will provide similar results that PISA, providing only the amount of high performing individuals in maths, science and literacy, but it would not provide an account of the most highly creative (Villalba, 2008). Further, a measure of this type might provide an elitist view of creativity, where only few can be seen as creative. Despite these difficulties, it would be beneficial to search for information in the educational systems that will tell us how much creativity is being enhanced. Preliminary analysis (as shown in Chapter 4) shows that creative education will enhance creative performance. However, as the authors point out: ‘For truly understanding the linkages between creativity, design and innovation new data are needed to construct more precise and direct indicators’. Without a survey specifically designed to capture aspects associated with the enhancement of creativity, such as the possibility of students to take risks, entrepreneurial education or teacher’s attitudes towards creativity, it would be difficult to achieve adequate indicators.

Measuring creativity at the individual level The previous sections have shown different sets of possible indicators for the creation of a composite indicator that would address aspects associated with creativity. However, these are only features of society that are associated with creativity. We would need actual evidence on the creativity levels in the population to know if, in fact, these aspects that seem to be incrementing people’s creative capacity are actually doing so. This is, of course, a very complicated challenge and there might be several reasons not to pursue such a project. But, specifically in education, such a project might be worthwhile. Assessment of creativity in education might be beneficial in providing an adequate incentive to the system to actually promote creativity, and to be able to monitor progress. Creativity needs to be measured taking into account its complexity and multidimensionality. Certain indicators at the aggregate level presented above can be seen as proxies of domain and field aspects. For example, cultures that are more heterogeneous and that permit the creative actor to be exposed to a major number of ideas will more likely foster creativity. One lesson to be learned from the system theory of creativity is that a creative product appears always associated with a specific domain and field. This does not 9


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imply that the creative process or the creative person cannot have some universal characteristics, but that the manifestation of it is necessarily associated with a field and a domain; that is to say, its manifestation is in a specific time, in a specific field. It is needed, thus, to identify certain aspects of the person and the process that are universal and common to all creative actions or as Runco puts it in this volume (see Chapter 25), to determine a parsimonious definition of creativity. First, certain measures would necessary refer to the creative person. That is to say, what personality traits are necessary in a universal definition of creativity? As in the case of a composite indicator, there is a need to build consensus around these characteristics. Rosa Aurora Chavez-Eakle (see Chapter 16) shows an overview of different methods to assess personality traits on creativity. Research seems to show that creative personality encompasses: autonomy, flexibility, preference for complexity, openness to experience, sensitivity, playfulness, tolerance of ambiguity, risk-taking and risk tolerance, intrinsic motivation, self-efficacy and wide interest and curiosity (see also Runco 2007). To what extent all these characteristics are necessary is a matter of debate and further research is probably needed, but there is enough information available to build consensus on some specific characteristics as a starting point for measuring. Secondly, since creativity is a capacity to produce, it would be necessary to look at the creative process. Some necessary characteristics of the process seem to be an adequate problem identification and specification, together with the capacity to recognise what ideas are worth. In addition, certain styles of thinking are most likely to be creative: tolerance to ambiguity and openness are also important in the creative process. Perez Alonso-Geta (see Chapter 19) concludes from its meta-analysis of creative literature that the creative process involves: divergent thinking, analytical skills and critical thinking. Thirdly, the most crucial characteristic of any definition of creativity presented above is that it involves something original and adequate. That something is original involves that it is different from the norm, it can be original in relation to the person, the peer group, the domain, etc. (see e.g. NACCCE, 1999). The problem of determining the originality could be dealt with by fixing the reference level of what constitutes ‘new’ or ‘original’. Does it have to be considered new-to-the-person, to-the-field, to-the-domain? In a large, international survey, because of the large number of respondents, it would be possible to establish measures of ‘originality’ in some of the responses to items, since one can get an estimate of the average responses. Techniques developed in developments of divergent thinking (see Runco, 2009). In the case of adequacy, the other crucial aspect of creativity, it would be necessary to have a reference to the problems presented when measuring creativity, that is to say, the items constructed through consensus. 10


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This approach to creativity measurement, compartmentalising its different aspects, is in line with the approaches marked by Sternberg and Lubart (1999) as ‘confluence approaches’. The main idea consists in being able to use multiple views on creativity together where different components must converge for creativity to occur. What a measurement model would do is, in fact, to search for what components are strictly necessary and which are not. In this sense, Runco’s (see Chapter 25) proposal of a parsimonious approach to creativity might be valuable. Runco proposes a hierarchical framework for the study of creativity dividing the different aspects of creativity into creative potential and creative performance. The former refers to the person, process and press (pressure of the environment), while the later to the products and persuasion. For him, creative potential would be much more worthy to study, since it would provide the highest returns on investment. Lubart (May, 2009) showed at the conference a multivariate approach to creativity. He considers cognitive, personal/motivational, affective and environmental aspects to study creativity in organisations. These different aspects constitute a profile that can be contrasted to the tasks (creative tasks) that the individual has to pursue. In this sense, it is not only necessary to create an environment that promotes creativity and that people become more creative, it is also important that the task matches the creative profile of the individual, otherwise, there will not be a creative output. Csikzentmihalyi’s (see Chapter 26) concerns on the theoretical bases of a measure for creativity are also noteworthy in this introduction. It is necessary to decide if creativity is an individual characteristic or it is necessarily the ‘post hoc social attribution to new ideas and objects that find favour in the marketplace of ideas or of commodities’. Assuming the latter, it would require measurement models that would include both, individual and aggregate level measurements. That is to say, we would have to assess individuals in specific aspects of creativity and the environment in how inductive to creativity it is.

Steps towards a large-scale survey The previous sections have shown that there are ways for measuring specific aspects of creativity, both at individual and aggregate levels. Now, it is important to ask how would it be possible to assess creativity in a large, cross-national survey? What would be the necessary steps? The complexity of creativity certainly makes it an enormous challenge, and it would be difficult to predict the actual outcome of such project. However, there are certain reasons for optimism in pursuing such a challenge measurement task. First, the field shows a certain degree of convergence towards a systemic approach to creativity, where different aspects must coexist for creativity to occur. This 11


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is important because, as Csikzentmihalyi points out (see Chapter 26), it will be a task of agreeing in a specific approach to creativity and what aspects are essential and necessary. In this way, the very first step for creating a measurement of creativity is in agreeing in its definition. A definition that involves the aspects presented above would have to be discussed in depth by the relevant stakeholders that would be interested in using the measure for decision-making. The next step would be the definition of a framework. A framework will determine what is and what is not considered creative. In this way, it might be more practical to focus at the beginning on one specific domain to launch a survey on creativity, or to focus on a specific aspect of it. To measure universal creativity might require too long a process of determining the specific aspects that are actually necessary. But this might be achievable in a given field and domain. The main challenge, from a confluent approach point of view, would be that there are several aspects that have to be measured at the same time, and this might be extremely costly. It might be adequate to focus in a specific aspect of creativity, such as the creative potential, or the creative personality traits. Several contributions in this book show specific examples of how creativity has been measured in specific contexts (see Chapters 17, 20, 21). They might provide preliminary insights in the ways to go further. With a reference framework well defined and built on consensus, it should be possible to create items to measure the agree characteristics of creativity. The instrument would have to be tested and adapted to the national contexts in the European Union. The tool would have to be pretested as a pilot study in as many different countries as possible. If the results of these pilot tests were satisfactory and the tool is good enough, it would be possible to start a full-scale process that would provide a picture of creative levels in society, or in the target population. A project of these characteristics would require strong leadership and a clear vision and structure in terms of resources. The potential of such a survey is enormous, since it would provide a picture of one of the most important aspects of human nature. If we can understand how to nurture it and improve it, using a value-loaded reference framework, it is clear that it will lead to positive outcomes for society in general.

The need of debate and consensus It is important to insist on the importance of a wide debate about the framework, both for aggregate and individual level measures. As stipulated in the handbook of composite indicators (Nardo et al., 2008), the first step in the creation of a complex measure is always determining what is to be measured and create consensus on how. 12


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The different stakeholders interested in using the measure have to be active in determining its most important aspects. In addition, the measurements derived from this framework, would have to be contrasted with other approaches referring mainly to innovation, and demonstrate a value added in terms of allowing for more informed political actions. One aspect that would most likely benefit from a composite indicator on ‘creativity’ would be social innovation. Social innovation is not usually considered in traditional innovation indexes. It is, however, of crucial importance, especially for policymakers. An index on creativity would be necessarily closer to social innovation, since it would have to widen the scope of creative products, or innovations, to include outputs that are not associated with market and production. In addition, an index related to creativity might provide a way to research into innovation in the public sector, and specifically in education. In terms of creativity measurement at the individual level, the study of the creativity of students will surely provide important insights in how to improve the quality of education and training systems. It would help to adapt the education and training systems to provide the adequate skills for the 21st century. This book aims at being a concrete point of departure for the debate.

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References Csikszentmihalyi, M. (1996). Creativity. New York: HarperCollins. Florida, R. (2002a) The rise of the creative class... And how it’s transforming work, leisure, community and everyday life. New York: Basic Books. Florida, R. (2002b), The economic geography of talent, Annals of the Association of American Geographers, 92 (4), pp. 743-755. Florida, R. (2002c). Bohemia and economic geography, Journal of Economic geography 2:55-71. Florida, R. (2004) The rise of the creative class... And how it’s transforming work, leisure, community and everyday life. 2nd edition. New York: Basic Books. Lubart, T. (May, 2009). The multivariate model an its measurement implications. Presentation at the Conference organised by DG EaC and CRELL, “Can creativity be measured”, 28-29 May, Brussels, Belgium. NACCCE (National Advisory Committee on Creative and Cultural Education) (1999). All Our Futures: Creativity, Culture and Education. London: DfES. Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A. and Giovannini, E. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. Paris: OECD. OECD and EUROSAT (2005). Oslo Manual: Guidelines for collecting and interpreting innovation data (third edition). Paris: OECD. Robinson, K. (June, 2006). Do schools kill creativity? Talk at the TED: Ideas worth spreading conference. Retrieved August 2008 from: http://www.ted.com/index. php/talks/ken_robinson_says_schools_kill_creativity.html. Runco, M. A. (2007). Creativity. Theories and Themes: Research, Development and Practice. Amsterdam: Elsevier. Runco, M. A. (2009) Divergent thinking. In B. Kerr (Eds.), .Encyclopedia of Giftedness, creativity, and talent. London: Sage Publications. Sternberg, R. J. (2006). The nature of creativity, Creativity Research Journal, 18 (1), 87-98. Sternberg, R. J. and Lubart, T. I. (1999), The concept of creativity: Prospects and Paradigms. In R.J. Sternberg (ed.) Handbook of Creativity, pp. 3-16. London: Cambridge University Press. Villalba, E. (2008). On Creativity: Towards an Understanding of Creativity and its Measurements. JRC Scientific and Technical Reports, EUR 23561. Luxemburg: Office for Official Publications of the European Communities.

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Exploring measures at the aggregate level


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How about composite indicators?

2. How about composite indicators?

Andrea Saltelli and Ernesto Villalba (Directorate-General Joint Research Center, European Commission)

Abstract Composite indicators can be useful to measure complex, multidimensional concepts such as competitiveness, good governance, environmental stewardship, as well as creativity. This chapter outlines some of the methodological issues related to the creation of composite indicators and the necessity of using sensitivity and robustness analysis to assess the quality of the measure obtained.

Introduction Knowledge-based policies are made possible by the availability of high quality statistical information and analytic tools to draw inference-based data. In the increasingly complex policy landscape of the 21st century with conflicting constituencies and stakeholders at several levels of government, new measures are needed. An example of this process was the creation of the Open Method of Coordination in the European Union. As Pisani-Ferry and Sapir (2006) have pointed out: ‘(…) civil societies learn from the experience of others. Such policy learning can be enhanced by initiatives that facilitate cross-country comparison and benchmarking’. Composite indicators can serve this purpose particularly well. An indicator is a ‘quantitative or a qualitative measure derived from a series of observed facts that can reveal relative positions (e.g. of a country) in an area’ (Nardo et al., 2005, 13). A composite indicator is formed when individual indicators are compiled into a single index, on the basis of an underlying model of the multidimensional latent concept that is being measured (ibid.). Composite indicators encapsulate a series of different dimen17


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sions to form a single measure that represents complex phenomena. It can provide a picture of a complex phenomena, possibly understandable for the public and nontechnical people.

Composite indicators and the media It is not surprising, thus, that media usually gives a lot of attention to this sort of indicator and uses them regularly. The journal The Economist, for example, uses different rankings — mostly created by The Economist’s own intelligence unit — to inform their readers about the housing market, country risk, education opportunities, and so on, including the celebrated Big Mac Index1. Composite indicators, such as the Global Competitive Index2 or the Human Development Index3, tend to create great media attention, often forcing the political establishment to react. The following quote taken from the The Economist, 16 October 2008, shows well the use of diverse range of statistical products in the media: The 1.3m people of Mauritius love to prove famous people wrong. On independence from Britain in 1968, pundits such as a Nobel Prize-winning economist, James Meade, and a novelist, V. S. Naipaul, did not give much of a chance to this tiny, isolated Indian Ocean island 1 800 km (1 100 miles) off the coast of east Africa. Its people depended on a sugar economy and enjoyed a GDP per person of only USD 200. Yet the island now boasts a GDP per person of USD 7 000, and very few of its people live in absolute poverty. It once again ranks first in the latest annual Mo Ibrahim index, which measures governance in Africa. And it bagged 24th spot in the World Bank’s global ranking for ease of doing business — the only African country in the top 30, ahead of countries such as Germany and France. How does it pull it off? (The Economist, October 2008, emphasis added). It is interesting to see how official demographic, geographic and national accounts (GDP) data are mixed, in the same breath, with composite indices created by international organisations. The two indices mentioned (Ease of Doing Business and Mo Ibrahim index of African governance), are composite indicators, and provide league tables that rank countries, regions or cities in a specific issue, providing a tool for ‘naming and shaming’ on specific issues, thus holding politicians accountable for the outcomes of policy. As discussed in the Pisani-Ferry and Sapir paper just mentioned ‘peer pressure and benchmarking should be integral parts of the political proc1 2 3

See The Economist web pages under ‘Market and Data’, ‘Rankings’. http://www.weforum.org/en/initiatives/gcp/index.htm http://hdr.undp.org/en/humandev/

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ess’; further the use of these indices benefit the democratic process, ‘as it empowers national electorates to review the performance of their own governments and it helps focus the debate on key areas of underperformance’.

Analysis via composite indicators In recent years, the use of composite indicators has increased tremendously. In 2005, a simple search in Google Scholar for ‘composite indicators’ would return little less than 1 000 entries. The same entry in June 2009 will give more than 4 000 entries. This provides an indication of the increasing interest, not only for policymaking, but also for research and analysis purposes. Because of the capacity of composite indicators to summarise complex constructs in a single number, they allow for country performance comparison with other variables. This might provide insight into the relationship between variables. The OECD, for example, has shown that differences in product market regulation (measured via a composite indicator by the same name) can explain divergent productivity trends (Cotis and Duval, 2007). The relationship between progress and fertility is compared in the journal Nature using the Human Development Index (Myrskylä et al., 2009). In a similar fashion Richard Florida discussed the importance of the creative class for economic growth of regions using composite indices.

Composite indicator methodology As discussed above a composite indicator can be used (and is in general used) for both analysis and advocacy (Saltelli, 2007). Thus it is not infrequent for these measures to be the subject of heated controversies (Saisana et al, 2005, 2007). The creator of one such measure is thus better advised to make sure that her work is of a sufficient quality to withstand scrutiny. A series of steps for the creation of a composite indicator have been proposed in an handbook by the OECD and the JRC (Nardo et al., 2008). This handbook is the result of five years of preparation, two round of consultation with OECD high level statistical committee and was finally endorsed March 2008. The 10 steps involve: yy Step 1: Developing a theoretical framework: it is necessary to create a sound theoretical framework and definition of the phenomena that is to be measured. In the creation of the framework, it is recommended that all stakeholders interested in the results of the measurements have an active participation. This also involves the decision on the structure and subgroups of indicators, that is to say, the pillars of the index. 19


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yy Step 2: Selecting indicators: once the definition is agreed and established, with a framework and a clear structure, it is necessary to find the adequate variables (or indicators) that will compose the index. Availability of the data is necessarily a crucial aspect for selection. It will also be necessary to know the source of the data and its strengths and weaknesses. Also in this process, it will be desirable to have input from the relevant stakeholders, in order to establish a list variables which are relevant to them. yy Step 3: Imputation of missing data: it is likely that not all the data will be available for all the countries. There are different techniques of inputting missing values, but it is important to establish the reliability of the imputed missing data. yy Step 4: Multivariate analysis: once there is a full list of indicators, with no missing data, then it is necessary to establish a multivariate analysis of the indicators chosen to see how the different indicators relate to each other. yy Step 5: Normalisation of data: before it is possible to aggregate the data into a single measure, it is necessary to put each indicator in a similar metric. There are a range of different techniques for normalisation, each with its specific characteristics. These include: ranking, z scores, and min-max normalisation among others. yy Step 6: Weighting and aggregation: unless the weights are determined using statistical arguments, they are established by the proponents of the index, and imply value judgements. Through weights one determines the importance of each of the indicators and pillars that create the composite indicator. Weights and aggregation procedure together determine the ‘model’ on which the index is built. yy Step 7: Robustness and sensitivity: each of the previous steps required a series of decisions and techniques. Each of these choices is a source of uncertainty. yy Step 8: Back to the details: it is important that once a holistic picture is obtained, the analysis turns back to the individual components to understand the results. In other words, what are the indicators that have more importance for each of the units of analysis, how do they affect the overall index? yy Step 9: Association with other variables: this can be used to test the explanatory power of a composite. Simple cross-plots are often very informative in showing relationship between variables, especially at country level. yy Step 10: Presentation and dissemination: it is important that the composite indicator is presented adequately to the end-users, policymakers, media, and 20


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other stakeholders. An organisation without the resources, the authority and the legitimacy to do this may have difficulty in developing a successful composite index.

The case of creativity In the case of creativity, the conference addresses mainly steps 1 and 2. There is a need to build consensus on what creativity is and establish a framework that can allow for the choice of indicators. The conference and this publication, as the introduction showed, present a variety of indicators that could be considered for the creation of a composite indicator on creativity. However, as discussed during the conference, further debate is needed on the importance of the different aspects of creativity and their relationship. Further, a composite indicator on creativity would have to prove that it can contribute to make policies and complement existing indicators in science and technology or innovation. Richard Florida proposed a creativity index (2002, 2004). As it is often the case with composite indicators, the index has attracted a large amount of attention. The index has inspired politicians to change urban policies. Media have also been sensitive to the issue, especially because of the inclusion of the controversial ‘gay index’ to measure aspects of tolerance. Finally, the index has created a wide debate in academic circles, both in economics and urban development (Glaeser 2004, Peck, 2005, Hoyman and Faricy, 2009). The structure and composition of Florida’s Creativity index is given in Table 1. Florida underlined the importance of numbers to provide advocacy for his arguments — although he also maintained that ‘(…) in retrospect, I probably could have written this book using no statistics at all’. Numbers, he maintains, are important because they show relative magnitude to the phenomena in focus and can confirm or disprove the assumptions put forward. In addition, numbers can ‘point towards connections you did not see before’ (Florida, 2004, 327). He was also aware of the need for a sound methodology: ‘None of these benefits accrue, however, unless the numbers themselves are sound and carefully derived’. Florida’s Creativity Index is a ‘composite measure that is based on four indices for the most current year available: the Innovation Index, High-Tech Index, the Gay Index and the Creative Class’ (Florida, 2004, 334). Table 1 presents the different indexes used for Florida to create the Creativity Index.

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Table 1: Richard Florida’s Creativity Index Technology

Patented innovation per capita (version 2002), Average annual patent growth from 1990 to 1999 (version 2004)

Innovation Index:

High-Tech Index

Developed by DeVol et al. (1999)

Metropolitan high-tech industrial output as a percentage of total US high-tech industrial output Percentage of region’s own total economic output that comes from high-tech industries compared to national percentage

Tolerance

Gay Index

Developed by Graves et al. (2000)

Fraction of all artistically creative people (includes authors, designers, musicians, composers, actors, directors, painters, sculptors, artist, printmakers, photographers, dancers, artists, and performers) who live in a given metropolitan area divided by the fraction of the total US population who live in that area

Bohemian Index

Racial Integration Index Talent

Fraction of all US gay people who live in a given metropolitan area divided by the fraction of the total US population who live in that area

(version 2004 only)

Creative Class Index

Census track ethnicity composition in relation to the composition of the whole MSA (metropolitan statistical area) Percentage of creative occupations of total employed

Florida does not explicitly present his normalisation technique, nor how exactly the composite was formed. Thus, it is not completely clear what method was used for normalisation in order to combine different indices. An analysis of his work would seem to imply that a ‘ranking’ normalisation techniques is used (see Nardo et al., 2008). Florida gives the best performing region the maximum scored for each of the indexes: innovation, technology, tolerance and talent; and then adds the different scores using equal weighting. Regions are then ranked according to their total scored. In the 2004 edition, the Creativity Index is expressed as a percentage of the maximum possible score of the groups being compared (in the 2004 edition, 268 regions in the US). That is to say, a perfect score in all three Ts (a region being first in all indexes of the 268 regions) would have a score of 1. Florida tries to present the indexes and its composition in a clear, transparent manner, short of technicalities. Unfortunately, this makes it very complicated to understand how the composites where formed. Further, he failed to evaluate the consequences of any of the assumptions he made. For example, a different normalisation technique could have given a different result, because of a different treatment of outliers. In a similar way, different aggregation methods could have led to different re22


12/9/2009 2:46:03 PM


sults. In other words, without analysing the sources of uncertainness it is not possible to conclude how robust his index is, and how useful it might be for policy purposes. The fact that a region ranks high in the three indexes would have to be tested against the assumptions made when constructing the different indexes. Despite these technical concerns, the index is and has been used to support policy, especially urban policies (see e.g. Peck, 2005). Without a clear understanding of how robust the indexes developed are, most of the conclusions drawn from the indexes cannot be properly supported, and decisions might be taken in an inadequate direction, or with unexpected consequences. A European measure of creativity should, without doubt, follow the steps described in the handbook discussed above and use, as much as possible, consensus for its construction and determination of components. It’s another story as to whether this index is useful for Europe. As argued elsewhere in this workshop different existing measures of human and social capital might already capture relevant measures of creativity.

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References Hoskins, B., Villalba, E., Van Nijlen, D. and Barber, C. (2008). Measuring civic competence in Europe: A composite Indicator based on IEA Civic Education Study 1999 for 14 years old in School. JRC Scientific and Technical Reports 23210 EN. Luxembourg: OPOCE. Glaeser, G. L. (2004). Review of Richard Florida’s The rise of the creative class. Retrieved last August 2008, from: http://www.creativeclass.org. Hoyman, M. and Faricy, C. (2009). It Takes a Village: A Test of the Creative Class, Social Capital and Human Capital Theories, Urban Affairs Review, 44 (3), 311-333. Cotis, J. P. and Duval, R. (2007). Competitiveness, Innovation and economic growth, Second OECD World Forum on “Statistics, Knowledge and Policy”. Istanbul, Turkey, 27-30 June 2007. Retrieved last, August 2009 from: http://www.oecd.org/dataoecd/20/52/38859413.pdf Myrskylä, M., Kohler, H.-P., and Billari, F.C. (2009). Advances in development reverse fertility declines, Nature, 460(6), 741-743 Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A. and Giovannini, E. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. Paris: OECD. Aghion, P. , Dewatripont, M., Hoxby, C. and Sapir, A. (2008). Higher aspirations: An agenda for reforming European universities, Bruegel Blueprint Series N.5, 2008. Brussels: Bruegel. Peck, J. (2005). Struggling with the creative class, International Journal of Urban and Regional Research, 29 (4), 740-770. Pisani Ferry, J. and Sapir, A. (2006). Last exit to Lisbon. Bruegel, Retrived last August 2009 from: http://www.bruegel.org/ Saisana, M., D’Hombres, B., Saltelli, A. (Forthcoming). Rickety Numbers: Volatility of university rankings and policy implications. Submitted to Research Policy. Saltelli, A. (2007). Composite indicators between analysis and advocacy, Social Indicators Research, 81(1), 65-77. Wilkinson, R. and Pickett, K. (2009). The Spirit Level, Why More Equal Societies Almost Always Do Better. London: Allen Lane Publisher.

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Innovation and creativity


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The European Innovation Scoreboard

3. Measuring innovation: the European Innovation Scoreboard

Hugo Hollanders (UNU-MERIT, Maastricht University)

Introduction The Lisbon European Council of 2000 established the strategic goal for the European Union to become the most competitive and dynamic knowledge-based economy in the world by 2010, with sustainable economic growth, more and better jobs, and greater social cohesion. Innovation has been recognised to be at the heart of the Lisbon process and the Lisbon Council asked the European Commission to develop and annually publish a European Innovation Scoreboard (EIS) to ‘track and benchmark the relative innovation performance of EU Member States’ (EC, 2009). Since the 2000 pilot report, eight full versions of the EIS have been published1. Each annual EIS report includes a benchmarking of the Member States’ most recent innovation performance, an analysis of the improvement of that performance over time, a detailed comparison of the performance of the EU against that of its main competitors — Japan and the US — and summaries of the results of the EIS thematic reports accompanying the EIS studying specific innovation topics in detail. In this chapter, first we will briefly discuss the rationale and use of innovation scoreboards in Section 2. Section 3 will then focus on the methodology and results of the EIS and Section 4 concludes.

1

All EIS reports are available from the EC’s PRO INNO Europe website: http://www.proinno-europe.eu/metrics

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Hugo Hollanders

Innovation Scoreboard: indicators and policy use 2 Innovation indicators are comparable measures of innovative activities derived from statistics on innovation activities. Since the mid 1990s there has been an increase in the number of available innovation indicators due to new statistics derived from improved methods of analysing existing statistics on R & D and patents and from newly developed innovation surveys as the Community Innovation Survey (CIS)3. These innovation indicators are used to construct innovation scoreboards whose main purpose is to assist policy by summarising a range of (diverse) innovation indicators. Following the increase in innovation indicators, the number of innovation scoreboards has increased significantly and well-known examples of such scoreboard are the OECD’s Science, Technology and Industry Scoreboard (OECD, 2007), the World Economic Forum’s Global Competitiveness Report (World Economic Forum, 2008) and the EC’s European Innovation Scoreboard (European Commission, 2009)4. It is crucial to meet the following criteria in selecting the indicators to be included in these scoreboards: the indicators should be of comparable importance as measures of the drivers of innovation activity; the indicators should be based on reliable statistics; the indicators should hold their value over time; and the indicators should be of relevance to medium and long-term policy issues. In practice it is difficult, if not impossible, to meet all four criteria as, for example, indicators are derived from both public and private sources and national differences on how firms respond to the questions in the innovation surveys will lead to differences in the quality and comparability of these statistics between countries. Many scoreboards use composite indicators to summarise the statistical information from these indicators in a single number providing an easy-to-grasp summary statistic of a country’s innovation performance. The construction of composite indicators is sensitive to the applied normalisation procedure — which ensures that indicators that measured using different units are comparable — and the selection of the weight of each indicator to the composite indicator. The Handbook on Constructing Composite Indicators provides detailed guidelines for constructing composite indicators (Nardo et al, 2008). The use of composite indicators has a.lso been criticised for not accurately summarising innovation performance in a single number (e.g. Grupp and Mogee, 2004). 2 3

4

This section is an abridged version of the discussion on innovation scoreboards in Arundel and Hollanders (2008). The Community Innovation Surveys (CIS) are a series of surveys executed by national statistical offices throughout the European Union since 1992. The harmonised surveys are designed to give information on the innovativeness of firms, sectors, regions and countries. Aggregate statistics at national and sectoral level are published by Eurostat, the Statistical Office of the European Union Archibugi et al. (2009) provides a recent more detailed overview of different innovation scoreboards.

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Innovation scoreboards can have high policy relevance for the following reasons. First, these scoreboards can act as an ‘early warning’ system for potential problems at national level. Of course, this requires very recent and up-to-date statistical indicators. Second, scoreboards can track changes in strengths and weaknesses over time. This requires that these scoreboards are constructed annually using the same methodology ensuring full comparability over time. Third, scoreboards can be used to attract the interest of policy(makers) and as such can help build consensus among governments, public institutions and private firms to introduce policies to improve the innovativeness of firms. In particular raising interest by European policymakers in innovation has perhaps been the most important contribution of the EC’s European Innovation Scoreboard (EIS). The following section will discuss this scoreboard in detail.

European Innovation Scoreboard (EIS) History, indicators and composite innovation index The EIS was developed by MERIT and SPRU as part of the European Commission’s Trend Chart project. The first version in 2000 covered 17 European countries and used 16 indicators; it was one of the first scoreboards to use results from innovation surveys with four indicators from the CIS. Full versions of the EIS have been published annually from 2001 and, following a number of small and sometimes larger revisions, the number of countries has steadily increased to 37 in 2007 and the number of indicators to 29 in 2008 (cf. Annex 1 for an overview of the change in the indicators used in the EIS over time). The EIS methodology was revised again in 2008 with the intention of using the new methodology in the consecutive 2008, 2009 and 2010 reports so as to ensure full comparability over time. The 2008 revision of the EIS was a direct result of the challenges discussed in the EIS 2007 report: to measure new forms of innovation; to (better) assess overall innovation performance; to improve comparability at national, regional and international level; and to measure progress and changes over time (EC, 2009). The EIS 2008 Methodology Report provided full details of the new methodology (Hollanders and van Cruysen, 2008). Innovation performance in the EIS is measured using data from 29 innovation indicators. These indicators are grouped in three main blocks covering enablers, firm activities and outputs covering seven different innovation dimensions.

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Hugo Hollanders

Enablers capture the main drivers of innovation that are external to the firm covering the availability of high-skilled and educated people as captured in the human resources dimensions and the availability of finance for innovation projects and the support of governments for innovation activities as captures in the Finance and support dimension. Firm activities capture innovation efforts that firms undertake recognising the fundamental importance of firms’ activities in the innovation process as captured by three innovation dimensions. Firm investments cover a range of different investments firms make in order to generate innovations; linkages & entrepreneurship captures entrepreneurial efforts and collaboration efforts among innovating firms and also with the public sector; and throughputs captures the Intellectual Property Rights (IPR) generated as a throughput in the innovation process and Technology Balance of Payments flows. Outputs capture the outputs of firm activities as measured by the number of firms that have introduced innovations onto the market or within their organisations, covering technological and non-technological innovations (the Innovators dimension) and by the economic success of innovation in employment, exports and sales due to innovation activities (the Economic effects dimension). These dimensions form the core of national innovation performance. In addition, there are wider socioeconomic factors that influence innovation, such as the role of governments, markets, social factors and the demand and acceptance of innovation. These factors and their relationship with innovation performance are as such not included in the EIS benchmarking but have been explored in various EIS thematic papers 5. The EIS 2008 uses the most recent statistics from Eurostat and other internationally recognised sources as available at the time of analysis. The 29 indicators which are included in each of the dimensions are shown in Table 1. It is important to note that, due to data availability, the data relates to actual performance in 2006 and 2007 6. As a consequence the 2008 EIS does not capture the most recent changes in innovation performance, or the impact of policies introduced in recent years which may take some time to impact on innovation performance.

5 6

cf. the full list of EIS thematic papers available for download at http://www.proinno-europe.eu/metrics Of the 29 indicators, 12 indicators capture in performance in 2007, 15 indicators capture performance in 2006 and two indicators capture performance in 2005.

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Table 1: European Innovation Scoreboard indicators Block Dimension/indicator ENABLERS Human resources S&E and SSH graduates per 1 000 population aged 20–29 (first stage of 1.1.1 tertiary education — ISCED 5) S&E and SSH doctorate graduates per 1 000 population aged 25–34 (second 1.1.2 stage of tertiary education — ISCED 6) 1.1.3 Population with tertiary education per 100 population aged 25–64 1.1.4 Participation in lifelong learning per 100 population aged 25–64 Youth education attainment level (share of young people aged 20–24 having 1.1.5 attained at least upper secondary education) Finance and support 1.2.1 Public R & D expenditures (% of GDP) 1.2.2 Venture capital (% of GDP) 1.2.3 Private credit (relative to GDP) 1.2.4 Broadband access by firms (% of firms) FIRM ACTIVITIES Firm investments 2.1.1 Business R & D expenditures (% of GDP) 2.1.2 IT expenditures (% of GDP) 2.1.3 Non-R & D innovation expenditures (% of turnover) Linkages & entrepreneurship 2.2.1 SMEs innovating in-house (% of SMEs) 2.2.2 Innovative SMEs collaborating with others (% of SMEs) 2.2.3 Firm renewal (SME entries plus exits) (% of SMEs) 2.2.4 2.3.1 2.3.2 2.3.3 2.3.4 OUTPUTS 3.1.1 3.1.2 3.1.3

3.2.1 3.2.2 3.2.3 3.2.4 3.2.5 3.2.6

Public-private co-publications per million population Throughputs EPO patents per million population Community trademarks per million population Community designs per million population Technology Balance of Payments flows (% of GDP) Innovators SMEs introducing product or process innovations (% of SMEs) SMEs introducing marketing or organisational innovations (% of SMEs) Resource efficiency innovators (% of firms), unweighted average of the share of innovators where innovation has significantly reduced labour costs and the share of innovators where innovation has significantly reduced the use of materials and energy Economic effects Employment in medium-high & high-tech manufacturing (% of workforce) Employment in knowledge-intensive services (% of workforce) Medium and high-tech manufacturing exports (% of total exports) Knowledge-intensive services exports (% of total services exports) New-to-market sales (% of turnover) New-to-firm sales (% of turnover)

Data source

Eurostat Eurostat Eurostat Eurostat Eurostat Eurostat EVCA/Eurostat IMF Eurostat

Eurostat EITO/Eurostat Eurostat — CIS Eurostat — CIS Eurostat — CIS Eurostat Thomson Reuters/ CWTS Eurostat OHIM/Eurostat OHIM/Eurostat World Bank

Eurostat — CIS Eurostat — CIS Eurostat — CIS

Eurostat Eurostat Eurostat Eurostat Eurostat — CIS Eurostat — CIS

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Hugo Hollanders

Innovation performance in the EIS is summarised using composite indicators for each year over a five-year period. The methodology involved the following steps: (i) for highly volatile and asymmetric distributed indicators the data are transformed; (ii) data outliers are identified; (iii) reference years are chosen for each of the indicators reflecting most recent data availability for most of the countries; (iv) missing time series data are imputed using the available data; (v) data are extrapolated for 2009 and 2010 ensuring that; (vi) the worst and best performers over all years can be identified such that these worst and best performing scores can also be used in the future EIS 2009 and EIS 2010; and (vii) all data are normalised within the same range such that the best performing score is equal to 1 and the worst performing score is equal to 0. For each of the innovation dimensions and main blocks composite indicators are then calculated as the average of the normalised data of the indicators included in each dimension or block. Overall innovation performance — the Summary Innovation Index — is calculated as the average of the normalised data of all 29 indicators (cf. EC (2009) and Hollanders and Cruysen (2008) for more details).

EIS benchmarking results The EIS 2008 includes innovation indicators and trend analyses for the EU-27 Member States as well as for Croatia, Iceland, Norway, Turkey, and Switzerland. Based on their innovation performance across 29 indicators as measured by the Summary Innovation Index (SII), EU Member States fall into the following four country groups (cf. Figure 1): yy Denmark, Germany, Finland, Sweden, and the UK are the Innovation leaders, with innovation performance well above that of the EU average and all other countries. Of these countries, Germany is improving its performance fastest while Denmark is stagnating. yy Belgium, Ireland, France, Luxembourg, the Netherlands and Austria are the Innovation followers, with innovation performance below those of the innovation leaders but above that the EU average. Ireland’s performance has been increasing fastest within this group, followed by Austria. yy Czech Republic, Estonia, Greece, Spain, Italy, Cyprus, Portugal and Slovenia are the Moderate innovators, with innovation performance below the EU average. The trend in Cyprus’ innovation performance is well above the average for this group, followed by Portugal, while Spain and Italy are not improving their relative position.

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yy Bulgaria, Latvia, Lithuania, Hungary, Malta, Poland, Romania and Slovakia are the catching-up countries with innovation performance well below the EU average. All of these countries have been catching up, with the exception of Lithuania. Bulgaria and Romania have been improving their performance the fastest. 0.750 0.700

Innovation performance (SII 2008)

0.650 0.600 0.550 0.500 0.450 0.400 0.350 0.300 0.250 0.200 0.150 -1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

Average annual growth in innovation performance Figure 1: Innovation performance: current and trend performance Colour coding as follows: green are the innovation leaders; yellow are the innovation followers; orange are the moderate innovators; blue are the catching-up countries. Average annual growth rates are calculated over a five-year period. The dotted lines show EU performance and growth. Source: European Innovation Scoreboard 2008 (EC, 2009).

The development in innovation performance has been calculated for each country and for the EU-27 using data over a five-year period. All countries, with the exception of Denmark show an absolute improvement in their innovation performance. Bulgaria and Romania have experienced the fastest growth in performance, albeit from a low starting point. Within the four identified country groups growth performance is very different. Within the innovation leaders, Switzerland is the growth leader and all other countries in this group show a rate of improvement that is below that of the EU-27. For the in33


12/9/2009 2:46:15 PM

Hugo Hollanders

novation followers we observe that only Austria and Ireland have managed to grow faster than the EU-27. These countries are the growth leaders within the innovation followers. Of the moderate innovators seven countries have grown faster than the EU-27, but three countries have shown a slower progress: Italy, Norway and Spain. The growth leaders here are Cyprus and Portugal. Of the catching-up countries two countries have actually grown at a slower pace than the EU-27: Croatia and Lithuania. Bulgaria and Romania are the growth leaders also showing the overall fastest rate of improvement in innovation performance. The average growth rates for the four country groups 7 show that there is between group convergence with the Moderate innovators and the catching-up countries growing at a faster rate than the Innovation leaders and Innovation followers. This overall process of catching up, where countries with below average performance have faster growth rates than those with above average performance, can also be observed at the level of most individual countries. Notable exceptions include Cyprus which combines a close to average level of performance with a high growth rate; Croatia, Italy, Lithuania, Norway and Spain which combine below average levels of performance with below average growth rates; and Switzerland which is combining a high level of innovation performance and an above average rate of improvement. Japan and the US are not included in the main EIS analysis as for both countries data are missing for too many indicators. Using a smaller selection of 17 indicators, average innovation performance of Japan and the US is well above that of the EU-27 (Figure 2). The EU-US gap has dropped significantly, in particular between 2005 and 2006 although the relative progress of the EU appears to have slowed down since then. The EU-Japan gap at first increased but has been declining at a steady rate in the last four years. There remains a significant gap between the EU and these two other regions and this gap is concentrated in four areas: international patenting (as measured under the patent cooperation treaty), public private linkages and numbers of researchers (despite the improvements in both these areas), and business R & D expenditures (where both EU and US values have stagnated, while Japan’s have increased).

7

Average growth for the innovation leaders is 1.6 %, for the innovation followers 2.0 %, for the moderate innovators 3.6 % and for the catching-up countries 4.1 %.

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EU-US

EU-Japan

0

0

-10

-10

-20

-20

-30 -40 -50

−33 −41

−40

2004

2005

−29

-30

−28

-40 -50

2006

2007

2008

−42

−44

2004

2005

−42

−40

−38

2006

2007

2008

Figure 2: EU Innovation gap towards US and Japan Performance for each reference year is measured using, on average, data with a two-year lag (e.g. performance for 2008 is measured using data for 2006). The EU innovation gap is measured as the distance between the average performance of the EU and those of the US and Japan on 16 indicators. An EU innovation gap of e.g. – 40 means that the US or Japan is performing at a level of 140, or 40 % above that of the EU. Source: European Innovation Scoreboard 2008 (EC, 2009).

Conclusions Innovation performance can be measured using innovation scoreboards which provide good overview of trends in innovation over a period of time. They also highlight individual countries’ strengths and weaknesses. Innovation performance in the EU is measured by the European Innovation Scoreboard. After its introduction in 2000 the EIS has undergone several revisions of which the last one was in 2008. The EIS now captures 29 innovation indicators classified in seven different innovation dimensions. Average performance is measured using composite indicators and the summary Innovation Index captures average performance at the country level. The 2008 EIS shows that the European countries can be divided in four different groups, of which the Innovation leaders show the best innovation performance and the catching-up countries show the fastest rate of improvement. A comparison with its main competitors the US and Japan shows that the innovation gap for the EU has been declining but that the rate of decline is slowing down and the remaining gap is still significant.

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Hugo Hollanders

Table 2: Changes in the European Innovation Scoreboard EIS 2000 (Pilot)

EIS 2001

EIS 2002

EIS 2003

EIS 2004

Number of indicators

16

18

18

22

22

Number of groups/dimensions

4

4

4

4

4

Indicators based on CIS

4

4

4

5

6

No

Yes

No

Yes

Yes

17: EU-15, US, JP

17

33: + 10 NMS BG, IS, NO, RO, CH, TR

33

33

Share of postsecondary graduates

Share of population aged 20–29

←

←

←

Summary Innovation Index Countries Indicators S&E (Science and engineering) graduates S&E and SSH graduates (ISDED 6)

x

x

x

x

x

Share of working-age population with tertiary education

←

←

←

←

←

Participation in lifelong learning

x

←

←

←

←

Youth education attainment level

x

x

x

x

x

Public R & D expenditures (% of GDP)

GOVERD only

GOVERD + HERD

GERD — BERD

←

←

Venture capital (% of GDP)

Early stage and expansion stage

Early stage only

←

High-tech venture capital

x

Share of GDP

←

←

Share of venture capital

Private credit (% of GDP)

x

x

x

x

x

Capitalisation of new markets (% of GDP)

←

←

←

x

x

Broadband penetration rate (population)

x

x

x

x

x

Users per 100 population

Share of households

←

Composite indicator for households and firms

←

Share of enterprises that receive public funding for innovation (CIS)

x

x

x

x

x

Business R & D expenditures (% of GDP)

←

←

←

←

←

Share of medium-high/high-tech R & D in manufacturing

x

x

x

x

x

←

←

←

←

← Total business sector

Internet use

ICT expenditures (% of GDP) Innovation expenditures (% of turnover) (CIS)

Manufacturing sector

←

←

+ Services sector

Share of SMEs innovating in-house (CIS)


←

←

+ Services sector

Total business sector

Share of SMEs cooperating in innovation (CIS)


←

←

+ Services sector


← : same definition as previous year; x: no longer included

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12/9/2009 2:46:16 PM


Table 2: Changes in the European Innovation Scoreboard (continued) EIS 2000 (Pilot)

EIS 2001

EIS 2002

EIS 2003

EIS 2004

Volatility rates of SMEs

x

x

x

←

x

Public-private co-publication per million population

x

x

x

x

x

Share of university R & D funded by private sector

x

x

x

x

x

EPO patents per million population

x

x

x

←

←

USPTO patents per million population

x

x

x

←

←

Triad patents per million population

x

x

x

x

x

Community trademarks per million population

x

x

x

x

x

Community designs per million population

x

x

x

x

X

High-tech EPO patents per million population

←

←

←

←

←

High-tech USPTO patents per million population

x

←

←

←

←

Technology Balance of Payments flows (% of GDP)

x

x

x

x

x

Share of SMEs introducing product or process innovation

x

x

x

x

x

Share of SMEs using organisational innovations (CIS)

x

x

x

x

Using nontechnological change

Share of resource efficiency innovators

x

x

x

x

x

Share of medium-high/high-tech manufacturing employment

←

←

←

←

←

Share of high-tech manufacturing value-added

Percent change

Share of value-added

←

←

←

Share of high-tech services employment

←

←

←

←

←

Share of high-tech exports

x

X

x

x

x

Share of knowledge-intensive services exports

x

X

x

x

x

New-to-market products (% of turnover) (CIS)


←

←

+ Services sector


x

X

x

Manufacturing + Services sector


New-to-firm products (% of turnover) (CIS)


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Hugo Hollanders

Table 2: Changes in the European Innovation Scoreboard (continued) EIS 2005

EIS 2006

EIS 2007

EIS 2008

Number of indicators

26

25

25

29

Number of groups/dimensions

5

5

5

7

Indicators based on CIS

7

7

7

8

Summary Innovation Index

Yes

Yes

Yes

Yes

Countries

33

34: + HR

37: + AU, CA, IL

32: EU-27, HR, IS,NO,CH,TR

S&E (Science and Engineering) graduates

←

←

←

S&E and SSH graduates (ISDED 6)

x

x

x

S&E and SSH graduates, ISCED 5 ←

Share of working-age population with tertiary education

←

←

←

←

Participation in lifelong learning

←

←

←

←

Youth education attainment level

←

←

←

←

Public R & D expenditures (% of GDP)

←

GOVERD+HERD

←

←

Venture capital (% of GDP)

←

←

←

←

High-tech venture capital

x

x

x

Private credit (% of GDP)

x

x

x

X ←

Capitalisation of new markets (% of GDP)

x

x

x

X

Broadband penetration rate (population)

x

←

←

Broadband access by firms

Internet use

x

x

x

x

Share of enterprises that receive public funding for innovation (CIS)

←

←

←

x

Business R & D expenditures (% of GDP)

←

←

←

←

Share of medium-high/high-tech R & D in manufacturing

←

←

←

x

ICT expenditures (% of GDP)

←

←

←

IT expenditures

Indicators

Innovation expenditures (% of turnover) (CIS)

←

←

←

Non-R & D innovation expenditures

Share of SMEs innovating in-house (CIS)

←

←

←

←

Share of SMEs cooperating in innovation (CIS)

←

←

←

←

Volatility rates of SMEs

x

x

x

Size class and sector limitation

Public-private co-publication per million population

x

x

x

←


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Table 2: Changes in the European Innovation Scoreboard (continued) EIS 2005

EIS 2006

EIS 2007

EIS 2008

Share of university R & D funded by private sector

←

x

x

x

EPO patents per million population

←

←

←

←

USPTO patents per million population

←

←

←

x

Triad patents per million population

←

←

←

x

Community trademarks per million population

←

←

←

←

Community designs per million population

←

←

←

←

High-tech EPO patents per million population

x

x

x

x

High-tech USPTO patents per million population

x

x

x

x

Technology Balance of Payments flows (% of GDP)

x

x

x

←

Share of SMEs introducing product or process innovation

x

x

x

←

Share of SMEs using organisational innovations (CIS)

←

Using organisational innovations

←

Marketing or organisational innovation

Share of resource efficiency innovators

x

x

x

←

Share of medium-high/high-tech manufacturing employment

←

←

←

←

Share of high-tech manufacturing value-added

x

x

x

x

Share of high-tech services employment

←

←

←

Knowledge-intensive services

Share of high-tech exports

←

←

←

Medium and high-tech manufacturing exports

Share of knowledge-intensive services exports

x

x

x

←

New-to-market products (% of turnover) (CIS)

←

←

←

←

New-to-firm products (% of turnover) (CIS)

←

←

←

←


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Hugo Hollanders

References Archibugi, A., Denni, M. and Filippetti, A. (2009), The Global Innovation Scoreboard 2008: The Dynamics of the Innovative Performances of Countries, INNO Metrics Thematic Paper, European Commission, Brussels. Arundel, A. and Hollanders, H. (2008), ‘Innovation Scoreboards: Indicators and Policy Use’, C. Nauwelaers and R. Wintjes (eds.), Innovation Policy in Europe, pp. 29–52, Edward Elgar, Cheltenham. European Commission (2009), European Innovation Scoreboard 2008 — Comparative Analysis of Innovation Performance, European Commission, Brussels. Grupp, H. and Mogee, M. E. (2004), ‘Indicators for National Science and Technology Policy: How Robust are Composite Indicators?’, Research Policy, 33:1374–1384. Hollanders, H. and van Cruysen, A. (2008), Rethinking the European Innovation Scoreboard: A New Methodology for 2008–10, INNO Metrics Thematic Paper, European Commission, Brussels. Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A. and Giovannini, E. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. Paris: OECD. OECD (2007), Science, Technology and Industry Scoreboard 2007 — Innovation and Performance in the Global Economy. OECD, Paris. World Economic Forum (2008), The Global Competitiveness Report 2008–09, World Economic Forum, Geneva.

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Design, creativity and innovation

4. Design, Creativity and Innovation: a scoreboard approach 1

Hugo Hollanders and Adriana van Cruysen (UNU-MERIT, Maastricht University)

Abstract Creativity and design are important features of a well-developed knowledge economy. Design transforms creative ideas into new products, services and systems. Design links creativity to innovation and has the potential to substantially improve brand image, sales and profitability of a company. The measurement of creativity and design is hampered by a lack of quantitative indicators which directly measure performance and we have to rely on proxy indicators, which only indirectly measure performance in creativity and design. Following the European Innovation Scoreboard (EIS), we adopt a ‘scoreboard approach’ to measure performance in creativity and design using 35 indicators which are classified in seven different dimensions of which three capture the Creative climate and four capture Creativity & design. The quality of the educational system, the desire of people to express themselves artistically and the openness of a society towards different cultures determine the creative climate in a country. The analysis confirms that a favourable creative climate has a positive effect on the creativity of a country. A more favourable creative climate results in more ideas and more creativity, which in turn increases R & D and design activities. R & D and design not only develop new ideas but also shape them into commercially attractive new products and processes, thus increasing innovation. 1

This chapter is based on the INNO Metrics publication ‘Design, Creativity and Innovation: A Scoreboard Approach’, February 2009.

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Hugo Hollanders, Adriana van Cruysen

Countries showing a higher performance in creativity and design also show a stronger innovation performance as measured in the EIS. Creative education shows the strongest relation to innovation. Policies aimed at improving levels of educational attainment and creative thinking in education will have a positive effect on a innovative performance.

Introduction Creativity and design have distinct roles in the innovation and the broader business performance context. Design has emerged as a key differentiator for businesses. As a result of the growing access to technology, firms increasingly have to compete at equal prices and functionality. Design increasingly assumes a new role, one of competitive advantage and differentiator, creating new markets by linking technology with commercial and user considerations, whether linked to functionality, aesthetics, brand or other intangibles. But measuring creativity and design in statistical terms is still a problem, as there is a lack of indicators to measure their contribution not only at national and international levels, but also in comparison with other economic sectors. In 2005 the UK Department of Trade and Industry concluded that ‘(t)here are few official statistics to support analysis of creativity and design’ (DTI, 2005). In this report we try to quantify countries’ performance in creativity and design using proxy indicators to build composite indicators. These composite indicators are then used to examine the link with the innovation performance data from the 2008 European Innovation Scoreboard (EIS). Section 2 will discuss the concepts of creativity and design and their relation to innovation. Section 3 will discuss the scoreboard approach used for measuring performance in creativity and design and will discuss the statistical indicators in detail. Section 4 presents statistical results on the relation between creativity, design an innovation and present rankings of countries’ relative performance in creativity and design and Section 5 concludes.

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Creativity and design as potential drivers of innovation Defining creativity and design According to Florida (2002) creativity is multidimensional and three different ‘types’ of creativity can be distinguished: technological creativity (invention), economic creativity (entrepreneurship) and artistic/cultural creativity. All these dimensions of creativity are interrelated, sharing a common process of thinking and reinforcing each other. The creative economy is then the result of the interrelations among technology, arts and businesses. Following the UK Department of Trade and Industry, creativity can be defined ‘… as the production of new ideas that are fit for a particular business purpose’ (DTI, 2005). As there are only a few indirect indicators for measuring the generation of new ideas, the creative sector is used as a proxy to measure creativity. The creative sector not only covers activities with an artistic component but also activities with creative output involving intellectual property, activities using creative input to add value, as in the service sector and more recently user-created activities and networks.(cf. Box 1). The existence of a vibrant creative sector is an indication of an underlying creativity activity permeating the whole economy. Design is a key driver not only of firms, but also of countries’ competitiveness. It is not only integrated into businesses as a strategic tool to drive innovation and growth, but also to foster national competitiveness by contributing to general creativity and the image of countries as a brand. For example, countries such as Denmark, Spain, Ireland, Finland and the UK have all developed national design policies and invested in design excellence, as a mean of producing unique and globally competitive products and services, a differentiator and driver of national competitiveness (Design Singapore Report, 2002). The New Zealand Design Taskforce (2003) found that 67 % of exporters identified design as a key factor in economic success and for 80 % of the companies design had added value to their business.

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Box 1: Definition of creativity industries According to Hartley (2008) the term ‘creative industries’ was introduced by the UK Department of Culture, Media and Sport (DCMS) in 1990, which focused on the industry itself by referring to firms whose outputs were considered creative. A major contribution by DCMS was to move the concept away from its association only with activities with a strong artistic component, to any activity producing symbolic products, and relying on intellectual property. These activities included advertising, film and video, architecture, music, art and antique markets, performing arts, computer and video games, publishing, crafts, software, design, television and radio, and designer fashion. According to this first definition, the creative industries are based on individual creativity, skill and talent. In a second phase, which according to Hartley (2008) is taking place now, the focus has widened from creative output to the whole economy, taking into account how creative inputs add value to businesses which are not considered creative, in particular in the services sector. In a third phase (emergent), which is being developed in parallel to the extension of digital media into popular culture, the focus is shifting to user-created content and open networks. Creativity is now seen as a collective process. The focus has been changing from a supply-driven approach to a demand-driven one. Consequently, any model to access creativity and its impact on innovation should incorporate variables that are not only supply but also demand oriented. What is now defined as the creative sector 2 is developing at a higher pace than other economic sectors. Employment is not only growing at a high pace but the sector also offers a high share of highly skilled jobs. The creative sector is estimated to account for more than 7 % of the world’s domestic product (World Bank, 2003) and is expected to grow by 10 % per year (UN, 2004). The creative industries represent a leading sector in many OECD countries, with annual growth rates between 5 and 20 % (UN, 2004) and having a positive impact on trade. Moreover, the creative industries produce significant economic spinoffs and promote integration between technology, arts and business. 2

The concept of design has been defined in different ways either focusing on design as an economic activity or, more generally, as the translation of the ideas generated by creativity into new products and processes (cf. Bitard and Basset, 2008): ‘Design is what links creativity and innovation. It shapes ideas to become practical and attractive propositions for users or customers. Design may be described as creativity deployed to a specific end.’ ‘… design can be approached as an economic sector of activity. Basically, design definitions are based on design professions with the following four main ensembles: fashion design, graphic design, interior design and product design … The list can be even more detailed, encompassing industrial design, product design (furniture, toys, jewellery), visual, communication, advertising, packaging, fashion design, architecture design, landscape design, interior design, urban design, etc.’ 2

The creative sector is defined as the mix of non-profit arts and for-profit creative industries, such as technology development, arts and entertainment, design, film-making, architecture that exhibit high rates of per employee value added input to the goods and services they produce (Creative Community Index, 2006).

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In this chapter creativity is defined as the generation of new ideas; design is defined as the shaping (or transformation) of ideas into new products and processes; and innovation is defined as the exploitation of ideas, i.e. the successful marketing of these new products and processes. It should be emphasised that creativity, design and innovation are therefore not limited to certain sectors or professions, but apply across the economy.

Creativity, design and innovation A number of existing studies have examined the link between creativity, design and economic performance. The Danish Design Centre (2003) found a correlation between the use of design and economic performance and macroeconomic growth and that job creation, revenues and exports were higher in firms that used design compared to other firms that did not. Power (2004), in his comparative study of the design sector in five Nordic countries (Denmark, Finland, Iceland, Norway and Sweden), concluded that in spite of the small size of the design industry in these countries, design is crucial to the competitiveness of firms in other industries. The use of design by Nordic firms helped to increase their profitably and level of innovation. Moreover, Power concludes that the design industry has experienced high levels of growth and tends to be concentrated in large cities. Creativity and design can thus be linked to innovation as the first contributes to the expansion of available ideas and the second to increased chance of successfully commercialising these ideas. Swann and Birke (2005) identified three different models linking creativity and design to innovation. In the linear model creativity has a positive effect on R & D which is turn has a positive effect on innovation (cf. in the top graph in Figure 1). The interactive model not only includes feedback effects between the different elements of the linear model (cf. in the middle graph in Figure 1) but also acknowledges the importance of design. Creativity relates directly with design and design relates directly with innovation. In the third and most complete model the creative climate takes a central position (cf. the bottom graph in Figure 1).

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Figure 1: Linking creativity, design and innovation Source: Adapted from Swann and Birke (2005).

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Swann and Birke treat design separately from R & D. Tether (2006) suggests that ‘much innovation-related design is hidden in “development”’. Lambert (2006) using British data indicated that design inputs into the innovation process have most impact when used together with more technology-based inputs, suggesting that although design and technology are different forms of activity, they complement each other. The flow-chart model in this report, which will be discussed in the following section, is an adapted version of the third model placing more emphasis on the creative climate and allowing an interaction effect between R & D and design.

Measuring creativity and design: a scoreboard approach Previous studies creating an index to measure creativity or design are rare. A creativity index for Hong Kong using a wide range of indicators has been developed by Hui et al. (2005). The Hong Kong Creativity Index uses six societal conditions (legal system, freedom of expression, international commitment to cultural development, ICT infrastructure, entrepreneurship and financial structure) to provide the context in which creativity takes place. Moreover, this context not only provides conditions for the development of creativity but also for its protection. Many of the indicators used were also used in other studies and come from the Global Competitiveness Report published by the World Forum. Following the European Innovation Scoreboard (EIS), we adopt a ‘scoreboard approach’ using a large set of indicators to capture the different dimensions. The 35 indicators are classified in seven different dimensions of which three capture performance in the creative climate and four capture performance in Creativity & design (cf. Figure 2). For benchmarking countries’ performance on design and creativity, we follow a similar approach as in the 2003 NIS and 2004 EXIS reports (cf. Arundel, 2004 respectively Arundel and Hollanders, 2005), by summarising performance on relevant dimensions using a small sample of indicators in so-called composite indicators, i.e. a ‘scoreboard approach’. In the scoreboard approach, the performance of an observed phenomenon is measured using a set of indicators which grasp some of the key features of that phenomenon. Potential indicators to be included in the analysis are identified based on a literature review and the indicators are then selected based on the results of both statistical analyses (correlation analyses and factor analyses) and what ‘common sense’ suggests would be the most directly relevant indicators. 47


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Figure 2: A ‘model’ linking creativity, design and innovation

The quality of the educational system, the desire of people to express themselves (artistically) and the openness of the society towards different countries and cultures determine the Creative climate. In a more favourable Creative climate the creation of new ideas is stimulated as people are better educated, have a stronger inclination to self-expression and the creation of new ideas, and are being exposed more to new ideas and thoughts from both foreigners and other cultures within the same country. Creativity generates new ideas, so a more favourable Creative climate should increase creativity as it raises the number of ideas. More creativity will result in a stronger creative sector and higher levels of creativity in R & D and design activities. We also introduce a dimension capturing the international competitiveness in design, to highlight the importance of design both within the wider innovation process and as an economic sector. The flow chart is completed with the European Innovation Scoreboard (EIS) dimensions capturing enablers of innovation (Human resources and Finance and support), innovation at the firm level (Firm investments, Linkages & entrepreneurship and Throughputs) and the Effects innovation (Innovators and Economic effects).

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The selected indicators and dimensions adopted for measuring creativity and design are shown in Table 1. The rationale for selecting these indicators will be explained in the remainder of this section. Table 1: Creativity and Design Scoreboard indicators and dimensions Indicators

Time period

Data source

A CREATIVE CLIMATE A1

CREATIVE EDUCATION

A1.1

Number of art schools per million population

A1.2

Quality of educational system (1 = does not meet the needs of a competitive economy, 7 = meets the needs of a competitive economy)

2006/07

Global Competitiveness Report 2007/08

A1.3

Public expenditure on education per capita

Average 2001–05

Eurostat

A1.4

Share of tertiary students by field of education related to culture

2004/05

Eurostat

A1.5

Extent of staff training (the general approach of companies in your country to human resources is: 1 = to invest little in training and employee development, 7 = to invest heavily to attract, train and retain employees)

2006/07


A2

ELIA (European League of Institutes of the Arts)/Eurostat (population)

SELF-EXPRESSION

A2.1

Language skills (share of population being able to have a conversation in at least one other language besides their mother tongue)

2005

Special Eurobarometer 243

A2.2

Share of population involved in artistic activities

2007

Eurobarometer 278

A2.3

Self-expression values

Average from 2nd to 4th wave of the World Values Survey (1990–2000)

Inglehart and Welzel (2004)

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Table 1: Creativity and Design Scoreboard indicators and dimensions (continued) Indicators A3

Time period

Data source

OPENNESS & TOLERANCE

A3.1

Share of foreign tertiary students

Average for 2002–06

Eurostat

A3.2

Share of foreigners in employment of population aged 25 to 64


Eurostat

A3.3

Share of cultural employment in total employment for employees with a completed tertiary education

2005

Eurostat

A3.4

Degree of urbanisation of population aged 25 to 64 (share of population living in densely-populated areas, i.e. at least 500 inhabitants/ km²)


Eurostat

A3.5

Openness to other countries, share of population very interested in arts and culture in own other European countries

2007

Eurobarometer 278

A3.6

Brain drain (reversed) (your country’s talented people: 1 = normally leave to pursue opportunities in other countries, 7 = almost always remain in the country)

2006/07


B CREATIVITY & DESIGN B1

CREATIVE SECTOR

B1.1

Share of creative occupations (ISCO classes 1 and 2) of population aged 25 to 64


Eurostat

B1.2

Share of knowledge workers in S&T Average for 2002–06 (HRSTC — Core of Human Resources in Science and Technology)

Eurostat

B1.3 B2

Value added share of creative and cultural industries

KEA (2006)

CREATIVITY IN R & D

B2.1

National patent applications per million population

B2.2

Scientific publications per million population

B2.3

Trademark applications by residents per million population

Average 2004–06

WIPO (patents)/Eurostat (population)

Average 2004–06

Thomson Reuters Web of Science & CWTS (Leiden University)/Eurostat (population)

Average 2004–06

WIPO (trademarks)/Eurostat (population)

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Table 1: Creativity and Design Scoreboard indicators and dimensions (continued) Indicators B2.4

B3 B3.1

B3.2 B3.3 B3.4

B3.5

B4 B4.1 B4.2 B4.3

B4.4

Capacity for innovation (companies obtain technology: 1 = exclusively from licensing or imitating foreign companies, 7 = by conducting formal research and pioneering their own new products and processes)

Time period

Data source Global Competitiveness Report 2007/08

2006/07

DESIGN ACTIVITIES Importance of design staff for innovation (In the last two years, has your company’s design staff been a major source of ideas for the innovative activities of your company?) Number of designers per million population Community design applications per million population Production process sophistication (production processes use: 1 = labour-intensive methods or previous generations of process technology, 7 = the world’s best and most efficient process technology) Uniqueness of product design (product designs are: 1 = copied or licensed from abroad, 7 = developed locally)

Innobarometer 2007 2007

2006 Average 2004–06

BEDA — Bureau of European Design Association/Eurostat (population) OHIM/Eurostat Global Competitiveness Report 2007/08

2006/07

2000/01

Global Competitiveness Report 200102

COMPETITIVENESS IN DESIGN Exports design related services as a percentage of services exports Exports design as a percentage of merchandise exports Value chain breadth (exporting companies in your country: 1 = are primarily involved in resource extraction or production, 7 = not only produce but also perform product design, marketing sales, logistics and after sales services) Extent of branding (companies that sell internationally: 1 = sell into commodity markets or to other companies that handle marketing, 7 = have well-developed international brands and sales organisations)

Average 2003–05 Average 2003–05

UNCTAD (Global databank on world trade in creative products) UNCTAD (global databank on world trade in creative products) Global Competitiveness Report 2007/08

2006/07

Global Competitiveness Report 2004–05 2003/04

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Sources: BEDA, the Bureau of European Design Association, works as a permanent liaison between the professional societies of designers, the promotional, educational, research, social and design management organisations and networks within the European countries and the authorities of the European Union. CWTS (Centre for Science and Technology Studies at Leiden University, the Netherlands) is a knowledge company dedicated to bibliometric and related information products. The ELIA, European League of Institutes of the Arts is an independent network organisation of major arts education institutions and universities representing all subject disciplines, with a membership of over 350 arts institutions in 47 countries, representing more than 250 000 art students. Eurobarometer 243 — Europeans and their Languages. This survey was requested by Directorate-General for Education and Culture and coordinated by Directorate-General Communication, European Commission, 2006. Eurobarometer 278 — European Cultural Values. This survey was requested by Directorate-General for Education and Culture and coordinated by Directorate-General Communication, European Commission, 2007. Eurostat — Statistical Office of the European Communities, whose main task is to provide the European Union with statistics at European level that enable comparisons between countries and regions. The Global Competitiveness Report is published by the World Economic Forum on a yearly basis assessing the comparative strengths and weaknesses of national economies. Its present coverage extends to 134 major and emerging economies. Inglehart, R. and Welzel, C. (2004), ‘What Insights can Multi-Country Surveys Provide about People and Societies?’ Comparative Politics Newsletter, American Political Science Association. The Innobarometer analyses specific aspects of innovation through a survey of 3 500 randomly selected companies in the EU. The Innobarometer is part of the INNO Metrics network funded by the Directorate-General for Enterprise and Industry. KEA is a Brussels-based strategic consultancy specialised in creative industries, cultural, entertainment, media and sport sectors. OHIM (Office of Harmonisation for the Internal Market) is the European Union agency responsible for registering trademarks and designs that are valid in all 27 countries of the EU. Thomson Reuters Web of Science is the world’s leading source of intelligent information for businesses and professionals, in the financial, legal, tax and accounting, scientific, healthcare and media markets. UNCTAD (United Nations Conference on Trade and Development) promotes the integration of developing countries into the world economy and undertakes research, policy analysis and data collection and provides technical assistance to the specific requirements of developing countries. WIPO — The World Intellectual Property Organisation is a specialised agency of the United Nations, involved in the development of an international intellectual property (IP) system.

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A1 Creative education The education system is generally seen as having a major impact on the creativeness of individuals and on the creative climate. This concerns all levels and fields of education, although available statistical data is biased in favour of measuring creativity in artistic and cultural fields. The following indicators are used to capture performance in Creative education:

yy A1.1 Number of art schools per million population There is growing evidence that the arts produce tangible social and economic benefits (Creative Community Index, 2006). Education in arts in particular is assumed to have a positive impact on the creativity of people. Here we use the number of art schools per million population as an indicator of the presence of such schools where a higher number of art schools is assumed to improve the creative potential of a country’s population. The data on the number of art schools were taken from the website of the European League of Institutes of the Arts (ELIA) and do not necessarily cover all art schools in each country.

yy A1.2 Quality of educational system The quality of the educational system is believed to be positively linked to creativity, by meeting the needs of a competitive economy. Moreover, educated consumers are more likely to be comfortable with new ideas, demand sophisticated and novel products and services, and consider different options. The data on quality of educational system were taken from ‘The Global Competitiveness Report 2007– 08’ published by the World Economic Forum. The indicator reflect answers to the question ‘The educational system in your country (1 = does not meet the needs of a competitive economy, 7 = meets the needs of a competitive economy)’.

yy A1.3 Public expenditure on education per capita Education is assumed to develop peoples’ skills and abilities, for all types and levels of education. We use public expenditure on education per capita as an additional indicator for the quality of the educational system, assuming that higher spending results in better education. Data were taken from Eurostat’s pocketbook on Cultural statistics (Eurostat, 2007).

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yy A1.4 Share of tertiary students by field of education related to culture The fields of education related to culture include Humanities, Arts, Journalism and information, Architecture and building 3. Educators have observed that students develop creative thinking through arts and transfer this capacity to other subjects. Whenever arts are a strong element in the school environment, students tend to achieve higher grades. Moreover dropout rates and absenteeism are lower (Galligan, 2001). Education in arts also helps building specific skills such as goal setting, flexible thinking, tolerance, cooperation, teamwork, creative problemsolving, self-confidence and motivation, all of them valuable in the business field (Business Week, 1996). Data were taken from Eurostat’s pocketbook on Cultural statistics (Eurostat, 2007).

yy A1.5 Extent of staff training The extent to which companies invest in their personnel is an indicator of the intensity of on the job training and reflects the relevance of lifelong education. Data on extent of staff training were taken from ‘The Global Competitiveness Report 2007–08’ published by the World Economic Forum. The indicator reflect answers to the question ‘The general approach of companies in your country to human resources is (1 = to invest little in training and employee development, 7 = to invest heavily to attract, train and retain employees)’.

A2 Self-expression Self-expression is seen as an individual person’s drive to act creatively. More individual creativity will have a positive effect on the generation of ideas relevant for the process of innovation. Self-expression is measured by proxy indicators on language skills, artistic activities and self-expression values.

yy A2.1 Language skills The indicator is defined as the share of population being able to have a conversation in at least one other language besides their mother tongue. It is assumed that being able to speak more than one’s own language will benefit the exchange of ideas. The willingness of people to invest time and effort in learning more languages reflects their willingness for self-expression. Arundel (2004) in the TrendChart report on 3

Owing to the lack of a robust definition of culture (or to an over-abundance of definitions), the Eurostat pocketbook relies on the pragmatic definition generally agreed upon during the earlier work by the European Leadership Group (LEG). First, it was decided to restrict the field to activities recognised as cultural by every Member State. Second, the field to culture was broken down into about 60 activities, cross-relating eight ‘domains’ (artistic and monumental heritage, archives, libraries, books and press, visual arts, architecture, performing arts and audiovisual/multimedia).

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National Innovation Systems used this indicator to measure the receptiveness to use new ideas. Data were obtained for the Special Eurobarometer 243 on ‘Europeans and their Languages’.

yy A2.2 Share of population involved in artistic activities Cultural capital 4 activities can be found in different forms of art and performance, attitude to innovation in everyday life, work context and in social activities. According to the Creative Community Index Survey (2005), respondents who worked in jobs requiring creative skills attended more cultural outings when compared to those in less creative jobs. Moreover, creativity was associated with ‘the capacity to generate original ideas’. In these sense, participation in cultural activities is linked to the generation of new ideas. We use the share of population involved in artistic activities as a proxy to measure cultural capital and involvement in creative activities. The data were taken from the Eurobarometer 278 on ‘European Cultural Values’.

yy A2.3 Self-expression values 5 The indicator on self-expression values was developed by Inglehart and Welzel (2004). The indicator uses data from the second to fourth round of the World Values Survey (1990–2000) and reflects the percentages of people who (i) emphasise freedom and participation, (ii) tolerate sexual liberty, (iii) sign petitions, (iv) trust other people and report high life satisfaction.

A3 Openness & Tolerance Tolerance relates to the level of acceptance in a society in terms of racism, discrimination and intolerance. Mobility of human capital is related to social conditions that are conducive to cultural exchange, exchange of skills and knowledge as well as international exposure. Creative environments attract talented and ambitious people, who bring new ideas and different world views (Stolarick et al., 2005). Cultural diversity provides sources of creative expression that are captured by the creative industries

4

5

The Creative Community Index (2006) used the term cultural capital to refer to more specific activities and qualities related to culture, art and creativity in everyday life. Cultural capital is related to the degree in which people in community value creative activities that are not directly related to economic returns. Indicator A2.3 — Self-expression values significantly correlates with indicator A2.2 — Share of population involved in artistic activities — (0.626), which in turn significantly correlates with indicator A2.1 — Language skills (0.476), and are consequently grouped together. Indicator A2.3 — Self-expression values do not significantly correlate with any indicator in Group A3, except with indicators A3.1 — Foreign Students (0.565) and Brain drain (reversed) (0.821). Indicator A2.3 — Self-expression values has a low correlation with indicator A3.5 — Cultural openness (0.270), most likely because while ‘Self-expression values’ refers to a broader level of acceptance, Culture openness only refers to other European arts and cultures.

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(Bell and Stolarick, 2008; Florida, 2002). The following indicators are used to capture performance in Openness & Tolerance:

yy A3.1 Share of foreign tertiary students Following the 2003 TrendChart report on National Innovation Systems (Arundel, 2004), ‘these students increase local diversity, respond to tolerance, and introduce new ideas’. It is to be noted that this indicator is biased towards the presence of universities or other higher education institutes. There are also cultural and language biases having an effect on the relative attractiveness of a country (or region within that country) for attracting foreign students. Data were taken from Eurostat’s educational statistics.

yy A3.2 Share of foreigners in employment of population aged 25 to 64 A large share of foreign employees is used as a proxy for the tolerance of the domestic population towards non-nationals. It would be better to have indicator focusing on skilled employees, but such data are not available in the public domain. Data were taken from Eurostat’s Labour Force Survey.

yy A3.3 Share of cultural employment in total employment for employees with a completed tertiary education Cultural employment is defined as both employment in cultural occupations in the whole economy and any employment in cultural economic activities. We focus on the share of cultural employment for the higher educated only as these are expected be involved in the most creative jobs. Data have been obtained from Eurostat (EU Labour Force Survey, 2005).

yy A3.4 Degree of urbanisation of population aged 25 to 64 Urban environments are thought to be conducive to creativity through their greater levels of diversity, ‘attractivity’ to talent, and proximity of individuals (Sacco and Segre, 2006). The authors highlighted that urban concentrations display a high number of high education and research institutes, facilitating start-ups activities and more complex relationships between producers and consumers in what they called ‘flexible networks’. Firms look for a talented workforce, with talented workers preferring to reside in places where there is a vibrant cultural life (Eger, 2003). Arts and culture are fundamental for attracting a talented workforce. Larger cities offer a more developed and diverse recreational, cultural and educational infrastructure, facilitating the exchange of ideas between individuals (and professionals). Larger cities have been found to more innovative than smaller cities (Carlino, 2001; Therrien, 2003). We use the share of population living in densely populated areas, i.e. at least 500 inhabitants/km², as a proxy for the degree of urbanisation. 56


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yy A3.5 Openness to other countries Openness to other countries is measured as the share of the population that respond to be very interested in other European countries arts and culture. Being interested in other cultures is likely to increase the exchange of ideas and improves the creative climate. Data were obtained from the Eurobarometer 278 on ‘European Cultural Values’.

yy A3.6 Brain drain (reversed) The development and demand for innovative products can be impacted by the ability of talented graduates to work, stay and consume in their countries after they complete their education. While in the past it was considered that offering companies tax and other incentives was a necessary condition for influencing business location decisions, today the requirements are much different. According to Florida (2002), ‘traditional economic development and growth strategies had been driven by ‘demand-side’ strategy: attract jobs to get the people. Today’s economy requires a ‘supply-side’ strategy: places must offer a balance between technology, talent and tolerance to sustain long-term growth and prosperity.’ This can partly be measured by a reverse indicator for ‘brain drain’, which is an indicator of the level of domestic opportunities for talented graduates. The inflow of talented people from abroad is assumed to have a positive effect on a country’s creativity and the relative size of this inflow indirectly reflects that country’s openness or attractiveness to foreign skilled workers. Data on brain drain (reversed) were taken from ‘The Global Competitiveness Report 2007–08’ published by the World Economic Forum. The indicator reflect answers to the question ‘Your country’s talented people (1 = normally leave to pursue opportunities in other countries, 7 = almost always remain in the country)’.

B1 Creative sector The Creative Community Index (2006) defines the creative sector as the mix of non-profit arts and for-profit creative industries, such as technology development, arts and entertainment, design, film-making and architecture that exhibit high rates of per employee valueadded input to the goods and services they produce. The creative sector is also characterised by high-paying jobs. Moreover, the development, production, marketing and sales of technology products involves more and more people trained in artistic skills. The following indicators are used to capture the degree of activity/dynamism of the creative sector.

yy B1.1 S hare of creative occupations (ISCO Classes 1 and 2) of population aged 25 to 64 This indicator reflects the indicator used by Florida (2002) for the share of population in creative occupations. In the NIS 2003 report (Arundel, 2004) a 57


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similar indicator was used to capture the receptiveness to new ideas but then also ISCO Class 3 (technical and associate professionals) was included. ISCO Class 1 includes legislators, senior officials and managers and ISCO Class 2 includes professionals. The NIS 2003 report referred to this indicator as coming ‘closest to measuring social creativity at the national level’. Data were taken from Eurostat’s Labour Force Survey.

yy B1.2 Share of knowledge workers in Science and Technology (HRSTC — Core of Human Resources in Science and Technology) Knowledge workers are central to any knowledge economy. Being university trained and being employed in an S&T occupation, knowledge workers not only add directly to enhancing the pool of creative ideas, but they also indirectly spur the diffusion of existing ideas and technologies. Data on knowledge workers were obtained from Eurostat and reflects average between years 2002 to 2006. Data were taken from Eurostat’s Labour Force Survey.

yy B1.3 Value added share of creative and cultural industries A direct measure of the relative importance of the creative industries is their value added share in the economy. Data were obtained from KEA (2006) (Table 3: Contribution of the European cultural & creative sector to the European and national economies). The definition by KEA of the cultural and creative sector overlaps with Hartley’s definition (Hartley, 2008) as described in Box 1, although Hartley also incorporates creative inputs (not only outputs), in particular in the services sector and the most recent developments in terms of user created activities and open networks.

B2 Creativity in R & D According to Howkins (2005), ‘the enforcement of IPR regimes, covering copyrights, patents, trademarks and licensing are fundamental not only to attract FDI (foreign direct investments) but also to create incentives for businesses to adopt new methods of production, and new knowledge.’ Intellectual property (IP) is considered a fundamental factor in the creative economy, regulating how people share ideas, and how ideas are rewarded and accessed. The following indicators are used to capture performance in creativity in R & D:

yy B2.1 Patent applications per million population Patent applications are one measure of ongoing ability to innovate and to create. Patents reflect the initial discovery and registration of innovative ideas (Creative Community Index, 2006). The capacity of firms to develop new products will 58


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determine their competitive advantage. The number of patents is one indicator of the rate of new product innovation. Patent applications are also a measure of the number of ideas resulting from R & D activities. In the European Innovation Scoreboard EPO patent applications are used as an innovation indicator, but application barriers for EPO patents are higher than for national patent applications. Instead of EPO patents we thus use resident patent filings from WIPO — World Intellectual Property Organisation.

yy B.2.2 Scientific publications per million population This indicator measures the number of scientific research publications as measured in the Thomson Reuters Web of Science database. Publications can be used as a measure of the creativity of university (but also enterprise) researchers. Being published implies that papers have been accepted after a peer review process. The actual number of ‘academic ideas’ that are published is only a (small) share of all submitted papers.

yy B2.3 Trademark applications per million population A trademark is a distinctive sign, which identifies certain goods or services as those produced or provided by a specific person or enterprise. Trademarks are an important innovation indicator, especially for the service sector (Frietsch, 2005). The EIS uses data on Community trademarks, but application barriers for Community trademarks are higher than for national trademark applications. We thus use data on direct resident trademark applications from WIPO.

yy B2.4 Capacity for innovation The data on capacity for innovation was taken from ‘The Global Competitiveness Report 2007–08’ published by the World Economic Forum. The indicator reflects answers to the question how companies obtain technology (1 = exclusively from licensing or imitating foreign companies, 7 = by conducting formal research and pioneering their own new products and more intense and creative R & D activities).

B3 Design activities Design is an important factor driving competitiveness and innovation, both at the micro and macro level (Bitard and Basset, 2008). The following indicators are used to capture performance:

yy B3.1 Importance of design staff for innovation The Innobarometer 2007 asks companies if in the two years prior to the survey the company’s design staff has been a major source of ideas for the innovative

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activities of that company 6. This indicator can be used as a direct proxy for the importance of design activities for innovation.

yy B3.2 Number of designers per million population According to Vinodrai (2005), designers develop and use their skills in a variety of employers (firms and economic sectors). Designers are able to transfer knowledge across via labour mobility, benefiting firms in general. The number of designers was obtained from the European Design Report supplement, based on the World Development Indicators database, World Bank in 2006. The total number of designers in Europe in 2006 amounted to 447 000, generating a turnover of more than EUR 36 billion (European Design Report, 2006).

yy B3.3 Community design applications per million population Design applications reflect the activities relating to ‘the outward appearance of a product or part of it resulting from the lines, contours, colours, shape, texture, materials and/or its ornamentation’ 7. For Community designs the same argument to higher application barriers holds as for EPO patents and Community trademarks, but as national design applications from WIPO are not available from 2003 onwards, we have chosen to use Community design data.

yy B3.4 Production process sophistication NZIER (2003) defines design as a process applied along the value added chain. It contributes to minimising production input costs, through more efficient production systems and it helps to maximise revenues, by providing a tool to create a product that satisfies customers’ requirements. According to Walsh et al. (1988), the use of design affects not only qualitative factors, such as product’s performance, reliability, appearance, safety, and ease of but also cost factors, through its impact on how easy the product is to manufacture and its life cycle cost to the user. Production process sophistication is used as a proxy to measure the relative importance of design in the production system in terms of efficiency. Data on production process sophistication were taken from ‘The Global Competitiveness Report 2007–08’ published by the World Economic Forum. The indicator reflects answers to the question: ‘In your country, production processes use (1 = labourintensive methods or previous generations of process technology, 7 = the world’s best and most efficient process technology)’. 6

7

i.e. Question 7 in the Innobarometer 2007: ‘In the last two years, have any of the following been a major source of ideas for the innovative activities of your company? (a) Your company’s production engineers or technicians: Yes/ No/(No such unit/department)/Do not know; (b) Your company’s marketing department: Yes/No/(No such unit/ department)/Do not know; (c) Your company’s design staff: Yes/No/(No such unit/department)/Do not know; (d) Your company’s management: Yes/No/(No such unit/department)/Do not know; (e) Your company’s research department: Yes/No/(No such unit/department)/Do not know’. Definition taken from the website of the Office of Harmonisation for the Internal Market (OHIM): http://oami. europa.eu/ows/rw/pages/RCD/design.en.do

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yy B3.5 Uniqueness of product design The data on uniqueness of product design were taken from ‘The Global Competitiveness Report 2001–02’ published by the World Economic Forum. The indicator reflect answers to the question ‘Product designs are: (1 = copied or licensed from abroad, 7 = developed locally). Unique product designs are assumed to be a proxy for the success of design activities.

B4 Competitiveness in design Various studies (Roy et al., 1998; Potter et al., 1991; Walsh et al., 1988; Hertenstein et al., 2005) clearly indicate that there is a relationship between investment in design and innovation and business performance. As summarised by Hertenstein et al. (2005), ‘results provide strong evidence that good design boost firms’ operating performance and growth, which is rewarded by stock market premiums’. The following indicators are used to capture performance:

yy B4.1 Design related services as a percentage of services export Following the definition by UNCTAD (cf. Table 5.1 in United Nations, 2008) designrelated services comprise the following three subcategories: yy Advertising and market research and public opinion polling services (Advertising): (EBOPS 278, level 3) ‘Advertising and market research services transacted between residents and non-residents cover the design, creation, and marketing of advertisements by advertising agencies; media placement, including the purchase and sale of advertising space; exhibition services provided by services fairs; the promotion of products abroad; market research; and public opinion polling abroad on various issues’. yy Architectural, engineering and other technical services (Architectural) (EBOPS 280, level 3): Architectural, engineering and other technical services cover resident and non-resident transactions related to architectural design of urban and other development projects; planning and project design and supervision of dams, bridges, airports, turnkey projects, etc.; surveying, cartography, product testing and certification, and technical inspection services’. yy Research and development services (R & D) (EBOPS 279, level 3): Research and development services cover those services that are transacted between residents and non-residents and associated with basic research, applied research, and experimental development of new product and processes. In principle, such activities in the sciences, social sciences and humanities are covered; included is the development of operating systems that represent technological advances’. 61


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The three subcategories of creative services data and services exports were obtained from UNCTAD’s ‘Global databank on world trade in creative products’ and consisted of the average data for 2003 to 2005.

yy B4.2 Exports design as a percentage of merchandise exports Data is based on the 1996 version of the Harmonised System (HS 1996) for creative goods. The classification of ‘creative goods’ and, in specific, design was based on the Unesco Framework for Cultural Statistics. Design is defined as comprising fashion (code 49); interior (code 50); toys (code 17); jewellery (code 12) and graphic (code 11). Both design data and merchandise exports were obtained from UNCTAD’s ‘Global databank on world trade in creative products’ and consisted of the average data for 2003 to 2005.

yy B4.3 Value chain breadth Related to Business sophistication, data on value chain breadth were taken from ‘The Global Competitiveness Report 2007–08’ published by the World Economic Forum. The indicator reflect answers to the question ‘Exporting companies in your country (1 = are primarily involved in resource extraction or production, 7 = not only produce but also perform product design, marketing sales, logistics, and after-sales services)’.

yy B4.4 Extent of branding The data on extent of branding were taken from ‘The Global Competitiveness Report 2004–05’ published by the World Economic Forum. The indicator reflect answers to the question ‘Companies in your country that sell internationally (1 = sell into commodity markets or to other companies that handle marketing, 7 = have welldeveloped international brands and sales organisations)’.

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Do creativity and design drive innovation performance? Correlation results at indicator level Innovativeness is measured using the composite indicator scores from the EIS 2008 for each of its innovation dimensions and overall performance as captured by the Summary Innovation Index (SII). The EIS 2008 distinguishes seven different dimensions 8. The first two dimensions — the Enablers — capture the main drivers of innovation that are external to the firm: yy Human resources capture the availability of high-skilled and educated people with performance being the summary of five different indicators. yy Finance and support capture the availability of finance for innovation projects and the support of governments for innovation activities with performance being the summary of five different indicators. The next three dimensions — Firm activities — capture innovation efforts that firms undertake recognising the fundamental importance of firms’ activities in the innovation process: yy Firm investments cover a range of different investments firms make in order to generate innovations with performance being the summary of three different indicators. yy Linkages & entrepreneurship capture entrepreneurial efforts and collaboration efforts among innovating firms and also with the public sector with performance being the summary of four different indicators. yy Throughputs capture the Intellectual Property Rights (IPR) generated as a throughput in the innovation process and Technology Balance of Payments flows with performance being the summary of four different indicators. yy The final two dimensions — Outputs — capture the outputs of firm activities as: yy Innovators capture the number of firms that have introduced innovations onto the market or within their organisations, covering technological and non-technological innovations with performance being the summary of three different indicators.

8

For more details, refer to both the EIS 2008 report and the accompanying EIS 2008 Methodology Report, available at http://www.proinno-europe.eu/metrics

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yy Economic effects capture the economic success of innovation in employment, exports and sales due to innovation activities with performance being the summary of six different indicators. The correlation results between the creativity and design indicators and the EIS innovation dimensions and SII reveal that several of the indicators are strongly correlated with innovation (refer to Annex 6 for detailed results). yy Most correlation coefficients for the indicators capturing Creative education are significant. The coefficients are significant and high for the EIS dimension Human resources, a result which can be explained by the fact that this EIS dimension also includes education related indicators. Public expenditure on education and the extent of staff training correlate best with innovation performance. yy Except for language skills the indicators capturing Self-expression correlate well with the EIS dimensions. In particular a high degree of Self-expression values relates well with Throughputs and the Summary Innovation Index. yy The indicators capturing Openness & Tolerance correlate less well with the EIS dimensions, with the exception of the Share of foreign students and Brain drain. The indicators correlate best with the EIS dimension Throughputs. These results are in contradiction to the importance assigned to Tolerance by, inter alia, Florida and Tinagli (2004) which can be partly explained by the use of different indicators to measure Tolerance 9. yy The Creative sector indicators correlate well with Enablers and Firm activities, but less well with Outputs. This would suggest that creativity is more important for creating favourable input and throughput conditions but less so for the actual successful marketing of the outputs of the innovation process. yy The indicators capturing Creativity in R & D correlate well with the EIS innovation dimensions, a result which can be explained by the fact that two of these indicators are included in the EIS dimension Throughputs (patents and trademarks, albeit at international rather than domestic levels) and that those scientific publications including at least one private and one public partner are included in the EIS dimension Linkages & entrepreneurship. yy Design activities correlates well with the EIS innovation dimensions, except for the indicator on the importance of design staff for innovation. Thus although more designers, more design applications, a more sophisticated production 9

Florida and Tinagli (2004) use data from the World Values Survey measuring to what degree a country reflects traditional as opposed to modern or secular values.

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process and a more unique product design seem to have a positive effect of the degree of innovativeness, the relative importance of design staff decreases with countries’ increasing innovation performance. This can be explained by the fact that in more innovative countries relatively more firms innovate by performing R & D and, and as R & D and design can be complementary (see Tether 2006) such firms may be less likely to report design staff as a major source of ideas for innovation 10. Another explanation could be that although design staff is important in the innovation process they are perceived to be the source of ideas for innovations (consistent with the definition used in this report that design ‘shapes’ ideas). yy The indicators measuring Competitiveness in design correlate well with the EIS innovation dimensions, in particular the Value chain breadth and the Extent of branding. However, exports of product design correlate negatively with five of the seven innovation dimensions. This may be because this indicator measures the volume of such exports (fashion, interior, toys, jewellery and graphic) and not necessarily their quality or, indeed, whether the design activities that lead to the exports took place in that country. Therefore, this measure of exports of product design is only a weak indicator of a country’s success in either innovation or economic terms 11.

10

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cf. footnote 5 showing the question from the Innobarometer 2007 on the major sources of ideas for a firm’s innovative activities. Another explanation is that, according to the Creative Economy Report (UN, 2008), it is problematic to measure trade in the creative economy, considering that available information sources have been developed to capture physical and financial flows, which are not always clear in the case of the creative economy. According to the report ‘much of the value in the creative economy has been a result of trade in physical products that are of relatively low value as materials but that contains real value in intellectual property’. While conventional trade measures focus on the flow of material goods, by either registering their price or weight, in the case of the creative economy, it is impossible to separate the intellectual property value or even to recognise it. Moreover, digitisation is facilitating the transfer and trade in intellectual property online, which is not monitored. For these reasons, trade in the creative economy is relatively invisible. Moreover, with rapid technological change, the relationships between goods and value are constantly changing. Traditional measures used in the evaluation of economic activity, such as output or turnover, may not be appropriate for the creative economy, since a significant proportion of this economy does not register in trade or economic statistics as the activity may take place in the informal economy. Based on the difficulties to properly measure trade in the creative economy, the indicator exports on product design may not reflect a country’s success in either innovation or in economic terms, contributing to the explanation on why it correlates negatively with five out of seven of the EIS innovation dimensions.

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Relative performance in Creative climate and Creativity and design The indicators discussed in Section 3 are used to measure average performance by using composite scores. The methodology for calculating these composite indicators is explained in Annex 1. Annex 2 shows the data for all indicators. Annex 3 shows the normalised data as calculated using the methodology as explained in Annex 1. The results for each country are shown in Annex 5. Sweden is the best performing country in Creative climate, closely followed by Denmark (Figure 3). Bulgaria, Poland and Romania show the least good performance. Figure 3 also shows that the relative importance of the different Creative climate dimensions differs among the EU Member States. Performance in Creative education is a relative strength 12 in Ireland and Finland and a relative weakness in Latvia. Self-expression is a relative strength in Latvia, Lithuania and Slovakia and a relative weakness in Ireland, Greece, Cyprus, Hungary and Portugal. Openness & tolerance is a relative strength in Bulgaria, Greece and Hungary and a relative weakness in Slovakia and Finland. 0.800 0.700 0.600 0.500 0.400 0.300 0.200 0.100 0.000 RO PL BG SK HU PT LT EL LV C Z SI IT ES EU MT FR C Y EE LU IE FI AT DE UK BE NL DK SE C REATIVE EDUC ATION

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Figure 3: Countries’ relative performance in Creative climate

Denmark is the best performing country in Creativity & design, followed by Sweden (Figure 4). Bulgaria and Romania show the least good performance. Figure 4 also shows that the relative importance of the different Creativity & design dimensions 12

Relative strengths (weaknesses) are defined as those dimensions with an overall share in explaining the Creative climate composite indicator being 33 % above or 33 % below the share of the EU-27.

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differs among the EU Member States. Performance in the Creative sector is a relative strength in Bulgaria, Estonia and Lithuania and a relative weakness in Italy, Malta, Austria, Portugal and Romania. Creativity in R & D is a relative strength in Bulgaria, the Czech Republic, Malta and Austria and a relative weakness in Lithuania. Design activities are a relative strength in Luxembourg and a relative weakness in Bulgaria, Estonia, Hungary, Lithuania, Poland and Romania. Competitiveness in design is a relative strength in Latvia, Lithuania, Hungary, Poland, Romania and Slovakia and a relative weakness in Ireland and Luxembourg. 0.900 0.800 0.700 0.600 0.500 0.400 0.300 0.200 0.100 0.000 BG RO SK HU C Y PL LV LT MT PT EE C Z EL EU SI ES IE LU IT AT FR UK BE DE FI NL SE DK C REATIVE SEC TOR

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Figure 4: Countries’ relative performance in Creativity & design

0.900 0.800 0.700 0.600 0.500 0.400 0.300 0.200 0.100 0.000 RO BG PL SK HU LT PT LV EL C Z MT C Y SI EE EU ES IT IE LU FR AT FI UK BE DE NL SE DK C REATIVE C LIMATE

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Figure 5: Countries’ overall performance: the DCI Index

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Figure 5 shows the overall performance in the seven dimensions capturing the Creative climate and Creativity & design. Belgium, Denmark, Germany, the Netherlands, Sweden, Finland and the UK are in the group of best performers. Ireland, France, Luxembourg and Austria are in the group of second-best performers. The Czech Republic, Estonia, Greece, Spain Italy, Cyprus, Malta, and Slovenia show a moderate performance and Bulgaria, Latvia, Lithuania, Hungary, Poland, Portugal, Romania and Slovakia show weakest performance.

Creativity, design and innovation performance Our ‘flow-chart model’ predicts that the dimensions capturing the Creative climate should have a positive impact on Creativity and design. Simple correlation results between the different creativity and design dimensions and the EIS innovation dimensions support this prediction with almost all correlation results being significant 13. The results show a strong correlation between Creativity and design and Innovation performance as measured by the EIS innovation dimensions. 0.70 FI

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However, these strong correlation results might be the result of what is known as spurious correlation, where two indicators appear to be strongly correlated not because they actually are, but because each of them is correlated with an unobserved third indicator. We therefore repeat the correlation analysis but this time we control for differences in per capita GDP, as many of the composite indicators correlate positively with per capita GDP.

The correlation results controlling for differences in per capita GDP confirm that the Creative climate dimensions Creative training and Self-expression have a favourable effect on Creativity and design activities. But Openness & tolerance no longer seems to have a positive effect on these dimensions, nor on innovation performance as measured by the EIS dimensions. The results also confirm the strong correlation between Creativity and design and Innovation performance as measured by the EIS innovation dimensions for Enablers and Firm activities. For Outputs we only find a significant correlation between Creativity in R & D and Economic effects (refer to Annex 8 for detailed results). 13

These correlations are not shown in this report but are available upon request.

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Figures 6 and 7 visualise the relation between performance in Creative 0.60 UK DK IE AT climate and Creativity & design and InLU BE 0.50 NL SI CY FR EE novation performance. Countries showCZ 0.40 ES PT IT ing a stronger performance in Creative EL SK HU MT 0.30 LT climate also show a better innovation RO P L LV BG 0.20 performance. However, as Figure 6 clearly shows, one could distinguish three 0.10 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 different groups of countries, and within C reativity & design each group the link between Creative cliFigure 7: Creativity & design and Innovation mate and Innovation is less clear. Countries showing a stronger performance in Creativity & design also show a better innovation performance. However, as shown in Figure 7, one could distinguish three different groups of countries, and within two of these groups the link between Creativity & design and Innovation is less clear. In particular within the dimensions Creative sector and Creativity in R & D the relation with innovation is strong as shown in Figure 8. 0.70

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Figure 9: DCI Index and Innovation performance

Overall performance in creativity and design as measured by the DCI index is positively correlated to overall innovation performance as measured by the SII (Figure 9). Figure 9 also provides some evidence about differences in relative strength in creativity and design among the Member States. The countries located in the green coloured area show a relative strength in creativity and design as opposed to the countries located in the orange coloured area. In particular Belgium, Bulgaria, Spain, Italy, Latvia, Malta, and the Netherlands perform relatively well in creativity and design given their innovation performance. Countries performing relatively less well include Ireland, Cyprus, Finland and Sweden.

Conclusions and recommendations Creativity and design are important features of a well-developed knowledge economy both having a positive impact on countries’ innovation performance. However, given the current lack of quantitative indicators it is not possible to directly measure the degree of creativity and design. We, therefore, have had to rely on a range of socalled proxy indicators indirectly measuring countries’ performance in creativity and design. For benchmarking countries a scoreboard approach has been used similar to that used in the European Innovation Scoreboard (EIS). 70


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A flow-chart model has been developed linking the Creative climate (measured by three distinct dimensions or groups of indicators) to Creativity and design (measured by four distinct dimensions) to Innovation (measured by the composite indicator scores from the EIS 2008). The statistical results show that there are strong relations between creativity, design and innovation. The best performing countries in creativity and design are the same countries — the innovation leaders and innovation followers — that show superior innovation performance in the EIS. Countries with a good creative climate tend to have higher levels of R & D and design activities and also strong overall innovation performance. These findings point to the need to consider design and other non-R & D activities as part of the broader approach to innovation policy as well as to the strong links between creativity and innovation. Creative education is the dimension which shows the strongest relation to innovation. This seems to suggest that policies aimed at improving levels of educational attainment and policies aimed at improving creative thinking in education will, after a number of years, have a positive effect on a society’s innovative performance. But the Scoreboard approach used in this report is seriously hampered by a lack of adequate indicators. For truly understanding the linkages between creativity, design and innovation new data are needed to construct more precise and direct indicators. Measuring creativity will be difficult, as creativity is a multidimensional phenomenon that can comprise technological (invention), economic (entrepreneurship) and artistic/ cultural creativity. Each of these would require a different set of indicators for which the data could be collected by special surveys focusing on some key attributes of creativity. Similar problems may be expected for measuring design, as different definitions for design are being used. The role of design should be better captured in the Community Innovation Survey (CIS), as the current CIS does not include a question on the role of design in product or process innovation. The CIS does include a question on if firms have made significant changes to product design as part of their marketing innovation, but this question does not fully capture the importance of design. References Arundel, A. (2003). NIS Indicators and Innovation: Are there European modes of innovation? Brussels: European Commission, DG Enterprise. Arundel, A. and Hollanders, H. (2005). EXIS: An Exploratory Approach to Innovation Scoreboards. Brussels: European Commission, DG Enterprise. Bell, A. and Stolarick, K. (2008). Funding to Arts and Cultural Organizations by the City of Toronto, 1990-2008. . 2008-WP-001.Toronto:Martin Prosperity Institute. Bitard, P. and Basset, J. (2008). Design as a tool for innovation. INNO-GRIPS Mini Study 05. 71


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Business Week (1996). Educating for the Workplace through the Arts. Carlino, G.A. (2001). Knowledge spillovers: Cities role in the New Economy, Federal Reserve Bank of Philadelphia Business Review, 110: 388-410. Danish Design Centre (2003). The economic effects of design. Copenhagen: National Agency for Enterprise and Housing. DTI (2005). Creativity, Design and Business Performance. DTI Economics Paper No. 15.London: DTI. Eger, J.M. (2003). The Creative Community. San Diego: The California Institute for Smart Communities. Eurobarometer (2007). European Cultural Values. Special Eurobarometer 278. Brussels: European Commission. Eurostat (2007). Cultural Statistics Pocketbook. Luxembourg: EUROSTAT. Florida, R. (2002a). The Rise of the Creative Class. New York: Basic Books. Florida, R. (2002b). Bohemia and Economic Geography, Journal of Economic Geography, 2, 55-71. Florida, R. and Tinagli, I. (2004). .Europe in the Creative Age. London: Carnegie Mellon Software Industry Center/DEMOS. Frietsch, R. (2005). Comments on the European Innovation Scoreboard 2005. Karlsruhe: Fraunhofer ISI. Galligan, A. M. (2001). Art, Culture and the National Agenda project. New York: Rockefeller Foundation. Hartley, J. (2005). Creative Industries. Malden, MA: Blackwell. Hertenstein, J.H., Platt, M.B. and Veryzer, R.W. (2005). Impact of Design Effectiveness on Corporate Financial Performance, The Journal of Product Innovation Management, 22, 3-21. Howkins, J. (2005). The Creative Economy: Knowledge-Driven Economic Growth.Paper presented at the Asia-Pacific Creative Communities: A Strategy for the 21st Century Senior Expert Symposium Jodhpur, India, 22-26 February 2005. Retrieved September 2009 from: http://www.unescobkk.org/fileadmin/user_upload/culture/Cultural_Industries/presentations/Session_Two_-_John_Howkins.pdf Hui, D., Ng, C., Mok, P., Ngai, F., Wan-kan, C. and Yuen, C. (2005). A Study on Creativity Index. Home Affairs Bureau. Hong Kong: The Hong Kong Special Administrative Region Government. Inglehart, R. and Welzel, C. (2004). What Insights can Multi-Country Surveys Provide about People and Societies? Comparative Politics Newsletter. Washington, DC: American Political Science Association. 72


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KEA (2006). .The Economy of Culture in Europe. Study prepared for the European Commission (Directorate-General for Education and Culture). Lambert, R. (2006). .Measuring and modelling design in innovation. Presented at Blue Sky II: What Indicators for Science, Technology, and Innovation Policies in the 21st Century? - OECD and Statistics Canada, September 2006. NZIER (New Zealand Institute of Economic Research) (2003). Building a case for added value through design – Report to Industry New Zealand. Potter, S., Roy, R., Capon, C.H. , Bruce, M., Walsh, V. and Lewis, J. (1991). The Benefits and Costs of Investment in Design: Using Professional Design Expertise in Product, Engineering and Graphics Projects. The Open University / UMIST – Design Innovation Group. Power, D. (2004). The Future in Design: The Competitiveness and Industrial Dynamics of the Nordic Design Industry. Uppsala, Sweden: Centre for Research on Innovation and Industrial Dynamics. Roy, R., Riedel, J., and Potter, S. (1998). Market Demands that Reward Investment in Design (Madrid). Design Innovation Group. Sacco, P.L. and Segre, G. (2006). Creativity, cultural investment and local development: a new theoretical framework for endogenous growth. Venezia: Universita Iuav di Venezia. Stolarick, K., Florida, R. and Musante, L. (2005). Montreal’s Capacity for Creative Connectivity: Outlook & Opportunities. Montreal, QC: Catalytix. Swann, P. and Birke, D. (2005). How do Creativity and Design Enhance Business Performance? A Framework for Interpreting the Evidence. ‘Think Piece’ for DTI Strategy Unit. Tether, B. (2006). Design in Innovation: Coming out from the Shadows of R&D? Presented at DTI Event to launch the results of the UK Innovation Survey 2005, London, 3 July 2006. Therrien, P. (2003). City and innovation: Different size, different strategy. Paper presented to the DRUID summer conference, Creating, Sharing and Transferring Knowledge, Copenhagen, June 12-14, 2003. United Nations (2004). Creative Industries and Development. Washington, DC: United Nations. United Nations (2008). Creative Economy Report 2008: The Challenge of Assessing the Creative Economy, towards Informed Policy-making. Vinodrai, T. (2005). Locating design work: Innovation, institutions and local labor market dynamics. Toroonto: University of Toronto. Walsh, V.M., Roy, R. and Bruce, M. (1988). Competitive by design, Journal of Marketing Management, Vol.4 (2), 201-216. World Bank (2003). Urban development needs creativity: How creative industries affect urban areas. Development Outreach, November. 73


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Annex 1: Methodology for calculating the DCI composite indicators For each of the seven dimensions average performance will be summarised by calculating a composite indicator as explained in the following steps:

Step 1: Identifying outliers Positive (negative) outliers are identified as those values which are higher (smaller) than the mean value plus (minus) two times the standard deviation 14. These outliers are not included in determining the maximum and minimum scores in the normalisation process (cf. Step 3).

Step 2: Transforming data Most of the indicators are fractional indicators with values between 0 and 100 %. Some indicators are unbound indicators, where values are not limited to an upper threshold (e.g. the Intellectual property indicators, Publications and Art schools). These indicators can be highly volatile over time and have skewed data distributions (where most countries show low performance levels and a few countries show exceptionally high performance levels). For most indicators we use three to six-year average values and all indicators where initial skewness (after having adjusted for outliers) is below – 0.50 or above 0.50 are transformed using a power root transformation such that skewness after the transformation is between – 0.50 and 0.50.

Step 3: Determining maximum and minimum values The maximum (minimum) score is the highest (lowest) value found within the group of EU-27 countries excluding the outliers identified in Step 1.

Step 4: Calculating rescaled values Rescaled values are calculated by first subtracting the minimum value and then dividing by the difference between the maximum and minimum value. The maximum rescaled value is thus equal to 1 and the minimum rescaled value is equal to 0. For positive and negative outliers, these rescaled values are limited to the upper value of 1 respectively lower value of 0.

Step 5: Calculating composite indicators For each dimension a composite indicator is calculated as the unweighted average of the rescaled scores for all indicators within the respective dimension.

Step 6: Calculating EU average 14

This approach follows the well-adopted Chauvenet’s Criterion in statistical theory.

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For the EU average we use the unweighted average of all EU-27 Member States.

Annex 2: Data Creativity and Design Scoreboard indicators BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK

A1.1

A1.2

A1.3

A1.4

A1. 5

A2.1

A2.2

A2.3

A3.1

A3.2

A3.3

A3.4

A3.5

A3.6

1.24 0.52 0.68 0.74 0.23 2.97 2.40 0.36 0.23 0.49 0.17 1.32 0.43 0.59 0.00 0.30 0.00 0.86 0.73 0.10 0.76 0.18 2.00 0.37 3.43 1.11 0.93

5.7 3.4 4.4 5.8 4.9 4.3 5.6 3.3 3.8 4.8 3.4 4.9 4.1 4.1 4.2 3.6 4.8 5.2 5.2 4.0 3.5 3.7 4.1 3.7 6.0 5.2 4.6

7.34 1.36 3.15 10.56 5.31 2.79 6.23 3.37 4.27 6.42 5.09 6.03 2.34 2.58 9.41 3.36 3.33 6.59 6.99 2.67 4.18 1.07 5.04 2.31 7.19 8.80 6.24

16.38 12.06 14.42 19.56 21.05 17.18 22.15 16.25 17.22 — 24.87 12.02 10.80 12.16 — 12.90 20.45 11.92 20.60 11.30 18.50 14.33 12.07 11.74 18.45 17.35 21.43

5.4 2.8 4.5 5.9 5.5 4.7 5.2 3.9 4.0 5.0 3.5 3.6 4.0 4.3 5.1 3.6 4.2 5.5 5.6 3.7 3.9 3.5 4.4 4.2 5.3 5.8 5.2

74.0 59.0 61.0 88.0 67.0 89.0 34.0 57.0 44.0 51.0 41.0 78.0 95.0 92.0 99.0 42.0 92.0 91.0 62.0 57.0 42.0 47.0 91.0 97.0 69.0 90.0 38.0

78.0 21.0 73.0 79.0 77.0 87.0 39.0 46.0 80.0 59.0 51.0 53.0 57.0 44.0 84.0 48.0 51.0 78.0 66.0 38.0 27.0 42.0 68.0 83.0 82.0 93.0 74.0

52.0 24.0 42.0 59.0 55.0 29.0 51.0 — 43.0 47.0 49.0 — 32.0 33.0 — 25.0 — 66.0 48.0 29.0 31.5 22.0 32.5 40.0 63.0 64.0 57.0

10.38 3.59 4.86 8.03 10.86 1.87 5.42 2.41 2.14 11.12 2.02 26.93 2.02 0.47 — 3.19 5.71 4.63 14.56 0.44 3.43 1.58 1.06 0.98 2.64 8.56 14.53

7.58 8.60 0.27 0.10 1.03 1.30 3.19 3.90 8.34 7.70 18.13 3.50 6.31 7.50 6.34 2.80 10.40 8.50 4.91 4.70 5.79 — 13.35 7.90 1.01 — 0.75 — 45.21 35.50 0.71 0.40 2.70 3.10 3.53 4.30 9.59 10.20 0.16 0.40 3.18 3.40 0.16 — 0.42 — 0.19 — 1.44 1.30 4.10 4.36 6.03 —

53.6 44.3 27.7 33.8 49.3 47.1 36.0 67.7 51.7 46.9 45.2 58.3 47.3 43.0 31.4 32.8 84.7 64.7 36.4 42.6 45.2 — 18.4 22.0 28.7 22.6 66.9

17.0 9.0 8.0 14.0 14.0 15.0 25.0 15.0 15.0 13.0 18.0 13.0 18.0 4.0 22.0 19.0 20.0 13.0 14.0 8.0 10.0 11.0 9.0 6.0 11.0 15.0 13.0

4.5 2.1 3.8 4.7 4.6 3.8 5.4 3.5 4.3 3.9 3.3 3.7 3.3 3.1 4.3 3.5 3.7 5.0 4.9 3.0 3.9 2.4 4.0 3.0 5.2 4.7 4.9

B1.1 B1.2 B1.3 B2.1 B2.2 B2.3 B2.4 B3.1 B3.2 B3.3 B3.4 B3.5 B4.1 B4.2 B4.3 B4.4 BE BG CZ DK DE EE IE EL ES FR IT

32.63 19.93 17.85 25.53 21.66 27.54 35.64 25.29 21.16 22.18 18.30

22.86 17.70 11.32 26.70 19.14 17.96 18.50 17.36 19.00 19.46 11.66

2.60 1.20 2.30 3.10 2.50 2.40 1.70 1.00 2.30 3.40 2.30

49 33 60 310 310 21 189 44 69 227 134

1288 764 223 878 596 918 1723 804 940 803 585 939 1033 369 737 520 743 1248 880 1022 722 674

5.1 2.9 4.3 5.5 6.1 3.7 4.4 3.0 3.8 5.5 4.7

42.0 — 21.0 — 13.9 314 26.0 2030 17.2 970 6.9 468 40.7 1927 55.5 767 24.5 489 38.8 198 34.5 258

117 1 34 182 182 11 63 2 97 85 168

5.9 2.9 4.7 6.0 6.3 4.4 5.3 4.1 4.7 5.8 4.8

0.100 0.010 0.010 — 0.120 0.030 0.010 — 0.050 — —

0.020 0.020 0.020 0.030 0.010 0.020 0.000 0.030 0.040 0.030 0.070

5.7 3.2 4.7 6.0 6.2 3.8 5.2 3.9 4.9 6.0 5.6

5.5 2.6 4.1 6.0 6.7 2.7 4.8 3.6 4.3 6.1 5.6

0.100 0.010 0.010 — 0.120 0.030 0.010 0.050 — —

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B1.1 B1.2 B1.3 B2.1 B2.2 B2.3 B2.4 B3.1 B3.2 B3.3 B3.4 B3.5 B4.1 B4.2 B4.3 B4.4 CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK

17.45 22.57 25.68 27.79 21.33 21.72 33.47 19.22 21.85 18.18 12.84 22.54 17.62 29.24 26.23 31.69

20.52 13.78 16.88 21.84 14.66 12.36 23.42 13.16 14.86 10.74 10.24 16.54 11.88 24.94 24.44 18.92

0.80 1.80 1.70 0.60 1.20 0.20 2.70 1.80 1.20 1.40 1.40 2.20 2.00 3.10 2.40 3.00

21 48 20 36 72 54 134 275 57 15 41 153 35 310 285 302

411 681 144 596 287 565 432 738 492 373 163 1020 1505 765 1126 913 376 364 548 904 119 526 1024 754 414 525 1649 523 1923 869 1400 413

3.0 3.3 3.6 4.7 3.7 3.1 5.3 5.4 3.7 3.9 3.1 4.7 3.4 5.8 5.9 5.1

31.3 25.4 19.0 30.3 6.5 26.7 29.8 17.1 26.6 16.8 21.8 18.9 14.8 44.5 11.9 37.1

— 209 117 1971 248 — 2817 1157 157 625 — 851 436 381 1108 3081

25 15 6 182 13 11 134 182 19 44 1 34 15 101 126 74

3.9 3.9 4.2 5.5 4.2 4.2 5.8 5.9 3.7 4.2 3.4 4.5 3.9 6.0 6.1 5.4

0.010 0.060 0.020 — 0.040 0.010 — — 0.040 0.030 0.050 0.070 0.030 0.060 0.110 —

0.020 0.030 0.030 0.000 0.010 0.040 0.010 0.020 0.040 0.030 0.050 0.030 0.020 0.010 0.010 0.020

4.0 3.7 4.7 5.3 4.4 4.1 5.7 6.0 4.3 4.3 3.5 5.0 4.0 5.7 6.2 5.8

3.4 3.1 3.8 4.9 4.0 3.3 6.0 5.6 3.8 3.6 3.1 4.3 3.6 5.9 6.2 6.2

0.010 0.060 0.020 — 0.040 0.010 — — 0.040 0.030 0.050 0.070 0.030 0.060 0.110 —

Annex 3: Normalised data Creativity and Design Scoreboard indicators EU-27 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK

A1.1

A1.2

A1.3

A1.4

A1. 5

A2.1

A2.2

A2.3

A3.1

A3.2

A3.3

A3.4

A3.5

A3.6

0.51 0.72 0.46 0.53 0.55 0.31 1.00 1.00 0.39 0.31 0.45 0.27 0.74 0.43 0.49 0.00 0.35 0.00 0.60 0.55 0.21 0.56 0.28 0.91 0.39

0.43 0.89 0.04 0.41 0.93 0.59 0.37 0.85 0.00 0.19 0.56 0.04 0.59 0.30 0.30 0.33 0.11 0.56 0.70 0.70 0.26 0.07 0.15 0.30 0.15

0.46 0.75 0.03 0.25 1.00 0.51 0.21 0.62 0.28 0.38 0.64 0.48 0.59 0.15 0.18 1.00 0.27 0.27 0.66 0.71 0.19 0.37 0.00 0.48 0.15

0.47 0.49 0.11 0.32 0.77 0.90 0.56 1.00 0.48 0.57 — 1.00 0.11 0.00 0.12 — 0.19 0.85 0.10 0.86 0.04 0.68 0.31 0.11 0.08

0.44 0.79 0.00 0.42 1.00 0.83 0.50 0.71 0.17 0.21 0.63 0.00 0.04 0.21 0.33 0.67 0.04 0.29 0.83 0.88 0.08 0.17 0.00 0.38 0.29

0.53 0.62 0.38 0.42 0.83 0.51 0.85 0.00 0.35 0.15 0.26 0.11 0.68 0.94 0.89 1.00 0.12 0.89 0.88 0.43 0.35 0.12 0.20 0.88 0.97

0.54 0.77 0.00 0.70 0.79 0.76 0.91 0.18 0.29 0.80 0.48 0.36 0.39 0.45 0.26 0.86 0.32 0.36 0.77 0.59 0.17 0.00 0.23 0.62 0.85

0.48 0.68 0.05 0.45 0.84 0.75 0.16 0.66 — 0.48 0.57 0.61 — 0.23 0.25 — 0.07 — 1.00 0.59 0.16 0.22 0.00 0.24 0.41

0.46 0.81 0.39 0.49 0.69 0.84 0.22 0.53 0.28 0.25 0.85 0.24 1.00 0.24 0.01 — 0.36 0.55 0.47 1.00 0.00 0.38 0.19 0.12 0.11

0.40 0.64 0.02 0.11 0.32 0.69 1.00 0.55 0.56 0.82 0.45 0.52 1.00 0.11 0.08 1.00 0.08 0.28 0.34 0.77 0.00 0.32 0.00 0.04 0.00

0.45 0.84 0.00 0.12 0.38 0.75 0.34 0.73 0.27 0.83 0.46 — 0.77 — — 1.00 0.03 0.30 0.42 1.00 0.03 0.33 — — —

0.51 0.71 0.53 0.19 0.31 0.63 0.58 0.36 1.00 0.68 0.58 0.54 0.81 0.59 0.50 0.26 0.29 1.00 0.94 0.37 0.49 0.54 — 0.00 0.07

0.48 0.69 0.19 0.13 0.50 0.50 0.56 1.00 0.56 0.56 0.44 0.75 0.44 0.75 0.00 1.00 0.81 0.88 0.44 0.50 0.13 0.25 0.31 0.19 0.00

0.52 0.70 0.00 0.47 0.77 0.73 0.47 1.00 0.37 0.63 0.50 0.30 0.43 0.30 0.23 0.63 0.37 0.43 0.87 0.83 0.20 0.50 0.00 0.53 0.20

76


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FI SE UK

A1.1

A1.2

A1.3

A1.4

A1. 5

A2.1

A2.2

A2.3

A3.1

A3.2

A3.3

A3.4

A3.5

A3.6

1.00 0.68 0.62

1.00 0.70 0.48

0.73 0.93 0.62

0.67 0.58 0.94

0.75 0.96 0.71

0.54 0.86 0.06

0.83 1.00 0.71

0.93 0.95 0.80

0.31 0.72 1.00

0.16 0.41 0.53

0.12 0.40 —

0.21 0.09 0.98

0.31 0.56 0.44

0.93 0.77 0.83

B1.1 B1.2 B1.3 B2.1 B2.2 B2.3 B2.4 B3.1 B3.2 B3.3 B3.4 B3.5 B4.1 B4.2 B4.3 B4.4 EU27 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK

0.41

0.49

0.48

0.48

0.46

0.53

0.44

0.50

0.42

0.44

0.49

0.51

0.37

0.71

0.56

0.48

0.95 0.18 0.03 0.54 0.30 0.67 1.00 0.53 0.26 0.33 0.06 0.00 0.36 0.55 0.68 0.27 0.30 1.00 0.13 0.31 0.05 0.00 0.35 0.01 0.76 0.59 0.90

0.86 0.51 0.07 1.00 0.61 0.53 0.56 0.48 0.60 0.63 0.10 0.70 0.24 0.45 0.79 0.30 0.14 0.90 0.20 0.31 0.03 0.00 0.43 0.11 1.00 0.97 0.59

0.71 0.21 0.61 0.89 0.68 0.64 0.39 0.14 0.61 1.00 0.61 0.07 0.43 0.39 0.00 0.21 0.00 0.75 0.43 0.21 0.29 0.29 0.57 0.50 0.89 0.64 0.86

0.28 0.18 0.34 1.00 1.00 0.07 0.76 0.25 0.38 0.84 0.62 0.08 0.28 0.06 0.19 0.40 0.31 0.62 0.94 0.33 0.00 0.23 0.67 0.19 1.00 0.96 0.99

0.77 0.09 0.37 1.00 0.58 0.36 0.63 0.46 0.46 0.54 0.45 0.24 0.02 0.15 0.25 0.30 0.04 0.89 0.68 0.21 0.33 0.00 0.63 0.24 0.96 1.00 0.83

0.61 0.78 0.84 0.67 0.67 0.87 0.01 0.24 1.00 1.00 0.47 0.48 0.35 0.31 0.57 0.01 1.00 0.61 0.84 0.00 0.82 0.25 0.59 0.24 0.24 0.77 0.08

0.69 0.00 0.44 0.81 1.00 0.25 0.47 0.03 0.28 0.81 0.56 0.03 0.13 0.22 0.56 0.25 0.06 0.75 0.78 0.25 0.31 0.06 0.56 0.16 0.91 0.94 0.69

0.93 0.38 0.19 0.51 0.28 0.01 0.90 1.00 0.47 0.85 0.74 0.65 0.50 0.33 0.63 0.00 0.53 0.61 0.28 0.53 0.27 0.40 0.33 0.22 1.00 0.14 0.81

— — 0.15 1.00 0.52 0.24 0.96 0.41 0.26 0.06 0.11 — 0.07 0.00 0.97 0.10 — 1.00 0.61 0.03 0.34 — 0.46 0.22 0.19 0.59 1.00

0.71 0.01 0.27 1.00 1.00 0.11 0.44 0.02 0.62 0.56 0.94 0.21 0.14 0.06 1.00 0.13 0.11 0.79 1.00 0.17 0.34 0.00 0.27 0.14 0.64 0.76 0.50

0.86 0.00 0.45 0.90 1.00 0.34 0.66 0.24 0.45 0.83 0.48 0.17 0.17 0.28 0.72 0.28 0.28 0.83 0.86 0.10 0.28 0.00 0.38 0.17 0.90 0.93 0.69

0.50 0.04 0.21 0.88 0.88 0.21 0.29 — 0.42 0.83 0.83 — 0.29 0.21 — — — 0.71 0.63 0.00 — — 0.25 — 1.00 0.88 0.58

1.00 0.00 0.00 — 1.00 0.22 0.00 — 0.44 — — 0.00 0.56 0.11 — 0.33 0.00 — — 0.33 0.22 0.44 0.67 0.22 0.56 1.00 —

0.71 0.71 0.71 0.87 0.50 0.71 0.00 0.87 1.00 0.87 1.00 0.71 0.87 0.87 0.00 0.50 1.00 0.50 0.71 1.00 0.87 1.00 0.87 0.71 0.50 0.50 0.71

0.83 0.00 0.50 0.93 1.00 0.20 0.67 0.23 0.57 0.93 0.80 0.27 0.17 0.50 0.70 0.40 0.30 0.83 0.93 0.37 0.37 0.10 0.60 0.27 0.83 1.00 0.87

0.71 0.00 0.37 0.83 1.00 0.02 0.54 0.24 0.41 0.85 0.73 0.20 0.12 0.29 0.56 0.34 0.17 0.83 0.73 0.29 0.24 0.12 0.41 0.24 0.80 0.88 0.88

Normalised data for EU‑27 have been calculated as the unweighted average of the normalised data for the EU‑27 Member States.

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2009.4140_Can creativity be measured_OK.indd 78 ***

***

***

A3.6 Brain drain (reversed)

A3.5 Openness to other countries

A3.4 Degree of urbanisation 0.602 ***

0.799

0.577

***

0.743

***

***

***

***

***

***

***

***

***

***

***

***

***

0.442 **

0.866

0.474 **

0.764

0.651

0.902

0.711

0.817 ***

0.544 ***

0.593 ***

0.590

0.717

0.549

0.770

0.711

0.719

0.501

Throughputs

A3.3 Share of cultural employment of tertiary educated

***

***

***

0.423 **

0.604

0.663

***

***

***

***

Linkages & entrepreneurship

0.483 **

0.452 **

0.781

0.583

0.676

0.551

0.659

0.524

Firm investments

FIRM ACTIVITIES

A3.2 Share of foreigners in employment

A3.1 Share of foreign tertiary students

– 0.346 *

0.631 ***

A2.3 Self-expression values

A3 OPENNESS & TOLERANCE

0.397 **

A2.2 Share of population involved in artistic activities

A2.1 Language skills

A2 SELF-EXPRESSION

***

0.711

0.658 ***

0.788

***

A1.5 Extent of staff training

0.579 ***

A1.3 Public expenditure on education

0.640

0.441 **

0.626 ***

A1.2 Quality of educational system

0.405 **

Finance and support

A1.4 Share of tertiary students in cultural education

0.582 ***

A1.1 Number of art schools

A1 CREATIVE EDUCATION

A CREATIVE CLIMATE

Human resources

ENABLERS

0.441 **

0.418 **

0.459 **

0.354 *

0.387 **

0.346 *

0.470 **

Innovators

***

***

0.502 ***

0.538

0.478 **

0.487

0.495 **

0.402 **

0.380 *

Economic effects

OUTPUTS

Annex 4: Pearson correlations (2-tailed) with EIS dimensions

***

***

***

***

***

***

0.875 ***

0.331 *

0.519 ***

0.834

0.647

0.875

0.508

0.865

0.788

0.473 **

Summary Innovation Index


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12/9/2009 2:46:32 PM


0.644 ***

B1.3 Value added share of creative industries

**

0.567

0.671

0.587

B4.4 Extent of branding

0.566

***

0.705

***

0.600

B4.3 Value chain breadth ***

***

***

– 0.442 **

– 0.365 *

– 0.425 **

B4.2 Exports product design

0.461 **

0.572 **

0.643 ***

0.451 **

0.698 ***

***

0.415 *

0.686 ***

B4.1 Exports design related services

B4 COMPETITIVENESS IN DESIGN

B3.5 Uniqueness of product design

0.745 ***

0.590 ***

B3.4 Production process sophistication

0.613 ***

0.682 ***

0.574 ***

0.400 *

0.648 ***

0.650 ***

0.776 ***

0.667 ***

0.523 ***

0.456 **

0.637 ***

0.529 ***

0.737 ***

0.587 ***

B3.3 Community design applications

B3.2 Number of designers

B3.1 Importance of design staff for innovation

B3 DESIGN ACTIVITIES

B2.4 Capacity for innovation

B2.3 Trademark applications

0.745

B2.2 Scientific publications ***

0.660 ***

B2.1 Patent applications

Correlation is significant at the 1 % level. Correlation is significant at the 5 % level. * Correlation is significant at the 10 % level.

***

0.676 ***

B1.2 Share of knowledge workers

B2 CREATIVITY IN R & D

0.641 ***

B1.1 Share of creative occupations

B1 CREATIVE SECTOR

B CREATIVITY & DESIGN

0.635

0.654

***

***

– 0.449 **

0.476 **

0.601 ***

0.740 ***

0.530 ***

0.562 ***

0.669 ***

0.769 ***

0.617 ***

0.533 ***

0.620 ***

0.460 **

0.754

0.782

***

***

– 0.437 **

0.401 *

0.759 ***

0.833 ***

0.848 ***

0.638 ***

0.744 ***

0.655 ***

0.656 ***

0.614 ***

0.501 ***

0.335

0.374

*

*

0.404 *

0.451 **

0.396 **

0.398 **

0.336 *

0.548

0.539

***

***

0.397 *

0.560 **

0.592 ***

0.469 **

0.518 ***

0.408 **

0.457 **

0.803 ***

0.825 ***

– 0.523 ***

0.545 **

0.729 ***

0.899 ***

0.695 ***

0.566 ***

0.849 ***

0.842 ***

0.770 ***

0.533 ***

0.703 ***

0.533 ***


79

12/9/2009 2:46:33 PM


0.174

0.423

0.740

0.671

0.602

0.583

0.359

0.454

0.513

0.420

0.547

0.397

0.328

0.679

0.270

0.534

0.712

0.655

0.187

0.272

0.130

0.439

0.365

0.670

BULGARIA

CZECH REPUBLIC

DENMARK

GERMANY

ESTONIA

IRELAND

GREECE

SPAIN

FRANCE

ITALY

CYPRUS

LATVIA

LITHUANIA

LUXEMBOURG

HUNGARY

MALTA

NETHERLANDS

AUSTRIA

POLAND

PORTUGAL

ROMANIA

SLOVENIA

SLOVAKIA

FINLAND

4

1

9

UNITED KINGDOM 0.652

7

20

16

27

23

25

8

3

13

24

5

22

19

12

18

14

15

21

11

10

6

2

17

26

0.755

SWEDEN

0.686

BELGIUM

0.674

0.769

0.832

0.213

0.434

0.147

0.371

0.157

0.741

0.579

0.394

0.193

0.500

0.285

0.217

0.416

0.357

0.569

0.330

0.262

0.836

0.528

0.629

0.850

0.385

0.129

0.729

7

4

3

23

13

26

17

25

5

9

15

24

12

20

22

14

18

10

19

21

2

11

8

1

16

27

6

Rank

0.463

Rank

0.488

EU-27

Creative education

CREATIVE CLIMATE

0.523

0.939

0.768

0.742

0.579

0.142

0.113

0.227

0.538

0.883

0.628

0.170

0.932

0.467

0.540

0.535

0.362

0.438

0.478

0.321

0.280

0.638

0.672

0.820

0.522

0.143

0.690

0.516

15

1

5

6

11

26

27

23

13

3

10

24

2

18

12

14

20

19

17

21

22

9

8

4

16

25

7

Rank

Self- expression

0.758

0.558

0.411

0.141

0.304

0.100

0.331

0.179

0.686

0.673

0.582

0.446

0.606

0.232

0.434

0.691

0.541

0.532

0.553

0.495

0.634

0.639

0.712

0.549

0.363

0.250

0.641

0.485

1

11

19

26

22

27

21

25

4

5

10

17

9

24

18

3

14

15

12

16

8

7

2

13

20

23

6

Rank

0.741

0.788

0.770

0.241

0.510

0.195

0.305

0.286

0.632

0.777

0.294

0.255

0.534

0.317

0.300

0.276

0.561

0.741

0.517

0.374

0.517

0.368

0.737

0.854

0.345

0.212

0.749

0.486

7

2

4

25

14

27

19

22

9

3

21

24

11

18

20

23

10

6

13

15

12

16

8

1

17

26

5

Rank

Openness & CREATIVITY Tolerance & DESIGN

0.783

0.732

0.886

0.208

0.452

0.095

0.125

0.279

0.252

0.882

0.148

0.263

0.490

0.466

0.342

0.257

0.256

0.653

0.489

0.386

0.652

0.611

0.527

0.812

0.237

0.300

0.842

0.460

5

6

1

24

14

27

26

18

22

2

25

19

11

13

16

20

21

7

12

15

8

9

10

4

23

17

3

Rank

Creative Sector

0.645

0.916

0.778

0.208

0.613

0.135

0.367

0.197

0.810

0.717

0.353

0.239

0.395

0.182

0.195

0.207

0.525

0.800

0.531

0.244

0.468

0.389

0.811

0.870

0.497

0.263

0.588

0.479

8

1

6

22

9

27

17

24

4

7

18

21

15

26

25

23

12

5

11

20

14

16

3

2

13

19

10

Rank

Creativity in R & D

Annex 5: Composite indicator scores and rankings

0.717

0.658

0.744

0.190

0.337

0.134

0.304

0.168

0.675

0.788

0.306

0.126

0.831

0.176

0.235

0.346

0.620

0.626

0.442

0.420

0.649

0.184

0.735

0.857

0.254

0.109

0.752

0.472

7

9

5

21

16

25

18

24

8

3

17

26

2

23

20

15

12

11

13

14

10

22

6

1

19

27

4

Rank

Design activities

0.817

0.845

0.673

0.360

0.637

0.417

0.425

0.498

0.791

0.721

0.368

0.394

0.420

0.442

0.428

0.292

0.844

0.884

0.606

0.448

0.301

0.288

0.875

0.876

0.393

0.177

0.812

0.531

6

4

10

23

11

19

17

13

8

9

22

20

18

15

16

25

5

1

12

14

24

26

3

2

21

27

7

Competitiveness in design Rank

0.705

0.751

0.704

0.269

0.459

0.169

0.308

0.233

0.661

0.731

0.406

0.275

0.581

0.300

0.333

0.411

0.504

0.633

0.488

0.373

0.570

0.462

0.714

0.788

0.374

0.196

0.714

0.485

6

2

7

24

15

27

21

25

8

3

17

23

10

22

20

16

12

9

13

19

11

14

4

1

18

26

5

Rank

DCI index


80

12/9/2009 2:46:34 PM


0.564 “

0.891 “

0.471 “”

0.821 “

0.890

0.928 “

0.679 “

0.802 “

0.789 “

0.948

0.699 “

0.917 “

0.685 “

0.457 “”

0.746 “

0.370 *

0.388 *

0.762 “

Creativity & design

0.642 “

0.629 “

0.773 “

0.351 *

0.424 “”

0.571 “

0.374 *

0.433 “”

0.849 “

Creative climate

0.767 “

0.500 “

Competiliveness in design

0.666 “

0.736 “

Design activities

*** Correlation is significant at the 1 % level. ** Correlation is significant at the 5 % level. * Correlation is significant at the 10 % level.

DCI index

Creative climate Creativity & design

Creative sector Creativity in R&D Design activities Competitiven ess in design

Creative education Self-expression Openness & tolerance

Creative Creativity sector in R&D

0.717 “””

0.583 “ 0.764 “”” 0.627”””

0.741 “

0.452 “”

0.584 “

0.556 “

0.556 “

0.482 “”

0.775 “

0.672 “””

0.609 “

0.636 “

0.426 “”

0.656 “

0.675 “

0.334 *

0.381 *

0.739 “

0.390 “”

Economic effects

OUTPUTS

Linkages & Through- Innoentrepre puts vators neurship

0.610 “

0.671 “

0.601 “

0.641 “

0.383 “”

0.425 “”

0.615 “

0.423 “”

0.528 “

0.673 “

Firm invest ments

FIRM ACTIVITIES

0.537 “

0.754 “

0.463 “”

0.560 “

0.668 “

0.673 “

0.547 “

0.418 “”

0.684 “

Finance and support

0.451 “”

0.395 “”

0.466 “”

0.505 “

0.773 “

0.658 “

Human resources

ENABLERS

Annex 6: Partial correlations (controlling for per capita GDP) between Creativity and design dimensions and EIS dimensions

0.828 “

0.745 “

0.792 “

0.545 “

0.647 “

0.783 “

0.614 “

0.425 “”

0.397 “”

0.887 “

Summar V Innovation


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12/9/2009 2:46:35 PM

Measuring creativity and innovation based on knowledge capital investment

5. Measuring creativity and innovation based on knowledge capital investment 1

Tony Clayton (ONS), Mariela Dal Borgo (University of Warwick), Jonathan Haskel (Imperial College, London), Mark Franklin (ONS)

Abstract Economists and policymakers agree that ideas and innovation contribute to productivity and economic growth, but the transmission mechanisms are less clear. The motivation for this presentation is the question posed by Jorgensen (2007) — How would an economy produce more output without innovation? Jorgensen’s answer is to use the same ideas, but duplicate existing capital and labour inputs. Following this logic, innovation is represented by the production of more output over and above that which would occur simply by duplicating existing capital and labour 1

This is an edited extract of the non-technical summary of a longer paper: ‘An Innovation Index Based on Knowledge Capital Investment: Definition and Results for the UK Market Sector’ written by Clayton, Dal Borgo and Haskel. For specialist economists, our definition of innovation is TFP plus the part of capital deepening accounted for by new knowledge investment. It, therefore, follows the research program set out in the expanded view of capital and TFP measurement proposed by Corrado, Hulten and Sichel (2004, 2006), which builds, of course, in turn on the work on growth accounting set out for example in the Jorgenson volumes (Jorgenson, 2007). The motivation for the index builds on an argument made by Jorgenson (2007) in his evidence to the Gutierrez committee. An important point of this work is the Corrado, Hulten and Sichel argument that admission of intangible spending as building a knowledge asset requires both the recomputation of inputs, since knowledge/intangible capital is an additional input and also output (value added) since the capitalisation of intangible spending removes it from intermediate spending and so raises value added. Thus both output, inputs and TFP are recalculated relative to the case where intangible spending is treated as an expense. To economists familiar with this work, we hope this paper will still have some interest: we explicitly ask how TFP relates to the many innovation definitions that have been proposed and bring new data on the TFP and intangible spending in the UK economy at the industry level (relative to Giorgio Marrano, Haskel and Wallis, 2007, we have new data on design; we use the industry data on intangible investment in Gill and Haskel (2008) and present industry growth accounting results). The full paper can be accessed at: http://www.innovationindex.org.uk/

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Tony Clayton, Mariela Dal Borgo, Jonathan Haskel, Mark

inputs. Where does this extra output come from? In this presentation we assume that output is a function of labour, physical capital and knowledge/intangible capital. Thus the extra output comes from knowledge capital or ideas, and the process of converting knowledge capital or ideas to increased output is the innovation process. We seek to measure all stages of the innovation process, both ‘upstream’ (R & D, design) and ‘downstream’ (marketing, organisational change). This needs totally new data — the prize being a much fuller understanding of innovation and modern knowledge-based economics. Conventional measures of GDP and productivity treat most knowledge capital accumulation as intermediate consumption. We, therefore, use a growth accounting framework to compute revised national accounts based on capitalising the principal components of knowledge capital. These revised accounts provide both a direct measure of innovation, and a systematic basis for analysis of productivity and growth in the knowledge economy.

Introduction A number of agencies have been charged with investigating and developing an innovation index. The National Endowment for Science Technology and the Arts (NESTA) in the UK is obliged to develop an index in 2010. An Advisory Committee to the US Commerce Department, including the CEOs of Microsoft, UPS and 3M have investigated the issue for the US (Innovation Measurement, 2008). The OECD is examining this question en route to an innovation strategy. There are three main current approaches to such an index. The first is to propose a definition of innovation and then produce an index. Thus far however whilst there are plenty of proposals there are rather fewer implementations of such proposals. The second approach is the reverse, namely to calculate an index and assume (explicitly or implicitly) it is innovation. The third is to suspend the notion of an index altogether and do something else (Innovation Measurement, 2008). The aim of this paper is pragmatic, namely to move toward producing an index (or to produce some unimpeachable logic as to why it cannot be done). This imposes the constraint that an innovation definition must be implementable with either existing data or data that can be collected quickly. To state our proposal upfront, our innovation measure is the contribution to GDP growth of (market sector) investment in knowledge or intangible capital. This contribution derived from spending on knowledge/intangible assets and from Total Factor Productivity (TFP) growth. We can also add human capital building into the innova84


12/9/2009 2:46:35 PM


tion index. Thus our measure of innovation is the additional GDP over and above the addition due to existing physical capital and labour. As background, it is worth starting by considering some of the definitions of innovation that have recently been proposed. NESTA (2007) proposed ‘change associated with the creation and adoption of ideas that are new-to-world, new-to-nation/region, new-to-industry or new-to-firm’ without being very clear on what ‘change’ is and how it might be measured. The Frascati Manual (2002), being the official R & D manual proposes ‘technological innovation activities are all of the scientific, technological, organisational, financial and commercial steps, including investments in new knowledge, which actually, or are intended to, lead to the implementation of technologically new or improved products and processes’ which confines attention to the technology and does not define how ‘implementation’ might be measured. Whilst the Oslo manual (OECD, 2002) broadens the definition to include organisational innovations ‘a technological product innovation is the implementation/commercialisation of a product with improved performance characteristics such as to deliver objectively new or improved services to the consumer. A technological process innovation is the implementation/adoption of new or significantly improved production or delivery methods. It may involve changes in equipment, human resources, working methods or a combination of these’, it introduces the term ‘objectively new or improved’ without defining it. Finally, the US Advisory Committee propose ‘the design, invention, development and/or implementation of new or altered products, services, processes, systems, organisational structures, or business models for the purpose of creating new value for customers and financial returns for the firm’ (Innovation Measurement, 2008), which is broad in innovation scope but focuses on commercialised products and so is, as they point out, orientated at a private sector definition (and in any case they end up rejecting the feasibility of an index altogether). The logic of the approach in this paper contains four key steps. The first is to ask why we are interested in innovation. For many, the reason is because we believe it is a prime cause of economic growth and specifically that the commercialisation of innovations has been a key factor in converting technological improvements to economic growth in the past two hundred years 2. Thus we propose to concentrate on the output of more and new goods and services as our main reason for interest in innovation. As we stress below, to implement this, we shall measure output as value 2

There are at least two reasons why one might disagree with this. First, one might argue that the interest in innovation is because we think that innovation leads to new ideas (which may or may not then lead to growth). The problem of measuring ideas is, of course, a formidable one, since rating the relative importance of two ideas is very hard. The patents literature is, of course, a well-developed attempt to solve these problems, but it is well acknowledged that not all ideas are patented. Thus we do not study invention in this paper, but innovation, namely the commercialisation of ideas. Second, one might argue that increases in goods are of no interest in themselves since they might not signal a rise in prosperity at all, e.g. see the discussion in de Long (2000).

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added or GDP, a key variable which avoids output double counting problems and is tightly related to measures of increased living standards and welfare. But how does innovation contribute to this increased output? To answer this, the second step follows the question set by Jorgenson (2007) in his evidence to the US Advisory Committee: how would we get more output with no innovation? His answer is to use the same ideas, but duplicate existing capital and labour inputs. So Ryanair could fly more passengers on an existing route by simply buying another airplane and hiring another set of crew. McDonalds could sell more food by opening at another location buying more cooking equipment and hiring another set of staff. Thus innovation is not just the production of more goods, but the production of more goods over and above that which would occur with simple duplication of existing labour and physical capital. A number of points are worth making. First, how does this relate to the definitions above? The NESTA definition refers to ‘change’ and the Frascati Manual to the production of ‘objectively new or improved goods’. The definition operationalises this by referring to more goods. Second, by referring to more goods net of increases in physical capital and labour, it helps clarify a number of ambiguities in the literature. For example, innovation is sometimes defined as something that is new. Now, many would argue that the advent of low-cost airlines flying routes with an entirely new business model is an innovation. But few would argue that a low-cost airline, already flying from A to B in the morning, who then adds an evening service, has innovated. Similarly, many firms who describe themselves as innovative are often alleged by others not to be so since they are simply adopting the innovations of others. So, buying a new aircraft that flies twice as many passengers as before at the same cost, under the definition above, would not be an example of an innovation in the airline (service) industry. But, under our definition, it would be an innovation in the aircraft (manufacturing) industry, for the improved aircraft, assuming that it used new ideas, would be an example of an increase in output over and above that from simply duplicating capital and labour inputs in the aircraft industry. The third step is to ask: if innovation is the extra output over and above capital and labour, where does this extra output come from? This requires us to make an explicit assumption about what inputs cause output. So we assume that production comes from labour, physical/tangible capital and knowledge/intangible capital. Thus extra production due to innovation, since we have ruled out more physical capital and labour, comes from more knowledge capital or ideas 3. But where does the increased knowledge capi3

Jones (2005) reviews what an idea is by quoting Romer (1993) who ‘divides goods into two categories: ideas and objects. Ideas can be thought of as instructions or recipes, things that can be codified in a bit string as a sequence of ones and zeros. Objects are all the rivalrous goods we are familiar with: capital, labour, output, computers, automobiles, and most fundamentally the elemental atoms that make up these goods. At some level, ideas are instructions for arranging the atoms and for using the arrangements to produce utility’. Mokyr (2003) prefers using prescriptive and propositional to describe the body of knowledge.

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tal or ideas come from? Unlike tangible capital, which has a location and cannot be used by others, intangible capital may be non-rivalrous. So some firms might get ideas for free by simply imitating what other firms did. Other firms might discover new ideas themselves. Such discoveries, we assume, will take resources. R & D is the usual measure for the spending needed to generate new ideas, but the innovation definitions above suggest that we broaden the scope of spending to other spending that builds knowledge capital: spending on software, design, training, organisational capital at firms. This assumption is described by Corrado (2007) as tantamount to trying to measure innovation spending at all stages of the innovation process: both the upstream spending of scientists, artists and designers on new ideas and the downstream spending on the commercialisation of these ideas by means of marketing, training and organisational change. Both spending on innovative ideas and obtaining them for free will show up as innovation in our measure, but in different ways, as we shall show below. The final step is to account for how much this extra spending on knowledge raises output. For this we apply the economic theory of growth accounting, which uses observable prices and quantities to infer the impact of increased inputs on outputs. This step involves a number of assumptions, such as competitive markets, the depreciation of the knowledge stock and prices of knowledge all of which will be tested for robustness and require further work. Thus our proposed index will be the part of capital deepening in the economy that is knowledge capital deepening plus TFP growth. To preview our results, our main findings are as follows. Over 2000–05, UK market sector labour productivity grew at 2.74 percentage points per annum (pppa), of which the contribution of knowledge capital, our innovation measure, was 1.24 pppa (of the 1.24 pppa, investment in knowledge assets contributed 1.19 pppa and TFP growth 0.05 pppa). In turn, manufacturing accounted for about 60 % of the 1.24 pppa figure. If one includes increase in labour skill deepening (0.45 pppa) as innovation, then innovation contributed 61 % (= (1.24 + 0.45)/2.74) of labour productivity growth over the period. There are of course a number of things that our work does not do. First, as mentioned above, we do not count new ideas. We count the value of the new output stemming from new ideas and we will count investment in new ideas. Second, since we focus on output, we have obvious problems with the hard-to-measure sectors. Thus at the moment we consider it unlikely that we can obtain good indices of the public sector, and many parts of financial services are also likely to be hard. This might be important depending slightly on the degree of disaggregation needed. Third, it is often argued that an important, possibly the most important, knowledge capital source is education. To the extent that this is paid for by firms, we count it as firm investment. To the extent that it is paid for by the public sector or households, 87


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it shows up (albeit somewhat indirectly) via our labour quality measures 4. Fourth, our approach of locating innovation via its effect on growth, clearly relies on a number of assumptions, in particular, using, respectively, knowledge capital deepening and TFP as summary measures of the growth impact of new ideas paid and not paid for by firms. For those who find the assumptions in building these measures unacceptable, we do provide data on spending on series of knowledge/intangible assets which should be of interest, (even if the assumptions on the mechanism by which such spending then changes output are of no interest). The present paper has dealt with the measurement of innovation, not with creativity per se. However, it seems clear that the development of new ideas, that are the origins of innovation, will require creative capacity. Thus, our measurement of innovation would have embodied also specific aspects of creativity and could be considered to measure aspects of it. References De Long, B., (2000), Consequences of Growth: Slouching Towards Utopia? http://econ161. berkeley.edu/TCEH/Slouch_causes3.html. Corrado, C. A. (2007), Comment submitted to the Advisory Committee on Measuring Innovation in the 21st century Economy: http://www.innovationmetrics.gov/co mments/051107FederalReserveBoard.pdf Corrado, C. A., Hulten, C. R. and Sichel, D. E. (2004). Measuring Capital and Technology: An Expanded Framework. In Corrado, C. A., Haltiwanger, J. C. and Sichel, D. E (eds), Measuring Capital in the New Economy, Vol. 65. Chicago: The University of Chicago Press. Corrado, C. A., Hulten, C. R. and Sichel, D. E. (2006). Intangible Capital and Economic Growth. NBER Working Papers 11948, National Bureau of Economic Research, Inc. Frascati Manual (2002), http://europa.eu.int/estatref/info/sdds/en/rd/rd_frascati_manual_2002.pdf Innovation Measurement (2008). A Report to the Secretary of Commerce by The Advisory Committee on Measuring Innovation in the 21st Century Economy, January 2008. Available at: http://www.innovationmetrics.gov/Innovation%20Measurement%2001-08%20rev%20040908.pdf. Jorgenson, D. W. and Griliches, Z. (1967). The Explanation of Productivity Change, The Review of Economic Studies 34, 249-283.

4

As a matter of official National Accounting measurement practice, households are not regarded as producers and so their education spending is not investment.

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Jorgenson, D. W., Ho, M. S., Samuels, J. D. and Stiroh, K. J. (2007). Industry Origins of the American Productivity Resurgence, Economic Systems Research, 19, 229-252. Marrano, M. G., Haskel, J. and Wallis, G. (2007). What Happened to the Knowledge Economy? ICT, Intangible Investment and Britain’s Productivity Record Revisited. London: Department of Economics, Queen Mary, University of London. Mokyr, Joel, 2005. Long-Term Economic Growth and the History of Technology. In P. Aghion & S. Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, pages 1113-1180. Amsterdam: Elsevier. Mokyr, J. (2006). Review of William J. Baumol, The Free-Market Innovation Machine: Analyzing the Growth Miracle of Capitalism.” EH.Net Economic History Services, Jul 26 2002. URL: http://eh.net/bookreviews/library/0517 NESTA (2007), Innovation Index Call for Ideas Document, http://www.innovationindex. org.uk/forum/attachment/download?id=2132323%3AUploadedFi38%3A394 OECD (2002), Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd Edition, http://www.oecd.org/document/23/0,3343,en_2649_34273_355956 07_1_1_1_37417,00.html

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Hong Kong Creativity Index

6. Design and construction of the Hong Kong Creativity Index

John Bacon-Shone (Social Sciences Research Center, The University of Hong Kong), Desmond Hui (Center for Culture and Development, Chinese University of Hong Kong)

Abstract This paper looks at the process of constructing the Hong Kong cultural index (Home Affairs Bureau HKSARG 2004). The process had three main elements: the conceptual framework, data availability and statistical methodology. It was predicated from the requirements that: yy the overall framework should follow the agreed conceptual framework as far as possible; yy the required data must either already be available or easily collected, possibly after interpolation to cover missing data; yy the sub-index structure should be validated using principal component analysis, to ensure that each sub-index is reliable. We discuss the practical difficulties in implementing this process and the lessons learned that may be useful for other jurisdictions that wish to implement a similar process. We also discuss what has happened since creation of the index

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John Bacon-Shone, Desmond Hui

Conceptual Framework The overall framework has five elements: Creativity Outcomes, Structural Capital, Human Capital, Social Capital and Cultural Capital. This starts from Florida (Florida 2003; Florida 2004)’s three Ts — Technology, Talent, Tolerance — which he argues drive technological innovation and economic output. However, our concept was broader than economic and technological outputs, so we incorporated ideas from the Silicon Valley Creativity Community Index (Cultural Initiatives Silicon Valley, 2005) to include cultural infrastructure, social connectedness, cultural participation and cultural policies. We also expanded the scope to cover other creativity and competitiveness elements taken from the World Values Survey of Inglehart (Inglehart and Baker, 2000) and the Global competitiveness report of Porter (Porter, Schwab et al., 2004).

Technology, Talent and Tolerance From Florida’s technology items, we used innovation (as measured by patents) while high-tech-related industry was replaced by R & D expenditure, which addresses the point that in Hong Kong most technology is related to financial services rather than hardware development. In other words, a hardware perspective of technology may be too narrow for Hong Kong and needs to be expanded. From Florida’s talent items, we used educational attainment and specific occupational categories that relate to creative activity (which were split into creative and scientific talent classes). From Florida’s tolerance items, we used the Gay Index (in terms of the coupled gay population), the Bohemian Index (in terms of the artistically creative population) and melting pot (foreign-born population), although this is arguable for Hong Kong as a Special Administrative Region of China, because it raises the question of whether mainland-born people should be treated as foreign-born. From the Florida and Tinagli (Florida, Tinagli et al., 2004) European study, we added Attitudes, Values, and Selfexpression (which are arguably strengths of Europe compared to US), as assessed by the World Values Study of Inglehart (Inglehart and Baker, 2000)

Social and cultural capital Social capital as defined by Putnam (Putnam, 2000) and others has been criticised by Florida because it traditionally provides opportunities to insiders and is this a barrier to creativity. However, social capital can be defined in terms of relationships across groups and civic participation, which facilitates creation, rather than creating barriers. 92


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Cultural capital is defined here as cultural assets that provide basis for public participation as argued in the Silicon Valley (Cultural Initiatives Silicon Valley, 2005) study and increased connectedness, which facilitates creative activities.

Asian additions Asian values have been controversial but there are differences in the social and cultural environment in Asia for which we need to account. One key element of economic development for the Asian Dragons is entrepreneurship, which is closely linked to the large number of small and medium-sized enterprises (SMEs) in Asia in contrast to the importance of large corporations in Europe and the US, so this element needs to be incorporated in a Hong Kong index. The aim was to ensure that the index was relevant to Asia, not just to western economies in Europe and North America.

The Creativity Index (The full list of items that comprise the Honk Kong creativity index can be found in the Appendix.)

Creative outputs Creative outputs are public goods that may stimulate further creative activity, so this is both an output and a potential input for creative activity. Elements included in the index were economic contribution, percentage of GDP, percentage of the workforce, percentage of the export trade, percentage of the import trade and percentage of e-commerce trade in relation to creative outputs. In terms of inventive activity, we included the ability to sell local brands internationally, the ability to obtain new technology, the number of patents per capita and the percentage of local patents filed by local applicants. Other indicators included were newspaper circulation per capita, new books and periodicals per capita, music titles per capita, lyrics per capita, film per capita, film shows per capita, performances per capita, and the floor area of new buildings per capita.

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Structural/institutional capital Structural and institutional capital are key issues in determining the willingness of investors to invest money in a particular location, especially within Asia. For institutional capital, the elements included in the index are independent legal system as assessed by an enumeration of independence, corruption perceptions as assessed by the world percentile on a corruption perception index, freedom of expression as assessed by the scoring of freedom of press, and freedom of speech. Information and communications infrastructure indicates access to technology for both businesses and the general public. This was assessed by measuring the percentage of businesses with personal computers, with Internet access, with websites, the percentage of households with personal computers, with Internet access and the number of mobile phone accounts per capita. Social and cultural infrastructure illustrates access to culture provided by government and NGOs. The indicators used were the number of community halls and centres per capita and the number of civic centres per capita, while for community facilities, the indicators used were the number of non-government organisations (NGOs) per capita, the number of public library users per capita, the number of books in libraries per capita, the number of seats in cultural venues per capita, the number of monuments per city, the number of museums per city. Financial infrastructure illustrates the ability to grow companies and businesses. The indicators used were the number of listed companies per capita, the stock market capitalisation relative to GDP, the amount of venture capital relative to GDP. Lastly, for entrepreneurship, which illustrates the ability to create new businesses, the indicators used were the number of SMEs relative to the number of companies and the percentile labour productivity index.

Human capital Expenditure on R & D and education are key elements of human capital, especially for home-grown talents. The indicators included were R & D expenditure relative to GDP by businesses, on higher education, and by the public as well as expenditure on public education relative to GDP. Florida’s work shows the importance specifically of knowledge workers, which were measured in terms of the proportion of the population aged 15 years and above who have tertiary education (with and without degrees) and the proportion of the labour force doing R & D work. 94


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Mobility is a key element of openness, which itself is important for creativity. For Hong Kong, we included the number of visitor arrivals, the number of resident departures, the number of emigrants and the number of working visas all relative to the total population.

Social capital The development of Social Capital indicates support for the community as assessed through charitable donations relative to GDP made personally and by companies. Norms and values for social capital that are inclusive were assessed through the World Values Survey (WVS) and included generalised trust, institutional trust, reciprocity, sense of efficacy, cooperation, attitude towards, acceptance of diversity, attitude towards human rights, towards immigrants, towards foreigners’ lifestyles, modern versus traditional values, and self-expression versus survival.

Social participation also used the WVS to assess interest in public affairs, participation in social organisations, social contact with acquaintances, with community, sense of efficacy, and number of volunteers per capita.

Cultural capital Cultural expenditure indicates how important culture is to the public. This was measured using the proportion of public expenditure on the arts and culture, and the percentage of household expenditure on designated cultural goods and services. Network quality also relates to the importance placed on culture through norms and values, for which elements of the WVS were used to assess the value placed on creative activity, on children’s creative activity, on arts and cultural activities, on children’s arts and cultural activities, and whether people were strong advocates for the arts and culture. Environmental factors relate to the support for creativity in general and use the WVS to assess the encouragement for creative and for cultural participation and the moral values relating to the purchase of pirated goods. Lastly, cultural participation was assessed via the number of books borrowed per year per capita, the amount of royalties paid per capita, the time spent per week for personal Internet use, the number of museum visits per year per capita, the number of cultural attendances per year per capita and the number of film attendances per year per capita.

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Data availability problems One of the key issues in constructing any index is the availability of relevant data. In this case, we could not obtain reliable data on the protection of intellectual property rights in Hong Kong, which is now much improved from the days when illegal CDs and DVDs could be found on any street corner. Other areas that had to be excluded for lack of data include social innovation (i.e. the application of entrepreneurship skills to social problems) which is an area where Hong Kong was genuinely innovative in the past and has been focusing attention on in recent years. Disposable personal income spent on the arts and culture had to be replaced by household expenditure on selected items and the arts and culture participation had to be restricted to government-sponsored shows, given the lack of any private sector data. There was also no historical data on tolerance, forcing the assumption that change over recent history is limited.

Statistical reliability and validity In order to ensure that the index is both reliable and valid, statistical analysis was applied in two ways. Firstly, for the tolerance data from the World Values Survey (where we had cross-sectional data from all the survey respondents), item reliability was evaluated to ensure that in a cross-sectional analysis, all items included together in an index were reliable. Secondly for items within an index where longitudinal data was available, principal components analysis was applied to the log transformed item measurements see whether the multiplicative changes in the items over time were correlated. Both cross-sectional and longitudinal analyses facilitate reflection over which items belong in the same or separate sub-scales and were critical in structuring the sub-scales within the five major scales. Ideally, both forms of analysis would be undertaken, but for many of the items only aggregate data was available, allowing only longitudinal analysis, while for the WVS items, data was only available for one time point, allowing only cross-sectional analysis. Nearly all items are ratios even before indexing process, so analysing log-transformed data (which changes ratios into differences) is sensible, and has the advantage of giving the same results regardless of which time point is the reference point (i.e. when the index is 100). One major weakness with the longitudinal analysis was that there were only resources provided to cover six time points, which is barely enough.

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Outcomes, use and value of the Index

Figure 1: The Hong Kong Creativity Index using 2004 as the base year

As seen in Figure 1, the index shows significant increases in all five major indices over the five-year period. In terms of the use and value of the index, the most positive outcome was that it stimulated invaluable debate about the changes and their importance. The increases in Structural and Cultural Capital are less than those for Human and Social Capital and Cultural Outcomes. Unfortunately, the Hong Kong government has not yet funded any updates to the Index, but the Index continues to be referenced by politicians in debates about the government’s grand plans for cultural developments. This suggests that the government will need to update the study in order to be able to show that the new investments are paying off in terms of improved outcomes.

Other relevant points In hindsight, the index raises some other important questions, which are particularly relevant for a small territory like Hong Kong that has always relied so heavily on human capital. Firstly, how to balance the strategies of importing talents versus develop97


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ing home-grown talents? With mainland China next door, and a timetable for integration, it is tempting to rely on imports from the Mainland, which is usually cheaper and easier than local development. Secondly, Hong Kong is not a centre for technological innovation, if that means hardware products. However, social and cultural innovation seem much more attractive given the openness relative to the mainland and most Asian countries. Lastly, does education increase creativity or does it sometimes stifle it? Human capital and educational reforms may need to address this question before we expand our education system to require high levels of education for everyone. References Cultural Initiatives Silicon Valley (2005). Creative Community Index: Measuring Progress Toward a Vibrant Silicon Valley, San Jose, CA: Cultural Initiatives Silicon Valley. Florida, R. (2003). Cities and the Creative Class, City & Community 2(1): 3-19. Florida, R. (2004). The rise of the creative class: and how it’s transforming work, leisure, community and everyday life. New York: Basic Books. Florida, R. and Tinagli, I. (2004). Europe in the Creative Age. London: Carnegie Mellon Software Industry Center/DEMOS. Home Affairs Bureau HKSARG. (2004). A Study on Creativity Index. Retrieved 2009, from http://www.hab.gov.hk/file_manager/en/documents/policy_responsibilities/arts_ culture_recreation_and_sport/HKCI-InteriReport-printed.pdf. Inglehart, R. and Baker, W. (2000). Modernization, cultural change, and the persistence of traditional values, American sociological review: 19-51. Porter, M., Schwab, C., et al. (2004). The Global competitiveness report: 2003-2004. Oxford University Press Inc, USA. Putnam, R. (2000). Bowling alone: The collapse and revival of American community, Simon & Schuster.

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Appendix 1 Components of the Hong Kong Creativity Index Outcomes of Creativity Index Economic contribution of creativity Value added of Hong Kong’s creative industries as % of GDP Persons engaged in creative industries as % of total employment Share of cultural goods relative to total export trade in goods Share of cultural goods relative to total import trade in goods Percentage of business receipts from selling goods, services or information through electronic means Inventive activity of economic sector The ability of local enterprises to sell branded products in international market The ability of local enterprises to acquire new technologies Patent applications per capita Percentage of patent applications originated from local applicants relative to all patent applications Other outcomes of creative activity Daily circulation of newspaper per capita Book and periodical titles newly registered per capita Music titles composed per capita Lyrics written per capita Films produced per capita Film shows presented by government cultural services per capita Performances by government cultural services per capita Gross floor area of new buildings per capita

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Structural/Institutional Capital Index Independence of the legal system Enumerated data about independence of the legal system Corruption perceptions in Hong Kong Percentile scoring in Corruption Perceptions Index Freedom of expression Percentile scoring on freedom of press Percentile scoring on freedom of speech Infrastructural conditions of ICT Percentage of establishments using personal computers Percentage of establishments with Internet connection Percentage of establishments with web page/website Percentage of households using personal computers Percentage of households with Internet connection Mobile phone subscribers per capita Robustness of social and cultural infrastructure NGOs per capita Registered public library users per capita Books in public libraries per capita Seats in all government cultural services’ performance venues per capita Declared monuments per city Museums per city Availability of community facilities Community halls and community centres per capita Civic centres per capita Financial infrastructure of Hong Kong Listed companies per capita Capitalisation of stock market (in local currency) per GDP Venture capital under the place’s management (in local currency) per GDP Robustness of entrepreneurship Share of SMEs to establishments Percentile scoring in Labour Productivity Index (Whole Economy)

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Human Capital Index R & D expenditure & educational expenditure R & D expenditure (business sector) as % of GDP R & D expenditure (higher education) as % of GDP R & D expenditure (public) as % of GDP Public expenditure in education as % of GDP Population of knowledge workers Share of population aged 15 and above with educational attainment at tertiary level (non-degree) Share of population aged 15 and above with educational attainment at tertiary level (degree and above) R & D personnel as percentage of total working population Transience/mobility of human capital Visitor arrivals per capita Residents’ departures per capita Estimated emigrants per capita Working visas per working population Social Capital Index Development of social capital Approved charitable donations allowed under Salaries Tax as % of GDP Approved charitable donations allowed under Profits Tax as % of GDP Expenditure on social welfare as % of total public expenditure Network quality: norms & values from World Value Survey Indicators on generalised trust Indicators on institutional trust Indicators on reciprocity Indicators on sense of efficacy (on control) Indicators on cooperation Indicators on attitude towards diversity Indicators on acceptance of diversity Indicators on attitude towards human rights Attitude towards rights and wrongs of foreign immigrants Attitude towards foreigners’ lifestyle Indicators on modern v traditional values 101


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Indicators on self-expression v survival Network quality: social participation from World Value Survey Interest in public affairs Participation in social organisation Social contact with acquaintance Social contact with community Indicators on sense of efficacy (on what you did) Volunteers per capita Cultural Capital Index Cultural expenditure Expenditure on arts & culture as % of total public expenditure Household expenses on designated cultural goods & services as % of total household expenses Attitude towards arts, cultural and creative activities Value placed on creative activity Value placed on school-aged children’s creative activity Value placed on arts and cultural activities Value placed on school-aged children’s arts and cultural activities Community leader to be a strong advocate for advancing the arts and culture of the place Environmental factors for cultural and creative activities Evaluation on milieu that encourages creative activities Evaluation of milieu that encourages cultural participation Value placed on the morality to buy pirated or counterfeit goods Network quality: cultural participation Library books borrowed per year per capita Royalty fees paid to copyright fees collecting agents (excluding revenue from overseas) (in local currency) per capita Average % of week spent on Internet for personal use Visits to government museums per capita Attendances to performances presented by government per capita Attendances to film and video shows presented by government per capita

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Is it possible to measure scientific creativity?

7. Is it possible to measure scientific creativity? Some first elements of reflection

Johan Stierna (Directorate-General Research) and Ernesto Villalba 1 (Directorate-General Joint Research Center)

Abstract This article elaborates on whether it is possible to measure scientific creativity. It is based on the assumption that the scientific process embeds an element of creativity. Which analogies can be drawn comparing creativity in science with creativity in a broader sense? What is purely qualitative and what is possible to quantify? What is the role of demand in scientific creativity? Is it possible to measure which input would generate optimal creative output? How could we measure the optimal framework conditions for the creative process in science? Given this new field of reflection, this article does not give definitive responses but only food for further development of indicators and for different interpretation of already existing data. Empirical data are largely taken from the European Commission, DG Research work on the Science, Technology and Competitiveness key figures report 2008/2009 as well as ad hoc studies.

Introduction The Research Directorate General (DG Research) is in charged of coordinating the efforts to develop a European Research Area, its mission consists on developing the 1

Disclaimer: The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission. 103


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Johan Stierna, Ernesto Villalba

European Union’s policy in the field of research and technological development and thereby contribute to the international competitiveness of European industry. In addition, DG Research coordinates European research activities with those carried out at the level of the Member States; it provides support to the Union’s policies in other fields and aims at providing a better understanding of the role of science in modern societies and stimulates a public debate about research-related issues at European level. To this end, DG Research produces, among others, a major publication every year on Science, Technology and Competitiveness (Research Directorate General 2009). In addition, DG Research is in charge of ERAWATCH that provides information on European, national and regional research policies, actors, and programmes in the EU and beyond. Currently ERAWATCH covers 43 countries in total: 27 EU Member States, countries associated with the European Community’s Research Framework Programme and main trading partners of the EU. There are, thus, a number of initiatives initiated by DG Research that provide a vast amount of information and indicators in research, science and technology that could have potential use for measurement creativity at aggregate levels. However, creativity itself has not been a specific area of coverage for DG research in terms of developing indicators. This paper presents some first elements of reflection about creativity in relation to indicators that have been used or are being developed in science and technology.

Measurable components It is clear that we do not have adequate measures of creativity. As the title of this monograph shows, it is still an open question if creativity can or not be measured. From our point of view, creativity is a black box that we cannot look into. We need, therefore, to define proxies for creativity. That is to say, we have to look for its measurable components. It seems clear, however, that the scientific process embeds an element of creativity, and, thus, science and technology indicators might provide useful insights into the measurement of creativity. In this way, it is possible to see creativity in relation to the cycle Input, Framework conditions, Output (see figure 1). In the case of scientific creativity, the indicators that are used for the monitoring progress towards creating a European Research Area can serve as a point of departure. Input indicators refer to both quantity and quality of human and financial resources. It is important to note that in addition to quantitative measures of input we need measures that can tell us something about the quality of 104


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the input. Combining, both quality and quantity indicators, we will be able to have a better picture of the effectiveness of the research cycle. Framework conditions refer to the aspects in the systems that are in place to foster scientific creativity. There are several aspects that could be interesting and that, potentially, could influence the appearance of scientific creativity. In here I will propose two areas of indicators: diversity of perspectives and the balance stimulis-security in research activities. Finally, output measures refer to the results of the scientific process. In here there are two aspects that we believe are crucial to look at, and that are related to the use-reuse of scientific creativity: Quality assurance and Open access to research results.

Figure 1: An illustration of some measurable aspects

These different components would have to be looked in a comprehensive manner. It will be necessary to understand how the three parts of the model relate to each other. In this way, it would be possible to identify the relationship between input and output and the mediating effect of framework conditions, which would allow us to understand one specific dimension of the efficiency of the research investment. The three components (input-framework conditions-output) compound a circle, where research outputs constitute, in fact, new research inputs. The present article outlines some examples of the framework presented in figure 1. It provides some examples of indicators and show figures related to some of them, 105


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taken mainly from the European Commission, DG Research work on the Science, Technology and Competitiveness key figures report 2008/2009.

Input measures It is possible to find indicators which provide us with information on the potential input to creativity, at least for specific professional areas. For quite some time now, one of the most common indicators referring to input measures into research is the R&D intensity, measured as the Gross Domestic Expenditure on R&D (GERD) as a percentage of the GDP. Figure 2 shows this indicator for 2007. This indicator points at financial resources which are necessary but not sufficient to enhance research-based creativity in Europe. R&D intensity (GERD as % of GDP), 2007

3.60

Sweden

3.46

Finland

3.44

Japan

2.67

US

2.66

Austria

2.55

Denmark

2.54

Germany

2.08

France

1.87

Belgium

1.85

EU-27

1.79

UK

1.70

Netherlands

1.62

Luxembourg

1.54

Czech Republic

1.45

Slovenia

1.45

Ireland

1.44

China

1.29

Estonia

1.27

Spain

1.18

Portugal

1.13

Italy

0.97

Hungary

0.82

Lithuania

0.59

Latvia

Figure 2: R&D Intensity 0.59 Malta 0.57 Greece Source: Science, Technology and Competitiveness key figures report 2008/2009 Poland

0.57 0.53

Romania

Creativity is always embodied in people, in this case researchers. Therefore, another relevant indicator for inputs, related to human resources, is the number of doctoral graduates. Figure 3 shows this indicator for 2005 and the average annual growth from 2000-2005. It seems that in terms of graduates, the EU is as prepared, at least, as the US or Japan. However, these indicators tell us little on the quality of the financial and human resource inputs in terms of creativity. We need to develop better indicators to assess quality. But quality can, in many instances, only be assessed in an ad-hoc manner, af0.48

Bulgaria

0.46

Slovakia Cyprus

0.45

0

1

2

3

4

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ter scientific results are provided, thus, the need of understanding the framework in a circular manner, where output indicators relate to input indicators. 120000

6.0%

100000

5.0%

80000

4.0%

60000

3.0%

40000

2.0%

20000

1.0%

0

0.0% EU-27

US Number in 2005

Japan

Average annual growth (%), 2000-2005

Source: DG Research Data: Eurostat

Key Figures 2008

Figure 3: Number of doctoral graduates in 2005 and average annual growth 2000-2005 Source: Science, Technology and Competitiveness key figures report 2008/2009

Input indicators, are thus, important but they need to be combined with other indicators. For example, we know that R&D intensity depends heavily on the sector structure of a country. In the context of measuring creativity: Which are the framework conditions under which financial and human resources are more likely to form part of a creative activity?

Framework Condition Under this heading, it should be possible to establish a number of indicators that provide information on the conditions where research as creative activity is taking place. One avenue could be to explore the “diversity of perspectives” in science. Diversity may be associated with more creative potential. A system that welcomes different points of views, allows for researchers to have exposure to other points of views, and is a source for new ideas, will most likely be more creative. Creativity in science, as in other domains, is also fertilised by cross-cutting boundaries and multi-disciplinary approaches (see Chapter XX in this volume). 107


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Measuring diversity is not an easy task. From the S&T indicators, one possible interesting indicator would be the proportion of female researchers, since this provides a picture of the diversity of the system in terms of gender. The number of doctoral candidates with citizenship of another Member State could be another of the indicators showing diversity of perspectives. Attractiveness and openness of the European Universities, in this case, plays a crucial role. Also in terms of diversity and connectivity of research universities, it would be possible to use the web-based hyperlinks between universities as a proxy of diversity of informationbased perspectives. This indicator would show how much universities are connected with other universities, at least from a theoretical point of view (see figure 4). Other indicators on this direction, showing the connection between business and universities could provide additional information on diversity of perspectives.

Figure 4: web-based hyperlinks between universities in EU 15 Source: Science, Technology and Competitiveness key figures report 2008/2009

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Another aspect of the framework conditions is the extent to which the system provides a balance between stimuli and security for research-based creativity. Figure 5 shows the different funding models for universities in the Member States. It shows the structure of different financing schemes.

Figure 5: Funding models for universities Source: Science, Technology and Competitiveness key figures report 2008/2009

From the perspective of creativity, a right balance between external stimuli and internal security contributes to the creative process. In the field of research, external stimuli can among other aspects be enhanced by the attention to competitive funding, to outlook in society-responsive thinking; internal security and stability in time is just as important for creativity, enhanced by institutional funding and long term free-mind research.

Output The measurement of scientific output is more and more an important area for research. As indicated above, the output is one way in which we can assess the quality of a scientific production. One of the indicators that is used, and that could be related to scientific creative outputs is the “citation impact”.

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Figure 6 shows the most active research universities by country from 1997-2004. This can provide a general picture of how much research from specific universities in each country is cited in scientific journals. From the perspective of creativity, an article is cited, among other reasons, because it represents a step forward, a result of a creative process.

Figure 6: The most active research universities – normalised citation impact by country, 1997-2004 Source: Science, Technology and Competitiveness key figures report 2008/2009

Finally, in finding information referring to the connection between scientific output and input, it might be interesting explore data related to “open access to research results”. Figure 7 shows the worldwide open access repositories, where almost half of the repositories belong to the EU 27. This is an area to explore, since there is an increasing number of research outcomes that are more and more available for other researchers to use. Creativity based on knowledge is in part self-generating: knowledge triggers creative processes that may result in new knowledge, given appropriate input in financial and human resources as well as optimal framework conditions for creativity.

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Figure 7: Worldwide open access repositories Source: Science, Technology and Competitiveness key figures report 2008/2009

Conclusion It is very difficult both conceptually and empirically to quantify scientific creativity in itself. However, we do dispose of some indicators that could contribute to our understanding and we could imagine a framework measuring the conditions that stimulate creativity. This article has provided a brief, general overview and some specific example of possible data that could be used. Measuring creativity is a new field of work that will most probably expand in the years to come. References Research Directorate General (2009). Science, Technology and Competitiveness key figures report 2008/2009. Brussels: Research Directorate General.http://ec.europa. eu/invest-in-research/monitoring/statistical01_en.htm

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The creative class and entrepreneurship


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The regional dimension of creativity and innovation

8. The regional dimension of creativity and innovation

Lewis Dijkstra (Directorate-General for Regional Policy)

Abstract This article analyses the regional dimension of creativity and innovation in the EU. It includes a strong focus on both the human side of creativity and the interaction between people and an economic analysis of the input and the impact of innovation. This presentation will also show a brief analysis of the creative class theory applied to the EU regions, which confirms the link between the creative class and cities with talent, technology and tolerance.

Introduction In my presentation, I focused on the research done in preparation of the sixth Progress Report on Social and Economic Cohesion titled Creative and Innovative Regions 1. For this new report, several new regional creativity and innovation indicators were developed. These are also included here in the 11 fiches and maps which follow. These maps and fiches were first published as a Commission staff working document. The analysis of the regional dimension of creativity and innovation shows that there is substantial variation within countries. As a result, regions and cities can, and often do, play an important role in fostering more creativity and innovation. To promote creativity, regions should both foster local talent and attract global talent. Less developed regions in the EU tend to have lower shares of graduates and participation in lifelong learning is much lower. They also attract far fewer immigrants and visitors 1

COM(2009) 295 http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/interim6_en.htm of 25 June 2009.

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than the more developed regions do. These regions also lag in broadband Internet access. They would benefit from increasing the education levels and participation in training as well as attracting more visitors and immigrants. The core creative class, as defined by Richard Florida, has a significant impact on the economy as they are more likely to set new (high-growth) businesses. They prefer to live in a tolerant, multicultural urban setting with good access to technology and creative individuals. My analysis confirms this pattern and shows that the core creative class is higher in urban regions with a high share of foreign-born residents, wide use of broadband Internet access, and in countries that are more tolerant. Promoting innovation stimulates long-term sustainable economic growth by allowing firms to become more productive and thus competitive. The less developed regions have supported high productivity growth by improving education, better and more use of ICT, and high FDI inflows. New firms often introduce innovations in the market place. However, the ease of starting a new business still needs to be improved in many EU Member States, as shown by the latest World Bank Ease of Doing Business Report. Also 18 Member States still need to reach the three targets set by Spring European Council in 2006 to facilitate the setting up of a new firm. Existing firms also support innovation, through R & D and other methods, such as technology adoption, non-technological innovation and combining existing knowledge in new ways. R & D expenditure is much lower in the less developed regions, but this is due to their distance to the technology frontier. Less developed regions tend to focus more on technology diffusion. In conclusion, both creativity and innovation have a strong regional dimension, which in turn has a strong impact on regional development. Regions should promote creativity and innovation to ensure stronger and more sustainable development; something which the crisis has made all the more relevant. As appropriate in a report on innovation, this report also includes a novelty. For the first time, data behind all maps and charts published in this report can be accessed through a data link. This is particularly useful since several of these indicators have never been published before. Please note that this link does not work with certain versions of Internet Explorer. The link works consistently with other browsers, such as Firefox, Chrome or Safari.

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1. GDP/head Gross Domestic Product per head in Purchasing Power Standards Why does this matter?

Country

Top 10 regions

GDP per head in PPS EU-27 =100

This table shows the 10 regions with the highest GDP per head in PPS in 2006 UK

Inner London *

335.9

LU

Luxembourg (Grand-Duché) *

267.1

BE

Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest *

233.3

DE

Hamburg *

199.7

NL

Groningen

173.7

FR

Île-de-France

169.7

DE

Oberbayern

167.9

AT

Wien

165.9

SE

Stockholm

165.8

UK

Berkshire, Buckinghamshire and Oxfordshire

164.0

*

In these regions, GDP/head figures tend to be overestimated because of commuter flows.

Gross domestic product (GDP) is the total value of all goods and services produced within a region in a given time span. GDP/head is the level of output per inhabitant which is an indication of the average level of economic wealth generated per person. In order to compare regions, it is computed in Purchasing Power Standards (PPS) which eliminates differences in purchasing power due to different price levels between regions. In general, the level of GDP per head is closely related to global economic performance, in particular to production factor productivity and employment. Its change in time rate indicates the pace of economic development.

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Country

Top 10 Movers

Difference in GDP per head in PPS

This table shows the 10 regions with the biggest increase in GDP per head in PPS between 2000 and 2006 SK

Bratislavský kraj

39.9

RO

Bucureşti — Ilfov

30.5

CZ

Praha

25.7

LU

Luxembourg (Grand-Duché)

23.4

EL

Attiki

23.0

NL

Groningen

23.0

BG

Yugozapaden

20.7

EE

Eesti

20.7

HU

Közép-Magyarország

19.3

RO

Vest

18.0

How do the EU regions score? The geographical distribution of GDP/head underlines large development gaps between EU regions and particularly between the western and the central and eastern Member States. The top 10 regions are all located in the west and are often capital city regions. At the other end of the spectrum, several regions in Bulgaria and Romania have levels of GDP/head below 30 % of the EU‑27 average. The lowest level is 25 % in Nord-Est, Romania. Regions where GDP per head has increased often host the national capital or a large city. Strong upward trends are also frequently observed in regions with a low level of GDP/head, like for instance Yugozapaden, Bulgaria, whose GDP/head is only 32 % of the EU average but whose index has grown by almost 21 percentage points between 2000 and 2006. On the other hand, modest changes in GDP per head are observed in regions with its level is already high, particularly in Northern Italy or in some regions of Denmark, Germany, France, Finland or Sweden. For example, in Provincia Autonoma Bolzano/Bozen where GDP/head index decreased from 159 to 136. This suggests that poor regions are catching up with the rest of the EU and is consistent with the fact that convergence among EU regions in terms of GDP/head has increased. Between 2000 and 2006, the coefficient of variation, which is a statistical measure of regional disparities, decreased by 8 %. The trend is however worrisome for regions of Southern Italy and Portugal where both GDP/head and growth are relatively low. 118


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2. Unemployment rate Measures the number of people aged 15 and more who are without work but looking for work and available for work, divided by the number of people aged 15 and more and active in the labour market, i.e. those working or looking for work. Why does this matter? High unemployment is a threat to social cohesion leading to poverty and social exclusion and it is one of the most important incentives for people to leave their regions. Convergence

Transition

RCE

Unemployment rate, 2007

9.2

8.4

6.1

Change in unemployment rate, 2000 - 2007

-4.6

-3.0

-0.5

The rapid reduction of unemployment rates in the Convergence regions between 2000 and 2007 reduced the gap between Convergence and the RCE regions by half. In 2000, the rate in Convergence regions was double that in RCE regions. The Convergence regions are faced mainly by structural unemployment due to a skills mismatch; which is often caused by rapid restructuring. Convergence regions tend to have low rates of participation rates. This means that as employment rates increase, people who were not working or looking for work may start to look for a work, and thus partially offsetting the decline in the unemployment rate. Country

Top Ten regions

Unemployment rate, %

This table shows the ten regions with the highest rate of unemployment in 2007 FR

Réunion

25.2

FR

Guadeloupe

25.0

FR

Martinique

22.1

FR

Guyane

21.0

ES

Ciudad Autónoma de Ceuta

20.3

ES

Ciudad Autónoma de Melilla

18.2

DE

Mecklenburg-Vorpommern

17.4

DE

Leipzig

17.2

BE

Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest

17.1

DE

Berlin

16.3

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How do the EU regions score? Regional disparities among the EU-27 regions remain high. The French overseas departments and Ciudad Autónoma de Ceuta and Melilla have the highest unemployment rates, partly due to the distance from the rest of the Union. The unemployment rates are also high in Leipzig, Berlin and Brussels, the latter both capital cities. Country

Top Ten Movers

Change in unemployment rate, percentage points

This table shows the ten regions in which unemployment rate decreased fastest between 2000 and 2007 ITF6

Calabria

-14.8

PL62

Warmińsko-Mazurskie

-13.1

ITF3

Campania

-12.5

LT00

Lietuva

-11.6

ES61

Andalucía

-11.3

ITG1

Sicilia

-11.0

FR83

Corse

-10.9

PL43

Lubuskie

-10.9

ITG2

Sardegna

-10.7

ES43

Extremadura

-10.5

excl. FR9 (=DOM), UKM5 (NE Scotland), UKM6 (Highlands and Islands), PT20 (Azores) and PT30 (Madeira)

The 45 regions with the rates over 10 % can be found mainly in Belgium, the east German Länder, Southern Italy and Poland. In contrast, regions like Zeeland, Praha and most regions in Northern Italy have rates of 3 % or lower. The 10 top movers had an average unemployment rate of 22 % in 2000 and only 10 % in 2007. The coefficient of variation, a statistical measure of regional disparities, in 2007 was 14 % lower than four years ago, which means that the difference between the regions with high and low unemployment rates has been narrowed. Unemployment rates dropped significantly in the Baltic States, Bulgaria, Southern Italy and Spain. On the other side, several regions in eastern Germany, Luxembourg, Hungary, Portugal and Austria witnessed a substantial increase in the unemployment rates. In most cases, reductions in unemployment rates are correlated with increased levels of GDP per capita and lower levels of poverty. Conversely, regions growing unemployment tend to have lower levels of economic growth and higher levels of poverty.

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3. Human Capital Intensity Index Measures the quality of the labour force Why does this matter? Human capital is at the core of the knowledge-based economy. It is the volume of all knowledge that in a country, a region or a sector is used or is potentially available for the production of goods and services. In many regions, the demographic change will produce a need to replace decreasing labour by increasing human capital to attain higher productivity. MS DE DE DE SE DE BE UK CZ EE FI

Top ten regions in 2007

HCI EU27 = 100

This table shows the ten regions with the highest human capital intensity index in 2007 Dresden 137 Leipzig 136 Chemnitz 134 Stockholm 134 Brandenburg - Südwest 133 Prov. Brabant Wallon 132 Inner London 132 Praha 131 Eesti 130 Etelä-Suomi 129

The Human Capital Intensity (HCI) is calculated from the Eurostat Labour Force Survey data by adding the share of population aged 25–64 with a ‘medium’ qualification level to the share of population aged 25–64 with a ‘high’ qualification level times two. A Human Capital Index is then calculated dividing by the EU-27 average and multiplying by 100. The tertiary educational attainment is weighted by a factor of two because the duration of tertiary education is about twice that of secondary II education (general education and vocational training). Since there is a strong relationship between formal education and an individual’s future career path, qualifications acquired in skills-intensive jobs are taken indirectly into account. How do the EU regions score? EU wide HCI has increased from 17.3 to 18.9 between 2000 and 2007, a remarkable increase of 9 % over a period of only seven years. Nevertheless, very substantial differences remain. National values vary between 7.9 in Malta and 24.5 in Estonia. 123


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Convergence

Transition

RCE

Human Capital Intensity (EU27 = 100)

95

92

104

Evolution 2000 - 2007

1

6

-1

As reflected by the top 10 regions, the highest growth rates have been in Ireland and in southern European regions. As a result disparities between Member States and between regions have actually declined over the period 2000–07. MS

Top ten regions movers

Change in HCI index

This table shows the ten regions in which the human capital index increased most between 2000 and 2007 IE Border, Midland and Western 30 IE Southern and Eastern 26 ES Galicia 22 ES Aragón 20 ES La Rioja 19 PT Região Autónoma da Madeira 19 ES País Vasco 18 GR Kriti 17 GR Dytiki Ellada 17 ES Castilla-La Mancha 17

This trend is set to continue. The differences in HCI concerning the younger age groups in working life are far less pronounced than for the population as a whole. This is the result of increasing participation rates in post-obligatory secondary education in regions that were lagging behind. Moreover much of the growth is actually due to rising shares in high qualifications. The diffusion of medium and higher qualifications in the economies of less developed regions is improving as well. These developments point to an increasing endogenous potential for innovation and creativity to be ‘exploited’ as well as a challenge for local institutions and firms.

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4. Human capital intensity by gender Measures the quality of the labour force by gender Why does this matter? Human capital is at the core of the knowledge-based economy. It is the volume of all knowledge that in a country, a region or a sector is used or is potentially available for the production of goods and services. Traditionally women had less access to medium and high level qualifications than men, reducing thereby the overall potential for innovation and creativity. MS

Top ten regions

HCI men HCI women

This table shows the ten regions with the highest HCI for women in 2007 DE

Leipzig

131

142

DE

Dresden

134

140

EE

Eesti

119

140

DE

Chemnitz

130

139

SE

Stockholm

129

139

FI

Etelä-Suomi

121

137

BG

Yugozapaden

120

136

BE

Prov. Brabant Wallon

129

135

DE

Brandenburg - Südwest

132

134

SE

Mellersta Norrland

109

134

The Human Capital Intensity (HCI) is calculated from the Eurostat Labour Force Survey data by adding the share of population aged 25–64 with a ‘medium’ qualification level to the share of population aged 25–64 with a ‘high’ qualification level times two. The tertiary educational attainment is weighted by a factor of two because the duration of tertiary education is about twice that of secondary II education (general education and vocational training). Since there is a strong relationship between formal education and an individual’s future career path, qualifications acquired in skillsintensive jobs are taken indirectly into account.

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How do the EU regions score? EU wide HCI has increased from 17.3 to 18.9 between 2000 and 2007, a remarkable increase of 9 % over a period of only seven years. This is mostly the result of the participation of younger age groups and more particularly young women in post-obligatory secondary and higher education. Over the period 2000–07 the HCI gap between men and women has reduced from 1.5 to 0.5. In 2000, the HCI index for women was higher or equal than for men in approximately one region in four. It is now the case in nearly half the regions. Convergence

Transition

RCE

HCI Index for women (2007)

96

65

103

Evolution 2000-2007

1.1

6.6

-0.9

Comparing the 2007 HCI by gender and by age groups gives an insight of the mechanisms underlying this trend. The HCI is higher for the age group 25–34 is in virtually all regions higher than for the age group 60–64, though more so for women than for men. While the HCI of men is higher than for women in the age group 55–64, it is generally the reverse in the age groups 25–34. Contrary to the generation that is 20 to 40 years older, young women are now better qualified than young men. MS

Top ten regions movers

Change in HCI index

This table shows the ten regions in wich the HCI index for women increased most between 2000 and 2007. IE

Border, Midland and Western

31

IE

Southern and Eastern

28

ES

Galicia

22

ES

Aragón

21

ES

Castilla-La Mancha

18

ES

País Vasco

18

GR

Thessalia

18

GR

Kriti

18

ES

Cantabria

17

FR

Nord - Pas-de-Calais

17

The proportion of the working population prepared to invent new products, to apply new techniques in marketing, to cover local demand for services and adapting to new technologies is growing for both genders and more rapidly for women than for men.

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5. Foreign-born population of working age Measures the number of people aged 15–64 residing in country which is different from the country of birth divided by the total population aged 15–64. The data does not take into account seasonal work and education/training (unless they imply a change of residence), movement of workplace over shorter periods (daily commuting) or movement of workplace without a change in permanent residence. Why does this matter? The diffusion of new ideas and practices by people with different backgrounds boosts creativity and productivity. Labour born abroad brings an important diversity to the working process. Migrants are often younger and more dynamic than the people who stay. International mobility of the working age population plays an important role also in the adjustment process to the changes induced by the globalisation, e.g. changes in demand, technologies and so on. Population aged 15-64 born in another country

Convergence

Transition

RCE

2.8

10.3

12.5

The working age population born in a different country tends to concentrate in wealthier regions. The Regional Competitiveness and Employment (RCE) regions have a considerably higher share of working-age population born in a different country. It is four times higher than in the Convergence regions. In the Transition regions, the share is three times higher than in the Convergence regions. How do the EU regions score? The share of working-age population born in a different country differs widely between regions and Member States. The capital regions in western Europe are the most attractive to the foreign-born working-age population and people of different backgrounds in general, which is one of the reasons that many metropolitan regions generate more patents and are more productive. The Balearic Islands and Flevoland form the only exception. In the latter case, the majority of people residing in the region actually work in the capital city. In all the cases, except Luxembourg, the vast majority of the foreign born were born in a country outside the EU.

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Country

Top Ten regions

Population aged 15-64 born in another country, % of total population 15-64

This tables shows the ten regions with the highest share of population aged 15-64 born in another country UK

Inner London Luxembourg (Grand-Duché)

45.3

LU

Région de Bruxelles-Capitale / Brussels Hoofdstedelijk

41.8

BE

Gewest

38.1

AT

Wien

36.1

UK

Outer London

34.6

ES

Illes Balears

25.2

FR

Île de France

23.2

SE

Stockholm

22.0

ES

Comunidad de Madrid

21.9

NL

Flevoland

21.8

DE: nationalit y not country of birth IE: nationality of t otal population (all ages)

The shares tend to be very low in most of the central and eastern Member States. All the regions with a share of working-age population born in a different country below 1 % are located in Bulgaria, Hungary, Poland and Romania. A differences in the innovation capacity and creativity between the richer and poorer regions is one of the reasons for the gap in the economic development.

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6. Hotel arrivals per inhabitant Why does this matter? This indicator measures the number of arrivals per inhabitant in hotels and similar establishments in 2007. Country

Top 10 regions

Hotel. arrivals per head

This table shows the 10 regions with the highest number of hotel arrivals per inhabitant IT

Provincia Autonoma Bolzano/Bozen

9.1

AT

Tirol

8.8

ES

Illes Balears

8.1

AT

Salzburg

7.3

EL

Notio Aigaio

7.0

PT

Algarve

6.0

IT

Valle d’Aosta/Vallée d’Aoste

5.1

EL

Ionia Nisia

4.9

IT

Provincia Autonoma Trento

4.7

UK

Highlands and Islands

4.4

Hotel arrivals are often used to measure the importance the tourism industry. Tourism is a key economic sector in some regions where it provides a substantial number of jobs, in particular for low-skilled workers. Travel and tourism are also important channels conveying new people and new ideas. Besides leisure and recreational activities, hotel arrivals account for business and scientific conferences, which constitute major source of growth in some regions. How do the EU regions score? Regions with a high number of hotel arrivals per inhabitant are generally located in the western Member States which host all top 10 regions. Most of these regions are in southern Europe and/or offer an attractive natural environment, notably mountainous areas. Most regions in the central and eastern Member States (CE Member States) feature much lower numbers of hotel arrivals per capita. Regions with the highest number of hotel arrivals are Praha (3.5), Malta (3.0) and Cyprus (3.0). Such records remain exceptional and on average, the number of hotel arrivals is 0.64 in the 10 CE Member States against 1.57 in the western Member States. 132


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Country

Top 10 Movers

Average annual change in hotel arrivals in %

This table shows the 10 regions with the fastest growth of hotel arrivals between 2000 and 2007 LT

Lietuva

22.4

BG

Yugoiztochen

22.3

LV

Latvija

16.4

BG

Yugozapaden

14.6

BG

Severozapaden

13.3

BG

Severen tsentralen

11.2

PL

Łódzkie

11.2

PL

Lubuskie

10.7

PL

Podlaskie

10.4

RO

Bucureşti — Ilfov

10.4

However, regions where the number of hotel arrivals has grown the fastest are mostly in the CE Member States. Between 2000 and 2007, hotel arrivals grew by 22.4 % in Lietuva and by 22.3 % in Yugoiztochen, Bulgaria. In the other Member States, the highest growth rate is in Região Autónoma dos Açores, Portugal but is only 7.6 %. This shows that the potential for tourism related development is far from fully exploited in the CE Member States. For some of their regions, these domains still present important opportunities for starting up new activities and therefore constitute a major source of future growth and employment.

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7. Tolerance Index This measure is based on nine questions in special Eurobarometer (269), 2008, on discrimination. The index is the share respondents who are comfortable 2 with the following nine situations: having a woman, or someone of a different ethnicity, a different religion or belief, with a disability or a homosexual in the highest elected political position or (with the exception of a woman) as a neighbour. A difference of more than five percentage points between Member States is statistically significant. Why does this matter? Discrimination greatly reduces the quality of life and the opportunities of its victims. It also hinders social and economic development as often the best candidates for a job or position are not selected and the most dynamic will move away. Innovation thrives in more open and tolerant societies, and in this way also boosts development. How do the Member States score? Overall, the EU is a relatively tolerant place: four out of five respondents said they were comfortable with these situations. Most respondents were comfortable with a neighbour with a disability (93 %) and a woman in the highest elected political position (92 %). The share or respondents for these questions was consistently high in all Member States. Least respondents were comfortable with someone with a different ethnicity (60 %) or religion (65 %) or a homosexual (67 %) in the highest elected political position. On these questions opinions differed more between Member States. For example, in the Netherlands 94 % are comfortable with a homosexual in the highest elected political position while in Bulgaria, it is 25 %. In Sweden 83 % are comfortable with a person with a different ethnicity in the highest elected political position as compared to 29 % in Cyprus. The majority of respondents said that discrimination was less widespread than five years ago, in particular for women and the disabled. But the majority, in 15 Member States, said that ethnic discrimination had become more widespread. For example, in the Bulgaria, Denmark and the Netherlands, two out three respondents thought that ethnic discrimination had become more widespread in their country. Overall, the EU is relatively tolerant, but tolerance of neighbours and politicians of a different ethnic group, religion or sexual orientation is lower and discrimination based on ethnicity was perceived as having grown in most Member States. 2

Score of 6 or higher on the range of 1 (very uncomfortable) to 10 (totally comfortable).

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8. Core Creative Class Measures the share of the population aged 15–64 in professions which require the creation of meaningful new forms as defined by Richard Florida in his book The Rise of the Creative Class. Why does this matter? The Core Creative Class has a strong impact on the number of new start-ups and new jobs. They are typically the people who come up with new ideas and put them into practice, which leads to more new and more innovative and productive firms and more jobs. Research has shown that this class has a stronger impact on economic development than the share of tertiary educated. How do the EU regions score?

Convergence

Transition

RCE

Core creative class on population aged 15-64 2006-07

5.4

6.9

8.3

Change in % core creative class 2000-01 - 2006-07 in % points

1.1

0.9

1.0

Country

Top Ten Movers

Cange in % in core creative class

The ten regions with the highest share of population aged 15-64 in the core creative class in 2006-07 SE

Stockholm

15

NL

Utrech

14.3

UK

Inner London

13.6

RO

Bucuresti- llfov

12.6

FI

Etela Suomi

12.6

UK

Bershire, Buckinghamshire and Oxfords hire

12.6

CZ

Praha

12.5

NL

Noor-holland

12.4

BE

Prov. Brabant Wallon

12.1

FR

He de France

11.9

No data for RO, FR9 and OK national level

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The Convergence regions lag behind the RCE regions. On average, the difference is just less than three percentage points. The top 10 regions are either capital regions or regions located close to the capital with a major university. In some Member States, the share of creative class tends to be high in most regions such as in Belgium, the Netherlands, Finland, Sweden and the UK, while in others such as Bulgaria, Portugal and Romania only the capital region has a high share. Country

Top Ten Movers

Change in % in core creative class

The ten regions where the state of population aged 15-64 in the core creative class increased most between 2000-01 and 2006-07 in % points UK

Comwall and Isles of Sicily

3.9

SI

Zahodna Slovenia

3.4

GR

Thessalia

2.7

DE

Trier

2.7

PL

Mazowieckie

2.7

ES

Pais Vasco

2.5

LU

Luxembourg (Grand-Duché)

2.5

GR

Ipeiros

2.5

PL

Slaskie

2.4

GR

Attiki

2.4

No data for RO, FR9 and DK national level

Over the six-year period, the share of creative class grew by 1 percentage point in the EU to 7 %. The top 10 movers, however, have increased their share substantially, which allowed all of these regions, with the exception of Śląskie, to surpass the EU average. Also the top 10 movers contain many capital regions or regions with major universities. In conclusion, capital regions and regions with major universities are successful at creating jobs for the creative class. This will give these regions an edge when it comes to employment growth and the number of start-ups, especially high-tech start-ups. Although the Convergence regions did not catch up with the RCE regions, they did manage to generate the same increase in the core creative class as the EU.

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Lewis Dijkstra

9. Productivity in industry and services Is Gross Value Added (GVA) divided by persons employed in industry and services. Why does this matter? Productivity growth is the main source of higher economic growth in the Union. Productivity can increase when employment declines or when GVA grows. The first is usually a sign of restructuring, with shifts out of labour-intensive activities. The increase in GVA relative to employment, on the other side, occurs independently from the phase of the economic development and it is an indication of high innovation capacity, high education level, good governance and so on. It has long-term implications for the competitiveness of the regions/countries. Productivity in industry and services (PPS) in EU27=100, 2006 Change in productivity in industry and services, average annual % change, 2000-2006

Convergence

Transition

RCE

63

90

113

1.94

1.27

0.94

The Convergence regions score better on productivity in industry and services than on GDP per capita because the high share of employment in agriculture distorts the productivity figures and because the lower employment rates in these regions are responsible for a part of the gap. How do the EU regions score? Country

Labour productivity in industry and services, in pps, indexed to the EU average

Top Ten regions

This table shows the ten regions with the highest labour productivity in industry and services in 2006 NL

Groningen Luxembourg (Grand-

196

LU

Duché)

153

DE

Hamburg

151

FR

Île de France Région de Bruxelles-

150

BE

Capitale / Brussels

148

DE

Oberbayern

141

SE

Stockholm

140

DE

Darmstadt

138

NL

Utrecht Prov. Brabant

138

BE

Wallon

136

excl. the regions of UK

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The top 10 regions are located mainly in capital cities and industrial areas of Northwest Europe. Most of other Dutch regions, the Belgian Vlaams Brabant, the regions in the north-western part of Germany and west of Austria also lie above 120 %. At the other end, the Bulgarian and the Romania regions occupy the first 10 places having improved from 12 to 25 % as compared to the EU average. All the CE Member States lie below the EU average. Change in productivity in industry and services, annual average % change, 2000 - 2006 This table shows the ten regions with the fastest growth of labour productivity in industry and services between 2000 and 2006 Country

Top Ten Movers

LV

Latvija

6.17

EE

Eesti

6.15

LT

Lietuva

5.82

CZ

Moravskoslezsko

5.28

RO

Sud - Muntenia

4.89

SK

Bratislavský kraj

4.72

RO

Sud-Vest Oltenia

4.69

PL

Dolnośląskie

4.67

NL

Groningen

4.58

HU

Közép-Magyarország

4.55

excl. the regions of UK

Except Groningen, the average labour productivity of the regions among the top 10 movers was below 30 % of the EU value in 2007 and 22 % in 2000. In fact, all the regions with an annual average percentage change of three or more are located in the CE Member States, except the capital region of Greece. Severozapaden and Yugoiztochen in Bulgaria, but also many regions in the south of Italy, have not followed this trend and recorded a negative change in the industrial and service’s labour productivity. The increase in productivity in the CE Member States signals a fast catching-up process to the average EU productivity and GDP/capita levels.

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10. New Foreign Firms Measures the number of new foreign firms created per million inhabitants Why does this matter? A new foreign firm means a significant amount of foreign direct investment. It could entail building an entirely new factory and employing hundreds of people or taking a controlling stake in a firm, freeing up funds for further investments. A new foreign firm means a new and often strong competitor for firms who produce a similar product or service in the region. However, it also presents an opportunity to develop a strong cluster and for both competitors and suppliers to learn new business practices. By embedding the firm in the region, positive knowledge spillovers can be enhanced, making the region more innovative and productive. How do the EU regions score?

Convergence

Transition

RCE

New foreign firms per million inhabitants 2005-07

267.5

61.6

224.7

Change in new foreign firms per million inh. 2001-03 to 2005-07

117.9

-33.9

-17.6

The Convergence regions have become an attractive destination for new foreign firms. In less than five years, these regions have almost doubled the number of new foreign firms moving in. In the most recent period, convergence region outperformed the RCE regions. Country

Top Ten regions

New Foreign firms per million inhabitants

This table shows the ten regions with the highest number of new foreign firms per million inhabitants in the period 2005-07 RO

Bucureşti - Ilfov

6,813

UK

Inner London

5,143

RO

Vest

1,911

RO

Centru

1,592

RO

Nord-Vest

1,340

UK

Berkshire, Buckinghamshire and Oxfordshire

1,155

IE


1,154

UK

Surrey, East and West Sussex

878

BE

Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest

843

UK

Outer London

771

No data for ES63 and ES64

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Lewis Dijkstra

The top 10 regions are located mostly in Romania and the UK. The map also shows the strong preference of new foreign firms to locate in the capital region. Five out of the top 10 regions include their national capital. The non-capital regions of the the Czech Republic, Portugal and Slovakia score low. All the Greek regions and most of the Italian and Spanish regions also score low. Overall, Belgium, Ireland, Luxembourg, the Netherlands, Austria, Poland and the UK attract many new foreign firms. Change in new foreign firms per million inhabitants This table shows the ten regions with the biggest increase in the number of new foreign firms per million inhabitants between the periods 2001-03 and 2005-07 Country

Top Ten Movers

RO

Bucureşti - Ilfov

2,602

RO

Vest

1,215

IE


1,123

RO

Centru

1,062

UK

Inner London

979

RO

Nord-Vest

867

RO

Sud-Est

504

UK

Surrey, East and West Sussex

452

SE

Stockholm

358

RO

Sud - Muntenia

353

Excluding ES63 and ES64

The changes over time have been substantial with Ireland, Romania, Stockhom and London improving their already good performance considerably. At the other end of the spectrum several regions also saw a big reduction in the number of new foreign firms. The capital regions of Belgium, Bulgaria, Denmark, Hamburg and Austria saw the number of new foreign firms per head drop by more than 400 firms. In conclusion, foreign firms and FDI will continue to play a key role in EU regional development. The key question is which regions will be able to capitalise on this trend and which will not, especially in light of the crisis.

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Lewis Dijkstra

11. Business expenditure on R & D This indicator measures the share of regional GDP invested in business expenditure on research and development (BERD). Why does this matter? BERD indicates the extent to which firms in the region are active in developing innovations and transforming new ideas into market opportunities through R & D. In general, the majority of activities related to R & D take place within the private sector. BERD is therefore also a key indicator of the region’s involvement in terms of innovation. How do the EU regions score? Scores on this dimension vary widely across EU regions. BERD is highly concentrated from a geographical point of view. Ten regions account for an 32 % of this type of expenditure in the EU. Country

Top 10 regions

BERD in % GDP

The 10 regions with the highest Business expenditure on R & D as a % of GDP in 2006 DE

Stuttgart

4.9

SE

Västsverige

4.6

DE

Braunschweig

3.9

FI

Pohjois-Suomi

3.7

DE

Oberbayern

3.7

UK

Lancashire

3.6

UK

Essex

3.4

SE

Sydsverige

3.4

SE

Stockholm

3.2

DE

Tübingen

3.2

BE NUTS1, DK national, no data for FR9 (=DOM) and BG31

Regions with the highest BERD to GDP ratio are all located in Germany, the Nordic Member States and the UK, with BERD exceeding 3 % of GDP. At the other end of the spectrum, a series of regions mainly located in Bulgaria, Greece, Poland, Portugal, Romania and Spain have shares that are practically negligible.

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Lewis Dijkstra

In general, regions in the western Member States have much higher BERD than in the CE Member States. On average, the share of regional GDP spent of BERD is 1 % in the western 15 Member States against 0.3 % in the 10 CE Member States, Cyprus and Malta. Country

Top 10 Movers

Change in BERD as % of GDP

The 10 regions with the biggest increase in % points in BERD as a % of GDP, 2000–06 FR

Midi-Pyrénées

1.20

AT

Kärnten

1.12

CZ

Moravskoslezsko

1.05

SE

Västsverige

0.90

CZ

Praha

0.75

IE

Border, Midland and Western

0.74

AT

Oberösterreich

0.73

ES

Comunidad Foral de Navarra

0.73

AT

Steiermark

0.62

SE

Sydsverige

0.59

BE and UK NUTS 1; BG, DK and SI national, no data for FR9 and seven PL regions

Changes in the BERD also feature important variations from one region to another. In Midi-Pyrénées and Kärnten, the ratio of BERD to GDP increased respectively by 1.20 and 1.12 percentage points between 2000 and 2006. In Rheinhessen-Pfalz and Střední Čechy, the share of GDP spent on BERD decreased by 0.82 and 0.73 respectively over the same period. Regions with a high growth of BERD are mostly located in the west, with some exceptions such as the two Czech regions. If this trend of high BERD growth in the west continues, R & D-based innovation would concentrate even further in this part of the Union.

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The Entrepreneurship Indicator programm

9. Linking creativity and entrepreneurship: a description of the joint OECD/Eurostat Entrepreneurship Indicators programme

Manfred Schmiemann (Eurostat)

Abstract The OECD-initiated programme to collect internationally harmonised indicators on entrepreneurship is complemented with work done by Eurostat since 2007. A comprehensive set of performance indicators has already been agreed and data have been made available. Work continues in getting more countries involved and in setting up a framework to measure determinants for entrepreneurship, like the regulatory framework or the area of ‘access to finance’.

Creativity is universal The online issue of the American Journal ‘Proceedings of the National Academy of Sciences’ (PNAS), 28 May 2009, reported on scientific findings by researchers from Cambridge and Queen Mary Universities in the UK (Birth and Emery, 2009) that challenge our notion of Homo sapiens or even primates being the only creative species: in short, captive non-tool-using rooks (a crow species) were offered pieces of wire, and it was shown that they are able to bend the wire pieces such that they can use them as creatively altered tools to get to food. It was previously known that crows will make even successive use of tools in their search for food. But with the newlydiscovered creative, ‘enterprising’ toolmaking, it could be argued that if those crows were to set up a business, start mass producing those tools and marketing them, and in this process notably employing other crows (preferably those previously lacking 149


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an occupation) they should then be called veritable entrepreneurs in the best sense of the word as coined by Jean-Baptiste Say 1 . This, however, is an unlikely scenario, but the link between creativity and entrepreneurship merits a closer look.

Creativity and entrepreneurship in the business economy Entrepreneurship has long been recognised as an important driver of economic growth, innovation and employment, and it is widely credited to support economic dynamism through the creation of new firms and their subsequent growth or downsizing. As firms enter and exit the market, theory suggests that the new arrivals will be more efficient than those they displace. Existing firms that are not driven out by the new, more creative competition are forced to innovate and become more productive. Numerous studies have offered empirical support for this process of ‘creative destruction’ first described by Joseph Schumpeter (1934). While economic studies have thus long acknowledged and analysed the entrepreneurship phenomenon, policymaking has not appropriately taken account of those findings. It was often an overriding objective of national, regional and even municipal policy efforts to simply increase the population of small new firms when it would have been more beneficial at the macroeconomic scale to stimulate entrepreneurs to introduce new products, processes or organisational forms (hence introduce innovation) in order to access new markets, increase their productivity or offer more and better paid employment. Policymakers only recently have discovered entrepreneurship and innovation to be the cornerstones of economies that can compete, nationally or internationally. Entrepreneurship policies are intrinsically closely related to innovation policies, with which they share many characteristics and challenges. Both are associated with ‘doing something new’ (and thus requiring creativity) and, if set up and controlled properly, they can be mutually reinforcing. The dynamic process of new firm creation introduces and disperses innovative products, processes and organisational structures throughout the economy, as the theory of creative destruction suggests. Despite the increasing importance of entrepreneurship and associated policies, measurement of the phenomenon, particularly at the international level, has long been deficient. There had been numerous ad hoc initiatives at local, regional or na1

Say, the first professor of political economy in France, introduced free-market economics to Europe in general and to France in particular. He presented his vision of the laws of political economy in his 1803 masterpiece, A Treatise on Political Economy. Say invented the term ‘entrepreneur’ and emphasised the vital and creative roles of the entrepreneur in the economy as forecaster, project appraiser, and risk taker.

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tional levels, and even a few at the international level, but consistent, comparable data were scarce. Moreover few, if any, National Statistical Institutes (NSIs) recognised the concept of entrepreneurship and no international forums existed to permit agreement on definitions or measures. The OECD itself had addressed entrepreneurship through various analytical studies and reports, but no systematic effort had been made to establish an ongoing database devoted to comparing entrepreneurship across OECD countries. In 2004, the second OECD Ministerial Conference on SMEs and Entrepreneurship in Istanbul concluded that the statistical base for entrepreneurship research was weak and urged the OECD to develop ‘a robust and comparable statistical base on which policy can be developed’. The rationale for developing entrepreneurship indicators is to help policymakers to understand how the policies they create or adjust will affect entrepreneurship and, eventually, higher-level objectives for the economy and society, like robust economic growth, reduction of poverty and unemployment, and immigration of talent. In order for countries to benefit from the experience of others, it is also essential that the indicators allow for comparisons across countries and over time. But it is not sufficient to measure how much entrepreneurship takes place. Countries need to understand the determinants of and obstacles to entrepreneurship, and they need to analyse the effectiveness of different policy approaches. The lack of internationally comparable empirical evidence has constrained serious research and many questions remain unanswered. Ultimately, policymaking must be guided, as far as possible, by evidence and facts.

The Entrepreneurship Indicators Programme The OECD began the Entrepreneurship Indicators Programme (EIP) under the mentorship and academic leadership of Tim Davis in 2006 in order to build internationally comparable data on entrepreneurship and its determinants (see Davis, 2006), in cooperation with NSIs. In 2007, Eurostat’s official involvement launched the joint OECD-Eurostat EIP, and work began on defining core indicators as the basis for the collection of empirical data. Since entrepreneurship is a multifaceted concept that manifests itself in many different ways, no single definition has been generally agreed upon. Furthermore, many definitions have an essentially theoretical basis and are not concerned with measurement. The European Commission has developed their definitions in the context of the Green Paper on Entrepreneurship (European Commission 2003). The OECD-Eurostat approach has built upon the conceptual definitions of entrepreneurship but with a view to the empirical measures relevant for policy interests. Drawing on the theoretical contributions of Richard Cantillon, Adam Smith, Jean-Bap151


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tiste Say, Alfred Marshall, Joseph Schumpeter, Israel Kirzner and Frank Knight, among others, the following definitions were established: yy Entrepreneurs are those persons (business owners) who seek to generate value through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets. yy Entrepreneurial activity is enterprising human action in pursuit of the generation of value through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets. yy Entrepreneurship is the phenomenon associated with entrepreneurial activity. In this context, creativity seems to be a necessary but not sufficient precondition of entrepreneurship — more input factors are needed. Audretsch and Thurik (2002) are to be credited to have widely established the term ‘determinants’ for input factors such as access to capital, provision of talent, and the regulatory framework. Also inspired by a number of other previous scholarly and policy-oriented studies, a simple, three-stage entrepreneurship model was proposed as the first component of a framework for empirical indicators that are both relevant and feasible. The first stage of this model (Figure 1) comprises various determinants which policy can affect and which in turn influence entrepreneurial performance, or the amount and type of entrepreneurship that takes place. The final stage is the impact of entrepreneurship on higher-level goals such as economic growth, job creation or poverty reduction. While the entrepreneurship framework is presented here in a linear fashion, it was explicitly recognised that there are complex relationships among the different main components and subcomponents.

Figure 1: Topic categories for entrepreneurship indicators

Within each of the three main stages of this model, several subcategories are identified to flesh out the overall framework and guide the selection of indicators.

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Given the multifaceted nature of entrepreneurship, the EIP does not propose any single measure as the key to understanding and comparing the amount and type of entrepreneurship that takes place across countries. It is very important for policy analysts to be able to understand and distinguish different types of entrepreneurial performance. The goal of the EIP is to establish a framework of relevant indicators as well as a core list of indicators with standard definitions, methodologies and classifications. The steering group that developed the metadata comprised policy analysts and, importantly, the responsible data experts from NSIs. This approach assured relevance and also feasibility. The core entrepreneurship indicators selected were either available or potentially available, from existing data sources 2 .

Determinants for entrepreneurship and their link to creativity As Figure 1 shows, the preliminary grouping of determinants is as follows: yy regulatory framework yy access to finance yy R & D and technology yy entrepreneurial capabilities yy culture yy market conditions The determinant group ‘R & D and technology’ is perhaps the main link between creativity and entrepreneurship, and is to be understood as ‘access to R & D and technology’ via university technology transfer, for example. An international workshop at Copenhagen in October 2008 attempted to provide an internationally harmonised list of potential indicators, yet to be approved by the EIP’s Steering Group 3 . Based on the discussions at the workshop it was proposed that the determinant group ‘R & D and Technology’ be changed to ‘Creation and diffusion of knowledge’. Moreover, the policy areas previously included are proposed to be modified. For instance, one important proposal is to move the policy area ‘Patent system, standards’ to the ‘Regulatory framework’ pillar in the EIP.

2

3

A unique (OECD and Eurostat) website entry to all available data, as well as a repository of background documents, is available (http://www.entrepreneurship-indicators.net) which gives access via a masked hyperlink to a secure European Commission data server. The workshop proceedings are available via the above mentioned website by clicking the ‘Copenhagen workshop’ icon.

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Manfred Schmiemann

All proposed subgroups of the ‘R & D’ determinant pillar have a clear link to creativity:

1. R & D activity Research and experimental development (R & D) creates opportunities for entrepreneurship and covers a wide variety of activities that raises and drives the availability of knowledge. R & D activity can be devoted to human and financial resources, also referred to as R & D input (OECD 2002). Thus, two main R & D inputs are normally identified: R & D personnel and R & D expenditure. The R & D can both be privately and publicly funded. Moreover, local knowledge created by firms conducting R & D may spill over to other firms run by entrepreneurs.

2. Transfer of non-commercial knowledge Effective technology or knowledge transfer regulation might open and speed up the process of transferring non-commercial research into the business economy, thereby effectively creating new opportunities for potential entrepreneurs. Non-commercial research might be conducted at universities, at other higher education, in non-profit organisations or in government agencies. The regulatory framework can for instance be enhanced by policies encouraging universities or other institutions engaged in research and development activities to facilitate the development of ventures, spinouts, or other forms and manifestations of knowledge and technology transfer based on publicly funded research. Universities often commercialise their research whereby their knowledge transfer has a commercial side effect. However, as research at universities originates as a non-commercial activity it is considered as a transfer of non-commercial knowledge.

3. Cooperation among firms In general cooperation among firms is important. Firms can benefit from cooperation activities with different partners, i.e. private or public partners from different countries. Cooperation manifests itself in for instance clusters or through joint ventures. Moreover, knowledge created in clusters due to cooperation may have spillover effects. One possible way of cooperation is for existing firms to play a role in developing entrepreneurship in new and younger firms either through corporate venturing or by actively working with these firms. For example, the success of Silicon Valley compared to the Boston ‘Route 128’ area in the early 1990s has been explained by the more open attitude towards cooperation in Silicon Valley (Herbig and Golden, 1993). 154


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4. Technology availability and take-up This policy area refers to the general availability of technology in societies. The spread and use of existing and new technologies — both products and processes — are important to firms. Examples include advanced technologies for energy efficiency, high-speed networks and new communication platforms. Many entrepreneurs may use existing technology in new ways and may benefit from the uptake and diffusion of technologies in general, i.e. among partners and consumers. For instance the wider use of the Internet is hugely beneficial to entrepreneurial activity. Entrepreneurs can buy patents to protect their own technology products or processes through the IPR system. Patent protection provides the availability of technologies and knowledge for entrepreneurs. ‘Access to finance’, another determinant pillar, has regrettably also seen some creative input before the onset the economic crisis (and triggering it?). Although this was not yet investigated or discussed by statistical experts, a planned data collection of small firms’ problems with access to capital will deliver results on this phenomenon in 2010/11. ‘Entrepreneurial capabilities’ will be the topic of another workshop of the Copenhagen type — venue and exact dates to be determined. The ‘Regulatory framework’ is for the moment best documented on the World Bank’s ‘Doing Business’ database and website 4. The determinant pillars ‘Culture’ and ‘Market conditions’ can be further researched via the EIP’s unique website entry 5.

Conclusions Creativity, like innovation or education, is a necessary but not sufficient precondition of entrepreneurship. The right framework conditions and the fitting research, educational, financing and marketing systems can fuel the creative spirit to bring about marketable products of creativity. It cannot be assessed from the point of view of an entrepreneurship expert how creativity can flourish over and beyond its marketable output, but the incentives to provide a functioning market economy with well defined business and entrepreneurship conditions seem to pay off. At least this is the primary results of a joint OECD/Eurostat EIP that aims at identifying and internationally harmonising indicators and determinant groups for entrepreneurship, with a clear link to their impact, such as economic growth and immigration of talent. This programme will ultimately, if extended to the regional level, also allow for a comparison of regions attracting the ‘creative class’. 4 5

http://www.doingbusiness.org/ http://www.entrepreneurship-indicators.net, click on ‘Determinants’ field and then access library.

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Manfred Schmiemann

References Audretsch, D. B., Thurik, R., Verheulm, I. and Wennekers, S. (Eds.) (2002): Entrepreneurship: Determinants and Policy in a European – U.S. Comparison. London: Kluwer Academic Publishers. Bird, C. D. and Emery, N. J. (2009): Insightful problem solving and creative tool modification by captive nontool-using rooks. Proceedings of the National Academy of Sciences. Retrieved May 28, 2009 from: http://www.pnas.org/content/early/2009/05/28/0901008106.abstract Davis, T. (2006): Understanding entrepreneurship: Developing indicators for international comparisons and assessments. OECD strategy paper, Paris 2006. Retrieved in June 2009 from http://www.olis.oecd.org/olis/2006doc.nsf/linkTo/STDCSTAT(2006)9 European Commission (2003), Green Paper Entrepreneurship in Europe. COM(2003) 27 final, Brussels: European Commission Herbig, P.A., J.E. Golden (1993): The rise of innovative hot spots: Silicon Valley and Route 128, International Marketing Review, vol. 10, issue 3. OECD (2002): Proposed Standard Practice for Surveys for Research and Experimental Development, Frascati Manual. Paris: OECD. Schumpeter, J A. (1934): The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle. Cambridge, MA: Harvard University Press.

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Creativity at work in the European Union

10. Creativity at work in the European Union

Edward Lorenz (CNRS-University of Nice) and Bengt-Aake Lundval (University of Aalborg)

Abstract While creativity has attracted the attention of researchers in such disciplines as behavioural psychology, management and education studies, relatively little attention has been given to comparison of creativity across national systems. Drawing on the results of the fourth European Working Conditions Survey carried out in 2005, this paper starts by developing a measure of creativity at work for the 27 member nations of the European Union and shows how the importance of creativity varies according to sector and occupational category for the European Union as a whole. A simple model is presented explaining the likelihood of an employee being engaged in creative work activity in terms of features of work organisation, human resource management policy, and such personal characteristics as educational background and years of working experience. National differences in the importance of creativity are then examined and the links between creativity at work and national innovative performance are explored, using aggregate indicators derived from the fifth Community Innovation Survey. The paper concludes by considering the policy implications of the results and argues that European policy efforts to improve innovation performance as part of the revised Lisbon strategy need to take a closer look at the effects of work organisation and employee learning dynamics on innovation 157


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Edward Lorenz, Bengt-Aake Lundval

Introduction Creativity has attracted the attention of researchers in a variety of disciplines including behavioural psychology and management. Within the field of psychology the focus has been primarily on the relation between creativity and such individual attributes as intelligence, knowledge and personality (Barron and Harrington, 1981; Helson, 1996; Sternberg, 1988; Sternberg and Lubart, 1991; Weisberg, 1993) 1. In the management literature the focus has been more on the how creativity emerges from the interaction between the individual employee and various aspects of management style and work organisation. Woodman, Sawyer, and Griffin (1993), for example, see creativity as resulting from the interaction of individual, group and organisational variables. Amabile et al. (1996) similarly focus on social and organisational factors arguing in particular that creativity at work is supported by organisational and supervisory encouragement as well as by a diversity of ideas within the work group (also see Baharadwag and Menon 2000; Drazin, Glynn and Kazanjian 1999; and Ford 1996). Although there has been some work on the cultural or systemic basis of creativity (Csikszentmihalyi, 1988; Lubart, 1999), prior to Richard Florida’s publication of The Rise of the Creative Class (2002) relatively little attention has been given to analysing creativity at the levels of regions and nations. By putting forward creativity as the driving force of economic growth, and by presenting the rise of creativity as a general account of the current transformation of the economy comparable to the knowledge-based economy hypothesis, Florida’s research has done more than any of the more specialised research to bring creativity to the forefront of debate in the social sciences. Further, in a series of empirical studies focusing on the relation between investments in human capital, creativity and regional economic performance, Florida and his co-authors have argued that the creative class provides a new and alternative standard to the level of educational attainment for measuring human capital in studies focusing on regional development (Florida, Mellander, and Stolarick, 2007; Mellander and Florida, 2006) Drawing inspiration from Florida’s research as well as from the more specialised research on creativity in the fields of behavioural psychology and management, in Section 2 of this paper we develop a measure of creativity at work and describe how the importance of creativity varies according to sector and occupational category for the European Union as a whole. We then, in Section 3, develop a simple model explaining the likelihood of creativity at work in terms of features of the employee’s work organisation, the human resource management policies he or she is subject to, and such personal characteristics as educational background and years of working expe1

See R. J. Sternberg (1999) for an overview of the literature.

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rience. In Section 4 we make use of logit regression analysis to examine differences in the importance of creative work across the 27 member nations of the EU, and we consider to what extent these variations in creativity are associated with differences in national innovative performance.

Measuring the creative workforce A major theme in the behavioural psychology literature on creativity is that of ‘eminence’ or being ‘unique in all the world’, and there are a number of empirical studies of creativity focusing on the lives of truly exceptional musicians, artists or scientists. In contrast to this focus on eminence, there is a body of research focusing on ‘everyday’ or ‘local’ creativity of the sort that a large percent of the working population engage in in the course of their daily problem-solving activities (Reilly, 2008; Craft, 2005; Richards 1996). Florida’s notion of the creative class corresponds to this latter, more broadly distributed, form of creativity. In Florida (2002), he states that the distinguishing characteristic of the creative class is that its members ‘engage in work whose function is to create meaningful new forms’ (p. 68). The highest level of creative work, characteristic of what Florida refers to as the ‘super-creative core’, involves ‘producing new forms or designs that are readily transferable and widely useful …’ (p. 69). This group includes such occupations as scientists, university professors, poets and architects. Beyond this core, Florida includes within the creative class a diverse group of creative professionals who, ‘engage in creative problem-solving, drawing on complex bodies of knowledge to solve specific problems.’ He observes, ‘what they (creative professionals) are required to do regularly is think on their own’ (p. 69). Further, he notes that many technicians are included in the creative class as they, ‘apply complex bodies of knowledge to working with physical materials’ and in a number of fields, ‘are taking on increased responsibility to interpret their work and make decisions …’ (pp. 69–70). As the above references show, Florida’s notion of the creative class is an economic one referring to the kinds of work activities or jobs that different occupational categories typically undertake. Consistent with this, and in order to measure the size of the creative class and its growth over time for the US economy, he draws on the occupational classifications and figures compiled by the US Bureau of Labor Statistics (BLS) which are based on the 1998 Standard Occupational Classification (SOC) system. The SOC, in common with the International Standard Classification of Occupations (ISCO), groups jobs together in occupations and more aggregate groups mainly on the basis of the similarity of skills required to fulfil the tasks and duties of the jobs. This identification of the standard skill requirements for different jobs allows Florida to assign occupations to three distinct social classes: the creative class, the service class and the 159


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working class. The creative class is defined to include most management occupations, professionals and selected categories of technicians and assistant professionals 2. Florida (2002, pp. 75, 330) estimates that the creative class increased from three million workers or 10 % of the workforce in 1900 to 38.3 million or 30 % in 1999. In 1999, the working and service classes are estimated at 26.1 and 43.4 % of the work force respectively, with agriculture making up the remaining 0.5 %. While this way of measuring the size of the creative workforce is appropriate for capturing broad changes in the importance of creativity within an economy over time, it has a number of limitations when it comes to pursue an internationally comparative analysis. Firstly, as Florida’s discussion of the creative factory emphasises (Florida, 2002, p. 52), creativity can extend down from the firm’s management and technical services to the shop floor, and highly creative firms typically seek to mobilise the knowledge and skills of the entire workforce. The blanket characterisation of the work of operators, sales and service staff and craft workers as non-creative is at odds with a vast literature on ‘learning organisations’ that emphasise the collective and multilevel nature of learning and creativity at the workplace. Second, there is a well-established internationally comparative literature which identifies important international differences in the organisation of work. In particular, detailed international comparisons show that the jobs and work activity of the same occupational categories can display significant national variations, requiring more or less learning and problem-solving activity and differences in responsibility and autonomy (Maurice, et al., 1982; R. Dore, 1973, Doeringer et al., 2003; Lorenz and Valeyre, 2006.) Third, work on sectoral systems of innovation (Malerba, 2002) points to important differences in the technological dynamism of different sectors of the economy and thus it can be anticipated that the work of the same occupational categories will display marked difference in terms of problem-solving activity and creativeness according to the sector. This implies a need to take into account differences in industrial structure across nations in any statistical analysis of the determinants of creativity at the workplace. In order to develop a measure of the creative workforce that is suitable for a comparative analysis of the EU-27, we draw on the results of the fourth European Working Conditions Survey carried out in 2005 by the European Foundation for the Improvement of Living and Working Conditions. The analysis covers private sector establish2

For the list of occupational categories included in the creative class see Florida 2002, pp. 328–29. In terms of the ISCO used by the European Union, Florida’s creative class is composed of Management Occupations (ISCO 12–13), Professionals (ISCO 21–24) and some of the occupations classified as Technicians and Associate Professionals (ISCO 31–34). The service class is composed of Clerks (ISCO 41–42), Service Workers (ISCO 51–52) and Sales and Service Elementary Occupations (ISCO 91). The working class is composed of Craft and Related Trade Workers (ISCO 71–74), Plant and Machine Operators (ISCO 81–83) and Labourers in Mining, Construction, Manufacturing and Transport (ISCO 93).

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ments of the EU-27 employing 10 or more salaried persons and the total size of the sample is 9 240 salaried persons 3. In order to develop a measure of the creative workforce that is consistent with Florida’s (2002) characterisation of the creative class, we use factor analysis to identify the underlying associations that exist among six binary variables that capture key features of creative work activity (See Table 1) 4. We then use hierarchical clustering in order to group the population into three basic types of workers: creative workers, routine problems solvers and taylorised workers 5. Table 1: Creative work variables % occupied persons affected Problem-solving activities in work

79

Learning new things in work

68

Undertaking complex tasks

62

Using one’s own ideas in work

50

Able to choose or change one’s work methods

60

Able to choose or change the order of one’s tasks

56

N

9 240

Source: Fourth Working Conditions Survey, 2005, European Foundation for the Improvement of Living and Working Conditions

Table 1 above shows the percentage of the population characterised by the six work activity variables that are used in order to classify a worker as creative. Thus, as Florida observes, creative workers typically engage in complex problem-solving activities. Further, workers who use their own ideas in settings where they exercise considerable discretion over their work methods or task order correspond to the distinguishing creative feature of being able to, ‘think on their own’ and to take on, ‘increased responsibility to interpret their work and make decisions’. These six work activity variables do not, however, provide a basis for discriminating between the creative workforce as a whole and the ‘super creative core’ which Florida defines in terms of the outcome of producing transferrable and widely used new forms or designs.

3

4 5

The sample excludes agriculture and fishing; public administration and social security; education, health and social work; and private domestic employees. The exact wording of the questions upon which the measures are based are presented in the Annex, Table A1. The factor method used is multiple correspondence analysis. In order to group the individuals, Ward’s method of hierarchical clustering is used on the basis of the factor scores, or the coordinates of the observations, of the first two factors which account 59 % of the total variance of the data set. See the Annex for a graphical presentation of the factor analysis.

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Table 2 shows the composition of the three groups resulting from the hierarchical cluster analysis. The first group, which accounts for 51 % of the population, is characterised by high levels of problems solving, learning and task complexity. The persons grouped in this cluster use their own ideas and exercise considerable autonomy in carrying out their jobs. We refer to them as ‘creative workers’. The second group is characterised by nearly as high levels of problem-solving and learning and comparable levels of task complexity. However, there is little use of one’s own ideas and levels of autonomy or discretion in work are low. This cluster groups employees who, while regularly solving technical or other problems in work, do so in highly supervised settings offering little scope for developing original or creative solutions based on their own ideas. We refer to them as ‘routine problem solvers’. The third group is composed largely of persons doing deskilled work. Levels of learning, problem-solving and task complexity are low. There is little use of one’s own ideas and there is limited scope for exercising discretion in how work is carried out. We refer to this group as ‘taylorised workers’. Table 2: Cluster analysis of types of workers % occupied persons by type of learner reporting each variable Creative workers

Routine problem-solvers

Taylorised workers

Average

Problem-solving activities in work

96

87

37

79

Learning new things in work

87

84

16

68

Undertaking complex tasks

80

81

8

62

24

19

50

Variable

Using one’s own ideas in work

77

Able to choose or change one’s work methods

94

21

29

60

Able to choose or change the order of one’s tasks

92

14

25

56

Total share of occupied persons

51

24

25

100


Table 3 shows that there are variations in the importance of creative learners according to industrial sector. In particular, creative learners are over-represented in business services and in community, social and personal services, while they are under-represented in manufacturing, construction and retail and other services.

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Table 3: Type of Worker by Sector of Activity % occupied persons by sector of activity and type of learner Creative workers

Routine problem solvers

Taylorised workers

Total

Manufacturing, construction and utilities

46

27

27

100

Retail and other services

49

23

29

100

Business and financial services

67

19

13

100

Community, social and personal services

59

18

22

100

Average

51

24

25

100

Variable


Table 4 points to the considerable diversity that exists in the importance of creative work across broadly defined occupational categories (as defined by the ISCO). Although the large majority of senior managers, professionals and technicians, which make up the bulk of Florida’s creative class, are highly over-represented in the creative worker cluster, roughly half of the occupations making up the clerks and sales and service category, who form Florida’s service class, engage in creative work activity. Moreover, a significant minority of the manual occupations making up Florida’s working class engage in work requiring creative learning, problem-solving and the use of one’s own ideas. The results shown in Table 4 point, for the EU at any rate, to the limitations of using standard occupational categories as the basis for identifying the group of workers who are creative in work. Significant proportions of service workers and manual workers may work in settings where they are called upon to make creative use of their own ideas. Table 4: Type of Worker by Occupational Category % occupied persons by occupational category and type of worker Creative workers


Taylorised workers

Total

Senior managers

82

10

7

100

Professionals and technicians

74

18

8

100

Clerks and service workers

53

23

24

100

Skilled workers and machine operators

38

30

32

100

Unskilled workers

33

24

43

100

Average

51

24

25

100

Variable


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Accounting for creativity at work The analysis above, while identifying important variations in creativity across sectors, shows that ‘the creative class’ is an elastic category that can be widened to include significant parts of what Florida has defined as the working and services classes. In this section we draw inspiration from the behavioural psychology and management literature in order to test a simple model where the likelihood of an employee having access to creative work activity is determined by features of work organisation and managerial practice as well as by the personal characteristics of the employee. The behavioural psychology literature focuses on the importance of domain specific expertise for creativity (Csikszentmihlyi, 1996; Sternberg, 2000). Expertise is seen as being based on the mastery of a body of codified knowledge as well as tacit knowledge based on experience. A variety of empirical evidence has been mustered to demonstrate that creativity is preceded by a number of years of working experience in the field, possibly accompanied by formal education and training (Weisberg, 1988; 1993). Although much of the anecdotal evidence focuses on eminent individuals characterised by exceptional creativity (Simonton, 1985), the importance of expert thinking has also been supported by research focusing on everyday or ‘local’ creativity such as that displayed by group facilitators or teaching assistants in academic settings (Craft, 1998; Reilly, 2008). Drawing inspiration from this literature, in the econometric analysis presented below we investigate the relation between the likelihood an employee is engaged in creative work activity and indicators of the acquisition of both formal codified knowledge and informal experience-based knowledge. In order to capture the acquisition of formal knowledge of the sort codified in academic texts and manuals, we use a three-level variable, EDUC, indicating whether the highest level of formal education successfully completed is primary or none, secondary or post-secondary but not tertiary, or tertiary. As a proxy for capturing the importance of domain-specific knowledge acquired through a number of years of practical work activity, we use a binary indicator of whether or not the employee has over 10 years of working experience since completing full-time education (EXPRC). The fourth European Survey of Working Conditions provides only limited information on the characteristics of work organisation and human resources practices. One of the key factors identified in the management literature as promoting creativity is support from management and support from work group members. Amabile et al. (1996, pp. 1158–1161), for example, observe that encouragement at the organisational, management and work groups levels is one of the most frequently cited factors in the literature on creativity at work. The management literature also points to a posi164


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tive relation between creativity and the diversity of team members’ ideas and backgrounds (Albrecht and Hall, 1991; Amabile, et al., 1996; Kimberly and Evanisko, 1981; Payne, 1990; Roffe, 1999). A third factor is the provision of off-the-job training which can enhance expertise both by updating skills and knowledge acquired through initial formal education and by imparting new formal knowledge that is complementary to that gained through practical work experience (Amabile, 1988; Basadur et al., 1986; Wheatley et al.1991). A fourth factor cited in the management literature is rewards and recognition for creative performance. The impact of rewards and recognition on creativity is ambiguous and contingent on whether or not they combine synergistically with such intrinsic motivating factors as curiosity, enjoyment or a personal sense of challenge. While it is often assumed that extrinsic motivators undermine intrinsic motivation, on Amabile’s (1997) account reward and recognition that confirm accomplishment do not necessarily weaken intrinsic motivation and can even enhance performance. On the other hand, if rewards and recognition are perceived by the employee as management tools that are being used to control his or her effort they are likely to be detrimental to intrinsic motivators. In order to capture the presence of supportive supervision and colleagues, we use two binary indicators. ASTSUP measures whether or not the individual can almost always or often get assistance from his or her superiors/boss when it is asked for; and ASTCLG is a binary indicator of whether or not the individual can almost always or often get assistance from his or her colleagues when it is asked for. In order to capture diversity in the knowledge of employees we use an indicator of whether or not the employee is involved in systems of task rotation requiring different skills, ROTSK. Further training that contributes to expertise is measured by a binary indicator, FTRAIN, of whether or not the employee has over the last 12 months received training to improve his or her skills paid for or provided by the employer. The distinction between rewards that complement intrinsically motivating factors versus those that don’t is difficult to capture with survey data. Here we address the issue indirectly by including binary indicators of two forms of variable pay, piece rate or productivity payment, PIECRT, and payments based on the overall performance of the enterprise such as profit sharing schemes, CMPAY. Our assumption is that piece rate or productivity payments are likely to be perceived by employees as management devices designed to control their individual effort. Payments linked to overall company performance, on the other hand, are more likely to be perceived by employees as rewards or recognition that confirm collective accomplishment. We thus expect a negative relation between the use of piece rate or productivity payments and the importance of creative work activity, and a positive relation with the use of payments linked to company performance. We also include controls for broadly defined sector of activity (SCRT), occupational 165


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category (OCC), establishment size (SIZE) and gender (GNDR). The formal definitions of the variables used in the econometric analysis including the control variables are provided in Table 5 below. Table 5: Definitions of variables used in econometric analysis Variable name

Definition

EDUC

Three level categorical variable, equal to 1 if the highest level of education successfully completed is primary or none; 2 if the highest level is secondary or post-secondary but not tertiary; 3 if tertiary.

EXPR

Binary variable equal to 1 if the employee has over 10 years of working experiences since completing full-time education; otherwise 0.

FTRAIN

Binary variable equal to 1 if the employee has received over the last 12 months training to improve his or her skills paid for or provided for by the employer; otherwise 0.

ASTUP

Binary variable equal to 1 if the employee can often or almost always get assistance from his or her superiors/boss if it is asked for; otherwise 0.

ASTCLG

Binary variable equal to 1 if the employee can often or almost always get assistance from colleagues if it is asked for; otherwise 0.

ROTSK

Binary variable equal to 1 if the employee’s job involves rotating tasks requiring different skills between him or herself and colleagues; otherwise 0.

PIECRT

Binary variable equal to 1 if the employee’s remuneration includes piece rate or productivity bonus payments; otherwise 0.

COMPAY

Binary variable equal to 1 if the employee’s remuneration includes payments based on the overall performance of the company; otherwise 0.

OCC

Five level categorical variables equal to 1 for senior manager; 2 for professionals, technicians and associate professionals; 3 for clerks and service workers; 4 for craft and related workers; 5 for operators, assemblers and elementary workers.

SCTR

Four level categorical variable equal to 1 for manufacturing, construction and utilities; 2 for retail and other services; 3 for business and financial services; 4 for community, social and personal services.

SIZE

Four level categorical variable equal to 1 if the size of the establishment is between 10 and 49 employees; 2 if between 50 and 99; 3 if between 100 and 499; 4 if 500 or more.

GNDR

Binary variable equal to 1 if the employee’s gender is female, 0 if male

Table 6 below presents the results of the econometric analysis for models with and without structural controls and controls for gender. Examining first the model without the control variables, we can see that the results confirm the various hy166


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potheses developed above concerning the organisational practices and personal characteristics that favour creativity at work. Thus there are positive and statistically significant coefficients on our measures of the acquisition of both formal codified knowledge (EDUC) and experienced-based knowledge (EXPRC). Moreover, higher levels of formal education are associated with a higher probability of being engaged in creative work activity. There are also positive and significant coefficients on the measures of supportive supervision and support from colleagues, the measure of job rotation practices favouring knowledge diversity, and the measure of further vocational training. As we anticipated, there is a negative relation between the likelihood of creative work and the use of individual piece rate or productivity bonuses, and a positive relation between creative work and the use of payment systems linking an employee’s remuneration to overall company performance. The results in the model including control variables are the same as regards the levels of significance with the exception of the negative coefficient on the use of individual piece rate which is no longer significant at the 5 % level. The positive coefficients on the variables measuring the level of formal education are reduced in size showing that once an employee’s occupation is taken into account the positive effect of higher levels of formal education on creative work activity is weakened. Considering the control variables, we can see that relative to manufacturing and mining creative work is more likely in community, social and personal services, while for business and financial services and retail and other services there are no significant differences. As expected, creative work activity is more likely for senior managers and professionals relative to skilled workers and machine operators, and it is also more likely for clerks and sales workers relative to skilled workers and machine operators. Expressed in terms of odds ratios, senior managers are nearly six times as likely to be engaged in creative work activity and professional and technicians are about four times as likely. Sales and clerks are about twice as likely as skilled workers and operators to be engaged in creative work activity. There is a quite strong and statistically significant negative coefficient on the gender variable. Expressed in terms of odds ratios, women are only about 40 % as likely as men to be engaged in creative work activity 6. The results also show that there are no statistically significant differences in the likelihood of creative work activity across different size categories of establishments.

6

It is important to note that this relation holds after controlling for education, years of experience, sector and occupational category. This points to a kind of inequality that might be more important in a dynamic context than gender pay differences.

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Table 6: Accounting for Creative Work Activity Logit estimates without structural controls

Logit estimates with structural controls

Educ2

.63 **

.50 **

Educ3

1.75 **

1.07 **

Exprc

.36 **

.32 **

Astsup

.37 **

.34 **

Astclg

.39 **

.39 **

Rotsk

.34 **

.37 **

Ftrain

.50 **

.37 **

Piecrt

– .37 **

– .23

Cmpay

.65 **

.56 **

Sctr2

-.05

Sctr3

.11

Sctr4

.50 **

Occ1

1.75 **

Occ2

1.39 **

Occ3

.74

Occ5

– .05

Size2

– .12

Size3

– .18

Size4

– .22

Female

– 1.90 **

* significant at the 5 % level; ** significant at the 1 % level.

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Considering the control variables, we can see that relative to manufacturing and mining creative work is more likely in community, social and personal services, while for business and financial services and retail and other services there are no significant differences. As expected, creative work activity is more likely for senior managers and professionals relative to skilled workers and machine operators, and it is also more likely for clerks and sales workers relative to skilled workers and machine operators. Expressed in terms of odds ratios, senior managers are nearly six times as likely to be engaged in creative work activity and professional and technicians are about four times as likely. Sales and clerks are about twice as likely as skilled workers and operators to be engaged in creative work activity. There is a quite strong and statistically significant negative coefficient on the gender variable. Expressed in terms of odds ratios, women are only about 40 % as likely as men to be engaged in creative work activity 7. The results also show that there are no statistically significant differences in the likelihood of creative work activity across different size categories of establishments.

National effects The analysis in Section 3 has brought out certain common determinants of creative work activity for the EU-27. While creative work everywhere is promoted by certain types of work organisation and management policies, as Table 7 below shows, there are wide differences in the importance of creative work activity across EU member nations. Creative workers are most present in Malta, the Netherlands and the Nordic nations and least present in Bulgaria, the Czech Republic, Greece, Spain, Italy, Cyprus, Lithuania, Hungary, Poland, Romania and Slovakia. There are intermediate levels of creative work activity in the continental European nations, Ireland, Portugal and the UK and, amongst the new member nations, in Estonia, Latvia, and Slovenia. The frequency of taylorised workers tends to show the reverse trend to that of creative workers, being lowest in Malta, the Netherlands and the Scandinavian countries and highest in the southern nations, Bulgaria, the Czech Republic, Cyprus, Lithuania, Hungary and Slovakia. The frequency of routine problem solvers is relatively high in Greece and in the new member nations with the exception of Latvia and Slovenia and, to a lesser, extent Lithuania.

7

It is important to note that this relation holds after controlling for education, years of experience, sector and occupational category. This points to a kind of inequality that might be more important in a dynamic context than gender pay differences.

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Table 7: National differences in Types of Learners: EU-27 (% occupied persons by country and type of learner) Creative workers


Taylorised workers

Total

Belgium

60

21

19

100

Czech Republic

40

30

30

100

Denmark

70

15

14

100

Germany

52

23

26

100

Estonia

58

22

20

100

Greece

39

33

28

100

Spain

35

30

36

100

France

63

18

19

100

Ireland

58

18

24

100

Italy

37

29

34

100

Cyprus

42

26

32

100

Latvia

53

19

27

100

Lithuania

35

27

38

100

Luxembourg

60

20

20

100

Hungary

44

31

25

100

Malta

70

14

16

100

Netherlands

67

16

16

100

Austria

50

28

23

100

Poland

43

34

23

100

Portugal

46

24

29

100

Slovenia

50

25

25

100

Slovakia

33

32

35

100

Finland

66

21

13

100

Sweden

82

10

8

100

United Kingdom

51

22

27

100

Bulgaria

39

30

31

100

Romania

35

38

27

100

EU-27

51

24

25

100


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Table 3 above identified differences in the importance of creative work activity across broadly defined sectors of activity, and some of the national differences in the frequency of creativity shown in Table 7 may be attributable to cross-national differences in industrial structure. It is also possible that international differences in occupational structure or in the size structure of establishments may explain some of the differences in the frequency of creative work across the member nations of the EU. In order to control for the effects of these structural variables, we have undertaken a logistic regression analysis explaining the likelihood an employee is engaged in creative work in terms of nation, industrial sector, occupation and establishment size. The results are presented in Table 8 below. The first column results in Table 8 show national effects on the likelihood of creative work without structural controls and the second column with these controls. Germany, which has a profile of types of learners close to the EU-27 average, is used as the reference case. The results thus show whether or not creative work activity is significantly more likely in a nation relative to the German case. The first column results (without structural controls) show that creative work is significantly more likely in the France, Malta, the Netehrlands and the Nordic countries. Expressed in odds ratios an employee working in Sweden is 4.4 times as likely as an employee in Germany to be engaged in creative work activity. The likelihood of creative work is not significantly different in the continental nations with the exception of France, and the likelihood is significantly lower in the southern nations with the exception of Portugal for which the difference is not significant. Creative work activity is less likely in a number of the new member nations including, Bulgaria, the Czech Republic, Lithuania, Poland, Romania and Slovakia. Expressed in odds ratios, the likelihood of creative work is only 0.46 times as likely in Slovakia as it is in Germany. The second column results report national effects after taking into account the effects of cross-national differences in the structure of sectors, occupational categories and establishment size. Most of the results reported in column one remain the same in terms of the direction of the sign and statistical significance. The exceptions are Belgium and Estonia for which the positive coefficients are now significant at the 5 % level, and Cyprus, Poland and Romania for which the negative coefficients are no longer significant at the 5 % level or better.

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Table 8: Logit estimates of national effects on creative work activity Logit estimates without structural controls Belgium Czech Republic Denmark

Logit estimates with structural controls

.33

.44 *

– .45 **

– .17

.81 **

.89 **

Estonia

.26

.45 *

Greece

– .52 **

– .48 *

Spain

– .70 **

– .49 *

France

.48 **

.51 **

.24

.06

Italy

Ireland

– .60 **

– .48 *

Cyprus

– .40 *

– .33

Latvia

.07

.23

– .67 **

– .36 *

.34

.21

Hungary

– .29

– .07

Malta

.81 **

1.03 **

Netherlands

.66 **

.60 **

Lithuania Luxembourg

Austria

– .08

.06

Poland

– .33 *

– .03

Portugal

– .21

.27

Slovenia

– .06

.10

Slovakia

– .77 **

– .61 **

Finland

.62 **

.68 **

Sweden

1.47 **

1.64 **

– .01

– .20

– .54 **

– .41 *

United Kingdom Bulgaria

Romania – .69 ** * significant at 5 % level; ** significant at 1 % level. Reference country: Germany

– .33

There are significant differences in the importance of creative work activity across the member nations of the European Union. Creativity is arguably at the foundation of nation’s capacity for knowledge development and in this section we make a prima facie case for the link between the level of creativity at work and a nation’s innovative performance. In Figures 1 through 3 below we present a series of scatter plot diagrams showing the correlations between the frequency of creative work activity and 172


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three measures of innovative performance. The first measure, shown in Figure 1, is the number of patent applications to the European Patent Office per million inhabitants. The figure shows that there is a positive correlation between the frequency of creative work and this classic measure of innovative performance (R2 = .46) 8.

Figure 1

While patents provide a measure of nation’s capacity to develop novel products or technologies, the weaknesses of patent statistics for measuring national innovative performance are well known. A large fraction of innovations are not patented and the importance of patenting varies across sectors and size categories of firms. In order to respond to these limitations, Figures 2 and 3 examine the relation between the importance of creativity and two more all encompassing measures of innovation performance based on the results of the fifth Community Innovation Survey, which concerns innovative activity over the period 2004–06. The first is a broad measure of innovation performance, the percentage of firms in the population which have introduced products that are new to the firm. The measure thus includes innovative activity that 8

The correlation is significant at the 0.0001 level.

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varies widely in terms of the firm’s in-house creative effort. Firms classified as innovative by this measure include not only those relying on intensive in-house R & D to develop products or services that are new to market, but also those that have expended minimal effort to introduce new products developed mainly by other enterprises or institutions. Figure 2 nonetheless shows a positive correlation (R2 = .18) between the frequency of creative work activity and national innovative performance 9.

Figure 2

Figure 3 shows the correlation between creativity and the percentage of firms introducing products that are not only new to the firm but also new to the market. This measure of innovation excludes cases of diffusion of innovations through imitation and the in-house creative effort of firms classified as innovative by this measure can be expected to be relatively high. The positive correlation shown in Figure 3 is positive and nearly as strong as that shown between the frequency of creative work and the less encompassing measure of innovation based on EPO patent applications.

8

The correlation is significant at the 5 % level. Figures for France and the UK in Figures 2 and 3 are based on the results of CIS4 and concern innovative activities for the period 2002–04.

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(R2 = .39) 10. The results thus provide support for the view that the capacity of a nation to develop and bring onto the market authentically new products is closely related to the level of creativity at work.

Figure 3

Conclusions One of the starting points for this paper was the analysis of ‘the creative class’ as developed by Richard Florida. With reference to his work we used employee-level survey data from European countries to classify workers as more or less involved in creative work activity. A first result is that while the occupational categories used by Florida to define the creative class provide a useful means for measuring the rise in the creative class over time within a single nation, they are misleading for purposes of international comparisons. National location matters and we find important ‘national effects’ on the likelihood of creative work activity after adjusting for the effects of an employee’s occupation, sector of activity or the size of the establishment he or she works in. Such national differences may have important impacts on economic performance, and the paper presents some preliminary evidence for systemic links between 9

The correlation is significant at the 1 % level or better.

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the level of creative work activity at establishment level and the capacity of firms to introduce new products or services onto the market. The link between creativity at work and innovation performance raises important questions about how creative work environments can be promoted, especially in those southern and new member nations with relatively weak innovative performance. National differences in creativity have different causes and elsewhere (Lorenz and Lundvall, 2009) we have used multilevel analysis to investigate the impact of differences in national institutional framework conditions at the level of education systems and labour markets on the development of creativity at work 11. Here we have focused more narrowly on the characteristics of work organisation and human resource policies at the establishment level that contribute to building creative work environments. The results suggest that important strides in increasing creativity at work can be made by making appropriate changes in human resource management policies and in organisational practice. More emphasis should be placed on upgrading skills by making investments in continuing vocational training and careful attention should be given to the way compensation policies may impact on intrinsically motivating factors such as personal accomplishment and enjoyment in work. Appropriate changes in work organisation should be made so as to foster knowledge diversity and greater communication and cooperation amongst workers and between workers and management. These results reinforce conclusions that we have developed with our co-authors elsewhere (Arundel et al., 2007) concerning the need for greater emphasis on EU-policies promoting ‘organisational innovation’ and the diffusion of good organisational practice. European policy efforts to improve innovation performance as part of the revised Lisbon strategy need to take a closer look at the effects of organisational practice on innovation. The most important bottleneck to improving the innovative capabilities of European firms might not be low levels of R & D expenditures, but rather the widespread presence of working environments that are unable to provide a fertile environment for learning and creative problem-solving. If this is the case, European policy should make a major effort to develop policy instruments that could stimulate the adoption of ‘pro-innovation’ organisational practice, particularly in countries with poor innovative performance.

10

Our analysis in that paper demonstrates that creative work thrives in countries with broad-based education systems and with labour markets that combine flexibility with active training policies and income security in periods of unemployment.

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References Albrecht, T. and Hall, B (1991). Facilitation talk about new ideas: The role of personal relationships in organizational innovation, Communication Monographs, 58, 273-288. Amabile, T., Hill, K. G., Hennessey, B. A., and Tighe, E. M. (1994). The Work Preference Inventory: Assessing Intrinsic and Extrinsic Motivational Orientations, Journal of Personality and Social Psychology, 66, No. 5, 950-967. Amabile, T., Conti, R., Coon, H., Lazenby, J. and Herron, M. (1996). Assessing the Work Environment for Creativity, Academy of Management Journal, Vol. 39, No. 5: 1154-1184. Amabile, T. R. (1997). Motivating Creativity in Organizations: On Doing What You Love and Loving What You Do, California Management Review, 40:1: 39-58. Arundel, A, Lorenz, E., Lundvall, BA. and Valeyre, A. (2007). How Europe’s economies learn: a comparison of work organization and innovation mode for the EU-15, Industrial and Corporate Change, Volume 16, Number 6, 1175–1210. Bharadwaj, S. and Menon, A. (2000). Making Innovation Happen in Organizations: Individual Creativity Mechanisms, Organizational Creativity Mechanisms or Both? Journal of Product Innovation Management, Vol. 17 Issue 6: 424 – 434 Barron and Harrington (1981). Creativity, Intelligence, and Personality, Annual Review of Psychology, Vol. 32: 439-476. Craft, A. (2005). Creativity in Schools: Tensions and Dilemmas. Oxford: Routledge Press. Csikszentmihalyi, M. (1988). Society, culture, and person: A systems view of creativity, In Sternberg, R. (ed.), The Nature of Creativity: Contemporary Psychological Perspectives, Cambridge, Cambridge University Press. Doeringer, P., E Lorenz, DG Terkla (2003). The adoption and diffusion of high-performance management: lessons from Japanese multinationals in the West, Cambridge Journal of Economics, 27:265-286. R. Dore (1973). British Factory, Japanese Factory: The Origins of National Diversity in Industrial Relations. Berkeley: University of California Press. Drazin, R., Glynn, M.A., Kazanjian, R.K. (1999). Multilevel Theorizing About Creativity in Organizations: A Sensemaking Perspective, The Academy of Management review, Vol. 24, no2: 286-307 Florida, R. (2002). The Rise of the Creative Class. New York: Basic Books. Ford, C. (1996). A Theory of Individual Creative Action in Multiple Social Domains, The Academy of Management Review, vol. 21, no4; 1112-1142

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Florida, R., Mellander, C., Stolarick, K. (2008).Inside the black box of regional development--human capital, the creative class and tolerance, Journal of Economic Geography, 8, 615–649. Mellander, C. and Florida. R. (2006). The Creative Class or Human Capital? - explaining regional development in Sweden, Working Paper Series in Economics and Institutions of Innovation 79. Stockholm; Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies. Helson, R.(1996). In Search of the Creative Personality, Creativity Research Journal, Vol.9, 295-306. Kimberly, J. and Evanisko, M. (1981). Organizational innovation: the influence of individual, organizational, and contextual factors on hospital adoption of technological and administrative innovations, Academy of Management Journal, 24 : 689 – 713 Lam, A. and Lundvall, B.A. (2006). The Learning Organisation and National Systems of Competence Building and Innovation. In E. Lorenz and B.A. Lundvall (eds.) How Europe’s Economies Learn: Coordinating competing models. Oxford: Oxford University Press. Lorenz, E and Valeyre, A. (2006). Organisational forms and innovative performance: a comparison of the EU-15. In E. Lorenz and B.-A. Lundvall (eds.) How Europe’s Economies Learn: Coordinating competing models. Oxford: Oxford University Press. Lorenz, E. and Lundvall, B-A. (eds.) (2006). How Europe’s Economies Learn: Coordinating competing models. Oxford: Oxford University Press. Lorenz, E. and Lundvall, B-A. (2009). Accounting for Creativity in the European Nation: a multi-level analysis of individual competence, labour market structure, and systems of education and training. Paper presented at the 21st Annual Meeting of SASE, Paris, 16-18 July, 2009. Lubart, T. (1999). Creativity across cultures. In R.J. Sternberg (ed.) Handbook of Creativity. Cambridge. Cambridge: Cambridge University Press. Malerba, F. (2002). Sectoral systems of innovation and production, Research Policy 31: 247–264 Maurice, M., Sellier, F. and Silvestre, J-J. (1986). The Social Foundations of Industrial Power. Cambridge: MIT Press. Parent-Thirion, A., Fernández Macías, E., Hurley, J., Vermeylen, G. (2007). Fourth European Working Conditions Survey. Dublin: European Foundation for the Improvement of Living and Working Conditions. Payne, (1990). The effectiveness of research issues: A review. In M. West and J. Farr (eds.), Innovation and creativity at work, 101-122. Chichester, UK: Wiley. 178


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Rasbash, J., Steele, F., Browne, W.and Prosser, B. (2005). A User’s Guide to MLwiN,. Bristol: University of Bristol, Centre for Multilevel Modelling. Reilly, R. (2008). Is expertise a necessary precondition for creativity? A case of four novice learning group facilitators, Thinking Skills and Creativity, 3: 59-76. Richards, R. (1996). Beyond Piaget: Accepting divergent, chaotic, and creative thought, New Direction for Child Development, 72: 67-78. Roffe, I. (1999). Innovation and creativity in organisations: a review of the implications for training and development, Journal of European Industrial Training, Vol. 23: 224-241. Sternberg, R. (ed.) (1988). The Nature of Creativity: Contemporary Psychological Perspectives. Cambridge; Cambridge University Press. Sternberg, R. and Lubart, T. (1991). An investment theory of creativity and its development. Human Development, Vol 34(1), 1-31. Sternberg, R. J. (ed.) (1999). Handbook of Creativity. Cambridge: Cambridge University Press. Weisberg, R. (1993). Creativity: beyond the myth of genius. New York : W.H. Freeman. Woodman, R. W., Sawyer, J. E. Griffin, R. W. (1993). Toward a Theory of Organizational Creativity, Academy of Management Review, Vol. 18, No. 2. pp. 293-321.

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Annex

Figure A1: Graphical Representation of first two factors of MCA-6 Organisational Variables12

The figure above presents graphically the first two axes or factors of the multiple correspondence analysis (MCA). The first factor, accounting for 42 % of the variance in the data set or the chi-squared statistic, distinguishes between creative workers and taylorised workers. On the one side of the axis we find the variables measuring the presence of autonomy, learning, problems solving, complexity and the use of one’s ideas, and on the other side we find the variables measuring their absence. The second factor, accounting for 17 % of the variance in the data set, is defined by the presence of problem-solving, learning and complexity combined with the absence of autonomy and the use of one’s own ideas in work. The projection of the centre of gravity of the three worker clusters coming out of the hierarchical classification analysis (see Table 2) onto the graphic representation of the first two factors of the MCA shows that the three clusters correspond to the quite different types of work activity. The creative cluster is located to the west of the graph, the taylorised cluster to the east, and the routine problem-solving cluster to the south.

11

The + sign indicates the presence of a feature of work activity and the – sign indicates its absence. See Table A1 below for the definitions of the variables.

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Table A1: Survey questions used for the construction of the binary work activity variables Variable

Survey questions

Learning new things (LEARN)

Generally, does your main paid job involve, or not, learning new things?

Employee problem-solving (PBSOLV)

Generally, does your main paid job involve, or not, solving unforeseen problems on your own?

Task Complexity (COMPLX)

Generally, does your main paid job involve, or not, complex tasks?

Using one’s own ideas in work (IDEAS)

Are you almost always or often able to apply your own ideas in your work?

Discretion in fixing work methods Are you able, or not, to choose or change your methods of work? (AUTOMET) Discretion in fixing the order of one’s tasks (AUTORD)

Are you able, or not, to choose or change your order of tasks?

Source: Agnès Parent-Thirion, et al., 2007, pp. 109–134.

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Openness and culture

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Tolerance, heterogeneity, creativity, and economic growth

11. Tolerance, heterogeneity, creativity, and economic growth

Thomas Tiemann, Cassandra DiRienzo, and Jayoti Das, (Economics Department, Elon University, USA)

Abstract The year 2009 has been declared the European Year of Creativity and Innovation by the European Union, at least in part in recognition of the growing importance of creativity in high-income, post-industrial (or at least post-Fordist) economies. Creativity is difficult to define and therefore difficult to measure, yet a two-day conference on measuring creativity has been organised. This paper will try to add to the conversation. First, we briefly place this paper into the conversation about why creativity is important and the measurement of creativity. Second, we present a simple model that shows that our approach is one valid approach to creativity measurement. Third, we briefly present results from other research. Finally, we offer suggestions for future work on measuring creativity.

Introduction The early 21st-century economy is different from past economies, especially in high and medium-income countries. Globalisation has resulted in a different world, where goods, especially commodity goods, are inexpensive and made in low-income countries by low-wage workers. While globalisation has resulted in the movement of most low-wage, low-skill jobs from high-income places, it has also resulted in the a reduction in the real cost of the goods needed for a middle-class lifestyle. Most households in high and medium income places have good food, warm clothing and shelter, and even an automobile. Most homes have good furnishings, space for everyone, and many have a pleasant garden. While displaced manufacturing workers are often struggling, their children are attending university or learning skilled trades. More and more 185


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workers in these countries are working with knowledge, information, and design. The rise in income and the change in how we work have also changed the goods we demand. As incomes have risen and work is changing, people have begun to demand more variety, more experience, and more self-actualisation in both their work and the goods they buy. They want to consume goods that require more creativity to produce, and they want to be more creative at work. As stated in the introduction to this book, there are at least two broad approaches to measuring creativity: measuring individual creativity and measuring societal creativity. Our approach is a societal approach. Within the societal approach, there are at least two streams. One tries to measure creative outcomes like patents issued or entrepreneurial activity. The other approach, the one we have adopted, is to try to measure the level of social capital that supports or encourages creativity in a society. Social capital, as used here, is an input that individuals can use in non-market settings to extract valuable products or resources. The most productive form of social capital probably varies with the level of GDP as Tiemann, Das, and DiRienzo (2006) found. Homogeneity seems to be an important source of social capital at lower levels of GDP; promoting industrialisation requires that people work together and agree on the basic rules of the economy and the workplace. At higher income levels, heterogeneity becomes important because it promotes creativity and innovation; generating new products or processes from ideas heard in non-workplace conversations or noticed while interacting with other people and products while away from work become important uses of social capital. The insights of Jane Jacobs (1961) and Richard Florida (2002) tell us that the greater the diversity of people, ideas, products and processes an individual notices, the greater his or her social capital. If high and medium-income consumers are demanding greater variety, then social capital becomes more important. While social capital is always important, it is especially important in promoting creativity and innovation.

A model Creativity has many definitions with many subtle differences, but most of those definitions centre on newness — the creation of something new. Newness is usually not brand new; it is seldom the creation of something as transformative as the railroad network or the personal computer. Most often, newness is the combination of ideas from different fields or different places, the application of an old concept in a new place; jazz musicians borrow classical themes, three dimensional artists borrow techniques building construction, automotive engineers apply materials long used in aircraft. If this type of thinking is common, then workers are used to crossing borders 186


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and thinking of doing things differently — being creative. The more ideas they have around them, the higher the probability that they will bring two together in new ways. Greater heterogeneity in a society will not only provide the greater variety of goods high income people want today, it will also make the economy more creative. Social capital acts as a catalyst to this process. If there is a wider diversity of people, more tolerance for differences, more interaction among people of different occupations, different industries, and different places, there will be a greater chance that creativity will occur as two old ideas will be combined into a new product. This gives us the model presented in Figure 1.

Figure 1: A model of modern creativity

Looking at Figure 1, heterogeneity both directly produces post-industrial goods by providing a wide variety of things to consume. Heterogeneity in another guise also supports creativity by providing a wide variety of ideas for creative people to combine in new ways. Creativity directly produces new goods, but also adds to the heterogeneity of the place. Social capital is a catalyst, possibly increasing heterogeneity if there is more tolerance of outsiders and new ways of doing things. Social capital also may increase creativity by resulting in more interaction among people in different occupations or from different ethnic groups with different ways of thinking and doing things. Food can be used to illustrate how this all works. People in high-income places have had variety on their menus for many decades, but recently they often want their meals to add surprise or excitement to their lives. Twenty or 30 years ago, restaurant chefs would perfect the menu they offered, carefully executing recipes so that the dishes they served were consistently the same, no matter the season. The same was true of people cooking at home where frozen fish and vegetables, and tomatoes and 187


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peppers grown in a greenhouse or thousands of miles away made preparing the same dishes possible winter and summer. Today, top restaurant chefs no longer carefully execute the same recipes day after day, but as Tom Colicchio, a famous American chef said recently in an interview, “recipes tell you nothing … I’ll walk through a market and see something and an idea will occur to me.” Like the customers at Colicchio’s and thousands of other restaurants, people now want a surprise at dinner. They want constantly changing experiences and providing that requires constant creativity.

Past research supporting this model The positive effect of heterogeneity on high income economies has been forcefully argued by Richard Florida (2002), elaborating on the ideas of Jane Jacobs (1969). Empirically, the importance of heterogeneity was shown by Tiemann, Das and DiRienzo (2006), who found a non-linear relationship between ethnic heterogeneity and GDP/ per capita. At the lowest levels of income, there might be high or low heterogeneity, but as income increases, at first heterogeneity decreases. Then at high incomes, heterogeneity increases. They conclude that heterogeneity may be bad for industrialisation, but good for high income, creativity-based economies. Similarly, Richard Florida (2002) shows broad relationships between his measure of social capital, his ‘creativity index’ and economic growth, both across cities in the US and with Tingali (Florida and Tinagli, 2004), across European countries. Das, DiRienzo and Tiemann (2006) created a ‘global tolerance index’ for 62 countries by using responses on the World Values Survey. Their findings support and extend those of Florida (2002) and Florida and Tingali (2004) as they find that more tolerant countries have greater net immigration, adding more heterogeneity. They also find that more tolerant countries have higher GDP per capita, and score higher on the Human Development Index and the Global Competitiveness Index. Lewis Dijkstra, Philip Kern, and Pascal Cools, in this volume, all argue that social capital is important in promoting creative economic activity. Together, these studies support the idea that social capital, especially tolerance, is a catalyst for greater heterogeneity, greater creativity, and a better life for the people living in a country.

Future ideas for measurement Like the work presented here, most of the work that tries to measure creativity, actually measures attributes in society that are thought to promote creativity. There is good evidence that when a society is more open to difference and has more differ-

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ence that here is greater economic growth, an outcome often attributed to greater creativity. The measures of tolerance and heterogeneity used until now have largely been measures of ethnic difference or acceptance of major differences in ethnicity, religion, or lifestyle. A next step could be to try to measure heterogeneity of skills or occupations at a regional level. If there are machinists and accountants and chefs and longshoremen all thrown together, will a place be more creative than a place that is dominated by bankers? This is a logical step from current practice and could support the ideas presented here and elsewhere. References Cools, P. (2009), ‘Stimulating creativity and innovation in a region needs a long-term and integrated approach’, presented at Can creativity be measured?, May 28 2009, Brussels. Das, J., DiRienzo, C. and Tiemann, T. (2008), ‘A global tolerance index’, Competitiveness Review.18:3, pp. 192–205. Dijkstra, L. (2009), ‘The regional dimension of creativity and innovation’, presented at Can creativity be measured?, 28 May 2009, Brussels. Florida, R. (2002), The Rise of the Creative Class, Basic Books, New York. Florida, R. and Tingali, I. (2004), Europe in the Creative Age. Demos, London. Jacobs, J. (1961), The death and life of great American cities, Random House, New York. Jacobs, J. (1969), The economy of cities, Random House, New York. Kern, P. (2009), ‘Towards a European creativity index’, presented at Can creativity be measured?, 28 May 2009, Brussels. Levine, E. (2009), ‘Craft House’, an interview with Tom Colicchio, The New York Times Magazine, 3 May 2009, pp. 18–20. Tiemann, T., Das, J. and DiRienzo, C. (2006), ‘A note on an ethnic homogeneity Kuznets curve’, Challenge, 49:2. 112–120.

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Towards a European creativity index

12. KEA briefing: towards a European creativity index 1 Philip Kern and Jan Runge (KEA European Affairs) Il faut apprendre à juger une société à ses bruits, à son art et à ses fêtes plus qu’à ses statistiques. Jacques Attali 2

Abstract This paper summarises KEA’s assessment concerning the potential establishment of a European Creativity Index. The assessment was undertaken as part of the study on the contribution of culture to creativity, conducted for the European Commission in 2008/09. It establishes a rationale for including indicators related to culture-based creativity into existing socioeconomic indicator schemes such as the European Innovation Scoreboard and other frameworks with a view to highlight the socioeconomic impacts that culture can have. Upon a brief review of existing indexes linked to innovation, creativity and cultural consumption we suggest that a focus on the cultural dimension of creativity implies taking into consideration a number of factors, many of which are usually not included in other indexes. These include, but are not limited to: education in art schools, cultural employment, cultural offering, cultural participation, technology penetration, regulatory and financial support to creation and the economic contribution of creative industries. We group these indicators in five pillars of creativity, namely: human capital, technology, the institutional environment, the social environment, openness and diversity. The cultural dimension as well as the creative contribution of each of these pillars is discussed and the paper then suggests 32 indicators (including data sources). 1

2

This briefing note is a summary of key messages of KEA’s report ‘The contribution of culture to creativity’, conducted for the European Commission in 2008/ 09; the report can be accessed via KEA’s website (http://www. keanet.eu). In Jacques Attali, Bruits, Fayard 1977.

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Philip Kern, Jan Runge

Introduction Jacques Attali’s words find resonance at a time when statistic projections and corporate management systems seem to have failed public trust at large. Yet, measuring the creative potentials of Europe should be understood as an exercise that ultimately helps to illustrate the importance of culture and creativity to stakeholders outside the cultural realm. Moreover, calls for increased evidence-based policymaking throughout Europe are most likely here to stay. They have so far resulted in the development of a number of statistic indicator schemes which by large do not take creative or cultural factors into account and thus fall short of painting a comprehensive picture of the state of Creative Europe. The following therefore examines the possibility of establishing such indicator framework with a view to set up a European Creativity Index (ECI). A key goal of such index would be to highlight the potential of including culture-based indicators in existing frameworks related to creativity, innovation and socioeconomic development. As part of its Lisbon strategy, the European Commission in 2000 developed a European Innovation Scoreboard to provide a comparative assessment of the innovation performance of EU Member States. This scoreboard has developed into an important tool of pan-European policy learning and succeeded in putting innovation high on the agenda of policymakers in European Member States and Regions. It is based on a wide range of indicators covering structural conditions, knowledge creation, and innovation (see Chapter 4 in this book) but has for long underestimated the role that creativity plays in the innovation process 3. But what do we really mean when we speak about this ubiquitous concept of creativity? In particular from a policy point of view creativity should not solely be considered as ‘a product oriented phenomenon aimed at solving problems’ Lubart (1999). It is as well a quest, a risk, an approach rather than a solution. Because creativity can mean so many things the KEA’s recent study develops the concept of culture-based creativity, which derives from art and cultural productions or activities which nurture innovation. Culture-based creativity is linked to the ability of people, notably artists, to think imaginatively or metaphorically, to challenge the conventional, and to call on the symbolic and affective to communicate. Culturebased creativity is a capacity to break the natural order, the usual way of thinking and to allow the development of a new vision, an idea or a product. Culture-based creativity is creativity that comes from artists, creative professionals and the cultural and creative industries. 3

A review of the Innovation Scoreboard approach is included in KEA’s full report for the European Commission.

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Measuring creativity: a challenging task Measuring creativity is most certainly as challenging as measuring innovation. Innovation can rely on data that is already captured by Eurostat, the statistical office of the European Communities: this includes number of science and engineers graduates, R & D expenditure, venture capital expenditure in ICT, patent applications, etc. However, European and national statistical agencies collect far less detailed data concerning the role of creativity, such as number of art students, expenditure in film, games development or A&R 1. Moreover, KEA’s report explains that it is rather unlikely that such attempts will be made at EU or Member State level in the near future given the subjective choices such exercise would entail. KEA’s report for the Commission briefly examines different strategies for measuring creativity (e.g. Guilford 1950, Kitto, Lock and Rudowicz, 1994, or Helson, 1999). With regards to measuring creativity at the individual level, it concludes that such approach should not be the main focus of policymakers that aim to establish a creativity index. The main reason for this recommendation is the context-dependency of individual creativity (Wallach, 1976). Because of this context-dependency, the reliability of data concerning the creativeness of individuals is often contested. On this basis, and in line with Villalba’s (2008) assessment, we conclude that it is preferable to build a creativity index that focuses on the social and economic factors that influence creativity in general. In order to identify indicators that could be included in an ECI we reviewed national and international indexes linked to innovation, creativity and cultural consumption.

1

Artist & Repertoire — money invested by record companies to develop new artists

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Review of existing indexes We assessed several creativity and innovation related indexes, as summarised below (for further information see Appendix III of KEA’s report on the contribution of culture to creativity): INDEXES

OBJECTIVE

SCOPE

— capture the characteristics of the sociocultural parameters and illustrate the interplay of various factors that are contributory to creativity — list elements that would attract the ‘creative class’ to a location

Set of cognitive, environmental and personality variables that interact to create creative outputs in the Hong Kong’s territory The ‘3Ts’: Technology, Tolerance and Talent Technical innovation, entrepreneurship and openness of society

Creativity Indexes Hong Kong Creativity Index 1 Euro-Creativity Index 54 Flemish Index 2

— benchmark regional innovation

Cultural Life Index

Finnish Report

3

— compile indicators of cultural life

The cultural sector including: music, dance, theatre, fine arts, cultural heritage, libraries, cinema and video, magazines and newspapers

Innovation Indexes EIS 4 Oslo Manual 5

1

2

3

4

5

6

— rank the most innovative Member States — have a better understanding of the innovation process

Technological innovation Economic output as well as human capital (education, talent)

The ‘Hong Kong Creativity Index’ developed by the Home Affairs Bureau of the Hong Kong Special Administrative Region Government published in November 2004 (A study on Hong Kong Creativity Index, November 2004). The ‘Euro-Creativity Index’ developed in the report ‘Europe in the creative age’ by Florida and Tinagli in 2004 on the basis of ‘The Rise of the Creative Class’ published in 2002 (Florida, 2002) (Florida, R., Tinagli, I., 2004). ‘A Composite Index of the Creative Economy’ by H. P. Bowen, and L. Sleuwaegen from Vlerick Leuven Gent Management School and W. Moesen from the Catholic University of Leuven, 2006, (Bowen, H. P., Sleuwaegen L., Moesen W., 2006). The report prepared for the Finnish Ministry of Education and Culture by R. G. Picard, M. Grölund and T. Toivonen on the ‘Means for Overall Assessment of Cultural Life and Measuring the Involvement of the Cultural Sector in the Information Society’ published in 2003 (Picard, R.G., Grölund, M. and Toivonen, T., The Media Group, Business Research and Development Centre, Turku School of Economics and Business Administration, 2003). The ‘European Innovation Scoreboard 2007’ prepared by the Directorate-General for Enterprise and Industry of the European Commission under the Lisbon strategy (European Innovation Scoreboard, 2007). The ‘Oslo Manual: the Measurement of Scientific and Technological Activities, Guidelines for collecting and interpreting innovation data’, third edition, a joint publication of OECD and Eurostat, 2005 (Oslo Manual: the Measurement of Scientific and Technological Activities, Guidelines for collecting and interpreting innovation data, 2005, third edition).

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Establishing the European Creativity Index (ECI) The European Creativity Index (ECI) is a new statistical framework for illustrating and measuring the interplay of various factors that contribute to the growth of creativity in the European Union. As other indicators it measures the performance of a phenomenon using a set of indicators which highlight some of the key features of that phenomenon. It is inspired by existing indexes concerning creativity, innovation and economic performance but introduces elements that are more specifically related to arts and culture. A focus on the cultural dimension of creativity implies taking into consideration a number of factors, many of which are usually not included in other indexes. These include, but are not limited to: education in art schools, cultural employment, cultural offering, cultural participation, technology penetration, regulatory and financial support to creation, economic contribution of creative industries. We group these indicators in six pillars of creativity, illustrated in the graph below.

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Analysis of the pillars of creativity Human capital While it is shaped by a range of external factors (including economic status and cultural norms and values). Learning and education are important indicators concerning the levels of human capital in any given society (OECD, 2001, Barro, 2001). Nevertheless, there are also arguments opposing this positive influence of education and training on creativity. For example, Claxton (2008) highlights that traditional teaching is mainly built on dispositions of analytical thinking and tends to neglect other qualities of mind, such as imagination, intuition and intrinsic curiosity — skills that are key to creativity. Policy documents increasingly seem to acknowledge that the way we learn and develop human capital needs to involve more interdisciplinary, non-cognitive and communicative approaches (OECD, 2001). Culture-based interventions in schools, higher education and lifelong learning can facilitate this creativity shift in learning: ‘The arts provide an environment where the learner is actively engaged in creative experiences, processes and development’ (Unesco, 2006); ‘Research indicates that introducing learners to artistic processes, while incorporating elements of their own culture into education, cultivates in each individual a sense of creativity and initiative, a fertile imagination, emotional intelligence and a moral “compass”, a capacity for critical reflection, a sense of autonomy, and freedom of thought and action 5. Education in and through art also stimulates cognitive development and can make how and what learners learn more relevant to the needs of modern society’ (Unesco, 2006). On the basis that culture plays an important role in fostering the creative dimensions of human capital we suggest a number of indicators related to (i) the potential of culture- and arts-based education (primary, secondary, tertiary) to help foster creative talents and (ii) the level of creative talents coming out of tertiary education and in cultural employment (see Annex 1).

5

For examples of research studies and evidence, refer to the reports from preparatory meetings for the World Conference on Arts Education; cf. LEA International at http://www.unesco.org/culture/lea

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Openness and diversity Contemporary notions of economic development put increasing emphasis on the link between open and diverse societies and their creative and innovative capacities — particularly so in an economic development context. Jane Jacobs (1993) was the first to suggest that diversity and the exchange of ideas are a source of innovation and thus play an important role in the creation of powerful and dynamic cities. Similarly, Richard Florida (2002) showed that creativity cannot flourish without a creative climate characterised by ‘a culture that’s openminded and diverse.’ Regional economic growth is powered by creative people, who prefer places that are diverse, tolerant and open to new ideas. Diversity increases the likeliness that a place will attract different types of creative people. Greater and more diverse concentrations of creative capital in turn lead to higher rates of innovation, high-technology business formation, job generation and economic growth. Importantly, the cultural offering of a city or region (whether indicated by the number of opera houses or the number of underground punk rock bands) makes a place more attractive to these creative talents. Indeed, many argue that there is a highly dynamic relationship between today’s creative entrepreneurs (that are increasingly seen as the motor of the general economy) and the publicly funded arts venues (which stimulate creatives to develop new products and services). On a different level, Sen’s (1993) capabilities approach shows that several substantive freedoms — including freedom of expression and the requirement to access a plurality of information sources — impact on individuals’ most basic ability to realise their full potential. Nussbaum (2000) further develops his line of reasoning and examines the importance of more imaginative, artistic and spiritual ways of individual expression in relation to one’s ability to fulfil individual potentials. The basic idea of such capabilities approach is that people who have access to cultural and information resources as well as the freedom to express themselves creatively and imaginatively stand better chances to lead a better life. We suggest a range of indicators that link issues of openness, diversity and media pluralism to the cultural domain.

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Cultural environment Today, few policy strategies in European Member States link cultural participation and the performance of the cultural and creative sectors to the general progress of society. ‘Successful societies in the 21st century will be those that nurture a spirit of creativity and foster the cultural activity which goes hand in hand with it’ claims a British policy document from 2001. The cultural environment — our concert venues, galleries, book stores and cinemas (to name but a few) — are essential to the development of a creative society. They are the hotspots of disruptive debate and provide ground for argumentation, idea development and networking beyond one’s restricted circle of contacts. As Elizabeth Currid (2007) points out, ‘creativity would not exist as successfully or efficiently without its social world — the social is not the by-product — it is the decisive mechanism by which cultural products and cultural producers are generated, evaluated and sent to the market. ‘Culture is a driver of creativity precisely because of its ‘social properties’. Moreover, various studies have demonstrated that museums and galleries are ‘places where creativity can flourish’ (Hooper et al., 2006) because they ‘encourage people to think differently, to take and transmit ideas and to generate new things based on the creativity of the past’ (Travers and Glaister, 2004). Yet, it is the exposure to arts and culture that will make people creative — not the mere existence of the earlier. Evidence shows that cultural participation — which we measure by looking into level of attendance at cultural events and participation in cultural activities for lack of better statistical data — produces new ideas and innovative ways of expressing oneself. Tony Travers of the London School of Economics and Stephen Glaister (2004) of Imperial College, London, highlighted in a report entitled Valuing Museums: Impact and innovation among national museums, that ‘a student visiting a fine art gallery may find inspiration for a stage design or a fabric. A child visiting a science museum may find inspiration for school that would otherwise be missing. These kinds of spontaneous use of museum and gallery holdings can together be seen as creativity.’ Similarly, a recent study by Engage looked into the learning benefits of engaging with galleries of contemporary art and living artists. It shows that cultural participation helps people to discover intrinsic resources of talent, ingenuity and aesthetic judgement 6. In line with this argumentation we suggest indicators linked to the cultural offer as well as the cultural participation in a given Member State.

6

Report Inspiring Learning in Galleries published by Engage, London, 2008 (Inspiring Learning in Galleries, 2008).

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Technology The fast development of digital technology transforms the global cultural sphere. In the past 10 years technology has had both disruptive and unifying effects in art and the cultural and creative industries, unleashing individual creativity and creating a virtual cultural commons while dismantling traditional business models. As shown by Manuel Castells (1998), digital technology has released two opposing processes taking place at the same time: on the one hand, culture is becoming global as media companies are able to reach out to the entire planet and provide a plethora of creative content to diverse audiences. On the other hand, culture becomes customised, personalised, user-generated and more local. It also shifts increasingly from being focused around experience to engagement. Audiences turn into a participants and consumers into creators. Helmut Anheier and Yudhishthir Raj Isar (2008), in Cultures and Globalisation: the Cultural Economy, point out that ‘the technological products made available to individuals can turn many into creators themselves: from the personal computer and digital camera to the cell phone, humankind inhabits an increasingly networked world in which communication and personal expression and development reign supreme.’ Our indicators concerning the roll out of digital technology infrastructure and equipment try to capture the reciprocity between culture, creativity and ICT proliferation. However, data concerning such phenomenon is limited. The uptake of new forms of content, such as creative user-generated content would, for example, be of interest in this context and more research in this area is needed 7. Data on open content and open source tools would also be beneficial.

The institutional environment The well-being of societies and countries is clearly linked to the transparency, accountability and resilience of their regulatory institutions, as highlighted by several NGO’s such as Transparency International 8. Michael Porter (1990) also identified the clear links between a country’s competitiveness and several institutional factors, including the rule of law and the appropriateness of public policies. The authors of this study suggest the commissioning of a short content analysis concerning the share of cultural content within a sample of member profiles on UCG sites such as Myspace, BEBO or Facebook in all European Member States. 8 The latest Corruption Index for the EU and central Europe (last accessed January 2009) is available online (http:// www.transparency.org). 7

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Residing primarily within the remit of Member States, cultural policies and support initiatives for creativity and the creative industries are diverse across the EU (as shown in Chapter 6). By assessing each Member States indirect and direct investments into culture we propose to assess a country’s ambition to foster an ecosystem conductive to creativity: A further fundamental factor that stimulates creativity and rewards creative people or investment in the cultural and creative industries is copyright (or authors’ right). Copyright is the equivalent to patent in R & D; its function is to provide a monopoly right to protect creators and promote investment in creativity.

The creative outputs Europe’s cultural and creative industries are increasingly considered to be drivers of creativity and economic growth throughout the economy. The National Endowment of Science, Technology and the Arts’ analysis of the Community Innovation Survey 2004 and input-output data concerning the trade between creative companies and companies operating outside the creative industries showed that firms who spend twice the average amount on creative inputs are 25 % more likely to introduce product innovations. It also showed that firms that have supply chain linkages with creative industries typically offer more diverse and higher quality products than those who don’t (Bakhshi et al., 2008). This causation has been a primary interest of this report and we therefore suggest including statistics concerning the performance of the cultural and creative industries as indicators concerning the creative potential of a country. To be sure, this does not imply that the economic contribution of the sector in terms of GDP is equal to its economic relevance for the general economy. It simply recognises that the cultural and creative sectors are an important motor of creativity and innovation in Europe. In this context, the index below includes indicators related to the economic contribution of the cultural and creative industries to a Member State’s GDP as well as indictors concerning outputs of the sector.

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The European creativity index The ECI is thus composed of 32 indicators, grouped over six sub-indexes. HUMAN CAPITAL

DATA SOURCES

The potential of culture- and arts-based education to help foster creative talents 1. Number of hours dedicated to arts and culture in primary and secondary education 2. Number of art schools per million population

‘Key data on education in Europe in 2005’, by Education and Culture DG, Eurydice and Eurostat, available on Eurydice website: www.eurydice.org/ European Leagues of Institutes of the Arts (Elia) website: http://www.elia-artschools.org/

The level of creative talents coming out of tertiary education and in cultural employment 3. Tertiary students by field of education related to culture

Eurostat’s, ‘Cultural statistics’, available on: http://epp. eurostat.ec.europa.eu/

4. Cultural employment in total employment

‘Cultural statistics in Europe’, Edition 2007, Eurostat, p. 54

OPENNESS AND DIVERSITY

DATA SOURCES

Attitude in population 5. Percentage of population that express tolerant attitudes toward minorities 6.Share of population interested in arts and culture in other European countries

EUMC and SORA ‘European cultural values’, 2007, Eurobarometer 278 requested by Education and Culture DG

Market data

8. Level of Media Pluralism in European Member States

The European Audiovisual Observatory: http://www.obs. coe.int/ Current Study on Media Pluralism Indicators carried out on behalf of Information Society and Media DG 1

9. Share of non-nationals in cultural employment

Eurobarometer 278

CULTURAL ENVIRONMENT

DATA SOURCES

7. Market shares of non-national European film

Cultural Participation 10. Average annual cultural expenditure per household 11. Percentage of persons participating in cultural activities at least once in 12 months

Eurostat’s ‘Cultural statistics’ available at: http://epp.eurostat.ec.europa.eu/ Eurostat’s ‘Cultural statistics’ available at: http://epp.eurostat.ec.europa.eu/

Cultural offering 12. Number of public theatres per capita

Data available from relevant national minister

13. Number of public museums per capita


14. Number of public concert halls


1

Currently developed by the University of Leuven as part of an Information Society and Media DG Study on Media Pluralism Indicators in Europe (http://ec.europa.eu/avpolicy/info_centre/library/studies/index_en.htm) (January 2008).

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15. Number of cinema screens by country

The European Audiovisual Observatory: http://www.obs. coe.int/

TECHNOLOGY

DATA SOURCES

16. Broadband penetration rate

Eurostat’s ‘ Sciences and technology ’: http://epp.eurostat. ec.europa.eu/

17. Percentage of households who have personal computers and video game consoles at home

‘Cultural statistics in Europe’, Edition 2007, Eurostat, p. 142

REGULATORY INCENTIVES TO CREATE

DATA SOURCES

Financial support 18. Tax break for artists or people who work in the creative sector 19. VAT rates on books, press, sound recordings, video, film receipts, freelance authors, visual artists 20. Tax incentives concerning donations and sponsoring 21. Direct public expenditure on culture 22. Level of state funding to cinema 23. Level of state funding to public TV

‘Etude sur les crédits d’impôt culturels à l’étranger ’, May 2008, KEA European Affairs, p. 37 Creative Europe, ERICarts Report presented by the Network of European Foundations for Innovative Co-operation, 2002, p. 100 ‘Etude sur les crédits d’impôt culturels à l’étranger ’, May 2008, KEA European Affairs, p. 28 ‘The Economy of Culture’, 2006, KEA, MKW, Turun Kauppakorkeakoulu, p. 125 The European Audiovisual Observatoroy, ‘KORDA’: http://korda.obs.coe.int/web/search_aide.php The European Audiovisual Observatory: http://www.obs. coe.int/

Intellectual Property 24. Level of rights collected by authors in music per capita OUTCOMES OF CREATIVITY

Available from the International Confederation of Societies of Authors and Composers: http://www.cisac.org DATA SOURCES

Economic contribution of creativity 25. Values added of creative industries as % of GDP

‘The Economy of Culture’, 2006, KEA, MKW, Turun Kauppakorkeakoulu, p. 66

26. Turnover in music industries per capita

IFPI website: http://www.ifpi.org/

27. Turnover in book industries per capita 28. Turnover in cinema industries per capita

Eurostats, ‘Cultural statistics’, available at: http://epp.eurostat.ec.europa.eu/ The European Audiovisual Observatory: http://www.obs. coe.int/

Other outcomes of creative activities 29. Number of feature films produced per year and per capita

European Audiovisual Observatory, Yearbook 2007 on ‘Film and home video’

30. Number of recordings released per capita

IFPI website: http://www.ifpi.org/

31. Number of books published per year and capita

Unesco, Institute for Statistics, ‘Culture and Communication’: http://www.uis.unesco.org

32. Number of design applications per million population

OHIM/Eurostat

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Conclusions On the previous pages we briefly summarised our suggestion to include more culturerelated indicators into existing and to be developed indicator frameworks concerning creativity, innovation and economic and social progress. Culture, as has been briefly highlighted in this Chapter and is further explored in our study on the contribution of culture to creativity, is an important resource of the European Union, which is evenly spread across its territory and has the potential to make EU Member States more creative, innovative and sustainable. It is therefore essential for policymakers, economists and statisticians to widen their horizons and start appreciating that culture-based interventions can help Europe to reform its economy and its public services. In these times of economic and social upheaval a rethink is required which firmly moves culture from the fringes of policymaking further to the centre. By developing a better understanding of what culture and creativity are and by attempting to measure their practical impacts on society (albeit acknowledging that not everything can be measured) Europe would take a step in the right direction. References Anheier, H. and Raj Isar, Y., (2008). Cultures and Globalization: the Cultural Economy. London: Sage. Attali, J. (1977). Bruits. Fayard. Bakhshi, H., McVittie, E. and Simmie, J. (2008). Creating innovation: do the creative industries support innovation in the wider economy. NESTA Research Report. London: NESTA Barro, R. (2001). Education and economic growth. In D. J. Helliwell (ed.), The contribution of Human and Social Capital to Sustained Economic Growth and Well-Being. Paris: OECD. Bowen, H.P., Sleuwaegen, L. and Moesen, W. (2006). A composite index of the creative economy with application to regional best practices. Leuven: Vlerick Leuven Gent Management School Working Paper Series . Castells, M. (1998). L’ère de l’information. Vol. 1. La société en réseaux. Paris: Fayard. Claxton, G. (2008). Cultivating positive learning dispositions. H. Daniels, H. Lauder and J. Porter (eds), Routledge Companion to Education. London: Routledge. Cultural Initiatives Silicon Valley (2005). Creative Community Index: Measuring Progress Toward a Vibrant Silicon Valley, San Jose, CA: Cultural Initiatives Silicon Valley. Currid, E. (2007). The Warhol Economy - How Fashion Art and Music drive New York City. Princeton: Princeton University Press. 203


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Directorate-General for Enterprises and Industry of the European Commission. European Innovation Scoreboard 2007. Florida, R. (2002). The Rise of the Creative Class. And How It’s Transforming Work, Leisure and Everyday Life. New York: Basic Books. Florida, R. and Tinagli, I. (2004). Europe in the Creative Age. Europe: Demos. Guilford, J. (1950). Creativity. American Psycholgist, 5 , 444-54. Helson, R. (1999). A longitudinal study of creative personality in women, Creativity Research Journal, 12 , 89-102. Home Affairs Bureau HKSARG. (2004). A Study on Creativity Index. Retrieved May 2009, from http://www.hab.gov.hk/file_manager/en/documents/policy_ responsibilities/arts_culture_recreation_and_sport/HKCI-InteriReport-printed.pdf. Hooper-Greenhill, E., Dodd, J., Gibson, L., Phillips, M., Jones C., Sullivan, E. and Museums, Libraries and Archives Council and Renaissance. (2006). What did you learn at the museum today? Second study: evaluation of the outcome and impact of learning through implementation of Education Programme Delivery Plans across nine Regional Hubs. Leicester: Research Centre for Museums and Galleries Citation (RCMG). Jacob, J. (1993). The Death and Life of Great American Cities. New York: Random House Publishing Group. Kitto, J., Lok, D. and Rudowicz, E. (1999). Measuring creative thinking : an activity-based approach, Creativity Research Journal, 12 , 89-102. Lubart, T. (1999). Creativity across Cultures. In R.J Sternberg (ed.),Handbook of Creativity, p339-350. Cambridge: Cambridge University Press. Nussbaum, M. (2000). Women and Human Development: The Capabilities Approach. Cambridge: Cambridge University Press. OECD. (2001). The Wellbeing of Nations – The Role of Human Social Capital. Paris: OECD. OECD and EURSTAT (2005). Oslo Manual: the Measurement of Scientific and Technological Activities, Guidelines for collecting and interpreting innovation data. (2005, 3rd edition). Paris: OECD. Picard, R.G., Grölund, M. and Toivonen, T. The Media Group, Business Research and Development Centre, Turku School of Economics and Business Administration . (2003). Means for Overall Assessment of Cultural Life and Measuring the Involvement of the Cultural Sector in the Information Society. Helsinki: Finnish Ministry of Education and Culture. Porter, M. E. (1990 ). The Competitive Advantage of Nations. London: Macmillan. Sen, A. (1993). Capability and Well-being. In M. Nussbaum and A. Sen (eds), The Quality of Life. Oxford: Clarendon Press. 204


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Travers, T. A. (2004). Valuing Museums: Impact and innovation among national museums. National Museums Directors’ Conference. United Kingdom. UK Department of Culture (2001). Culture and Creativity: The Next Ten Years. Green Paper. UNESCO. (6-9 March 2006). Road Map for arts education. The World conference on Arts Education: building creative capacity for the 21st Century. Lisbon : UNESCO. Villalba, E. (2008). On Creativity: Towards an understanding of creativity and its measurements. JRC Scientific and Technical Reports 23561 EN. Luxembourg: OPOCE. Wallach, M. (January-February 1976). Tests tell us little about talent, American Scientist, 57-63.

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The role of creative industries

13. The roles of creative industries in regional innovation and knowledge transfer — The Case of Austria

Simone Kimpeler and Peter Georgieff (Fraunhofer Institute Systems and Innovation Research (Fraunhofer ISI), Karlsruhe, Germany)

Abstract Creative Industries are regarded as one of the most promising economic sectors with high potential to contribute to local and regional wealth and jobs creation. Thus, the settlement of creative industries firms is an important location, image and economic development factor for the competitiveness of a region. This article presents findings of a study for the third Austrian creative industries report on the role of the creative industries in the innovation system and cross-sectoral knowledge transfer. It starts with a definition of the sector in relation to the ‘Three-sector-model’ of creative industries and then uses the systems of innovation approach to further explain the innovation activities of creative industries firms and its impacts on the regional knowledge-base and competitiveness. A summary of the main results of the company survey carried out for the study concentrates on the economic significance, innovativeness and role within regional knowledge transfer of the creative firms. It shows that the creative industries, characterised by a rather small-scale company structure and flexible work design obtain new ideas and approaches principally through the mobility of freelance employees. As creative industries make a decisive contribution to the competitiveness of the national innovation system, finally the consequences and challenges for regional innovation policies are outlined, which aim at the improvement of the framework conditions for creative industries. 207


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Simone Kimpeler, Peter Georgieff

Introduction According to recent creative industry reports in several countries and regions worldwide as well as an increasing number of research articles in economics, the creative industries are regarded as one of the most promising economic segments with high potential to contribute to wealth and jobs creation. Creative industries are characterised by their cross-sectoral scope and profit particularly well from the growing demand for high-quality services and customised solutions. The sector offers itself as partner to diverse industries supporting the development of new products and services as well as manufacture and marketing. The creative industries are at the crossroads of the arts, culture, business and technology and defined by carrying out economic activities that strongly rest on individual creativity, skill and talent and predominantly produce intellectual property (UNCTAD, 2008). Due to the worldwide Internet-based diffusion of audiovisual goods, software and copyright products and services, the sector plays a key role in the knowledge and innovation transfer in the information economy. Thus, the settlement of creative industries firms is an important location, image and economic development factor for the competitiveness of a region. In this article, we will outline some findings on the roles of the creative industries in innovation systems and cross-sectoral knowledge transfer, based on the study ‘Contribution of the Creative Industries to the Innovation System — The Example of Austria’ (Georgieff et al., 2008; Müller et al., 2008) 6. First, we will give a definition of the sector and a brief overview of studies on the economic significance and characteristics of the creative industries. We use the systems of innovation approach to further explain the innovation activities of creative industries firms and its impacts on the regional knowledge-base and competitiveness. Next we will summarise the main results of the company survey carried out for the third Austrian creative industries report. Finally the consequences and challenges for regional innovation policies are outlined.

Definition of creative industries Since the end of the 1990s, studies on the scope, structure and specific situation of the Creative Industries have been published and discussed from an economic as well as a culture policy perspective. Most of the (continental-)European sector studies and industry reports by now use a so-called ‘Three-sector-model’ (Söndermann 2007: 7) 6

The study was carried out by jointly by Fraunhofer ISI and ZEW on behalf of arge creativ wirtschaft Austria in the Austrian Federal Economic Chamber. It served as information base for the third Austrian Creative Industries Report. The Authors would like to thank Gertraud Leimüller from arge creativ wirtschaft and our project partners Christian Rammer and Kathrin Müller (ZEW) and Helmut Gassler for their contributions. Special thanks to the ZEW colleagues for their empirical expertise and the survey.

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to describe the creative and/or cultural sector by distinguishing between the public, intermediate and private sector (Georgieff et al., 2008: 18). Organisations and activities with primarily non-commercial, societal objectives, following a public mission of education and participation belong to the public or intermediate sector. The private sector, in contrast, comprises all firms, organisations and activities which follow commercial or operations side motives of the creation, production, distribution and diffusion of cultural and creative goods and services (Söndermann et al., 2009: 22). The private sector of the creative industries, its capacity for innovation and its impact on the innovativeness of other industries is the focus of this paper. The private sector can be split into 11 sub-segments: music industry, advertising, books, software and games industry, art, film, broadcasting industries, performing arts, design, architecture, publishing and printing industries. The definition used in the study on the creative industries in Austria is close to the German ‘Three-Sector-model’ (Söndermann et al., 2009) as well as strongly in line with the definition of UK’s Department for Culture, Media and Sport (DCMS, 1998), as it defines the sector by firms engaged in a business activity which is quintessentially based on the creativity of the company owners and their staff. They create economic value primarily by generating and utilising intellectual property, which includes artistic works. In addition to the sub-segments mentioned above, the Austrian report includes R & D services, consulting and training are also included. In Austria reports on the Creative Industries have been published not only with a national but also with a regional focus and have already highlighted the special features of the different lines of business in the sector and their outstanding economic dynamism (among others KMU Forschung Austria, IKM 2003:2006).

Creative industries and the innovation system The significance of the Creative Industries is twofold: firstly, they comprise of particularly innovative lines of businesses which produce a multitude of new products and services; secondly, they are also important suppliers of ideas and new approaches for other companies. They play a special role as creative input providers in the innovation system; in that they increase the innovative capacity of other firms (compare Miles, Green, 2008). Besides, the use of Information and Communications Technology (ICT) plays a prominent role in Creative Industries. Their competitiveness is thereby closely linked to the innovative dynamics of this technology sector. Only a few studies have analysed innovation activities of creative industries or even the contribution of creative industries to the innovative capacity of the economy (Castaner, Campos, 2002; Handke, 2007; Müller et al., 2008). Examples for studies are 209


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the creative industries positioning based on input-output analyses (see Bakhshi et al., 2008), special evaluations of cross-sectoral innovation surveys (cf. Bakhshi et al., 2008; Miles, Green, 2008; Wilkinson, 2007), special surveys in certain fields of the Creative Industries like the music industry (see Handke, 2006) or case studies (see Miles, Green, 2008). Statements for the economy as a whole on the innovation activities and contributions to innovation on the part of the creative industries in Austria are available which complement the relevant regional studies carried out up to now (cf. Ratzenböck et al., 2004; Traxler et al., 2006). Miles and Green (2008) introduced the phrase of ‘hidden innovations’ when describing innovations which could not be measured by traditional indicators and assumed that the share of hidden innovations must be very high in creative industries due to less formalised innovation processes and difficulties in measuring creative service output. Due to a high percentage of small firms within the creative industries, their strong structural dynamics and increasing importance of intangible goods and services it is difficult to assess and measure the innovation activities and its output in this kind of industries (Hill, 1999). Creative Industries can be defined as a sectoral innovation system, whose institutional structures display national (respectively, regional/local) characteristics, whose enterprises, however, have developed a specific knowledge and technology base as well as organisational structures unique to themselves, enabling them and firms cooperating with them from other branches to carry out innovations. Figure 1 depicts the Creative Industries as an element of the national innovation system. Three product characteristics play a particular role for innovations in the Creative Industries: yy mainly text, audio or video, respectively, multimedia content is concerned; yy the assessment by clients and users is based on experience; yy aesthetic criteria play a crucial role in the evaluation. In the third report on creative industries in Austria (arge creative wirtschaft, 2008), which summarises the results of our study, the sector of creative industries was defined as a sectoral innovation system with institutional structures shaped both by its regional and national frameworks (Figure 1).

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Figure 1: Creative Industries as Element of the National Innovation System

We have learned from the sectoral innovation systems approach (Malerba, 2004) that the firms of one sector have developed their sector-specific knowledge- and technology-base which enables them and their cooperating partners to create innovations. In addition, also the competences, learning processes, organisational structures, goals and business activities and models are sector-specific and developed further by intensive location-based cooperations, high cross-sectoral mobility of experts and institutional settings in the region. So the knowledge generation in innovation systems takes place through learning processes in cooperations, joint acquisitions, competition and market coordination, and not just with enterprises from the same branch, but also cross-sectoral. Furthermore, cultural, social and geographic proximity are pre-requisite for knowledge-transfer in innovation processes (Koschatzky, 2007).

Economic significance of the sreative industries in Austria — Results of a company survey In spring 2008 the comprehensive survey of more than 2 000 Austrian creative industries companies was conducted to empirically investigate the role of the creative industries for the innovation system in depth and to arrive at a quantitative assessment (Müller et al., 2008). The central characteristic of the survey is that it focused on firms which are active in a branch of the creative industries and whose business activity is 211


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also characterised by a high degree of creativity. This was operationalised by the use of three criteria: (i) originality and singularity of the product; (ii) appreciation of talents and creativity of own staff; (iii) mainly custom-made products and services (Georgieff et al., 2008: 71; cf. Traxler et al., 2006). In this context, we can speak of ‘highly creative’ enterprises. With this the survey differs from all other studies in this field, which are based on a delimitation of sectors. At the beginning of 2008 the total number of ‘highly creative’ enterprises in Austria amounted to almost 20 000. The creative industries encompass the arts content (music, film/photography, writers, games, etc.), design, architecture, advertising, software, publishing houses and technical offices, as well as the area consulting/training, which up to now was only marginally considered in the creative industries. The low number of creative enterprises in comparison to other studies like ‘Kreativwirtschaft in Österreich (Mandl & Dörflinger, 2008) results from the fact that in the survey public or non-profit organisations are not considered. Additionally, no enterprises from the areas of retail trade and rental and leasing were surveyed and, besides, enterprises from creative industries which do not provide any own creative service were excluded (see Müller et al., 2008). The core of the creative industries is formed by firms which incorporate their creativity in the design of products (including digital products) (design), which produce artistic or otherwise creative work in the areas of film, photography, music, literature and dramatic arts (content), which shape public spaces, buildings and interiors (architecture), which conceive creative approaches to market products and services (advertising) and the varied requirements of IT-technical problem solutions by means of creative programming solutions (software). Furthermore, companies which offer creative consulting and further education courses for other enterprises (consultancy/training), which publish and produce publications and digital media (publishing/ printing) and which solve technical problems in a creative fashion (engineering offices) are also regarded as part of the creative industries. As seen from the number of enterprises the areas architecture, software and technical/engineering offices dominate, whereas regarding the number of employees, technical offices, advertising and consulting/training represent the largest share. For the first time ever, the comprehensive study has investigated the role of the creative industries in the innovation system on a broad empirical basis. It shows that the creative industries can make a decisive contribution to the competitiveness of the Austrian innovation system. The creative industries are a decidedly innovative bunch. The creative potential of the entrepreneurs and employees is utilised by the majority of the enterprises when introducing innovative products. Sixty percent of all creative companies have 212


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introduced new products (including services) to the market within three years. This puts them on par with branches of the high-tech industry. The creative industries are an important source of original innovation ideas, i.e. new products, which were not offered on the market by any other firms. This can be perceived by the high share of companies conducting own R & D as well as the fact that one third of the product innovators have introduced novelties to the market. In many cases, these are niche products or are services specifically tailor-made to client specifications. Their direct impact on the overall economy is presumably not very large. It is, however, decisive that the creative industries permanently develop and test innovative ideas. Only this guarantees that such innovations are repeatedly brought forth to meet a large demand and achieve major sales successes. The creative industries serve as important innovation partners for enterprises from other branches. Almost every second company in the creative industries has supported its client enterprise in innovation activities. This support can range from brainstorming via R & D and product design up to market introduction as, for example, regarding marketing concepts. A decisive factor is that the creative industries affect all branches. In particular those branches which invest little in creativity and R & D themselves, profit from the creative inputs of the creative industries companies. Almost all creative industries companies use modern technologies, above all ICT. They are not merely passive technology users, but repeatedly supply the technology manufacturers and developers with impulses for new technology variations or adaptations. The creative industries stand out because of the very high qualification level of the employees. The high proportion of academics among the personnel reflects the strong science orientation and cross-sectoral networking ability of the creative industries. Almost a quarter of the companies in creative industries conducts R & D cooperations with science or collaborates in supervising students writing diploma theses or doctoral theses. This allows creative industries to form an important link connecting scientific research results to their creative application in industry. Personnel fluctuation is a further important element in the exchange of ideas and innovations within the creative industries themselves, as well as with other branches. An essential impulse stems from the high share of freelance employees. According to Florida (2002) the creative class is gathered in metropolitan cities and thus plays a key role for their economic growth. His concept on the ‘rise of the creative class’ has been discussed quite controversially (Wiesand, 2006; Hoyman & Faricy, 2006; Fritsch & Stürzer, 2007) and the main criticism is that Florida does not provide evidence of a causal link between creative class and economic growth. In this context, the Austrian study aims at filling this gap by measuring the performance of creative industries and 213


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its impact on the innovativeness of the region by also taking into account the role of the creative industries in local knowledge transfer. The sub-segments of the creative industries are closely networked. This applies not only to the procurement of creative inputs and for personnel fluctuation, but also for team collaborating. ‘Content providers’ (e.g. artists, photographers, copywriters), advertising agencies, graphic designers and the publishing and printing trade form a creative cluster characterised to a high degree by collaborating which results in creative value-added chains.

Conclusions: principal challenges and policy recommendations Different studies show that in recent years the creative industries’ value added contribution and their share in the number of dependently employed persons has remained relatively constant, while the share of turnovers is declining. The share of all firms, however, has clearly risen, which points to a high level of start-up activity and a lower share of market failures. Due to the rather small-scale company structure and flexible work design (mainly project work), the creative companies obtain new ideas and approaches principally through the mobility of freelance employees. The creative industries’ contribution to the innovative capability of their clients, the so-called user industries of creative products and services, is expected to be considerable. The survey of our study shows that creative industries in Austria are typical cross-cutting industries, which due to their specific situation act with particular flexibility in different markets and for different client segments. Given to their strong service orientation and the associated proximity to clients, creative industries play an important leading role in opening up the innovation process by integrating clients in the value added. This way cooperation and interactions with other actors of the creative branches as well as data on branch structure, the availability of qualified staff, educational/training focuses of the skilled personnel and the networking activities prove to be relevant indicators for measuring the innovation activities of the creative industries. The realisation of the high innovative potential of the creative industries is confronted by some challenges arising from the structural idiosyncrasies of the branch. Most creative industries companies are very small and for this reason face typical problems of mini firms, such as issues of financing, maintaining capacities and competences, market cultivation and investment in R & D.

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The high innovation orientation is accompanied by high growth. However, the majority of innovative products also find willing buyers. This presents many of the very small creative industries companies with new challenges, for instance, as far as time management or hiring qualified additional personnel are concerned. A (justifiably) cautious attitude towards an increase in staff — which in the case of an unfavourable development represents a costly burden — also prevents full utilisation of the growth potentials. The high personnel fluctuation is accompanied by the danger of losing important knowledge and competences. The lack of copyright protection is a problem for the further supply of digital products and services. Users are required to play an increasingly active role in codesign and distribution of creative content. Users are not only co-producers of the content, they also play an active role in selecting, editing, with reference to the recombination and the reference to the digital content. Possible measures to prevent these problems arising from the small-scale structure of the branch are: yy A strong network of persons and service providers who can stand in and help out at short notice when the workload is especially heavy. Greater market transparency concerning exisiting offers and if necessary, knock-on actions to help establish if such offers are needed. yy The possibility to take ‘time off’ from everyday business, possibly by accumulating corresponding tax-favoured reserves. One way could be to transfer income from one calendar year to the next so that, in a profitable year, profits can be transferred to the following year and so finance ‘time off’ for the new and further development of business ideas. Such a transfer could amount to 20 % of the annual turnover of a one-man business and would, of course, only be possible once. yy The offer of financially attractive contingency insurance in case of illness or other reasons for not working.

To improve the finance situation in companies of the creative industries, the following measures could be considered: yy The above mentioned possibilities to accumulate reserves should strengthen the equity capital base of the enterprise. In the year 2007, with the permitted deduction for invested profits for cash basis accounting, an instrument was introduced which makes tax-free treatment possible to a small extent (up to 10 % of the annual profits). A further improvement, especially for only self-employed

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enterprises could be that they would be treated exactly like dependent employees as regards tax benefits of a virtual 13th and 14th month’s salary. yy On the other hand, the access to possible outside financing such as small credits for ‘intangible investments’ should be improved. This can be achieved either by improved marketing of already existing offers or by collaborating with banks as to whether specific offers geared to the creative industries could be set up. yy The availability of venture capital is an important precondition in particular for those creative companies which would like to grow swiftly, on the basis of innovative products and service offers. In this context, the establishment of a corresponding venture capital (VC) fund which could be designed as a public-private partnership model would be extremely helpful. Most of the existing VC funds investments in creative firms are either too low from the amount involved or require very specific investigation of the market situation and the innovation projects. This means high handling costs on the part of the potential capital provider. Creative industries play a significant role in the innovative ability of national innovation systems, as well as ensuring innovative activities which can be compared to those of the high-tech industry. This calls for stronger integration of the creative industries companies in economic and technology policy programmes. The interest of innovation policymakers in the creative industries should, in addition to promoting the education and culture sector also include safeguarding the competitiveness of the creative companies. Improving the framework conditions for start-up founders and creative clusters, as well as for knowledge transfer should be an important component of a sustainable location policy. Appropriate promotional measures to integrate the creative industries in mainstream innovation policy even closer are: yy Promoting creative potentials: expanding offers in education and further education in fields relevant for the creative sector, ideally in cooperation with local industry on the spot. This will support the broadly based promotion of creative potentials, on the one hand, and the development of the unique selling points of a location, on the other hand. Promoting creative potentials should start as early as possible, even at pre-school age. yy Promoting innovation: direct or indirect measures to stimulate innovations on the spot by means of events, platforms for knowledge exchange, knowledge transfer, promotion of network building, competitions, innovation funds, transfer between different sectors, etc. 216


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yy Promoting start-up activities: qualification measures (marketing, management, accounting, corporate planning), providing information, network promotion, start-up support for young founders, support in the development of new business models are part of this category. In addition, stronger integration of the creative industries in university incubator initiatives is recommended, as creative potentials can in this way be recognised and promoted economically as early as possible. yy Supporting access to venture capital: as regards the creative industries, an own VC fund for the sector and an improved access of the sector to private VC is proposed. yy Promotion of (inter)national market development: government support for international market development is common practice in all industrialised countries. For creative industries the support in the development of new markets at home and abroad by means of traditional export promotion, support through trade missions, foreign missions, encouragement for network building, etc., is called for. yy Promoting the development of industrial clusters: this type of promotion has become generally accepted in the past few years. Promoting local networks of organisations/actors, whose production processes are characterised by the exchange of goods, services and/or knowledge. Many cluster policies do not develop only on a regional or local plane, but also on a national level, e.g. competence clusters. yy Questions of Digital Rights Management (DRM): these play a vital role in the creative industries. As a result of the ‘content revolution’, new possibilities of integrating user-generated content in Web 2.0, amendments to the laws are urgently required. In this connection, issues here are national and European legislation and regulations, as well as support for structuring applications for protection and preservation of copyright protection. When judging the economic significance of the creative industries, the high share of self-employed and freelance workers must not be forgotten. In this respect, analyses which only cover enterprises with dependent employees or refer to the number of dependent employees are less reliable, as a large share of the personnel in creative industries companies is self-employed. Far more than 30 % of the creative industries companies are one-man firms.

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References Arge creativ wirtschaft Austria der Wirtschaftskammer Österreich (2008). Dritter Österreichischer Kreativwirtschaftsbericht 2008, Retrieved June 2009: www.creativwirtschaft.at/factsfigures/kreativwirtschaftsberichte/20610 Bakhshi, H., McVittie, E. and Simmie, J. (2008): Research report: Creating Innovation. Do the creative industries support innovation in the wider economy? London: NESTA. Retrieved June 2009: http://www.nesta.org.uk/assets/Uploads/pdf/Research-Report/creating_innovation_report_NESTA.pdf Castaner, X. and Campos, L. (2002). The Determinants of Artistic Innovation: Bringing in the Role of Organizations, Journal of Cultural Economics 26 (1), 29-52. DCMS (1998): Creative Industries – Mapping Document. London: Department for Culture, Media and Sport. Eurostat (2007): Cultural Statistics, Eurostat Pocketbooks. Luxemburg: OPOCE. Florida, R. (2002), The Rise of the Creative Class…and how it is transforming work, leisure, community & everyday life. New York: Basic Books. Fritsch, M. and Stürzer, M. (2007): Die Geographie der Kreativen Klasse in Deutschland, Raumforschung und Raumordnung, 65 (1), 15-29. Georgieff, P., Kimpeler, S., Müller, K. and Rammer, C. (2008), Beitrag der Creative Industries zum Innovationssystem am Beispiel Österreichs. Final report to the arge creativ wirtschaft. Mannheim and Karlsruhe: Wirtschaftskammer Österreich. Handke, C. (2007): Surveying Innovation in the Creative Industries. Berlin: Humboldt University. Retrieved June 2009: http://www.business.mmu.ac.uk/emaee/ papers/26handke.pdf Hill, T.P.(1999). Tangibles, Intangibles and Service: A Taxonomy for the Classification of Output, Canadian Journal of Economics, 32 (2), 426-444. Hoyman, M. and Faricy, C. (2006): It Takes a Village: A Test of the Creative Class, Social Capital and Human Capital Theories. Retrieved July 2009: http://ssrn.com/ abstract=1313563 KMU FORSCHUNG AUSTRIA; IKM (2003). Erster Österreichischer Kreativwirtschaftsbericht. Wien: KMU Forschung Austria (Austrian Institute for SME Research). Retrieved June 2009 from: http://www.smeresearch.org/de/Projekte/Kreativwirtschaft/Erster%20%C3%B6sterr%20Kreativwirtschaftsbericht.pdf . KMU FORSCHUNG AUSTRIA; IKM (2006). Zweiter Österreichischer Kreativwirtschaftsbericht. Wien: KMU Forschung Austria (Austrian Institute for SME Research). Retrieved June 2009 from: http://wko.at/kreativwirtschaftsbericht/kwb2_2006.pdf Koschatzky, K. (2007). Social Capital and Cooperation within Innovation Systems. In: Landabaso, M., Kuklinski, A., Roman, C. (eds.), Europe – Reflections on social capi218


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tal, innovation and regional development: The Otsuni Consensus. Recifer Eurofutures Publication Series REUPUS; Vol. 3. Malerba, F.(Ed.)(2004). Sectoral Systems of Innovation. Concepts, Issues and Analyses of Six Major Sectors in Europe. Cambridge: Cambridge University Press. Mandl, I. and Dörflinger, A. (2008). Kreativwirtschaft in Österreich, Wirtschaftspolitische Blätter, 55 (1), 161-182. Miles, I. and Green, L. (2008). Research report July 2008: Hidden innovation in the creative industries, London: NESTA. Retrieved June 2009: http://www.nesta.org.uk/ hidden-innovation-in-the-creative-industries/ Müller, K., Rammer, C. and Trüby, J. (2008): The Role of Creative Industries in Industrial Innovation. Discussion Paper No. 08-109. Mannheim: Zentrum für Europäische Wirtschaftsforschung, ZEW.b Söndermann, M.(2007): Kulturwirtschaft und Creative Industries in Deutschland 2007. In Kultur- und Kreativwirtschaft in Europa 2007 – Jahrbuch Kulturwirtschaft 2007. Berlin: Friedrich-Naumann-Stiftung für die Freiheit, 21-35. Söndermann, M., Backes, C. and Arndt, O.; Brünink, D. (2009). Kultur- und Kreativwirtschaft: Ermittlung der gemeinsamen charakteristischen Definitionselemente der heterogenen Teilbereiche der ‘Kulturwirtschaft’ zur Bestimmung ihrer Perspektiven aus volkswirtschaftlicher Sicht. Final report to the Bundesministerium für Wirtschaft und Technologie, Köln, Bremen, Berlin 2009. Retrieved June 2009: http://bmwi.de/BMWi/Navigation/Service/publikationen,did=289974.html Ratzenböck, V., Demel, K., Harauer, R., Landsteiner, G., Falk, R., Leo, H. and Schwarz, G. (2004). Endbericht: Untersuchung des ökonomischen Potenzials der „Creative Industries“ in Wien. Wien: Kulturdokumentation, Wifo, Mediacult. Retrieved June 2009: http://www.creativeindustries.at/pdf/Endbericht.pdf. Traxler, J., Grossgasteiger, S., Kurzmann, R., Ploder, M., Behr, M., Gigler, C., Müller, W., Niegelhell, F., Schirmbacher, B., Sittinger, E. and Wildner, W. (2006). Potenzialanalyse Kreativwirtschaft im Großraum Graz. Graz: Sparte Information und Consulting der Wirtschaftskammer Steiermark. Retrieved June 2009: http://www2.wkstmk. at/wko.at/IC/PotenzialanalyseKreativwirtschaftimGrossraumGraz.pdf UNCTAD (2008): Creative Economy Report 2008: The challenge of assessing the creative economy towards informed policy-making, United Nations. Retrieved June 2009: http://ssc.undp.org/creative_economy Wiesand, A. (2006). Kultur- oder „Kreativwirtschaft”: Was ist das eigentlich? Aus Politik und Zeitgeschichte. Kulturwirtschaft, 34-35/2006, 8-23. Wilkinson, A. (2007). An Assessment of Productivity Indicators for the Creative Indus-tries. London: DCMS. 219


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Contribution of leisure to creativity and innovation

14. Contribution of leisure to creativity and innovation of a region

Manuel Cuenca Cabeza, Roberto San Salvador del Valle, Eduardo Aguilar and Cristina Ortega Institute of Leisure Studies, University of Deusto

Abstract This paper deals with the contribution of leisure and culture to the creativity of a region. The study proposes four main ideas: the transformer strength of leisure; the value of people (people who innovate and learn by enjoying are people who enjoy learning); the role of leisure and innovation in the organisations; and the promotion of innovation and creativity by means of good practices of leisure. The research also provides an approach to measure the creativity of a region under the leisure and culture point of view. The framework of the study is the Basque Country where innovation and creativity is one of the main stays of the Basque government developed by means of the Basque Innovation Agency Innobasque.

Introduction We would like to thank the European Commission for this opportunity to outline some of the main ideas relating to the project: Ideas, People and Leisure Organisations Serving Innovation study (Cuenca, M. San Salvador del Valle, R., Aguilar, E. and Ortega, C., 2008), commissioned by Innobasque , the Basque Innovation Agency, which was completed last autumn. This paper does not seek to set out the study’s approaches and conclusions, which would require more space, but it provides some ideas that suggest new approaches in areas the area of leisure and creativity. The study reflects on the contribution of leisure and culture to creativity and inno221


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Manuel Cuenca Cabeza, Roberto San Salvador del Valle, Eduardo Aguilar, Cristina Ortega

vation of a region. The study was carried out by the Institute of Leisure Studies of the University of Deusto, located in the Basque Autonomous Community, Spain, a region that has made innovation a sign of its identity, with the goal of confronting its Second Great Economic and Social Transformation, in which leisure and culture play a fundamental role. The study is a first inquiry into the specific aspects in which leisure can contribute to increase creativity and innovation, and more concretely into the social innovation of a region. We define social innovation as the collective change in values that changes the referents and forces us to reformulate the meaning of actions. Leisure is a value highlighted by sociological studies in recent years. It is very difficult to understand present-day society without the contribution of leisure as an important pillar of development in the 21st century. It is enough to stop and think about what is the meaning today, economically and culturally, of tourism, the world of spectacle, television, sports, modern music, theme parks, games of chance or museums. The human experience of leisure is everywhere and in everyone. It is present in games, sport’s practice, travel, vacations and weekends full (or empty) of music, celebration, etc. Its absence can be seen in boredom, lack of creativity, initiative, integration … and, consequently, in sadness and ‘meaninglessness’. Leisure has become a source of economic and social development at global level. Nevertheless, the transforming force of leisure resides in the way of conceptualising it, understanding it and making it a reality. With the purpose of shedding light into the idea of leisure as a Transforming Force.

Starting framework The departure framework constitutes the social changes. First, we emphasise the new concept of time; with the high speed of change, time is increasing in value. The second variable subject to profound change is referring to socio-demographic characteristics. The life cycle is modified in a significant way: childhood ends earlier, young people are halted in a prolonged adultescence (a term coined by Gil Calvo), adulthood is confined to two decades of intense productive and reproductive work, old age arrives before 60 and extends through a prolonged active ageing, first, and dependent ageing, later. The third variable affects the socioeconomic sphere, in which the consolidation of the market economy based on products and services implies the germ of the economy of experience (Pine, J. B. and Gilmore, J. H. 2000) The fictional Capitalism (Verdú, V., 2006) is imposing the intangible on the tangi-


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ble. The fourth variable concentrates on the socio-political scope. An important economic globalisation takes place without a similar and comparable evolution in what could be termed a political globalisation. The fifth variable has to do with identity. We live in multiple spaces in accelerated time, in the meeting of diverse realities, with different people, in a fluid society (Bauman, Z., 2006) that affects our affective, personal, social and labour relations. The result is the miscegenation, with multiplicity of identities and senses of belonging. Intellectuals worldwide agree that we have entered a new era in which we will need to redefine habits and customs, time and space, work and leisure. We are facing a transcendental change that has its epicentre in the construction of a new civilisation. The political, social, economic and cultural transformations that we experience at present have their origin in technological revolution, but the change is much greater. The crisis of interests, values and models is generating new social, institutional and cultural forms. In a context of this nature what role will leisure take? What are the factors that explain new ways to experience it and to understand it? In order to answer these questions, we will discuss the importance of leisure in today’s society, the innovative function of leisure, the value of the concept and the importance of valid leisure experiences for its innovative function. We will end by providing a series of good practices based on valid experiences in different spheres in order to exemplify what has been previously discussed.

Importance of leisure in today’s society The value of leisure time has increased exponentially, not only as an economic and social value, one can also appreciate its rapid increase in the average life of the new societies, in the average life of a person, in the importance that leisure times acquire in a year and in daily practices. The following graph provides an overview of what non-working time currently means, a good part of which would consist of free time.

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Graph 1: Leisure as part of life as a whole, according to societies Source: Prepared using EU data (Report, 1994)

Graph 1 shows the percentage of time that the vital non-working time represents in different social periods in history. The criteria used to determine the time spent in leisure is constructed using the overall view of life, disseminated by the New York Metropolitan Life Insurance Company: eight hours dedicated to sleep, work and non-working time. In line with this proposals, an individual in technological societies would spend around 48.6 years on education, eating, games, leisure and other activities, while it would be 38.7 years by an individual in the second half of the 20th century — which is depicted as an industrial society in the graphic. The percentages highlight the importance that non-working time has acquired in recent history. Modern leisure, the result of the industrial era, has been a continuous developing concept. Not only has it increased in quantity and new uses, but also in terms of generalised and democratic access. Leisure practices are an essential part of the new lifestyles, which have steadily and imperceptibly been replacing customs that were previously considered to be unchangeable. The average citizen dedicates more and more time to leisure every day. Furthermore, people have increasingly more opportunities for free time throughout their lifetime, as they start work later and frequently take early retirement. We will consider these aspects in brief over the coming pages. Amando de Miguel (2000:253), in his analysis of the data of the survey conducted among young Spaniards in 1988, pointed out that the general increase value of leisure was noteworthy and, more specifically, among young people of both sexes aged between 21 and 29. They reported that leisure was in first place on their scale of value, above work and family. The data are in line with other studies at that time. Thus, in 224


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the Encuesta Europea de Valores de España 2000 (European Values Study for Spain 2000), Maria S. Cabrera (2000:25–47) stated that free time and leisure was in fourth place of the hierarchy of priorities for Spaniards at that time. Some 80.4 % indicated that it was something very important or quite important, which puts it closely behind the top places occupied by family, work and friends/acquaintances, and some away ahead of the value given to religion (41.7 %) and politics (19.1 %). Graph 2 shows the situation in the Basque Autonomous Community and Navarra:

Graph 2: CAPV and Navarra, 1995–99 (%) Source: European Values Study, 1995 and 1999

The increase in the value of leisure is not only of interest in Spain, but is common to developed countries. Other research, such as that carried out by Antonella delle Fave and Fausto Massimini (1998:191–209) in the north of Italy found similar results. The following graph exemplified the change in leisure values according to the new generations and their different approaches to life. It shows how leisure is viewed by a three-generation family group, who live in a small town of Valle de Gressoney. The researchers found that the oldest generation, the grandparents’, achieved their greatest satisfaction through work (58 %) and barely any from leisure (16 %). With regard to the parents’ generation, it can be said that there was a balance between work (41 %) and leisure (44 %) and, finally, in the grandchildren’s generation, the importance of leisure, 70 %, compared to 19 % attributed to work, 225


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was noteworthy. The importance of leisure as a life experience exceeded, in this case, the place occupied by work in the generation of their grandparents.

Graph 3: Value changes according to the generational change Source: Based on A. delle Faye and F. Massimini, 1988: 199

The aforementioned research exemplifies that the rise in the value of leisure in the scale of social values was already a consolidated reality at the turnover of the century. We should now ask ourselves if that importance is truly reflected in the present environment and in what way.

The economic Importance of leisure industries The current importance of leisure industries is a well-known aspect. We shall only recall some figures, statistics and graphs, disseminated in recent years, which reveal some complementary aspects relating to the leisure economy. Enjoying music or the dramatic arts is an example that we find in the cultural sphere. Music is the most popular of cultural activities and the most difficult to determine, as it can be considered as a recreational or a cultural practice. It has become the most commonplace cultural activity in Spain. The latest data used in our Institute reveals that 86.2 % of

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the Spanish population acknowledge that they listen to music, compared to 13.8 % who do not do so. The dramatic arts sector has also grown, as it has been able to retain the capacity to attract audience and generate income (see Graph 4). In the same way, it is likely that this slow but steady growth is going to continue over the coming years.

Graph 4: Total income from theatre performances in Spain (EUR) Source: SGAE (Spanish General Society of Authors and Editors)

Radio and television are the most popular home leisure activities. Television continues to be the most widespread leisure pastime. A TV consumer profile would show that the elderly are, by a long way, the age group that spends most minutes watching television. In terms of ‘gender/sex’, women are seen to spend much more time watching TV than men (around 40 minutes more) and, at the same time, households consisting of one or two people tend to watch more television, while that figure decreases as the number of members of the family unit increases in Spain. The number of minutes that the population spends watching television depends, among things, on the day of the week. Sundays are the days with the highest audience figures, a fact that has been noted over the last three years. During the working week, 227


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the number of minutes spent watching television has remained steady between 210 and 220 minutes a day. However, the time spent on taking part in televised leisure in 2005 decreased compared to 2004.

Incidence of leisure in quality of life The relation between leisure and quality of life of can be observed through two important indicators: health and community intervention. The WHO considers leisure as essential for the correct development of the human being, and basic for his or her psychic and social balance. It has been shown that the correct enjoyment of leisure prevents disease, increases creativity and provides a better quality of life. Leisure that is a satisfactory experience has a beneficial effect that goes far beyond its own existence, affects our whole being and has an impact on other aspects of our life and our relations with our surroundings. The English bibliography and, in particular, North American research, contains abundant specific research that highlights the important function that leisure activities play in our lives. In psychology, this work area is known under the generic name of ‘leisure benefits’. Another social quality of life indicator that we would like to highlight is the one that refers to community intervention in leisure spheres. Community intervention has two preferential channels. One pays special attention to the negative, claims rights and duties not fulfilled, and tries to seek solutions to problems and conflicts that appear in the society. The other fosters satisfactory experiences by generating positive community citizen involvement. Both are complementary approaches and, in no case, excluding; but negative leisure behaviour, such as young people drinking in the street, frequently gets greater social attention than others.

Innovative function of leisure Before questioning directly the relationship that exists between the practices of leisure and creativity and innovation it seems advisable to reflect on the consequences of leisure experiences in the people as in the community. Besides the three functions of leisure, known as Dumazedier’s three Ds: Rest, Diversion and Personal Development; and the psychological, social and economic functions mentioned by Roger Sue, we maintain that leisure also serves to harness creativity in the individual and, therefore, to favour innovation. With respect to psychological functions, the practice of leisure can be something with special incidence in social innovation, to the extent that it can become personally something beneficial, a cause for satisfaction, identification, crea-

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tivity, recovery or catharsis, reflection or spirituality. Some proposals of social, innovative and possible functions, which could make specific some of the ideas previously enunciated are: socialisation, solidarity, natural surroundings and consumption.

Graph 5: Leisure Functions Source: Own elaboration

The innovative function of leisure acquires special importance in the Leisure Studies Team of Deusto, where we consider it to have special relevance. Considering the work of E. Cohen, as well as the reflection on the psychological and social functions of leisure, M. Cuenca (2008) draws attention to the incidence that leisure practices have on social innovation and cultural creativity. Both concepts are directly related to the intrinsic meaning of experiences and the search for quality of life of the citizen. The innovative function of leisure is related to the fact that it is a propitious area for development and the promotion of new lifestyles but it also arises as a result of the appearance of new social situations, which harness innovating motivations of leisure and, consequently, new markets. The change over recent years, particularly in developed countries, has highlighted the importance of the new lifestyles that raise unknown questions. Leisure is a significant element of this change and an increasingly more important aspect of our society. The new lifestyles of young people and pensioners is therefore very significant. In both cases, leisure is an essential aspect to understand the meaning of their lives and motivations. In the knowledge era, we are learning to live in a different context that is unprecedented in the history of humanity, even though it is not yet a day-to-day reality. In this new context, we will redefine habits, uses of time and space, but the way of seeing work and leisure in particular. 229


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There is no doubt that the lifestyles of today’s society are directly related to the appearance of new forms of leisure and its development in specific population groups. All have a social incidence far beyond what we thought; but normally we only pay attention to those which pose immediate problems.

Value of the concept and relevance of valuable experiences of leisure for their innovative function What is leisure? What do we understand by the experience of leisure? Can any experience of leisure acquire this innovative function? Is some type of experience more appropriate than another to perform this function and to create more creative people with a capacity to innovate? In order to try to answer these questions, we shall first look further into the value of the leisure concept and, then, into leisure as a valid experience.

The value of the concept The concept of leisure has had and continues to have many meanings (free time, idleness, activity, liking, entertainment, pastime, disconnecting, escapism). How should we understand this reality at the moment? The concept developed by the Institute of Leisure Studies of the University of Deusto maintains that leisure is an integral experience of the person and a fundamental human right. An integral, that is to say, total, complex human experience (directional and multidimensional), focused on beloved activities (free, satisfactory), autotelic (being an end in themselves) and personal (with individual and social implications). Also it is a basic human right that favours development, just as much as does education, work or health, and of which nobody should be deprived for reasons of gender, sexual orientation, age, race, religion, belief, health, incapacity or economic status. A right legally recognised by different legislatures. Leisure is an experience of great value at present and, mainly, it is explained because it is a type of human experience that the subject perceives in a satisfactory way, not obligatory and non-utilitarian. Affirmatively stated it can be said that leisure is a free, satisfactory human experience which is an end in itself; that is to say, voluntary and separated from need, understood as a primary need. A leisure experience is characterised as being a subjective perception influenced both by one’s own personal experience as by the social surroundings in which it is experienced.

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The Institute of Leisure Studies has been working for 20 years on the concept of Experiential Leisure which, from a business point of view, has become an innovative finding in the 21st century. From the scope of consumption, the same idea has a referent in the work of B. J. Pine and J. H. Gilmore, the Economy of experience, whose antecedent is The Tourist of D. MacCannell. Pine and Gilmore state that the economy of experience is the beginning of a new economic era and seek to explain it with examples like the following: why does a cup of coffee cost more when it is served in a fashionable cafeteria that in the bar on the corner? The economy of experience understands that the key is in the subjects who want to live memorable experiences.

Graph 6: The leisure experience Source: Own elaboration

In the Institute we also start from leisure understood as a human experience, but we defend the values of the person and their dignity over other values, as it could be mere economic benefit. Our humanist thought has the originality to orient reflection based on the European and North American contribution centred on personal and humanist values. Here also is the nucleus of our way of understanding Experiential Leisure. A experience of personal, satisfactory, significant and memorable leisure, is a key factor in the construction of an innovative social fabric. But are some experiences better than others with respect to their capacity to generate more creative and innovating people? Both personally and socially, activities can have diverse functions. To determine whether they are better than others, at certain times, it is fundamental to secure to any objective of transformation and innovation. Research indicates that it is not sufficient to live Experiential Leisure, but we need to make a valuable experience of it. Manuel Cuenca (2004) puts forward four options of verified importance in 231


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the value of leisure experience and its innovative function: active, substantial, creative leisure and leisure with solidarity.

Leisure as a valuable experience Different Researchers who have considered the phenomenon of leisure, among which we emphasise Csikszentmihalyi, induce us to think that it is not sufficient to live leisure as a human experience, but we should tend to make of it a valuable human experience. In this line of thought we indicate two options that, while well known, do not cease to be important in the value of leisure experience: active leisure and substantial leisure. Together with these we also address the less well-known positions, although ever more valued: creative leisure and leisure with solidarity. We begin by speaking of active leisure because it is the easiest to understand, although not so easy to practice. Active leisure, from our point of view, is not only a physically active, ‘moving’, leisure that is translated into physical activity, but also one that implies mental activity. From a general approach it is possible to say that active leisure is one in which you involve yourself, with which you react and into which you put something of yourself. The practice of active leisure contributes to an increase in greater vital satisfaction, understood as physical, psychological and social well-being. Substantial or serious leisure implies the practice of a reiterated leisure activity which systematically seeks an intense satisfaction(Stebbins, 2000). It manifests itself in amateur activity, voluntary service and in the practice of hobbies. The characteristics of substantial leisure are perseverance, effort, training, benefits, social scope and identification. Creative leisure is a self-motivated, conscious, active, complex and playful leisure. This type of leisure finds its closest scope of accomplishment in culture, an area that is characterised as separate from the instinctive and the easy, introducing us to a vision and an enjoyment of the world that is more difficult and complex but, in the long term, enriching, satisfactory and much more human (Csizentmihalyi, 2001). Creative leisure is characterised by the experience of creative experiences, understood in its more global sense, as creation and recreation. It has two aspects: (a) expressive, characterised by producing something new; and (b) compressive, giving life or recreating something created. Leisure in solidarity is that which finds its cause for satisfaction in helping others through actions in solidarity. For some authors it is a superior form of leisure (Jensen, 1995). Research indicates that leisure in solidarity provides experiences full of satisfaction and meaning, these aspects being key to understanding all of the others. 232


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Graph 7: The leisure pyramid Source: Based on K.A. Henderson and Maslow

In the pyramid of leisure, which is based on Maslow’s pyramid of needs (1943), we see that the valuable experiences of leisure about which we are talking can be indicated in diverse forms and degrees, from the simplest, understood as pastime and escapism, to the most complex, such as the experiences of creative leisure and leisure in solidarity.

Good practices of valuable experiences in different scopes: Education, work and free time Those set out so far are not just theoretical, but also have their practical side. We take good leisure practices to mean those initiatives capable of generating free, satisfying leisure experiences that have a purpose in themselves, whose innovative, proven and evaluated approach tends to be successful in other contexts. There are leisure initiatives that have facilitated the improvement of the present and which, therefore, can become a referent for the transformation of any region from the point of view of innovation. People who innovate and learn by enjoying are people who enjoy learning. The link between leisure and training becomes a vitally important aspect for the development of the society of knowledge. Formative experiences of leisure as processes of individual improvement and social transformation acquire an essential value for the enormous value that leisure experiences have based in freedom and intrinsic motivation. Experiences of formative leisure, like those developed in OcioBide, based on self-directed learning and conjugation with personal tastes, offer us the keys that the true processes of learning must follow (htp://www.ocio.deusto.es).

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The role of leisure in the innovation of organisations Through an analysis of Google working practices, we can see that the link between the workers of an organisation and their leisure is manifested as a space for the promotion of innovative culture. The provision by the company of spaces, services, and breaks in routine acts as an interesting method of facilitating creativity. To understand work as a constant challenge, looking for workers who perceive it as such and who are allowed to link their tastes and interests with the work that they do, are presented as key aspects for this increase of creativity. To find workers who are able to have ‘optimal’ experiences in their professional scope and to facilitate spatial and professional possibilities for this, is revealed as one of the keys to innovation in organisations. For example, the case of LEGO demonstrates how at present users and clients are turning from consumers to prosumers, making the importance of serious leisure in the innovating processes of products and organisations ever greater. The experience realised by LEGO shows the innovative power that fans can have. The processes of open innovation are becoming an ever more evaluated and effective innovative process. Both the model denominated Open Innovation OUT (based on the development of a platform at the service of users and collaborators which allows to increase and take advantage of their creativity) and the model denominated Open Innovation IN (in which an external network of collaborators for the innovating process is used) proposed by Leadbeater (2007) can become a fundamental value for the development of societies.

Fomenting innovation in free time The analysis of organisations like Wikipedia or the Gutenberg Project, shows us the value of social life and cooperation in innovation in leisure. The increasing amount of time dedicated in today’s society to leisure, and the possibilities for social transformation through the use of ICT, provide possibilities to use leisure for solidarity. The possibilities of collaborative work promote processes of digital voluntary service that are becoming key elements of 21st-century society. The use of leisure time as a transforming social force goes beyond its temporary importance, and allows it to become, through its existential value, an element with a great power of social innovation.

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Final reflection A society that seeks to have innovation as a sign of its identity must harness the creativity of people. How we can construct an innovative society? What must we do from the point of view of leisure to make people more creative? How we can make people able to live valuable experiences of leisure? What can this type of experience contribute to the promotion of innovation processes? A society that innovates needs continuous learning and the ability to adapt to changes in technology, in markets and in our mode of thinking. Leisure education is not a minor subject, since leisure occupies one of the highest positions in our scale of values and is an essential part of the new lifestyles. Active, substantial, creative and solidarity experiential leisure provide development and quality of life, but they do not arise spontaneously. In order to promote them, it is necessary to have suitably oriented training and socioeconomic policies. The innovative challenge of today’s leisure can be specified in the following aspects: yy to reject mistaken ideas; yy to know its meaning and incidence; yy to promote active, substantial, healthful, creative and solidarity experiential leisure; yy to develop to new interests and habits that allow these forms of leisure to be experienced; yy to provide people with access to valuable experiences of leisure; yy in addition, at community level it is important: to promote accessible and inclusive leisure, to prevent the risks of damaging leisure, to promote forms of leisure that facilitate cohesion as well as intergenerational leisure. Training is the only means for us to gradually achieve valuable leisure. Leisure, understood as an area of innovation and social development, needs a group of people who are positive, decided, solidarity, hopeful, able to enjoy the projects that they undertake. A healthy society should ensure that leisure is a vital area which meets the needs of human development that are difficult to satisfy in other areas. For all these reasons, leisure education should occupy a place no less important than education for work at the time of the industrial revolution.

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References Bauman, Z. (2006). Vida Líquida. Madrid: Paidós. Csikszentmihalyi, M., (2001). Ocio y Creatividad en el desarrollo humano. In Ocio y Desarrollo. Bilbao: Universidad de Deusto. Cuenca, M., San Salvador del Valle, R., Aguilar, E., and Ortega, C. (2008). Ideas, Personas y Organizaciones del Ocio al servicio de la Innovació. Bilbao: ,Universidad de Deusto (unpublished paper) Cuenca, M., (2000). Ocio humanista: dimensiones y manifestaciones actuales del ocio, Colección de Documentos de Estudios de Ocio nº16. Bilbao: Universidad de Deusto (re-edición 2003). Cuenca, M., (2004). Pedagogía del ocio: Modelos y Propuestas. Bilbao: Universidad de Deusto de Miguel, A., (2000). Dos generaciones de jóvenes 1960-1998. Madrid: Instituto de la Juventud, Delle Fave A. and MASSIMINI, F. (1998). La modernización y los contextos cambiantes de flujo en el trabajo y el ocio. In Csikszentmihalyi, M. Y I. S. (ed.), Experiencia óptima. Estudios psicológicos del flujo de la conciencia, pp.191-209. Bilbao: Desclée De Brouwer Dumazedier, J. (1964). Hacia una civilización del ocio. Barcelona: Estela. Jensen, R. (1995). Outdoor Recreation in America. Human Kinetics. Maccannell, D. (1976/1999). El Turista. Una nueva teoría de la clase ociosa. Barcelona, Edit Melusina. Maslow A., (1993). El hombre autorrealizado. Hacia una psicología del ser, 10ª Edición . Barcelona: Kairós. SGAE, (2005). Anuario 2005. Accessed las August 2009 at: www.artenetsgae.com/ anuario/home.html, Pine II, B.J., Gilmore,J.H. (2000). La economía de la experiencia. Barcelona: Granica. Stebbins, R.A. (2000). Un estilo de vida óptimo de ocio: combinar ocio serio y casual en la búsqueda del bienestar personal. In Cuenca, M. (ed.), Ocio y desarrollo humano, p.111. Bilbao: Universidad de Deusto/World Leisure, Verdú, V. (2006). El Estilo del mundo: la vida en el capitalismo de ficción. Barcelona: Anagrama.

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Exploring measures at the individual level

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Creativity and key competences

15. Creativity and key competences

Hélène Clark (Directorate-General for Education and Culture)

I am very pleased to be here today and to open today’s discussion on creativity skills, their link to key competences, and, in particular, how the creativity of individuals can be supported and measured. As we all know, there is no doubt about the need for creativity and key competences in today’s working life: globalisation brings both opportunities and challenges that education and training systems cannot ignore. Young people, indeed, need to learn how to use their full potential of creativity, to be able to turn challenges into opportunities and to see learning as a lifetime task for their personal, social and professional development. The European Framework of Key Competences for lifelong learning, which describes the eight key competences, has proved to be a valuable tool for European cooperation in education and training, and as a reference point for national reforms of curricula and teaching, for both school students and adults. I am convinced that this European Framework can also be a useful tool for thinking about how creativity and innovation can best be promoted. Let me start by raising three things that, in my view, link creativity and innovation to key competences. First, the innovation of the Framework of key competences is that it does not look at existing school systems and how learning is organised around subjects, but instead looks at the desired outcomes of schooling — what young people are able and willing to do after their initial education and training, in order to be prepared for adult life. This idea of competences as learning outcomes — the expected knowledge, skills and attitudes — helps us to look at the systems in a wider perspective, including their lifelong and life-wide aspects, as well as their quality. I think this perspective — which goes far beyond a static body of knowledge and involves the whole person — is both very helpful and very challenging for policymaking. 239


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Secondly — and I think it is essential to keep this in mind — the key competences serve: personal fulfilment, social inclusion and active citizenship, and employability and professional development. In our post-industrial, ever more networked society, creativity is increasingly central to all these three areas of life. Almost gone are the days of repetitive industrial work and the fixed competences needed to perform it. Our societies are becoming ever more diverse and less traditionally-structured. The way we communicate is evolving at a dizzying speed, and is changing personal, social and work relationships and structures faster than anyone would have imagined even five years ago. This puts increasing demands on personal competences, not just knowledge, and in particular brings the need to adapt creatively. Therefore the eight key competences include not only the ‘traditional’ competences like mother tongue, foreign languages, basic competences in maths and science, and digital competence, but also the more transversal ones such as learning to learn, social and civic competence, initiative taking and entrepreneurship, and cultural awareness and expression. The recommendation also makes it clear that creativity, critical thinking, problem-solving, and the management of feelings, for instance, underpin all of these eight key competences.

Creativity as an integrated aspect of key competences There are many definitions of creativity, but most of them refer to creativity being an everyday activity for all people, helping them to adapt to new situations and bringing something new and useful. Is this not, after all, one of the characteristics that makes us human? Creativity is required for our personal fulfilment, but also for the interpersonal or social dimension of our lives. I think the framework of key competences enables us to look at creativity from all of these aspects. Creativity is an essential dimension of a ‘package’ of competences that prepares people to take their place in the knowledge society as active learners, citizens and contributors to economy. But if we look at each of the eight competences we can see clearly how creativity is embedded in each and every one of them. Some might think that only the competences ‘Initiative taking and entrepreneurship’ and ‘cultural expression and awareness’ are relevant for creativity and innovation. Yes, turning ideas into action, and expressing oneself through various forms or artistic and culture are indeed about creativity. But this is, I think, much too narrow a point of view. Creativity is an essential element of each key competence, and, on the other hand, creativity itself can be enhanced through the development of these competences.

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Creativity and key competences

Let me give you some examples: yy Creativity is an essential part of mother tongue and languages; we need only think of poetry and theatre … Also, creativity is certainly a key in learning languages and getting acquainted with other cultures. yy Maths, science and technological competence, or the digital competences: without the dimension of creativity these would not lead to any innovation; creativity is an essential for innovations in these areas. yy Learning to learn, the very important competence for developing one’s learning skills is about becoming aware of one’s own learning style, gaining, processing, and assimilating new knowledge and skills autonomously and in groups. Creativity obviously enriches the learning process, and should be an aspect of any teaching activity. yy But we cannot ignore the role of creativity in the ‘Social and civic’ competence either. Creativity is a part of active citizenship, and can be enriched thorough interaction with others. In fact, the social aspect of creativity is at the heart of European diversity! I think these examples show that creativity is an essential element of all key competences, and, in turn, possessing these competences help individuals to make full use of their creative potential.

Implementation and assessment of key competences Ladies and Gentlemen, let me now say a few words on the implementation and assessment of the eight key competences and their creativity dimension. Obviously, the teaching of those competences that follow the division of knowledge and skills into traditional subjects is much easier for schools to organise, and it is much easier to measure students’ progress in developing them. However, we still tend to assess mainly the knowledge part of competences, while the skills and attitudes that are essential for the creative use of knowledge are much more difficult to test in traditional ways. There are some good examples around, however, to which we should pay more attention; and the European project on an indicators for Learning to Learning is indeed a promising one. But even more challenging are those competences — such as social and civic, entrepreneurship and cultural competences — that should be developed both within and across subjects and as a whole school project. I see here two main challenges. First, the development of these competences calls for a whole school approach: a common vision on how the competences are best nurtured, more collaboration both 241


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Hélène Clark

within schools and with the outside world, plus new kinds of leadership that encourages this to happen. In short, this calls for attention to the creativity and innovation of schools as learning communities. The second challenge brings me to the topic of the day: assessment and evaluation. We tend to place more value on things that can be measured as this helps us to justify that what we do is useful and serves a purpose. This poses a major challenge for competences that are hard to measure, multidimensional and often qualitative in nature: they risk being left aside as they are not part of the formal testing system. And yet they are the foundations for lifelong learning. Creativity, for sure, belongs in this category.

Concluding remarks Ladies and gentlemen, whilst I think the European Framework of key competences for lifelong learning provides a useful starting point for thinking about creativity and innovation, I am not at all sure it will give a straightforward answer on how to measure them. However, I think the framework well reflects the many dimensions of creativity in human nature and interaction as it gives equal importance to knowledge, skills and attitudes on the one hand, and on the use of competences for personal development, social inclusion and adaptation, and in the word of work, on the other. It allows us to examine competences and creativity as an underpinning quality both from the individual’s point of view and from a systemic perspective — that is the kind of environment that nurtures creativity and work in that way. I hope it will provide you with a useful starting point for today’s discussions and I would like to encourage you to use it in a most creative way in our discussions today.

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General Measurement approaches

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Creativity and personality

16. Creativity and personality

Rosa Aurora Chávez-Eakle, M.D., Ph.D. (Washington International Center for Creativity and The Johns Hopkins University)

Abstract The aim of this paper is to review the multiple relations between creativity and personality, including: (a) an introduction to the main measurement instruments that have been used to evaluate personality in the field of creativity; (b) specific personality characteristics and traits found in highly creative and successful scientists and artists studied at the National Institute of Psychiatry Ramon de la Fuente in Mexico City, and how these personality traits and behaviours were associated to differences in brain activation and molecular genetic variations in neurotransmitters systems; (c) a review of the impact of personality in the realisation of the creative potential, and the impact of creativity in personality growth; and (d) an overview of developmental events critical for both personality formation and creativity maturation, highlighting how these events should be considered when designing strategies, programs and policies in order to achieve quality education for all children.

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Rosa Aurora Chávez-Eakle

Introduction Why is it important to develop creativity? Creative thinking and creative problemsolving not only enhance our ability to adapt to our environment and circumstances but also allow us to transform them. Creativity provides the foundation for art, science, philosophy, and technology. The creative process involves the integration of several mental functions and also involves all the components of the life experience. Personality involves the everyday ways of feeling, thinking and acting of an individual involving two overlapping components: temperament, the biological, inheritable traits; and character, the traits acquired by cultural and social interaction (Cloninger, 2002, De la Fuente, 1959, 1992). These components are closely related; recent genetic research has shown that genetic factors have an impact in the way we experience our environment, and the environment has an impact on how genes are expressed at a given time (Plomin, 2003). It is importance to notice that personality is structured after adolescence is completed; however, there are temperament traits that are evident early in life. The aim of this article is to review the multiple relations between creativity and personality including the personality traits present in highly creative individuals, the effects of personality on the realisation of the creative potential, the effects of creative potential in personality development, and the critical events during development that impact both personality development and the realisation of the creative potential.

Personality assessment instruments used in the field of creativity This section summarises some of the most used personality assessment instruments in the field of creativity. These instruments have been created by psychologists, psychiatrists and by creativity researchers. Some of these instruments were developed to identify highly creative individuals, others were created to assess personality but have also been used in creativity research, and there are instruments that evaluate styles or preferences in creative thinking and behaviour, as shown in Table 1.

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Table 1: Personality Assessment Instruments Used in the Field of Creativity Instrument

Theoretical background and purpose

Structure

Administration

Age range

Reference

Adjective Checklist (ACL)

Adjectives describe a person’s attributes, ‘actual’ & ‘ideal’ self; identification of potentially creative persons

300 item list of adjectives measures 37 traits

Self-assessment or by observers, 10 to 15 minutes

Widely used in adults

Gough & Heilbrun, 1983

Khatena-Torrance Creative Perception Inventory

Measures artistic inclination, intelligence, individuality, sensitivity, initiative, and selfstrength; imagination, appeal to authority, selfconfidence, inquisitiveness, and awareness of others

Comprises two tests: Something About Myself (SAM) What Kind of Person Are You? (WKOPAY)

Self report 20–40 minutes

12 years and older

Khatena & Torrance, 1976

Myers-Briggs Type Indicator

Uses the Jungian dichotomies of introversion/ extroversion, sensing/intuiting, thinking/feeling, perceiving/judging

16 different personality types

166 multiple choice items

14 years and older

Myers & McCaulley, 1985

Kirton Adaptation Innovation Inventory (KAI)

Evaluates differences in preferred styles of problem-solving and creativity: adaptors improve things; innovators do things differently

Adaptation/ Innovation continuum

32 items

Teens and adults

Kirton, 1994

Buffalo Creative Process Inventory (BCPI)

Identifies problemsolving styles based on the three stages of the creative problem-solving model (CPS)

Styles: the clarifier or collector; the ideator; the developer; and the executor

36 items

Teens and adults

Puccio, 1999

Minnesota Multiphasic Personality Inventory (MMPI)

Identifies personality structure and psychopathology based on the assumption that psychopathology is a homogenous condition that is additive

Clinical, validity, content and temperament scales

1 to 2 hours

Adults MMPI-A for use with teens

Nassif & Quevillon, 2008

Rorschach inkblot test

Psychological assessment of the personality function and psychotic/nonpsychotic thinking

Adults

Created by Hermann Rorschach in 1921 Reference: Gregory, 2000

Designed to elicit perceptions

Ten ink blots

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Table 1: Personality Assessment Instruments Used in the Field of Creativity (Continued) Theoretical background and purpose

Structure

Temperament and Character Inventory (TCI)

Based on Cloninger, Svrakic & Przybeck psychobiological model

Temperament: novelty seeking, harm avoidance, reward dependence and persistence Character: self-directedness, cooperativeness, self-transcendence

Overexcitability Questionnaire II (OEQII)

Based on Dabrowski’s theory of positive disintegration

Emotional, sensual, intellectual, imaginational and psychomotor overexcitabilities

Instrument

Administration

Age range

Reference

240 Items

Adults, there is a new junior TCI for children and teens

Cloninger, Svrakic & Przybeck, 1993 Svrakic, et al., 2002

50 items

Children, teens, adults

Falk, Yakmaci-Guzel, Chang & ChávezEakle, 2007

Temperament and character traits present in highly creative individuals Scientific data result of research projects conducted at the National Institute of Psychiatry Ramon de la Fuente in Mexico City is presented in this section (Chavez-Eakle, Lara & Cruz, 2006). In these projects three groups of individuals were evaluated: Group I was composed of 30 individuals with high creative achievement, dedicated to fulltime scientific and/or artistic creation, who had won national prizes in art or science, and who were members of the National System of Researchers or the National System of Creators in Mexico; Group II, the control group, was composed of 30 healthy individuals; Group III consisted of 30 psychiatric outpatients of the National Institute of Psychiatry ‘Ramon de la Fuente.’ All the procedures were performed in compliance with the relevant laws and institutional guidelines and were approved by the National Institute of Psychiatry ‘Ramón de la Fuente’ Ethics Committee. The Torrance Tests of Creative Thinking (TTCT) figural and verbal (Torrance, 1990) were administered to all the participants. The TTCT are the most widely used instruments that assess creative potential. These tests have been used for identification of the creatively gifted and are reliable in multicultural settings. The TTCT provide a creativity index (CI) and scores for the following dimensions: flexibility, fluency, originality, elaboration, resistance to premature closure, and abstractness of titles. Additional points are added to the final score for emotional expressiveness, storytelling 248


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articulateness, movement or action, expressiveness of titles, synthesis of incomplete figures, unusual visualisation, internal visualisation, extending or breaking boundaries, humour, richness of imagery, colourfulness of imagery, and fantasy (Torrance and Safter, 1999). The TTCT have shown high reliability and high predictive validity for future career image, and for academic, and style-living creative achievements in 22 and 30-year follow-up studies (Torrance, 1988, Torrance, 1990, Torrance, 1993). Further, the TTCT have been used in more than 2 000 research projects and translated into 30 languages (Cramond, 1999). The Temperament and Character Inventory (TCI) was also administered to the participants in our projects. We found that the personality profile associated with a high creativity index included the following traits: high exploratory excitability, low harm avoidance, high persistence, high self-directedness, and high cooperativeness. This means that highly creative individuals display exploratory behaviour when encountering novelty, are optimistic, they are tolerant of uncertainty, they pursue goals with intensity against adversity; display responsibility, are directed to their goals, are able to utilise resources, are self-accepting and congruent, and they display empathy, tolerance, and integrated consciousness (Chavez-Eakle, Lara & Cruz, 2006). In addition, there were strong negative correlations between creativity and psychopathology; flexibility, abstraction, premature closure resistance, emotional expressiveness, imagination, humour, fantasy were the most affected by the presence of psychopathology (Chavez-Eakle, Lara & Cruz, 2006).

Figure 1: Correlation regions between cerebral blood flow and creativity index obtained with the Torrance Tests of creative thinking, figural and verbal (reproduced with permission of the editor).

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Using the Overexcitability Questionnaire II (OEQII) we found that highly creative individuals present significantly higher scores on sensual, intellectual and imaginational overexcitabilities (Chavez, 2004). There are five types of overexcitabilities: emotional, sensual, intellectual, imaginational and psychomotor and these patterns of intense responses have been found to be indicators of creative potential and giftedness (Dabrowski, Kawczak & Piechowski, 1970). According to Dabrowski some people have a strong potential for development and the overexcitabilities are critical components of this potential which allows a person to become authentic and autonomous. The OEQII is a 50 item instrument that evaluates the five overexcitabilities, it has been used in cross-cultural studies involving China, Mexico, Spain, Turkey and the US (Falk, Yakmaci-Guzel, Chang & Chávez-Eakle, 2007). As demonstrated in this research, personality has an impact in the realisation of the creative potential and creativity also has consequences in personality growth. Highly creative individuals are permanently open to personality reorganisations that make it possible to experience states that, in appearance, could seem to be pathological (Eissler, 1978), they are in constant self-actualisation (May, 1975) and creativity is intimately related to the sense and meaning of being alive (Winnicott, 1971).

Neurobiological findings In related research, when studying fine molecular variations associated with high creative potential and high creative achievement we found a significant association between the serotonin transporter gene 5’SLC6A4 and the temperament traits harm avoidance and novelty seeking in highly creative individuals (Chavez et al., 2003) and an association between the dopamine receptor DRD4 gene and the creativity index (Chavez, 2004, Chavez-Eakle, 2007). To our knowledge, this was the first molecular genetics study evaluating creativity. In addition, we evaluated differences in brain cerebral blood flow (CBF) between highly creative individuals using Single Photon Emission Computerised Tomography (SPECT) and statistical parametric mapping. Subjects with a high creative performance showed greater CBF activity in the right precentral gyrus, right culmen, left and right middle frontal gyrus, right frontal rectal gyrus, left frontal orbital gyrus, and left inferior gyrus (BA 6, 10, 11, 47, 20), and cerebellum, confirming activation of both brain hemispheres at the same time. These structures have been involved in cognition, emotion, working memory, novelty response, imagery, multimodal processing and sexual arousal (Chávez-Eakle, Graff-Guerrero, García-Reyna, Vaugier, & Cruz-Fuentes, 2007).

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Developmental events critical for both personality formation and creativity maturation Creativity can be present at any age but it is related to first life experiences which are critical for the formation of a healthy personality and for the fulfilment of creative potential. Caregivers’ attunement and adaptations to the child’s needs produce in the child the illusion of an exterior reality that corresponds with their own capacity to create, allowing children to experience their feelings as their own (Winnicott, 1971). If the adult is attuned and involved, children will be able to experience their emotions within manageable boundaries, to make meaning and regulate them; children will learn to feel comfortable about their own impulses therefore they will become able to build and use their internal resources and to develop their intuition (Bion, 1967; Rayner, Joyce, Rose, Twyman & Clulow, 2005). The adult provides the context to explore the inner impulses as coming from the self, therefore, children become able to relate to the self, the caregiver and the world in a benign, creative way. However, if the experience is negative all the frustrations that the child cannot handle become impingements, individuality and creativity remain hidden in a false self-organisation and impulses are experienced ‘as a clap of thunder from elsewhere’ not as part of the self (Winnicott, 1960). Caregivers act as a mirror where the child can find a coherent, creative sense of the self; what is seen by the child in this mirror is what the child becomes able to see in the self (Fonagy, 1999; Winnicott, 1960, Rayner, Joyce, Rose, Twyman & Clulow, 2005). The experience of shame at early stages of development can lead to future blockages in the creative process. Play, fantasy, the experiences of control and ownership over the own body, role imitation of adults, early literacies broadly defined (Eakle, 2007), and socialisation are other developmental experiences critical for both personality formation and creativity development. Play is especially important because it involves the basic components of the creative process such as combining and generating new possibilities, experimentation, exploration of the limits of reality and fantasy. A good session of play leaves a child calmer and satisfied, whereas disrupted play can leave a child in deep distress. An over strict climate where playing is devaluated can prevent play from happening. A terrified child is unable to play. If play is disrupted the child feels full of frustrations that are torturing the self; therefore such a child can begin to torture others, an develops ruthless play that involves sadistic, unempathic, cold, and even cruel behaviours (Rayner, 2005). These ruthless games can continue into adult life, for instance, in malevolent creativity, empire building, or criminal behaviour (Rayner, Joyce, Rose, Twyman & Clulow, 2005). That is why it is fundamental to re-evaluate education policies regarding play.

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Conclusions Creativity and personality have multiple and multidimensional relations. All the tests reviewed in this article have been used for research in diverse cultural settings; the tests assessing temperament traits (e.g. the JrTCI or the OEQ-II) are useful with younger individuals because these traits are present very early in life. The TTCT are creativity assessment instruments that have been useful to identify creative potential in children and adults from different cultural backgrounds and from under-represented populations due to the neutrality of the test stimuli that can elicit creative responses in multiple and diverse cultures. Using these instruments, there have been documented personality traits that are present in highly creative individuals; deeper knowledge of these traits could be helpful in understanding the behaviour of highly creative individuals in educational settings. It is important to keep in mind that personality is in continuous development during childhood and adolescence, therefore substantial changes in education strategies and policies could have an impact in the development and consolidation of the children and adolescents personality traits. Furthermore, personality can have an influence on the realisation of the creative potential and the creative potential has lifespan implications for personality development by offering possibilities for personality reorganisation. As it has been illustrated, there are events during development, in particular during childhood that impact both personality formation and the development of the creative potential. The quality of the children’s experience with caregivers, their attunement to the child’s need, their reactions to the child’s ‘unusual’ behaviours and the availability of free play and play incorporated into learning activities are relevant events that should be carefully considered when developing education programs and policies. Perhaps we should begin to consider personality formation and creativity development as priorities when designing education strategies, programs and policies in order to achieve quality education and wellbeing for all children. References Bion, W. (1967). Second Thoughts. London: Heinemann. Chávez R. A., Cruz, C., Eakle, A. J., Gómez A., Lara M. C., Lartigue T. (2003). Association Analysis of the Serotonin Transporter Gene Promoter Regulatory Polymorphism, Creativity Index, and Temperament and Character Traits. Cancun, Mexico: Proceedings of the Annual Meeting of the Human Genome Conference. Chavez-Eakle, R. A. (2004). On the neurobiology of the creative process, Bulletin of Psychology and the Arts, 5, 29-35. Chávez, R. A. (2004). Evaluación Integral de la Personalidad Creativa: Fenomenología, Clínica y Genética (Integral Evaluation of the Creative Personality: Phenomenology, 252


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Clinic and Genetics). Unpublished Dissertation. Facultad de Medicina, National Autonomous University of Mexico UNAM, Mexico City. Chavez-Eakle, R. A. (2004). On the neurobiology of the creative process, Bulletin of Psychology and the Arts, 5, 29-35. Chávez-Eakle, R. A., Lara, M. C., & Cruz, C. (2006). Personality: A possible bridge between creativity and psychopathology? Creativity Research Journal, 18(1), 27-38. Chávez-Eakle, R. A., Graff-Guerrero, A., García-Reyna, J. C., Vaugier, V., and Cruz-Fuentes, C. (2004). Neurobiology of creativity: Preliminary results of a brain activation study. Salud Mental, 27 (3). Chávez-Eakle, R. A., Graff-Guerrero, A., García-Reyna, J. C., Vaugier, V., and Cruz-Fuentes, C. (2007). Cerebral blood flow associated with creative performance: A comparative study, Neuroimage, 38(3), 519-528. Chavez-Eakle, R. A. (2007). On the neurobiology of creativity: DNA and brain blood flow. In Martindale, C., Locher, P. V. and Petrov, V. (Eds.). Evolutionary and neurocognitive approaches to the arts. Amityville, NY: Baywood. Cloninger, C. R., Svrakic, D. M., and Przybeck, T. R. (1993). A psychobiological model of temperament and character, Archives of General Psychiatry, 50, 975-990. Cloninger, C. R. (2002). Relevance of normal personality for psychiatrists. In B. J. Ebstein, and R. Belmaker (Eds.), Molecular Genetics and the Human Personality (pp.33-42). Washington D.C: American Psychiatric Publishing. Cramond, B. (1999). The Torrance Tests of Creative Thinking: Going beyond the scores. In: Fishkin, A. et al. (Eds.), Investigating creativity in youth. NJ: Hampton Press. Dabrowski, K., Kawczak, A. and Piechowski, M. (1970). Mental Growth through positive desintegration. London: Gryf Publications. De la Fuente, R. (1992) Psicología Médica. México City: Fondo de Cultura Económica. (Original work published in 1959). Domino, G., & Giuliani, I. (1997) Creativity in three samples of photographers: a validation of the adjective check list creativity scale, Creativity Research Journal, 10, 193-200. Eakle, A. J. (2007). Museum literacy, art, and space study. In Lapp, D., Flood, J. and Heath, S. B. (Eds), Handbook of research on teaching literacy through the communicative and visual arts (2nd Edition). Mahwah NJ: Lawrence Erlbaum Eissler, K.R. (1978). Creativity and Adolescence—The Effect of Trauma in Freud’s Adolescence, The Psychoanalytic Study of the Child, 33, 461-517. Falk, R. F., Yakmaci-Guzel, B., Chang, A. and Chávez-Eakle, R. A. (2007). Measuring Overexcitability: Replication across Five Countries. In S. Mendaglio (Ed.). Dabrowski’s Theory of Positive Disintegration. Scottsdale, AZ: Great Potential Press. Fonagy, P. (1999). Final remarks. In: Perelberg, R. J. (ed) Psychoanalytic Understanding of Violence and Suicide. London: New Library of Psychoanalysis. 253


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Gough, H. G., & Heilbrun, A .B. (1983). The Adjective Check List Manual (1983 ed.). Palo Alto, CA: Consulting Psychologists Press. Gregory, R. (2000). Reversing Rorschach, Nature, 404, 19. Helson, R. (1996). In search of the creative personality, Creativity Research Journal, 9, 295-306. Helson, R., Jones, C., and Kwan, V. (2002). Personality change over 40 years of adulthood: hierarchical linear modeling analyses of two longitudinal samples, Journal of Personality and Social Psychology, 38, 752-766. Helson, R., and Pals, J. (2000). Creative potential, creative achievement, and personal growth, Journal of Personality, 68, 1-27. Joyce, A. (2005). The first six months: the baby getting started. In Rayner, E., Joyce, A., Rose, J., Twyman, M., & Clulow, C. Human Development: an Introduction to the Psychodynamics of Growth, Maturity and Ageing. Sussex, England: Routledge. Khatena, J. and Torrance, E. P. (1976). Khatena-Torrance Creative Perception Inventory (KTCPI). Chicago, IL: Stoeling Company. Kirton, M. (1994). Adaptors and innovators. London: Routledge. Martindale, C., Anderson, K., Moore, K. and West, A. N. (1996). Creativity, oversensitivity, and rate of habituation, Personality and individual differences. 20, 423-427 MacKinnon, D. W. (1962). The nature and nurture of creative talent, American Psychologist, 17, 484-95. Myers, I. B., and McCaulley, M. H. (1985). A guide to the development and use of the MyersBriggs Type Indicator. Palo Alto, CA: Consulting Psychologists Press. Nassif, C. and Quevillon, R. (2008). The development of a preliminary creativity scale for the MMPI-2: The C scale, Creativity Research Journal. 20(1), 13–20. Plomin, R. (2003). General cognitive ability. In R. Plomin, J. C. Defries, I. W. Craig & P. McGuffin (Eds.), Behavioral genetics in the postgenomic era (pp. 183-202). Washington, DC: American Psychological Association Press. Puccio, G. J. (1999). Creative problem solving preferences: Their identification and implications, Creativity and Innovation Management, 8 (3), 171-178. Rayner, E. (2005). Three to five years old. In Rayner, E., Joyce, A., Rose, J., Twyman, M., and Clulow, C. Human Development: an Introduction to the Psychodynamics of Growth, Maturity and Ageing. Sussex, England: Routledge. Rayner, E., Joyce, A., Rose, J., Twyman, M., and Clulow, C. (2005). Human Development: an Introduction to the Psychodynamics of Growth, Maturity and Ageing. Sussex, England: Routledge. Svrakic, D. M., Draganic, S., Hill, K., Bayon, C., Przybeck, T. R., and Cloninger, C. R. (2002). Temperament, character, and personality disorders: Ethiologic, diagnostic, and treatment issues, Acta Psychiatrica Scandinavica, 106, 189-195. 254


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Torrance, E. P., (1988). The nature of creativity as manifest in its testing. In: Sternberg, R. J. (Ed.), The nature of creativity. (pp. 43-75). New York, NY: Cambridge University Press Torrance, E. P. (1990). Torrance tests of creative thinking. Bensenville, IL: Scholastic Testing Service. Torrance, E. P. (1993). The beyonders in a thirty year longitudinal study of creative achievement, Roeper Review. 15, 131-135. Torrance, E. P. (1999). Making the creative leap beyond. Buffalo, NY: Creative Education Foundation Press. Winnicott, D. W. (1960). Ego distortions in terms of the true and false self. In the Maturational Processes and the Facilitating Environment. London: Hogarth Press and the Institute of Psychoanalysis. Winnicott, D. W. (1971). Playing and reality. London: Tavistock Publications. Zeki, S. (2001). Artistic creativity and the brain, Science, 293, 51-52.

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Fostering and measuring creativity and innovation

17. Fostering and measuring creativity and innovation: individuals, organisations and products

David H. Cropley (Defence and Systems Institute, University of South Australia)

Abstract There is no doubt that creativity, and innovation, can be measured. It is not necessary to go into the detail of the range of tests and instruments that have been developed over many years. What is far more significant is the fact that these measures have been developed across a range of disciplines — from psychology to business — and must be integrated in order to realise their potential to foster change. It is highly significant that this discussion takes place against a backdrop of global economic turmoil. Now, more than ever, individuals and organisations must be able to harness creativity and innovation in order to rebuild the strength of our economies. This paper will outline ways that creativity — of individuals, of products and of organisations — can be measured, and how these measures must interact in order to fully realise the potential of creativity and innovation to drive sustainable economic growth. The role of education in driving the development and application of measures of creativity will be discussed.

Business models of innovation Innovation involves the introduction of something new and valuable — an artefact or a method — into a functioning production, marketing, or management system. There are a number of what might be called traditional business models of this process, largely based on Schumpeter’s (1942) Theory of Economic Development. These are char257


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acterised by their primary focus on the commercial and organisational aspects of innovation. Leifer et al (2000), for example, describe radical and incremental innovation in terms of their relative timelines: the ‘trajectory’ they follow, where in the process the idea generation and opportunity recognition occur, the degree of formality and linearity of the process, the nature of the players in the process, the organisational structures that support the process, and the resources and competencies required. Afuah (1998) links new technological knowledge and new market knowledge to processes and people, leading to innovation. Christensen et al (2004) reiterate the importance of resources (what a firm has), processes (how a firm does its work), and values (what a firm wants to do) in his RPV theory, and stresses that these define an organisation’s strengths and weaknesses in relation to the innovation process. It may be said that these models view the ‘introduction of a new thing or method’ and the ‘embodiment, combination, or synthesis of knowledge in original, relevant, valued new products, processes, or services’ (Luecke and Katz, 2003) through the lens of the business functions and processes needed to turn an idea into a commercial product. A typical example is that in Luecke and Katz (2003) and shown in Figure 1, highlighting two stages in the process of innovation: invention and exploitation. Idea Generation, Idea Evaluation and Opportunity Recognition embody processes and concepts associated with invention (or what may be called ‘creativity’), while Development and Commercialisation are concerned with the exploitation of ideas. Together, these stages give us innovation.

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Business models of innovation, such as that shown in Figure 1, give rise to a variety of diagnostic tools that examine the management of the innovation process within the business organisation, including such factors as: the physical environment in which innovation takes place; the structure of the organisation engaging in innovation; and the traditions of the organisation. Such tools frequently offer not only a description of the business innovation process, but also a prescriptive approach to the improvement of the process. Luecke and Katz (2003) offer, for example, a ‘Workplace Assessment Checklist’ that allows managers to examine, inter alia, their leadership style; the diversity of thinking and learning styles among their staff; characteristics of their work groups; the psychological environment; and the nature of the physical workspace, to see if these are fostering the organisation’s ability to innovate, or hindering it. Higgins (1995) adopts a more extensive approach to organisational diagnosis examining characteristics across seven dimensions: Skills; Strategy; Structure; Systems; Style; Staff and Shared values. These checklists offer an insight into an organisation’s potential to innovate, and permit remedial action to be taken in dimensions inhibiting innovation. The models, and associated tools, are limited in their usefulness for one or more of the following reasons: yy they do not adequately address the psychological factors that foster or inhibit the creativity and innovation of the actors in the process; yy they do not adequately address the social/environmental factors that impact on the innovation process; yy they do not adequately explain the detailed steps involved in the innovation process — in particular the early stages of ‘invention’ or creativity; yy they do not adequately address the manner in which the importance of certain social and psychological factors changes during the innovation process.

Psychological approaches to understanding innovation Many of the dimensions in well-known models of the innovation process are tied to the behaviours, actions and personalities of the individuals, or actors, engaged in the initial, creative steps (invention) as well as the latter steps of exploitation. It makes sense, therefore, to examine innovation not only as an organisational and environmental phenomenon, but also from a psychological point of view. This is the purpose of the present article. In particular, this article will draw on psychological research and theory on creativity — conceptualised here as the process of systematic and purposeful generation of novelty. Before it can be inserted into a system 259


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(for example, the market), novelty has first to be brought into existence; this is the fundamental task of creativity. Looked at it in this way, creativity is a component of the process of innovation and is necessary, but not sufficient, for innovation. Creativity is not identical with innovation; however, it can be regarded as the first step in a two-part process of innovation starting with generation of novelty (invention, or, creativity) and moving on to ‘exploitation’ of it (what we call ‘insertion’ into a functioning system). It is not the purpose here to develop a definitive theoretical model of creativity or of the role of creativity in innovation. However, this paper will turn to psychological research and theory on creativity as a source of ideas on how innovation can be fostered in practical settings such as a business or organisation.

Psychological dimensions of creativity From early in the modern era psychological researchers have looked at creativity from the point of view of the ‘three Ps’ (e.g. Barron, 1969): Person, Product and Process, to which Rhodes (1961, p. 305) added the fourth ‘P’ (Press; i.e. the pressure exerted by the environment). Starting with Guilford (e.g. 1950), who can be regarded as the initiator of the modern creativity era in psychological research, numbers of psychologically oriented authors have discussed the Process, usually from the point of view of thinking processes within creative individuals (i.e. from the cognitive point of view, emphasising above all convergent and divergent thinking). There have also been numerous psychological discussions of the creative Person. These have been summarised by, among others, Eysenck (1997) and Helson (1999). Discussion of the Person can be seen as involving: (a) personal properties such as openness; (b) motivation such as dissatisfaction with the status quo; and, more recently, (c) feelings such as positive or negative affect associated with creativity (e.g. Kaufman, 2003). From a practical point of view, however, the most interesting aspect of creativity is the Products it yields and the environmental circumstances (such as management style) that foster the emergence of such products. These latter are referred to here as involving Press. There has been a tendency for psychological theorists to pay relatively little attention to products, except for ‘trivial’ products such as drawings linking pages full of circles or suggestions for fanciful uses of common objects, possibly because psychologists and educators have largely, although not exclusively, concentrated on children. Once creativity is seen as the first step in the process of innovation, it is inevitable that attention shifts more explicitly to the output of the process, namely the Product, and then to the conditions that encourage (or discourage) appropriate products (i.e. Press). 260


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The idea of using psychological concepts from creativity research to expand understanding of innovation is, in fact, not new. A number of approaches of this kind exist and, regardless of their theoretical quality, several are highly developed and widely applied. Kirton (1989), for instance, distinguished between people who seek to solve problems by making use of what they already know and can do (adaptors), and people who try to reorganise and restructure the problem (innovators). Kirton regarded three psychological characteristics as central in innovation: originality (cognition), conformity (social), and efficiency (cognition), although he also recognised the role of risk-taking (motivation), and self-confidence (personality), which he believed are higher in innovators than in adaptors. Lipman-Blumen (1991) introduced a more social-psychological approach focused not on problem-solving but on ‘achieving style’. She identified three broad styles (Relational, Direct and Instrumental). Each of these has three forms of expression: vicarious, contributory, and collaborative (Relational style); intrinsic, competitive, and power-oriented (Direct style); and entrusting, social, and personal (Instrumental style). Most of these (e.g. collaborative, competitive, power-oriented, entrusting, social) are concerned with social interactions. Individual people, as well as the organisation itself, can be rated on their achieving style, and the degree of goodness of fit between people and organisation.

The paradoxes of creativity It is implicit in many of these models, both psychological and business-oriented, that characteristics favourable to creativity are universally favourable throughout the innovation process. For example, in Luecke and Katz’s (2003) ‘Assessing the Psychological Environment’ checklist the question is posed: ‘Do you, as the manager, encourage risktaking? ’ The rating scale allows this to be seen either as a ‘strength’, as ‘adequate’, or as a characteristic that ‘needs improvement’. This implies that a factor that is favourable to risk-taking is universally favourable in the innovation process. However, almost from the beginning of the modern era, research on creativity has yielded surprising findings that have led various writers to refer to it as involving ‘a bundle of paradoxes’ (e.g., Cropley, 1997, p. 8). A complete discussion of the paradoxes of creativity would go far beyond the limits of this article, but they can be illustrated with some examples. In the area of Process, for instance, creativity came to be equated with divergent thinking almost immediately after Guilford’s (1950) seminal paper. However, the early research of Hudson (1968) showed that people identified by psychological tests as having a marked preference for convergent thinking none-the-less showed high creativity on some tasks. Numerous modern writers (for a summary, see 261


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Cropley, 2006) have also emphasised the importance of convergent thinking, whereas intuitively divergent thinking would be expected to be of paramount importance. In the case of the Person, Csikszentmihalyi (1996) referred to the importance of a ‘complex’ personality that combines contradictions such as sensitivity occurring together with toughness, or high intelligence with naivety. In a 30-year longitudinal study, Helson (1999) showed that personality traits such as openness and flexibility that intuitively seem favourable to creativity can hinder it under certain circumstances. As Kirton (1989) pointed out, both adaptation of what exists and production of something new (which he called ‘innovation’) can lead to useful novel products, so that both adaptive personal characteristics (such as a preference for dealing with the new by extending the already known) and also innovative characteristics (e.g. a preference for dealing with the new by generating something novel) are involved in creativity. In an overview of research on mood and creativity, Kaufman (2003) showed that mood is a precursor to creativity, accompanies it, and results from it. Furthermore, despite the widespread belief that positive mood is necessary for creativity and negative mood is fatal to it, Kaufman showed that research indicates that there is a role in creativity for negative mood too. Thus both ‘generative’ feelings such as the ‘thrill of the chase’ when facing a challenge, the feeling of excited anticipation when generating novelty, or the feeling of satisfaction after achieving an effectively novel product, but also ‘conserving’ feelings such as anxiety in the face of uncertainty, frustration when progress is impeded, or disappointment when a product is not validated play a role in generating effective novelty. Many studies have confirmed that motivation plays an important role in creativity. To take a single example, Park and Jang (2005) investigated motivation for scientific creativity by interviewing both theoretical and applied physicists. They concluded that, in addition to feelings such as interest or curiosity, these scientists were also affected by what they called cognitive motives — essentially deriving from their knowledge about phenomena in the external world. In particular, they identified: (a) recognition of gaps in existing knowledge (incompleteness); (b) a drive to round out recently emerging novelty (development); and (c) identification of contradictions in accepted knowledge (conflict/discrepancy) as cognitive motives for creativity. They gave examples from statements by Albert Einstein that indicate he experienced all three of these motivating forces, but at different times.

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The factors discussed above suggest that the motivation for creativity may arise within the individual, rather than in the external world. Indeed, a widely accepted position is that creativity is based on intrinsic motivation (Amabile, 1996): the wish to carry out an activity for the sake of the activity, regardless of external reward. This position can be contrasted with working for external rewards such as praise, awards, pay raises, promotion, and even avoidance of punishment (extrinsic motivation). More recently, however, researchers, including Amabile herself (e.g. Collins and Amabile, 1999), have accepted that extrinsic motivation is not necessarily fatal to creativity. Indeed, as Kasof et al. (2007) put it, some researchers report negative effects of extrinsic motivation, to be sure, but others claim positive effects, and still others report mixed effects. Unsworth (2001) argued that there are four kinds of creativity, and her system can be used to demonstrate the paradoxical relationship of motivation and creativity. She distinguished between creativity where: (a) the person is driven by external pressure to solve problems defined by other people (what she called ‘responsive’ creativity — this is the most clearly externally motivated creativity); (b) the person is motivated by external pressure to solve self-discovered problems (‘expected’ creativity — a mixed kind of motivation); (c) the person is self-motivated but the problem is defined externally (‘contributory’ creativity — a second pattern of mixed motivation); and finally, (d) the person is self-motivated to solve self-defined problems (‘proactive’ creativity — the most clearly internally-motivated creativity). The crucial point for our purposes here is that all four of these constellations can lead to production and exploitation of effective novelty. Thus, a further paradox arises: forcing this into a bipolar dimension, we distinguish between ‘proactive’ motivation at one pole (internal motivation and self-discovered problems) to ‘reactive’ motivation at the other (external motivation and imposed problems), with various ‘mixed’ constellations between the poles. Turning to Product, it is more or less self-evidently true that creative products must be novel. However, as Cropley and Cropley (2005) emphasised, especially in practical areas such as business, novelty alone is not enough: A product must also be relevant and effective. A deviation from the customary that results from ignorance, blind nonconformity, or unreasoning rebelliousness involves only pseudo-creativity (Cattell and Butcher, 1968), while novelty that is in itself sensible but impossible to put into practice involves only quasi-creativity (Heinelt, 1974). Furthermore, not only must novelty work (do what it is supposed to do), but in business it must also be understandable, usable, and acceptable to other people (it must make sense). Christensen (1997) gave examples of highly effective (and often ultimately successful) novelty that led to disasters for otherwise successful and well-run ‘great firms,’ because it could not be fitted into the existing 263


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framework and customers rejected it. Thus, products need to be simultaneously novel, original and even surprising, and yet routine (in the sense of reliable and effective). In a research program stretching over more than 30 years and largely based on daily logs or diaries kept by managers (i.e. involving what the managers actually did and thought, not what they claimed in questionnaires), Amabile (e.g. 1996) showed that there was a complex interaction between Press (management pressure) and innovation. Where the task involved carrying out predefined steps, a high level of environmental demand facilitated performance. However, where the task involved exploring possibilities, a low level of demand was facilitatory. Thus, high managerial pressure is facilitatory under some circumstances, but destructive under others. Table 1: The social/psychological paradoxes of creativity Social/psychological dimension

Poles of the paradox

Process

convergent thinking v divergent thinking

reactive v proactive

Motivation

Personal characteristics

adaptive v innovative

Feelings

conserving v generative

Product

routine v creative

Press

high demand v low demand

Examples of characteristics Reapplying the known, being fast and accurate, being strictly logical Branching out, making unexpected links, seeing surprising implications Problem accepting: focusing on existing problems Driven by external pressure Problem finding: focusing on self-identified (unexpected) problems Driven by internal pressure Conforming, preferring the well-considered, relying on the tried and trusted Autonomous, open, high in self-confidence, non-conforming, spontaneous Exposure to the unexpected triggers negative effect, departure from the usual arouses discomfort Exposure to the unexpected triggers positive effect, departure from the usual arouses excitement Effective, accurate, conventional Surprising, seminal, germinal Problems and nature of desired solution closely defined by management, high pressure for quick results, high demand for accuracy, low tolerance of error or failure, rewards for being right, high status given to people who fit in well Problems and nature of solutions loosely defined, low pressure for quick results, tolerance of ‘good’ errors, rewards for opening up perspectives, high status given to people who are ‘different’

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Table 1 contains an illustrative overview of the paradoxes in the six social/psychological areas (process, personal properties, motivation, feelings, product, and press) (see also Cropley and Cropley, 2008). For the sake of brevity each paradox is presented as a single bipolar dimension (e.g. convergent v divergent thinking, reactive v proactive motivation, etc.) and examples of the main characteristics of each pole listed for illustrative purposes (e.g. convergent thinking involves, among other things, reapplying the already known, being fast and accurate, and being strictly logical, whereas divergent thinking involves processes like branching out, making unexpected links, and seeing surprising implications). The central issue here is that research has shown that both poles of these paradoxes are needed in creativity (and indeed, innovation), despite the fact that they seem to be mutually antagonistic. How is this possible? Koberg and Bagnall (1991) argued that the interaction of mutually antagonistic poles involves fluctuation backwards and forwards in ‘alternating, psycho-behavioural waves.’ They highlighted the ‘need for alternative thinking (and behaving)’ meaning a ‘continual variation of style between convergent and divergent behaviour …’ and that, in one stage, ‘you must allow yourself to remain open to all kinds of input’ whereas ‘in another stage, often just moments later, you must wear ‘blinkers’ and narrow your attention to all but a few items.’ The question that now arises is How this fluctuation is organised?

The phases of creativity Csikszentmihalyi (2006) argued that the creative process may include distinct phases or different forms that draw on different psychological resources. A simple early empirical investigation along these lines was that of Prindle (1906). He studied inventors, and concluded that every invention is the result of a series of small, compounding steps. The gain in one step creates a new jumping off point for the next step, and so on. In another early study with inventors who had successfully applied for patents, Rossman (1931) proposed a more formal phase model of invention involving seven phases: Observation of a need or difficulty; Analysis of the need; Survey of all available information; Formulation of all objectively possible solutions; Critical Analysis of these solutions for their advantages and disadvantages; the Birth of new ideas; and Experimentation to test out the most promising idea. The father of brainstorming, Osborn (1953), also argued for a seven-step creativity process involving: Orientation (identifying the problem); Preparation (gathering relevant data); Analysis (breaking it all down into its constituent elements); Ideation (collecting a large number of alternative solution possibilities); Incubation (letting it all churn); Synthesis (putting it all together); and Evaluation (judging the value of the result). 265


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In the post-Sputnik era (after 1957), further psychological discussions of phase models have taken place. Koberg and Bagnall (1991) proposed a ‘universal traveller’ phase model involving the by now familiar seven phases: Accept the situation as a challenge; Analyse the ‘world of the problem’; Define the main issues and goals; Ideate in order to generate options; Select among these options; Implement the idea in a workable physical form; and Evaluate it, if necessary returning to an earlier phase to improve it. The classical phase model is that of Wallas (1926). The Wallas (1926) model is more sophisticated than a small-step, incremental approach. Of central importance for the present discussion is that it sees the differences between phases in the production of a creative product as not simply quantitative (for instance, step-by-step increases in amount of knowledge), but as qualitative (involving different kinds of operation). Initially, Wallas (1926) too suggested that there were seven phases: Encounter (a problem or challenge is identified); Preparation (information is gathered); Concentration (an effort is made to solve the problem); Incubation (ideas churn in the person’s head); Illumination (what seems to be a solution becomes apparent); Verification (the individual checks out the apparent solution); and Persuasion (the individual attempts to convince others that the product really does solve the problem). Nowadays, in modern discussions of creativity the Wallas model is usually reduced to four phases: Preparation, Incubation, Illumination, and Verification. This may well be appropriate for the first part of the process, the production of effective novelty (i.e. creativity). However, a phase model that goes beyond mere production and encompasses introduction into a functioning system (i.e. a model of innovation) requires a seven-phase model. At the very beginning Wallas’s phase of Preparation must be subdivided into Preparation (familiarity with a field is developed — it is impossible to generate effective novelty in a field about which you know nothing, except perhaps through a blind guess and lucky fluke) and Activation (dissatisfaction with the status quo: problem awareness emerges). After Illumination and Verification, innovation requires making the result of the creative process to other people (often customers), i.e. Communication, and acceptance by the customers (Validation). Brown (1989) reviewed the extensive modern discussion of the importance for creativity of becoming aware of problems (i.e. what we call Activation), starting with Guilford’s (1950) emphasis on ‘sensitivity to problems’. Einstein (see Miller, 1992) described how his recognition that existing theories of thermodynamics were inadequate motivated him to develop the special theory of relativity and then the general theory. He continued to be dissatisfied with his own theory, and worked 266


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on it for much of the rest of his life. Edison was never satisfied with his invention of the incandescent light bulb, and over the course of time took out more than 100 patents on improvements to it. Mumford and Moertl (2003) described a case study of innovation in management practice, and concluded that innovation was activated by ‘intense dissatisfaction’ (p. 262) with the status quo. It is this recognition that there is a problem and a resulting urge to do something about it that may be called ‘Activation’. However, problem finding/recognition/awareness does not come from nowhere: you cannot see problems in, and be dissatisfied with, something that you do not know exists. In fact, the Canadian Intellectual Property Office reported (2007) that 90 % of new patents are improvements of existing knowledge. Cropley (2006) listed a number of creativity researchers who all give a prominent place to existing knowledge in creativity (e.g. Albert, Amabile, Campbell, Chi, Feldhusen, Gardner, Gruber, Mednick, Simonton, Wallas, and Weisberg). As Louis Pasteur, one of the celebrated fathers of vaccination, put it in a frequently cited aphorism he uttered in a lecture in 1854 (Peterson, 1954, p. 473): ‘Chance favours only the prepared mind.’ Thus, the whole process commences with Preparation. Preparation involves, in the first instance, acquisition of general knowledge of an area. This does not mean targeted and focused collection of information relevant to an already defined task, but the general process of gaining the knowledge and skills that form the basis of the potential for seeing problems. However, more is required: a problem can only be refined and applied (exploited) in a focused, goal-oriented way through the application of specific knowledge. The acquisition of specific knowledge is the second element of Preparation. It is a prerequisite for the later processes of problem finding, solution building, evaluation of candidate solutions, etc. Simonton (2003) draws attention to contrasting views on the role that preparation, in the form of education and training, plays in relation to creativity. He contrasts Csikszentmihalyi’s (1990) findings that new ideas in creative individuals arise from a ‘large set of well-developed skills and a rich body of domain knowledge’, in other words, a high degree of preparation, with Weisberg’s (2003) findings suggesting that this relationship is moderated by factors such as motivation. Simonton (2003) further highlights the fact that preparation and its role in creativity may be influenced by the focus of the activity. There is evidence, for example Hudson (1966), Schaefer and Anastasi (1968) and Simonton (1984), that scientific creativity may benefit more from preparatory activities, such as education and training, compared to artistic creativity. 267


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It can be argued that innovation in a business context, focused on the ‘embodiment, combination or synthesis of knowledge in original, relevant, valued new products, processes or services’ (Luecke and Katz, 2003) is most closely aligned to scientific creativity in its goals. Therefore preparation plays a critical role in enhancing creativity, which in turn leads to more effective innovation processes. It should be borne in mind, however, that knowledge can be a two-edged sword. Although this paper has just argued that it is necessary for innovation, as Gardner (1993) pointed out, there may be ‘tension between creativity and expertise’: the pre-existing knowledge of an expert can channel information processing into a narrow range of approaches — possibly without the person concerned being aware of this — and thus limit the novelty of what is produced via divergent thinking, or even block generation of novelty altogether. Research (e.g. Ericsson and Smith, 1991, Root-Bernstein, Bernstein, and Garnier, 1993) has looked at this interesting problem: although working successfully in an area over a long period of time (i.e. becoming an expert) can provide a knowledge base of both the subject matter and the organisation, it can also produce a kind of tunnel vision that narrows thinking and restricts it to the conventional. Thus, despite possessing the knowledge base that is required for generating effective novelty, knowledgeable people can actually inhibit it. To be creativity-fostering, they must not only know the facts, but also be capable of breaking away from them and seeing them in a fresh light. Preparation and Activation occur at the front end of the process of innovation. Turning to the other end of the process, Dasgupta (2004, p. 406) summarised the need for Communication very aptly: to be judged innovative, novelty must reach a sufficient state of maturity or completeness to be ‘manifested publicly.’ Of course, communication involves very different tools, skills, and products in different fields such as physics and art, on the one hand, or business, on the other. In the case of business, communication involves marketing novelty. As Csikszentmihalyi (e.g. 1999) has stated strongly, novelty (in whatever form it is manifested) only achieves the status of being regarded as creative when it is judged by external authorities (such as customers) to involve effective surprise. In other words, not only is Communication necessary, but the approval of those to whom the novelty is communicated. To put it bluntly, an innovation such as a new process or product needs to be accepted by customers, regardless of any other virtues it has, before it can be regarded as successful. We call this final step ‘Validation.’

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Wallas’s phase of ‘Incubation’ is also problematic. It seems intuitively clear that innovation requires processing of information. However, in reviewing a number of relevant studies Howe, McWilliam and Cross (2005) showed that many researchers deny that this involves ideas churning around with no apparent order or sequence until something good suddenly pops up, as a label like ‘Incubation’ implies. Howe, McWilliam and Cross emphasised the importance of heuristic processes such as setbreaking or construction of neural networks. Indeed, this objection was raised early by Vinacke (1953). Simonton (2007, p. 329) contrasted ‘Darwinian’ or non-monotonic processes (blind variation and selective retention leading to sudden jumps) with monotonic processes (step-by-step improvement based on, for instance, systematic and sequential application of expertise to a series of intermediate products, each of which is closer to the final product than the previous one). The purpose here, however, is not to define the precise nature of generation of effective novelty, but to emphasise that some kind of mental review of information (however this occurs) is one element of the process. It is possible to label this phase ‘Generation’, which can be used to refer to both non-monotonic and monotonic processes, i.e. it is more general than Incubation in Wallas’s sense. An Expanded Phase Model of the process of generation of effective novelty, drawing together the elements discussed in this section, is shown in Figure 2. It would be possible to consider only the phases up to but not including Communication. However, this would not involve innovation, for which the final two phases are essential, but only the novelty production component of the total process (i.e. creativity only).

A social/psychological phase model of innovation Drawing together the threads of business models of innovation with the social/psychological dimensions of creativity leads us to propose a more highly differentiated, and therefore more diagnostically useful, social/psychological model of innovation. Figure 2 started by linking the phases of invention/creativity with those necessary for exploitation of the creativity, for instance by emphasising acceptance of a novel product in the market place in the phase of Validation.

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Figure 2: The Expanded Phase Model of the Innovation Process

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The Social/Psychological Phase Model of Innovation can now be mapped against a typical business model (Luecke and Katz, 2003). Figure 3 illustrates the seven phases suggested by the Expanded Phase Model (Figure 2), the interaction of the four social/ psychological dimensions (the four Ps) with each phase, and a mapping to a typical business model. Unlike the business model, the social/psychological phase model recognises the changing, and often paradoxical psychological dimensions of innovation that must be understood and fostered for successful innovation to take place.

Figure 3: The Social/Psychological Model mapped to a Business Model

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Using the social/psychological phase model of innovation The value to an organisation of a model of the innovation process is not simply its role as a description of the process. Managers require a model that will enable them to translate description into action. A successful model needs to provide guidance on how the process of innovation can be optimised to yield the best possible outcomes. The Social/Psychological Phase Model of Innovation achieves this by drawing on the more detailed representation of innovation encapsulated in the seven phases of the Expanded Phase Model of the Innovation Process (Figure 2). The paradoxical social/psychological factors (Table 1) that operate in each phase of the process can be mapped onto this framework. This mapping highlights the different, and often contradictory, social-psychological dimensions that influence actors during the innovation process. Together, these elements therefore describe the innovation process in social/psychological terms, namely: (a) what the actors in the innovation process DO (Process) in each phase; (b) what they THINK and FEEL (Person) in each phase; (c) what they generate at each phase (Product); and (d) how the organisational environment impacts on them (Press) in each phase. Table 2 offers a summary overview of the social/psychological model’s mapping of each phase (preparation, activation, etc.) of the innovation process onto the dimensions expressed in the four Ps (Process, Person, Product and Press). The dimension Person is expanded into three sub-dimensions (Motivation, Personal Properties and Feelings) to offer a more differentiated analysis. Table 2 illustrates the ideal constellation of social/psychological dimensions across the seven phases of the innovation process. It is important to note that this paper is not arguing that, in practice, the various phases are totally separate from each other, or that every successful innovation commences with a concrete and specifiable phase of Preparation, followed by Activation, and so on. In practice, for instance, the process may be broken off in one phase and later recommence part way through, let us say in the phase of generation. The output from one phase may lead not to an illumination but instead to, for instance, a restart of generation; the process may thus run in loops.

Conclusions At the theoretical level, the model presented here broadens and deepens the more traditional business-oriented models of innovation. In addition, it looks at apparently irrational elements of the process such as the fact that the very qualities that are a strength in a company are sometimes simultaneously a weakness (as the systems approach has shown but for which it offers no explanation). 272


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Preparation

Convergent

Mixed

Convergent v Divergent

Reactive v Proactive

Process

Motivation


Conserving

Routine

High

Conserving v Generative

Routine v Creative

High demand v Low demand

Feelings

Product

Press

Adaptive

Adaptive v Innovative

Personal Properties

Dimension

Phase Paradox

Low

Creative

Generative

Innovative

Proactive

Divergent

Activation

Low

Creative

Generative

Innovative

Proactive

Divergent

Generation

Low

Creative

Generative

Innovative

Proactive

Convergent

Illumination

High

Routine

Conserving

Adaptive

Mixed

Convergent

Verification

High

Routine

Conserving

Adaptive

Reactive

Mixed

Communication

Table 2: The social/psychological phase model of innovation — ideal constellation of paradoxical dimensions

High

Routine

Conserving

Adaptive

Reactive

Convergent

Validation


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The approach presented here also broadens the strictly rational, mechanistic approach of linear models by taking account of the vagaries of the human actors involved in innovation. The Social/Psychological Phase Model extends the usefulness of present analyses by recognising the role of ‘hot,’ non-cognitive human factors such as motivation and feelings. At a less theoretical and more practical level, the ideal constellation depicted in Table 2 offers differentiated suggestions for action. Above all, it shows that there is no simple ‘golden bullet’: For instance, managers who wish to promote innovation need to vary the amount and kind of pressure they exert according to the phase in the process of innovation which is currently active and the motives, personal properties and feelings of the people involved. On its own this is a platitude, but the idealised table suggests how to take account of these factors. For instance, a high level of pressure for rapid results is beneficial in early and late stages, but inhibitory in the middle phases. Managers should activate and support proactive motivation and generative feelings when they want to foster Activation and Generation, but facilitate reactive motivation and conserving feelings when Communication and Validation are of central importance. The model also provides a more person-centred vocabulary for discussing what is actually happening at any stage of the innovation process. The possibility of saying more precisely what is going on, what is needed, what should be changed, and so on, would be a considerable help in improving actions during the innovation process. At a more formal level, such discussions could be extended to form a more detailed and more explicitly differentiated diagnosis of creativity and innovation in organisations. Drawing on the combination of models and concepts, the Social/Psychological Phase Model of Innovation permits the following: (i) mapping of the current activities of an organisation onto the sequence of phases required for innovation; (ii) identification of the social-psychological dimensions that are favourable to innovation for any given phase; (iii) diagnosis of an organisation’s strengths and weaknesses in the innovation process; (iv) analysis and optimisation of activities to maximise the outcomes of each phase of innovation. These thoughts raise the possibility of a diagnostic instrument based on the Social/Psychological Phase Model which would offer a more formal and structured analysis. 274


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Leifer, R., McDermott, C., O’Connor, G., Peters, L., Rice, M. and Veryzer, R. (2000). Radical Innovation. Boston, MA: Harvard Business School Press. Lipman-Blumen, J. (1991). Individual and Organizational Achieving Styles: A Handbook for Researchers and Human Resource Professionals (4th edn). Claremont, CA: Achieving Styles Institute. Luecke, R. and Katz, R. (2003). Managing Creativity and Innovation. Boston, MA: Harvard Business School Press. Marinova, D. & Phillimore, J. (2003). Models of Innovation. In L. V. Shavinina (Ed.), International Handbook on Innovation, 44-53. Oxford: Elsevier Science. Miller, A. I. (1992). Scientific creativity: A comparative study of Henri Poincaré and Albert Einstein, Creativity Research Journal, 5, 385–418. Mumford, M. D. and Moertl, P. (2003). Cases of social innovation: Lessons from two innovations in the 20th Century, Creativity Research Journal, 13, 261-266. Nobel Foundation. (1967). Nobel lectures, Physics 1901-1927. Amsterdam: Elsevier. Osborn, A. F. (1953). Applied Imagination. New York: Scribner’s. Park, J. and Jang, K. (2005). Analysis of the actual scientific inquiries of physicists. Accessed from www. arxiv.org/abs/physics/0506191, on September 17, 2006. Peterson, H. (1954). (Ed.). A Treasury of the World’s Great Speeches. Danbury, CT: Grolier. Prindle, E. J. (1906). The art of inventing, Transactions of the American Institute for Engineering Education, 25, 519-547. Rhodes, H. (1961). An analysis of creativity, Phi Delta Kappan, 42, 305-310. Root-Bernstein, R. S., Bernstein, M. and Garnier, H. (1993). Identification of scientists making long-term high-impact contributions, with notes on their methods of working, Creativity Research Journal, 6, 329–343. Rossman, J. (1931). The Psychology of the Inventor: A Study of the Patentee. Washington: Inventors’ Publishing Company. Rothwell, R. and Zegveld, W. (1985). Reindustrialisation and Technology. Harlow, UK: Longman. Rothwell, R. (1994). Towards the fifth-generation innovation process, International Marketing Review, 11, no.1, 7-31. Schaefer, C. E. and Anastasi, A. (1968). A biographical inventory for identifying creativity in adolescent boys, Journal of Applied Psychology, 58, 42-48. Schumpeter, J. A. (1942). The Theory of Economic Development. Cambridge, MA: Harvard University Press. Simonton, D. K. (1984). Genius, Creativity, and Leadership: Historiometric Inquiries. Cambridge, MA: Harvard University Press. Simonton, D. K. (2003). Exceptional creativity across the lifespan. In L. V. Shavinina (Ed.), International Handbook on Innovation, 293-308. Oxford: Elsevier Science. 277


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Simonton, D. K. (2007). The creative process in Picasso’s Guernica sketches: Monotonic improvements versus nonmonotonic variants, Creativity Research Journal, 19, 329-344. Unsworth, K. L. (2001). Unpacking creativity, Academy of Management Review, 26, 286-297. Vinacke, W. E. (1953). The Psychology of Thinking. New York: McGraw Hill. Wallas, G. (1926). The Art of Thought. New York: Harcourt Brace. Weisberg, R. (2003). Case studies of innovation: Ordinary thinking, extraordinary outcomes. In L. V. Shavinina (Ed.), International Handbook on Innovation, 204247. Oxford: Elsevier Science.

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Creation in science, art and everyday life

18. Creation in science, art and everyday life: ideas on creativity and its varying conceptions

Yrjö-Paavo Häyrynen (University of Joensuu and Helsinki University)

Abstract A basic condition for ‘measuring’ creativity directly is the theoretical clarity of the concept, and that creativity as a facet of human activity is clearly separable from its cultural, historical and collaboratory context. The essay discusses theories of praxis and sociocultural context of behaviour, such as the work on the habitus, the field and human practices by Bourdieu, the thesis of creativity as an intrinsic part of action by Joas, revising the ideas of American pragmatists Dewey and Mead, and recent interpretations of the cultural historical theory of L. S. Vygotsky (e.g. Tulviste, Moran & John-Steiner, Clot). Creative action is seen as situation-bound, where the actor, the situation, and the activity milieu form an integrated whole. In new situations creative reactions of the actor emerge, based on accumulated and often pre-symbolic experiences of people and on the formation of the actor in a social field and its network of tacit rules. New knowledge is generated when internalising cultural commodities, the previous products of creativity, and transforming them in the inner work of the actor to new cultural products (Yaroshevskii, Lotman); a process stressing at least the role of broad general education in promoting shared creativity in a nation. The end chapters evaluate the sense of cross-national research on creativity in the European scope. A cultural comparison of creativity in miscellaneous European populations cannot simply be made with available test scales and without an adequate theoretical notion of what creativity is in the 279


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context of national civilizations. Thus, a study of European civil society could start with examining representations and experiences of creativity in its different subcultures. One phase could be analysis of how students and teachers rate the capacity of teaching in inspiring creativity. In general, creativity emerges to be a component related intrinsically to the actor, the milieu, the collaboratory networks, and a specific situation, in which it cannot be measured as a set of previously selected indicators. A qualitative approach toward cultural comparison looks more reasonable than a quantitative presentation of ‘national degrees of creativity.’

Introduction This essay asks whether creativity is actually a measurable entity or a ‘simple dimension’, in the light of newest theoretical discourse. It discusses in the first part some ‘praxis theories’ of creativity, such as the French sociologist Pierre Bourdieu’s eminent work on the habitus (the collection of the characteristic dispositions of the actor) and the social field resembling these dispositions, then the thesis of creativity of human action by the German researcher Hans Joas, revising the ideas of American pragmatists, and as as a third moment, some newest approaches of the famous semiotic and sociocultural theory of Vygotsky and the formation of human creative ability through activities (Tulviste, Lotman, Moran & John-Steiner, and Sawyer). Creative action is seen here as situation-bound, where preparedness for action and the milieu form an integrated whole in each period. In new situations creative reactions of the actors work as based one, accumulated experiences of people; new knowledge and new habits are generated when internalising cultural commodities and transforming them in the inner work of the actor. People create the social system with their ‘habitus’ but are results of this unfinished creation at the same time, which is a basic autoproductive, ‘autopoietic’ process of self-organising entities (Christian Fuchs). The conceptions on what creativity is and whether it can be taught in school have varied since the ideas of Plato, who explained creativity, in his dialog ‘Phaidros’, a charismatic phenomenon, coming to a cultivated citizen as an inspiration from Gods. The end chapters evaluate purposiveness of cross-national research on creativity and its possible gains and negative sides. Instead of a direct use of the test scales for creativity that are already available it would be better to construct instruments that best correspond to the notion of cultural creativity, relevant in an international comparison of different European nations and their variable subcultures. Also, a qualitative type of analysis of results should be considered as an alternative of heavy statistical procedures. The risk is that otherwise ’pre-given images’ of what ‘creativity’ is are readily embedded in the standard methods selected for a cross-cultural investigation. 280


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The study of European civil society could start with examining social representations and experiences of creativity in different cultures, using the methods and ideas presented by Moscovici, Mugny and Carugati. A conclusion is that as creativity is a many dimensional construct, a system in which different elements — the actor, the milieu, the period — tightly cooperate, it cannot be studied as a bundle of separate indicators or variables (cf. Danziger 1996, on creativity as a historically changing whole). Instead, a qualitative comparison of several cultures appears quite possible. The primary task of the educational system is to increase people’s sensitivity to their genuine experiences and offer general education in which all will adopt the earlier products of creativity that lead to creation of the new.

Prologue: naissance of psyche and creativity It is not possible to reach the borders of psyche, even if you follow every possible road: so deep is its Logos (Heraclites). The Russian psychologist F. T. Mikhailov, a sharp thinker of the sociocultural school of thought, has written a book The Riddle of the Self (1980), in which he analyses how human self-hood arises as culture enters the brain and connects the individual with an enormous potential to work and with different historical and current resources of thinking. He concludes this inspiring treatise with a description of how four severely handicapped people could gradually develop self-hood and become participants in our common cultural history. This study concerned the hardest possible experiment of nature with humans: people born deaf-blind. Four natively deaf-blind people were first taught to use objects functionally in a special Moscow clinic (spoons, toys, bowls, showers, keys, etc.), and then to name these objects by means of a spelling system using the faculty of their sense of touch. The teaching followed the Vygotskian principles of sign-mediated activities, through which children learn in the everyday life to control things, symbols, and instruments, and become persons of their community. The idea was that cultural sign-mediation and participation in the social discourse generates in people self-hood and makes them able to discuss, create, and produce new. Olga Skorokhodova, one of the rehabilitated native deafblind, later earned a Master’s Degree in Psychology at Moscow University. She illustrates vividly how this ‘second birth’ of her person was achieved: Now even in the most complex situations I am able to be my own critic because a sum total of historically completed actions live in me, unfolded in the language of my people. Besides my friends and teachers I have had interlocutors — in those who through many centuries have dealt with the most difficult riddles of existence. Together with them, I take part in the discovery of new ideas. Their thoughts are born again in my mind. Different voices of different periods and cultures come to life in my own existence (Skorokhodova cit. by Mikhailov, 1980, 264–66). 281


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This passage is a splendid example of the power of commonly owned cultural selfhood, where culture literally enters the neural system of humans and starts to work through their brains and bodies; culture becomes an inner creative activity of the individual (cf. also Vygotski 2002, 61, Yves Clot 2002, 59). As Clot interprets the Vygotskian thinking, this culturally produced consciousness can be conceived as a liaison of people’s personal experiences forming their identity and leading to psychic labour of civilisation, mediated through the individual’s objectified (analysed), conscious and joint experiences. Psychologist Olga Skorokhodova accents in her text the ‘interplay of different voices of different periods and cultures,’ coming to life in her own self; in her awakened consciousness. This interplay between living and virtual personalities of different periods and cultures forms — to use a statement of Bourdieu — a truly selfish, social gene or the DNA of the tissue of collective creativity, repeating and changing the social patterns and even material nature, and using people as if they were its mediating tools. This social and cultural DNA is not necessarily tied to certain period or to a definite place, but is an overall generator of change and patterns the new environment

Creativity — an inbuilt element of action The idea to study creativity in the European scope and as a macro-structure, including the cultures of about 20 million immigrants and tens of minority populations, is really a brave enterprise, whoever invented it. But conditions of this kind of study, especially if it is conceived of as a large-scale measurement or comparison, are naturally rather hard. One task is to build a more comprehensive picture of creativity as an overall human potential. From this angle, it is possible to understand creativity as people’s shared inventive movement, using the cooperative potential of language as well as of prelinguistic communication, and the respective modes of thinking. The utmost tendency of creativity is changing the circumstances in which people live, using their accumulated experiences and the varying situations of their milieu as elements of creative activity. It does not seem reasonable to divide human actions unconditionally into the creative and the non-creative; nor to estimate creativity of individuals and cultures as a plain dimension, when all people anyway possess a capacity for continuous creation in their specific environment. Creativity could be seen an intrinsic part of human action, a condition of the survival or individuals and cultures, and not any issue of an extraordinary activity with its own specific ‘laws’ as the German sociologist Hans Joas (1996/2001) emphasises in his recent study of creative action and its European metaphors. A paradoxical fact is that not only individuals but also the products of creativity take part in the joint processes of creativity. An eternal problem of the psychology of 282


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creativity is, thus, to comprehend that the universal products of human creation have their own right of existence and they are no longer psychological or individualistic. This is the point of view that the Russian historian of psychology M. G. Yaroshevskii (1985) underscores in his works on creativity. An artistic creation, such as the sculpture of David by Michelangelo, the Jupiter Symphony of Mozart, or Hamlet by William Shakespeare, is like an arrow in time or a cultural missile, producing in every period new meanings, when it passes through different historical eras and meets new generations and new populations. So, prior works of creativity generate permanently new ideas and ways of life, on the basis of their complex historical existence. What is more, Yaroshevskii suggests that the products of creative action no longer reflect the particular individual traits of their creators (or do so in a ‘coded form’ alone), as they are assimilated into universal culture and to common social praxis. One understands easily that a nuclear reactor does not reflect the mentality or the subconscious images of its inventor, but is more liable to figure out that this kind of personal features, images, and emotions could be present in the artistic creations, music, the fine art, and poetry, disregarding how much they reflect their period and the collectively invented styles, may these be ‘academic’ or ‘revolutionary’. However this may be, an attempt to correlate the facets of different works of art, e.g. the styles of painting or composing during the epoch of Baroque, with the personality traits of individual creators, disregarding the historical field and context in which they live and in which they are connectedly intermingled, remains inevitably an hopeless enterprise. To understand the whole collective field and the growth of its creativity one may examine Bourdieu’s (1992) vast analysis of historical genesis and maintenance of the ‘field of literature’, which was the great achievement of the French writers of the nineteenth century, especially Gustave Flaubert and all other ‘agents’ building and inventing this new entity with its own rules and new definitions of creativity. Yaroshevskii refers to S. L. Rubinstein’s definition of creativity (1976), which underlines creation of new knowledge, not only within an individual life-course but also as a contribution to the universal phylogeny of knowledge.

A macro-psychological point of view This essay examines creativeness as connected with social macro-structures and cultural phenomena, a point of view that I defined in a 1972 editorial of the Finnish Journal of Psychology as the new macro-psychological approach. The idea of this approach was investigating how psychic phenomena are intrinsically tied to social formations and are inherent parts of these formations. Some ideas of macro-psychology are tightly related to philosophical psychology, a branch concerned with the return to thinking and explanation of eternal psychological problems. Another familiar ingredi283


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ent of macro-psychology is the historically oriented psychology and sociology, which still is located in the periphery of human studies. But how to define creativity, this important component of future social change? Can that be done with measuring sticks, as guided by some everyday conceptions or tautological designations of ‘creativity’? Imagination has been about 2 500 years, a cherished but debatable construct among scholars, but the notion of imagination has nevertheless opened the space for the current notion of human creativity. However, the idea of creativity or imagination as producing something new dates only back to the epoch of Renaissance, before which the scholastic thought and gothic architecture tried to produce everything on the rule, permitting variations only in micro-structures depending on the skill and handicraft of the artisans of mental or physical work. Thus, in this essay into creativity, the starting point is that creativity forms an inherent part of human action and history, and is not a specific ‘ingenious activity’, allotted only to few (see also Joas 1996/2002 below). It is the leading principle here that the notion of creativity cannot be measured if there is something unclear in that concept, or if it happens to be a ‘systemic notion’, containing the actor, the field and the period as inseparable elements, as an integrated whole another leading principle in this examination is that creativity is basically a shared and collaboratory social and psychological phenomenon. The works of Vygotsky (2002), John-Steiner (2000), and Sawyer (2003) all illuminate the emergence of the new in collaboratory processes, in conversation, cooperative efforts, in creative interaction of intellectual actors, or — in the mother-child communication. This collaboratory facet of creativity, understanding it as an auto-productive activity, displays a chance for developing creativity in pedagogic and group activities and in other types of joint practical projects. Vera JohnSteiner (2000) has insightfully analysed the interactions and discussions between creative personalities such as Albert Einstein and Niels Bohr, Marie and Pierre Curie, Pablo Picasso and Georges Braque, or Igor Stravinsky and George Balanchine, showing how this social interaction in itself produces significant insights. David Henry Feldman writes in the foreword of this book that ‘even when considering achievements typically believed to be individually created such as Einstein’s theory of relativity or Darwin’s theory of evolution, John-Steiner shows unmistakable signs of collaboration, joint effort, and social support necessary to worthwhile human endeavours’ (Feldman 2002, xi). If the purpose is to analyse whether ‘creativity’ is measurable with methods that are already there, I believe that a careful theoretic analysis of the concept and its genesis is necessary, even before pilot attempts of a cross-cultural study.

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The inseparable dynamic of field and creative project Pierre Bourdieu (1966) refers to the painter Vassili Kandinski who said that ‘it is the inner necessity which drives the artist to create the new’ and, sometimes, to transform the existing ‘rules of creativity’ (as was actually done during the Impressionist Revolution in France in the 19th century). The creative project of an artist or scholar is a compromise between the his/her inner necessity or ‘creative obsession’, as it is also sometimes called, and the demands of administrative authorities, commercial institutions, or the public opinion, which all demand a higher or lesser conformity, resembling the conventional taste and the mode of harmless description of things and people (Bourdieu op. cit.). Bourdieu refers to the French poet Paul Valéry, who said that it is the immunity toward these outer demands that leads authors to write as they think and feel, instead of writing what the audience claims. In any rate, outer social pressures are always mirrored in the inner dynamics of creative work. The result may be shared defences of thinking in an intellectual community, defence mechanisms that restrict elaboration and infiltration of new unpopular ideas (see also Häyrynen, 1980). These collective constraints of creativity can be visible even in the academic world. In question might be a defensive attitude toward competitive new ideas that are declared not fulfilling the norms of the academic field, an exaggerated formalism, a naïve desire for defining everything logically and with tautology, resentment, or heightened control of what younger researchers do. Creative projects are always loaded with social, moral, and intellectual tensions and their agents or actors have to decide, in the final analysis, to what causes they are committed. It is important to see that our own cultural consciousness and its fundamental dynamics depend drastically on how we in point of fact conceive of the other cultures, or other creative projects, and in which way we employ the social presence of a strange Other in our intellectual enterprises. It is relevant to mention what the excellent social psychologist G. H. Mead says about the social and shared nature of creative experiences, not permitting a reduction of the dynamics of creativity to an abstract system of ‘universal and timeless laws’: ‘— I shall claim that the analysis of experimental science, including experimental psychology, never operates in a mind or an experience that is not social, and by the term ‘social’ I imply that in the thought of the scientist the supposition of his mind and his self always involves other minds and selves as presuppositions — the dividend that I wish to see declared on this social nature of mind and the self is the equal immediacy that may attach to the assimilation of others’ experience with that of our own …’ (Mead, 1938, 53).

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Mead claims that in all scientific work we inevitably utilise the attitude of the other, which is involved in addressing ourselves and in attending to the other social actors. ‘Our World’ indeed means the assimilated experience of all people, it is established in the early phases when people are contacting each others. This common experience unmistakably comes before the ‘individualised versions’ of reality, so that even our emotions appear to be first shared and collective, and individualised only afterwards (the Finnish physiological psychologist Timo Järvilehto launched this proposition about emotions in 1996). Thus, in creativity we use a mass of experiences caused by earlier creativity and the attitudes of our co-citizens, as communicated verbally and non-verbally. To recapitulate: creativity occurs in the context of social and cultural macrostructures, and people are not only ‘related’ to these structures and do not merely ‘interact’ with them but are intrinsic components of these social and cultural structures. Creativity is a continuous discovery of new ways in which humans examine and utilise their symbolic and physical environment. The environment is structured for our perception on the basis of the practical values and utility of things and matters, as the German philosopher Martin Heidegger presents (cf. Dreyfus & Dreyfus, 1986). In our society the function of a wide general education would evidently be transmitting the creative cultural potential to the cohorts of new people, so it is one of the most important inventions of the collective creative movement.

European metaphors and American solutions of creativity The German expert of pragmatist sociology and psychology Hans Joas opens a significant way to the analysis of creativity of action in his work Kreativität des Handels (1996, available also in French and English, Joas 2001). Joas starts with an inclusive study of metaphors of creativity in the European thought. The main metaphors and their inventors have been, from the 18th century. They comprise expression as defined by Johann Gottfried von Herder (1744–1808), who underlined the emotional functions of language, revolution and production in the works of the young Karl Marx (1818–83), the life in itself by Friedrich Nietzsche (1841–1900) and other romantic philosophers, and élan vital by Henri Bergson (1859–1941); all figures in the European history who have dealt with human creativeness in one way or the other. Yet, it should be mentioned that Nietzsche’s programme for creativity did not count on good problem-solving, but rather on creating the problems and destructing habitual practices, a project that still has its capacity to generate movement. The only aspect of the central metaphors of creativity Joas seems to omit is imagination, which James Engell describes, in his outstanding work, as the key concept of the thinkers of Enlightenment and Romanticism. In fact, ‘Imagination’ corresponded to the idea of creativity before creativity was discovered (Engell, 1981). 286


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After a wide discussion on various concepts of creativity in action, Hans Joas decides that the best working idea of creativity can be found amongst the American Pragmatism: thinkers such as John Dewey (1858–1952) and G. H. Mead (1863–1931), prominent scholars both in the educational, philosophical and psychological domains. He found in the thoughts of these scholars an explanation of human action that is fundamentally creative, in the sense that it is continuously oriented towards different problems. The pragmatic philosophers represented no metaphor for creativity since seeing it basically as problem-solving. Still they stressed the aesthetic, motional and social aspects of comprehension more than its rational elements. People act with routines, adopted habits, mostly without conscious reflection, as long as these routines work. In a totally new situation a process of contemplation is needed, which some scholars identify as objectifying of the situation of action. Dewey assumed that people are driven toward experiencing, touching objects, smelling, designing, listening, and talking to other people by a sympathetic interest, a bodily scheme, connecting the social and the aesthetic, and stronger than a mere intellectual need: ‘All persons have a natural desire — akin to curiosity — for a widening of their range of acquaintance with persons and things … this sympathetic interest provides the medium for carrying and binding together what would otherwise be a multitude of items, diverse, disconnected, and of no intellectual use’ (Dewey, 1910, p. 189). This does not mean that all people are at all times ‘creative’, but a continuous habit of exploration and a social and aesthetic orientation gives all people the potential to create and survive every time when the outer situation asks for it. It is the situation, not primarily habits or impulses, or even the personal properties, which is the strong centre of creative action. Creativity is, first of all, composed of active responses toward the challenges of time, and an opposite of an apathetic attitude toward the world. As Vygotsky said: ‘The most important property of creativity is courage.’

A room full of angels — truth of pre-symbolic and practical knowledge in creation ‘What are the demands of scientific imagination? Is it any different from trying to imagine that the room is full of invisible angels? No, it is not like imagining invisible angels … whatever we are allowed to imagine in science must be consistent with everything else we know … the problem of creating something which is new, but which is consistent with everything which has been seen before, is one of extreme difficulty,’ Physicist Richard Feynman (cit. R. D. Tweney, 1996, p. 164). 287


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Many aspects of scientific, artistic and technological creativity are related to presymbolic and non-spoken meanings, sometimes to everyday life experiences, which are not usually comprehended as elements of High Creativity. Tweney says on this: ‘In particular, I suggest that any account that tries to bridge the gap between the physical world (reality) and the finished conceptual world of scientific thought (imagined reality) can do so only if attention is paid to the nature of the pre-symbolic events that mediate the relation between the two’, (1996, 163). When interpreting a new phenomenon, scientists and artists utilise everything they have learned in their life, from childhood memories to experiences with lifts, social situations in one’s laboratory, or recollections of an exceptional phenomenon of light. Faraday’s diary, which Tweney screened carefully, is in its loose descriptions of the scientist’s impressions and sensorimotor experiences an example of non-conceptual processes, which guide the early phases of analysis, if placed in a new context. Tweney suggests that these pre-symbolic and practical processes are constituents of the products of imagination (cf. also Stehr, 2001). Another conclusion is that scientific knowledge is often produced with non-scientific rhetoric or thinking. If creativity is psychologically intermingled with several codes of thinking and expression, and utilises both conceptual and pre-symbolic elements learned in the early childhood, it seems useless to try to measure it as only one and clearly arranged dimension.

Is measuring creativity conceivable and what is its gain? Research on creativity with comparative methods and on a European scale is surely an impressive project in which a new application of statistical methods may offer interesting possibilities. However, it may be difficult to observe the tacit hypotheses that guide the use of statistics in various research enterprises outside of the original problem sphere, as Sally Stares noted when discussing the problems of the world poverty statistics (2009). The scientific theories are always in play with some outer social factors of research. whether overtly or tacitly; ‘— researchers cannot escape drawing on the socially constructed knowledge about the world, which comprises scripts, schemes and heuristics that they use every day to navigate a path through it’ (Stares 2009, 42). She concludes that the use of statistics is always a more or less political matter. Gigerenzer applies the idea of socially constructed preconceptions to psychology, indicating that universal technological and logical changes offer new models for psychology, even if they do not have a theoretical connection with the phenomena we study (Gigerenzer, 2001); thus, available methods and tools shape the theoretical concepts tacitly. Gigerenzer remarks that despite prayers that were backed up by 288


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statistics, some 90 years of factor analysing and correlating IQ tests has not noticeably increased our understanding of the mechanisms of human intelligence: ’I fear that the proposal to look for correlations between some tests for social complexity, social skill, and individual intelligence will be doomed to the same failure’ (Gigerenzer op. cit.). The main argument is that available techniques and tools cannot compensate a lack of conceptual sharpness in empirical investigations, including the study of creativity. Despite many interesting findings the conclusion appears to be that no direct approach of measuring creativity or increasing it with training programmes has proved unambiguous (e. g. J. Baer, 1993; R. K. Sawyer 2008, 44–45, 54–55, 300–301). One problem is that justifying something as creativity belongs in our society to the relatively autonomous fields of cultural and scientific production, and cannot be defined as a mere psychological variable by psychologists. A comparative study of different forms of creativity among different European countries is not only a psychological but also a cultural sociological, if not a philosophical question.

The sociocultural theory and creative appropriation of culture ‘Behaviour is never a combat which will calm down’ (L. S. Vygotski). The early Russian psychologist L. S. Vygotski saw human consciousness as an instrument of the cultural labour of the individual (Vygotski, 2002): culture enters the brain of the individual and starts to work in the human body. Various aspects of the sociocultural theory of Lev Vygotsky, as related to research into creativity, have been recently discussed by Peeter Tulviste (2001), Yves Clot (2002), Seana Moran and Vera John-Steiner (2003), and Keith Sawyer (2008), who all have fresh ideas about the sociocultural and collaboratory basis of creativity. These approaches draw attention to the notion of goal-directed activity in explaining people being connected with formative cultural influences. In using and naming the cultural and social instruments people internalise the key meanings embedded in their cultural and physical environment. When coping with their milieu, transforming it, and perceiving it from different points of view people actually ‘learn creativity’. Seana Moran and Vera John-Steiner quote a passage of Vygotsky’s work The Problem Age: ‘Development never ends its creative work.’ They stress the basically creative nature of internalisation or appropriation of cultural tools, the process that we already considered in discussing the effect of the earlier products of creativity on the creative process: ’Internationalisation is not just coping but rather a transformation or reorganisation of incoming information and mental structures based on the individual’s characteristics and existing knowledge’ (Moran & John-Steiner, 2003, p. 63). I suggest that the most important factor in persuading people to learn ‘large-scale creativity’ 289


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would be to support the processes, in which the new generations of people acquire civilisation and internalise the earlier products of creativity of the mankind. This may simply mean an activating, rich and broad general education to all, as a basis of professional training and experience. Tulviste (2001), in particular, stresses that it is activity that mediates the relationship between people and culture. As a result, his basic formula is the triad subject → activity → culture, which can equally be read in the opposite direction: culture → activity → individual. The cognitive strategies people use in resolving their actual problems are not inherent potentials of the brain nor universal features of human mind, but their thinking corresponds to the array of activities that their culture exposes and demands. Tulviste refers to Vygotsky’s statement that as words are related to language, the meanings behind the words are anchored in practice that means in all human activities. He discusses thoroughly the difference between ‘modern’ and ‘traditional cultures’, a separation that he does not see very clear and justifiable though. ‘Modernity’ usually refers to cultures in which thinking is based on theoretical notions and linear logic, as mediated by the school teaching. A decisive factor is, nevertheless, the range of new activities that science-based, urbanised and technical cultures offer, as compared to ‘traditional’ cultures with collecting or agrarian economy. ‘Hunting people think about the moon differently from people in a culture that has invented astronomy’, Tulviste notifies. What is more, he concludes that thinking in ‘modern’ cultures is still more diverse, more heterogeneous, than we usually think. In addition to scientific thinking it (the modern culture) includes other types of verbal thinking, whose study and purposeful development have received too little attention thus far (Tulviste, op, cit., 183). What makes thinking in problem situations so diverse, even among modern cultures, is that, in addition to conceptual thinking, people in these cultures — even the scientific experts — use a variety of verbal and non-verbal codes, vernaculars, and even pre-symbolic patterns learned in their childhood, as Tweney stressed above. These codes or ‘languages’ of situational thinking are not determined in advance, but they are selected on the basis of the character of the dilemma or the predicament in question. Tulviste refers to the absorbing idea of the influential Russian expert of semiotic Juri Lotman, from the University of Tartu in Estonia, who suggests that in creative thinking people always use several codes to achieve the ends, and it is exactly the incompatibility of these codes of thinking that permits a new thinking to emerge: ‘… Creativity, the production of something new in culture and the individual, is possible only because there is a translation of knowledge from one language 290


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of representation to another. Due to existing differences between languages, the translation cannot in principle be completely adequate, and due to this, in the process of translation new knowledge is generated. No thinking apparatus can have only a single structure and be monolingual; it must necessarily include in it semiotic formations which make use of different languages and are mutually not translatable’ (B. A. Uspenskij & Yu. M. Lotman in 1973, cit. by Tulviste, 2002, p. 80). Furthermore, Lotman emphasises that metaphors and other modes of analogous thinking and expression are not only applied in artistic but also in scientific thinking, in which a less conventional ‘rhetoric’ and a more modest logic always alternate (cf. also Gruber, 1996): ‘Rhetoric is proper to scientific consciousness to the same extent as to the artistic. In the area of scientific consciousness, two spheres can be distinguished. The first, the rhetorical, is the area of approximation, analogy and simulation. This is the sphere promoting new ideas, establishing new postulates — that formerly seemed absurd. The second is the logical. Here the new ideas are subjected to confirmation, the conclusions for owing from them are analysed and internal contradictions in evidence and arguments are eliminated. The first, the ‘Faustian’ sphere of scientific thinking comprises an integral part of investigation’ (Juri Lotman in The phenomenon of culture, University of Tartu 1978 (in Russian), cit. by Tulviste, p. 81). This exploration illuminates vividly the processes generating new knowledge and explains why the practical activities are not translatable to formal ‘academic’ language, or even resist this translation analysis similarly supports to the ideas of Howard Gruber (1996), who has carefully studied how the eminent researcher of intelligence, Jean Piaget, utilised a lot of various metaphors in developing his theoretical ideas: writing, a circle of sciences, toys, songs, an adolescent boy, etc. Bourdieu remarks: ‘it is just this incompatibility of different languages that creates novel wisdom.’ Another corollary concerns the social representations of creativity and their possible heterogeneity: it is not expectable that in all countries which represent a ‘modern culture’ the representations of creativity would be homogeneous and refer to the same meanings. But one may ask if current university and school teaching omits totally the ‘Faustian’ aspect of thinking, which means that the process of teaching is repeating and arranging available knowledge but not inspiring new ideas, passions, or questions.

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The social representations of creativity I shall now turn to discuss some research initiatives, which may permit the study of certain aspects of creativity among different European subcultures. First of all, has the multitude of the population the luck to utilise the full spectrum of cultural commodities, which have been created since the first Paleolithic people, invented fire, tools, decorations, and shelter against the weather and animals (see Steiner, 2001, who submits a similar question)? How people interpret creativity in different European countries, have they biased conceptions of each other’s creativeness, and do they believe that school or university stimulate a capacity for creativity? Research on social representations has been initiated by Serge Moscovici and his collectively oriented social psychology in France (2001). Moscovici suggests that the subjects do not perceive a social object directly and individually, but are reflecting first the official and unofficial discussion around that matter, for instance ‘creativity’ as it emerges in everyday discussion, in different media, or in the scientific discourse. They can decide, then, from which part of this cauldron of discussion they will search their personal opinion. Moscovici defines a triadic model of subject–collective discourse– object, instead of the standard dyadic model of psychology, the standard subject– object scheme. Many concepts such as ‘creativity’ or ‘intelligence’ shuttle between the everyday talk and scholarly discussion, and bear traces of the former discussion when entering, for example, from everyday public treatment into scientific articulation. Nonetheless, these conceptions affect fundamentally the aims of educational or cultural policy, as concerns producing of the general preparedness for creativity. If one wishes to analyse the patterns of creativity in present European countries, the first step could be to discover what teachers and students actually understand by ‘creativity’ in different university and school systems, vocational or general. Someone on the web log of the EU conference on Measurement of Creativity suggested that we should not only analyse how people in certain cultures rate their own creativity, but also how they interpret each other’s ‘creativity’: the expressions of creativity of their Other (cf. G. H. Mead, above). This is a sound proposal. It could result in an exploratory study of social representations of creativity in different European cultures; or what personal experiences people genuinely consider creative. In the background of social representations are the public discourse of creativity and the scope of social meanings in which the discourse of creativity moves. As Michel Foucault has stated the historical period determines the architecture and the sediments of knowledge people dwell in and how they lance the problems on which they disagree or agree (cf. Dreyfus & Rabinow, 1983). Individual experiences of creativity may include sensorimotor impressions, emotional 292


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states of mind, and activities that have been fulfilled and have resulted in new experiences. In our life-course study (reported later) we asked academic people to freely describe in which past activities they feel to have been ‘creative’. It may be symptomatic that only two thirds of them responded to this open-ended question, and a still smaller proportion were able to describe a concrete activity, such as presenting a doctoral dissertation, building one’s own house, preparing a sermon for a service, meeting foreign cultures, or artistic painting or publishing fine literature. Hannu Räty and his Finnish research group studied thoroughly what ‘intelligence’ means to students and school teachers. Later, the researcher studied the conception of academic ability, how it arranges the hierarchy of students in the school and how malleable students describe this property (Kärkkäinen & al., 2008). The method has been developed by Gabriel Mugny and Felice Carugati (1989) to cover dimensions of discourse around the conception of intelligence. Ruey-Yun Horng (1990), from National Chiao Tung University in Taiwan, has presented one of the earliest empirical studies of conceptions of creativity. In a collaborative project with the French psychologists we have recently collected a material on how the students of these countries describe ‘the intellectual’, and whom they nominate as ‘intellectuals’ of their national culture in Finland or France. S. B. F. Paletz & K. Peng (2008) reports a study of cross-cultural differences in the implicit theories of creativity, comparing American, Chinese and Japanese college students. They attach importance to biases that exist as the stereotypical notions on ‘western’ and ‘non-western’ creativity: culture is in this case is suggested as a factor in explaining the ‘economic backwardness’ of some countries. Their study is not directly concerned with the theory of social representation but stresses the importance of having a wider theory on cross-cultural factors of creativity. C. Chen et al. (2003) have done research on the differences between European American and Chinese children in drawing and evaluating geometric shapes. This study did not reinforce the conception about wide cultural variation in evaluating non-verbal creativity but is significant as indicating that representations can be also studied through pictorial codes. It can be expected that if all semantic dimensions of ‘creativity’ or ‘creative person’ are scanned, the variation would be unmistakably visible among different ethnic groups and professional communities. Notions such as ‘creativity’ or ‘intelligence’ shuttle between the everyday talk and scholarly discussion, and bear traces of the former discussion when entering, for example, from everyday public treatment into scientific articulation. A consequence may be that ‘creativity’ or ‘intelligence’ are not pure scholarly concepts after all. None the less, these conceptions — though not justified scientifically — affect interpretations of the aims of educational or cultural policy in various 293


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nations. The problem is that the ‘implicit theories of intelligence’ or of ‘creativity’ often attribute success and failure of students not necessarily to the teaching they receive but to the students themselves, their lacking ‘motivation’ or ‘talent’ factors of failure or their deficient cultivation. The matter seems to be similar with ‘creativity” — students who are described as creative have the strongest cultural capital, meaning they come from highly educated homes, and speak the ‘same language’ as the professors in the elite classes (Bourdieu & Passeron, 1964). This model holds good in those European countries that still cherish upper-class traditions. Anyway, the study of the social representations of creativity should cover all important key groups of the educational range in various nations. The ongoing study of what ‘giftedness’ means in various national types of education in different EU member countries might support this kind of novel project (EURYDICE). If the social representations of creativity are analysed among the university students, one should acknowledge that the field of students is composed differently as compared to the field’s artistic or scientific production or the commercial field. The field of students is made up of hidden rules of competitiveness, success and failure in examinations, gaining entrance to the desired institutions, and the social aspects of student life. This does not mean that students are indifferent towards a problemoriented and effervescent teaching, but their main activity is still to gain entrance and achieve a diploma and professional competence. This may also be the context of their representations of creativity; people never conserve a static array of adopted concepts but these mirror both their motivations and the circumstances in which they find themselves. Hence, the ideas about ‘creativity’ among currently unemployed workers or immigrants who find themselves in a strange environment are surely different from university professors or students of an elite school.

Conclusions: creation, discovery and the MP’s of innovation Creativity is a process, just as history and evolution are; it is not basically a dimension of performances or a shop that offers new commodities to a sophisticated audience. The empirical approach to creativity could resemble a historical analysis in some respects, as a study of how creative action is developed in communicative processes (cf. Sawyer, 2003, his experimentation on student actors who improvise in a dyadic discourse, leading to new and unexpected creative responses), It may be, however, that the sociological forms of creativity are not equally important in different subcultures of the member countries of European Union. 294


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The fact is that habitants of current European nations display fairly numerous subcultures, dissimilar in religion, language, political past and their historical roots. The huge proportion of immigrant population in western Europe adds to the diversity of these subcultures. In addition to the western model of modernisation, the cultures of present Europe represent traditions of Muslim and east-European multinational cultures, having probably their own interpretations of what creativity is and how it should be cultivated (cf. N. Göle, 2000). One should not imagine that the western model of modernisation is the only one, or the only valuable, or that its explanation of the development of the Self and creative consciousness is exceptional among all world cultures. In these circumstances, a qualitative cultural comparison of representations or experiences of creativity would be a wise solution of research in the European scope, at least as a pilot enterprise. I fear that a comparison of the ‘means’ or ‘degrees’ of national creativity along merely one scale would not offer much wisdom for making pedagogical or cultural political conclusions. These political arenas suffer from obvious ‘everydayness’ and confusion of the concept of ‘creativity’, and a result of an attractive discourse on creativity might be a more distinct and unbiased notion of creativity in these practical domains. In practice, different workable concepts of innovativeness and creativity exist. George Steiner submits in his salient work on ‘grammars of creation’ (2001) the idea that the task of science is invention and discovery but not creation, since the things it discovers are already there, I suppose that chances of testing and evaluating what is totally new do locate outside the standard psychological or sociological sphere. Quite interesting is A. H. Maslow’s division into two different kinds of creativity (Maslow 2000, Part III: Creativity and Innovation). These modes of creativity comprehend (i) generating something totally new and (ii) discovering new combinations of elements that already exist in the social sphere (or the Noosphere, as the Russian physicist Vernadski calls it). The French philosopher Cornelis Castoriadis defined a process of radical imagination, which is the process creating new institutions, ideas and modes of speech, and historically new models of society, being in itself a part of history (Castoriadis, 1996). The idea of imagination was already present in the philosophy of Aristotle and the way in which he defined the function of imagination (Aristotle, trans. 1986, 196–203, and see explanations by Lawson-Tancred 1986, 83–87). Castoriadis, himself a Greek by birth, suggests that the society of Athens — comprising its institutions, philosophy, political order, and the people of Athens — was created in its time in this way, through radical collective imagination, the thinkers inventing new language and new significations as well (the non-computable linguistic meanings that Castoriadis 295


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calls as the ‘magma’ of each civilisation, its tacit reservoir of new meanings). He believes that Aristotle was actually defining imagination as a procedure of gaining new knowledge, though this idea was not fully followed in the philosopher’s later texts. The elements of the Greek society — its citizens, language, architecture, and social institutions — constructed a new totality in history, consequently imagined first by citizens and thinkers of the early Greek city-society. An important factor of global creativity would be sufficient diversity of regional subcultures, which perhaps would propel radical imagination in the European sphere. If people in different subcultures are persuaded to think in similar categories, which the modern administrative body favours, it is unlikely that new insights would emerge in the mutual discourse. The works of Pierre Bourdieu open a more diverse picture, though as the Austrian scientist C. Fuchs (2003) reads them the habitus is a means of self-creation or ‘autopoiesis’ of social systems, in terms of human beings who are permanent creators of society and permanent results of this creation. Maslow calls the avant-garde creators ‘pioneers’ or ‘commandos’, and the secondary creativity that follows ‘settlers’ or ‘military police behind the lines’ (Maslow, op. cit., p. 30). It is likely that with testing and surveying it is possible to merely catch this latter type of creativity, since it is improbable that in laboratory tests or competitions something totally new in history does surface. Yet one problem remains: how to evaluate the products of the primary or pioneer creativity; since the truth is that even 10 psychologists representing different nationalities and domains cannot consensually evaluate what the next new phase or order of art, human sciences, society will be, or the expanding universe. A consensual definition of creativity probably has not much value in this case, but it is useful in the reconnaissance type of creativity type Two. Maslow actually suggests the existence of a third type of creativity that incorporates the two earlier types: an integrated model of creative process. This seems not to be very different from the interplay of ‘rhetoric’ and ‘logical’ components of scientific thinking that Juri Lotman suggests, though the vocabularies of these theories are dissimilar. The integrated model is that which Maslow believes all historical creative persons have applied. It is the type of creativity that is situated in the semi-autonomous fields of cultural production, each having its own dynamics and own history of battles. A sociological solution of the problem of evaluation might be to leave the definition and evaluation of creativity to the fields of art, science, philosophy, and invention, which deal daily with this question and battle about different ways to achieve creativity and ride into history. The degree of ‘creativity’ of the music of Pierre Boulez, texts of Virginia 296


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Woolf, or paintings of Paul Klee is by no means a psychological question, though we should be aware of how they inspire further waves of creativity in people. Creativity was handled in this essay as an inherent element of action, a part of an integrated whole, in which all components form a kind ‘unified theory’ together, and not dealing with a list of isolated concepts. In American psychology the systemic layouts suggested by Feldman, Czikszentmihalyi and Gardner (1994), Czikszentmihalyi (1996) or Sawyer (2008) may be closest to this idea of unified theory of creativity, though no intrinsic relationships are presented in these compositions to integrate the theory of persons, period, and the social field as a dynamic whole, that which is present, for instance, in the comprehensive theories of Bourdieu, Joas, or the Vygotskian school. It seems that creativity can best be explained as a part of a more general theory of culture, society and people, in which its total significance in history and human life is explained. A working explanation of creativity is offered by different variations of the theory of praxis, in particular, and the notion of activity, underscoring the practical content of creative action and the situation-bound nature of creativity. It is the reservoir of assimilated experiences that is mobilised in creative action, both the individual memory and the memory of humankind (see Järvilehto, 2000). A considerable part of these experiences are embedded in earlier products of creativity, and an extensive number are embodied in people’s pre-symbolic and non-spoken experiences, which are still important factors in their creative activity. It is the mass of cultural experiences people produce during very long historical periods, comprising all aspects of their everyday life as well, even the micro-structures of their life (cf. Braudel, 1976). This history remains in the brains of people, in some form or other — and it also explains the often unexpected patterns of creativity in crowds. This thesis of pre-symbolic part of memory does not prevent, however, the researchers studying personal experiences of creativity, for example as they emerge from current education, or the interpretations of creativity among different nations and their key groups. Finally, we should seriously consider the ways in which the flat higher teaching — I am speaking of my own experience as student, professor and researcher into higher education (cf. Häyrynen, 1987, and 1999, and see Y.-P. & Liisa Häyrynen, 1996) — could be turned into an intellectual adventure: for it to be effervescent and passionate, not only faithfully repeating what is found in hundreds of textbooks and endless auxiliary figures of lecturers. Teaching should be interaction as Vera JohnSteiner describes it in her book on collaborative creativity (2000). What should be kept in mind, though, is that all processes of creativity include a reminder of tacit elements of practical noesis (le savoir faire) and pre-symbolic practices, which cannot 297


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be re-described as formal models of creativity, as logical definitions, or as criterions of educational or cultural policy. These pre-symbolic processes and products of creativity that have been already fabricated — the world of drama, music, ballet, dance, philosophy, exact sciences, engineering, painting, literature, speech, and sports — actually form a bypassed but immense reservoir of creativity today. What the continent still lacks appears to be an incentive for radical imagination, returning the passion to the spirit of scholarship and science. References Aristotle: De Anima (On the Soul). Trans. with introduction and notes by H. LawsonTancred. 1986. London: Penguin Books. Baer, J. (1993). Creativity and divergent thinking – a task specific approach, New York: Erlbaum Bourdieu. P. (1966). “Champ intellectuel et projet createur.” Les temps modernes (Paris), XXII (246), 865-906. [“Intellectual field and the creative project”]. Bourdieu, P. (1977). The outline of a theory of praxis. Cambridge: Cambridge University Press. Bourdieu, P. (1992). Les règles de l’art. Genese et structure du champ litteraire. Paris: Editions du Seuil. [“The rules of art. Birth and structure of the field of literature”]. Bourdieu, P. and Passeron, J.-C. (1964). Les héritiers. Les étudiants et la culture. Paris: Les Editions du Minuit. [“The Inheritors. Students and culture”]. Braudel, F. (1960) History and social sciences: The long duration, American Behavioral Scientist, 3 (3). (pp. 2-12) [Original article in French 1959]. Castoriadis, C. (1999). The imaginary institution of society. Trans. by Kathleen Blamey. Cambridge, MA: The M.I.T. Press. Chen, C. et al. (2002). Creativity in drawings of geometric shapes a cross-cultural examination with the consensual assessment technique, Journal of Cross-cultural Psychology, 33, 171-187. Clot, Y. (2002). Vygotski: la conscience comme liason, in Vygotski (2002). (“Vygotsky: Consciousness as a link [between various experiences]” Paris : La Dispute. Csikszentmihalyi, M. (1996). Creativity – Flow and the psychology of discovery and invention. New York: Harper. Dalton, B. (2004). Creativity, habit, and the social products of creative action: Revising Joas, incorporating Bourdieu, Sociological Theory, 22, 603-622. Danziger, K. (1996). Neither science nor history? Psychological Inquiry, 8, 115-117. Dewey, J. 1910. How we think. London: Heath. Dreyfus, H. L. and Dreyfus, S. E. (1986). The power of human intuition and expertise in the era of the computer. New York: The Free Press. 298


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Dreyfus, H. L. and Rabinow, P. (1983). Michel Foucault. Beyond structuralism and hermeneutics. Chicago: Chicago University Press. Engell, J. (1981). The Creative imagination – enlightenment to romanticism. Cambridge MA & London: Harvard University Press. Feldman, DH (2000). Foreward. In V. John-Steiner (Ed.), Creative Collaborations. Oxford: Oxford University Press. Feldman, D. H., Csikszentmihalyi, M. and Gardner, H. (1994) (Eds.) Changing the world. A framework for the study of creativity. Westport, Connecticut & London: Praeger. Fuchs, C. (2003). Some implications of Pierre Bourdieu’s works for a theory of social self-organization, European Journal of Social Theory, 6, 387-408. Gigerenzer, G. (2001). From tools to theories – a heuristic of discovery in Cognitive Psychology, Psychological Review, 98, 254- 267. Göle, N. (2000). Global expectations, local experiences: Non-Western modernities.” In Arts, W. (Ed.) through a glass, darkly. Blurred images of cultural tradition and modernization. Leiden: Blin. Gruber, H. L. (1996). The life space of a scientist.The visionary function and other aspects of Jean Piaget’s thinking, Creativity Research Journal, 9, 251-265. Häyrynen, Y.-P. (1980). Det skapande tänkandet och dess sociala dynamik, Nordisk Pedagogik 1(1), 5-12. [“Creative thinking and its social dynamics”]. Häyrynen, Y.-P. (1987). The life contents of Finnish intellectuals. In Eyerman, R., Svensson, L. G. & Söderqvist, T. (Eds.) Intellectuals, university and the State in modern Western societies, pp. 211-234. Berkeley, Los Angeles & London: University of California Press. Häyrynen, Y.-P. (1999). Collapse, creation and continuity in Europe: how do people change? In Engeström, Y., Miettinen, R. & Punamäki, R.-L. (Eds.) Perspectives on activity theory, pp. 115–132. Cambridge: Cambridge University Press. Häyrynen, Y.-P. and Häyrynen, L. (1996). From students to intellectuals and professionals: Subsequent career patterns of a Finnish student generation of the 1960’s. In Brennan, J. Kogan. M. & Teichler, U. (Eds.) Higher education and work, pp. 178-203. London & Bristol, Pennsylvania: Jessica King Publishers. Horng, R.-Y. (1990). Individual differences in people’s conception of creativity and their motivational implications. Paper presented in the 22nd International Congress of Applied Psychology (Colloquium “Conceptions of Creativity”), Kyoto, Japan. Järvilehto, T. (2000). Theory of the Organism-Environment system: IV. The problem on mental activity and consciousness, Integrative Psychology and Behavioral Science, 35 (2), 35-57.

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Joas, H. (2001). The creativity of action. [Original work Die Kreativität des Handels in 1996.] Translated by Jeremy Gaines and Paul Keast. Chicago: The University of Chicago Press. John-Steiner, V. (2000). Creative collaboration. New York: Oxford University Press. Kärkkäinen, R., Räty, H. and Kasanen, K. (2008). Children’s notions of the malleability of their academic competences., Social Psychology of Education, 11,445-458. Maslow, A. H. (2000) Maslow Business Reader (Part III: Creativity and innovation). Deborah C. Stephens (Ed.) New York: Wiley. Mead, G. H. (1938) The philosophy of act. Ed. by Charles Morris with John M. Brewster, Albert M. Dunham & David L. Miller. Chicago, IL: University of Chicago Press. Mikhailov, F. T. (1980) The Riddle of the self. Moscow: The Progress Publishers. Moran, S. and John-Steiner, V. (2003). Creativity in Making: Vygotsky’s contemporary contribution to the dialectic of development and creativity. In Sawyer, R. K. (Ed.), Creativity and development. Oxford: Oxford University Press. Moscovici, S. (2001). Social representations. Essays in Social Psychology. New York: New York University Press. Mugny, G. and Carugati, F. (1989). Social representations of intelligence. Cambridge, New York: Cambridge University Press. Paletz, S. and Peng, K. (2008). Implicit theories of creativity. Novelty and appropriateness in two product domains, Journal of Cross-cultural Psychology, 39, 286-302 Rubinstein, S. L. (1976). Grundlagen der Allgemeinen Psychologie. Berlin: Volk und Wissen Verlag. Sawyer, R. K. (2003). Improvised dialogues: Emergence and creativity in conversation Westport, CT & London: Ablex Publishing. Sawyer, R. K. (2008). Explaining creativity. The science of human innovation. New York: Oxford. Sawyer, R. K., John-Steiner, V., Moran, S., Sternberg, R. J., Nakamura, J. and Csikskentmihalyi, M.(Eds.) (2003). Creativity and development. New York: Oxford. Stares, S. (2009). Global poverty statistics and civil society. In Kumar, A. & al. (Eds), Global Civil Society Yearbook 2009, 42-56. London: SAGE. Stehr, N. (1991). The power of scientific knowledge – and its limits, Canadian Review of Sociology and Anthropology, 28(4), 47. Steiner, G. (2001). Grammaires de la creation. [Orig. in English: The Grammars of creation] Traduit par Pierre-Emmanuel Dauzat. Paris: Gallimard. Tulviste, P. (2001). The cultural-historical development of verbal thinking. Transl.from Russian by Marie Jaroszewska Hall. New York: Nova Science Publishers. Tweney, R. D. (1996). Presymbolic processes in scientific creativity, Creativity Research Journal, 9 (3),163-172. 300


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Vygotski, L. S. (2002), Conscience – inconscient – émotions. Transl. from Russian by Françoise Sève & Gabriel Fernandez) Paris: La Dispute. [Consciousness – unconscious – emotions.]. Yaroshevskii, M. G. (1985). Psychology of creativity and Creativity in Psychology, Soviet Psychology, 6/1985, 23-44. [In Russian Voprosii Psichologii 6/1985, Moscow: “Pedagogika” Publishers].

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Creativity, measurement and education

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A strategy for the future

19. Researching, measuring and teaching creativity and innovation: a strategy for the future

Petra Mª Pérez Alonso-Geta (Institute of Creativity and Educational Innovation, University of Valencia)

Abstract The Institute of Creativity and Educational Innovations (INCIE) has developed an Educational Model for Creative Development (PECEI) in order to promote creativity and innovation, and has proven its worth among schoolchildren. It is a strategic model that relates to the individual (development of a creative and entrepreneurship spirit), to the process (of innovation), to the product, and to context. This model has been developed based on the indicators that the most relevant authors in the field have traditionally considered as those that define innovation and a creative person. We now want to provide the model with a solid empirical basis in order to expand it, which will allow empirical validation and, if necessary, the re-elaboration of the model in order to use it with the general population. We have, therefore, proceeded to analyse the bibliographical corpus of all the authors who in recent years have published papers on indicators of creativity. Based on this information, we have defined a series of basic factors, which have served as a basis for a working definition of creativity as a reference for producing a measuring instrument (questionnaire) within the traditional theoretical structure of the elaboration of norm-referenced tests. This paper outlines the main aspects covered by the instrument and the future steps to be taken in order to improve the instrument.

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Petra Mª Pérez Alonso-Geta

Introduction Human beings need to innovate and be creative within their surroundings in order to live and progress. Creativity is a trait all human beings possess to a greater or lesser extent. We understand creativity and the capacity to innovate as attainable skills, as strategies for the future that need to be stimulated by education in order for individuals to be able to meet the challenges that arise nowadays in the different domains of reality. The research and measurement of creativity demands the introduction of changes: new practices in teaching; changes in objectives, curriculum, methods, etc. In this way, teaching, measuring and research on creativity become a strategy for the future. The Institute of Creativity and Educational Innovations has developed an Educational Model for Creative Development (PECEI) in order to promote creativity and innovation. The present article shows some of the aspects that these new tools pertain to measure.

Creativity and education Creativity is a human characteristic, archetypal of the ‘being that ponders’ that thinks, that senses the relation of cause and effect. Humans are capable of imagining, formulating hypotheses, planning and carrying out ‘something new and worthy,’ establishing objectives and putting in order one’s priorities. To achieve their purposes, humans frequently have to walk down new roads, give birth to what has never been done: create. Humans create by giving answers adapted to a changing environment by establishing scenarios, strategies for the future, and by designing, making art, or finding a solution to one’s problems. In order to carry out innovation, our accumulated experience is not enough. Humans innovate when they perceive a new necessity and they do so by reviewing and combining existing knowledge in a process of interaction with their surroundings, searching for the best solution. From this perspective we may interpret innovation as a learning process whose basic resource and main result is knowledge. It is, however, a complex process, which feeds itself both with tacit knowledge and with explicit and specialised knowledge, and which can be affected by a diversity of factors. Some of these are internal and individual (sensitivity, flexibility, motivation, proactivity, ability to analyse, etc.), whereas others are present in the environment (education, personal interactions, and social context). Education and creativity are manifestations of integral human development, but they are different. Education is a process that aims to go beyond socialisation (to be like others) and to make the educated person a unique individual. It is precisely through this function that education has the possibility of promoting creativity and innovation. 306


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Torrance (1976), one of the great theorists of creativity, stated back in 1977, that there are many reasons to think of the education of the future in creative terms. There is a fast pace of change: today’s children will live as adults in a world profoundly different from the one we know now. Many will work in jobs that do not yet exist and that will require abilities, skills, attitudes, and information that we cannot yet imagine. In this new society, these changes will require high levels of inventiveness and creativity, and knowledge will be the basic wealth. When we talk of the human beings and our creative development we have to start with our condition as a being that learns. This provides us with great freedom of action, since our survival is not determined by the innate pressure of instinctive actions. Our learning capacity and the guiding influence of the environment are included in the biological development plan of the species, which determines a very long period of immaturity and a notable retention of features of early childhood. We are basically animals that learn: our cerebral immaturity and long infancy allow for cultural learning or, in other words, the acquisition of ways of behaviour through education. Educability is found within the genetic code as a possibility and requires that the process takes place through social mediation (García Carrasco, García del Dujo, 2001). Likewise, the educability of the human being is the result of evolutionary processes. It is not a static ability, but it is defined in terms of a process; that is to say, the level of educability depends on the quantity and quality of the individual’s learning (Castillejo Brull, 1983). This great potential, determined by the acquisition of knowledge, educability and our biological indeterminacy, opens up the possibility of being creative and of developing this potentiality through education. To teach creativity we need to have a model based on the indicators that define innovation and the creative person. This will allow the structuring of programs that define the process of creative teaching-learning. It is important, however, to note that all models require evaluation and measurement in order to guarantee their pertinence and to allow for the constant improvement of the educational process. We also need to know what the implications of measuring creativity are for educational processes, since creativity introduces substantial changes in the educational process; not only for the teacher but also for the students.

The person and the teacher in the PECEI model PECEI is a model focused on the subject and the process. The model assumes that creativity involves the development of a set of attitudes and thinking skills that permit improving our environment by applying our learning and experience in order to obtain original and suitable responses. Creativity increases our intellectual potential and 307


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leads to self-realisation and satisfaction. PECEI is a model for teaching creativity, that includes also evaluative aspects, thus, a model with a measurement tool. The model, once developed, will permit to justify the establishment of criteria for judging the educational quality of creativity in its most important dimensions. In relation to the individual, our model defines creativity by divergent thinking, originality, flexibility, independence, the motivation to succeed, sensitivity, the capacity for inventiveness, imagination, etc. Creativity is defined by the capacity to change ‘the patterns of perception’ established by experience, in order to develop ‘patterns of action’ (De Bono, 1988). The development of creative attitudes is crucial for this to appear, in fact, numerous investigations have found constant associations between creativity and attitude (Nickerson, Perkins and Smith, 1987). Moreover, students must be freed from the limitations and obstacles which impede creative behaviour: fear of making mistakes, fear of failure, lack of motivation, laziness, negativity, dependence on the group, insecurity, etc. Other potentialities must also be developed such as: self-reference, belief in oneself (self-confidence), proactivity, and knowing how to put off gratification, overcome frustration and persevere toward achievement. Also necessary are imagination, curiosity, interest, a critical sense, the ability to assume collective thought, etc. These characteristics, of a personal nature, are fundamental to creativity and are also the basis of entrepreneurship (Castells and Vilaseca, 2007). Regarding attitudes, the creative attitude provides a multiplicity of perspectives and the possibility of ‘seeing again’. The creative attitude is opposed to routines, continuity or the same way of understanding causes and effects. It demands freedom from narrow limitations, the ability to go beyond and leave behind automatic reasoning in order to appreciate other types of relationships. Creative attitude involves playing with metaphors when describing what exists, and revising the paradigms we use to understand reality, opening the door to imaginative responses. Thus, the first step is to promote (at a cognitive level) the development of new beliefs and opinions. That is to say, it is necessary to develop new patterns of perception that allow us to free ourselves from previous judgements (prejudices). Beliefs (preconceptions gathered from the information that the person has about something) with sufficient reinforcement generate attitudes, and attitudes precede action. One must take into account the three fundamental components of attitude (cognitive, emotional and behavioural). These three components are not necessarily linked: people do not always act as they think and feel. For this reason, in order to indicate a change in attitude, one must take into account the guiding influences of the individual, such as his or her expectations.. 308


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Based on these assumptions, the teacher of creative education, as a starting point, must not confuse education with ‘manufacturing.’ The educator cannot predict the nature of his or her work, since the teaching practice will always be ‘probabilistic’ in the sense that there is certain likelihood of certain teaching practices to produce certain outcomes, but there is no guarantee. The ‘resistance’ of the students to engage in the educational situation must be taken into account, and it must be understood as a call to rework educational action, based on the right of the individual being educated to be recognised as a ‘self’. This also implies that the educator assumes the role of authentic authority (not authoritarian) from an asymmetrical standpoint. The students will grant authority to the teacher by recognising his or hers qualification, knowledge and know-how. The educator cannot abandon authority, but neither can he/she cling to it as a privilege and confuse education with training and subjection. This would favour convergent thinking, submission, and would impede the development of creative ability. Thus, the education of creativity is not possible without first creating an educative environment that permits original contributions and divergent thinking to flourish. Designing creative educational spaces is necessary in order to encourage divergent attitudes that allow individuals to dare to think for themselves. An environment of freedom helps individuals liberate themselves from their burdens, emboldened by the security that authentic authority provides. Routine activities, which move through the trite arriving at answers that are known beforehand as the only possible ones, have no place in creative learning.

Process in the PECEI model The process is understood here as a tool of thought, which can be employed deliberately to produce a result. The result (the creative product) can only be valued and admired, but the creative process (like any process) can be taught, learned, and practiced. That is to say, it can be improved with training. The creative process requires inventiveness: having an idea, a hypothesis, a project, and being able to develop it. It demands the ability to use ideas outside of the judgement system: because judgement keeps us in the channels of experience, making the process of creation impossible. Ideas have to manifest, be developed, tested, evaluated and modified. Also necessary is the ability to escape the typical dominant idea in order to be able to attend to the influx of new ideas. Stimulation, intuition, direction, and perseverance are necessary to give incentive to the effort of achieving, because in this way only is it possible to finally overcome the environment and its resistance. 309


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During the process, divergent thinking is essential, as is critical thinking, which defines the direction when confronted with multiple options. Moreover, critical thinking generates sub-objectives by looking for the most parsimonious. Critical thinking contributes to the improvement of the creative product. Critical thinking may not be creative, but the development of the creative process cannot be but critical. For its implementation the creative process can use diverse strategies, which in turn can improve the process itself. Among the most common strategies are brainstorming, analogy, imaginative transformations, enumerating attributes, and liberation from the dominant idea. Finally, it is necessary to examine the measurement of creativity for educational purposes, since evaluation is an integral part of the model for teaching creativity.

What aspects of creativity are being measured? Measuring creativity in itself is a challenge because it tries to measure, beyond that which is established, it tries to measure that which is divergent. In fact, the creation of measuring instruments to identify the creative abilities that permit the individual to bring to life his or hers creative disposition, is the main problem facing those who want to establish, with precision, educational models and models to evaluate creativity. Based in different theories, numerous tests have been produced. We will briefly review those that have obtained general recognition. Since the 1950s the great theorists of creativity (Guilford, Torrance, Getzels and Jackson, Wallach and Kogan, Barron, Marín, among others) have worked to evaluate and measure creativity. To measure creativity, we started with the different categories that we want to measure. In the first group of test types we have Guilford’s tests of creative production (divergent production, fluency, flexibility, originality, convergent production, etc.) and association tests, creative aptitude tests or Torrance’s tests of creativity. What underlines all of these is that they measure aspects of aptitude, generally through the answers of individuals to certain closed or open stimuli (graphic, verbal, etc.) that are presented to them. Secondly, we have tests based on the creative personality, which try to evaluate dimensions of the personality (attitudinal, motivational or behavioural characteristics, interests, etc.) typical of creative individuals. Elements evaluated include: confidence in one’s own ideas; fantasy; desire for novelty and innovation; willingness to face risks; complexity of thought; independence; security; self-affirmation; curiosity, etc.

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A third group would be formed by the so-called inventory tests, which compare the evolutionary development patterns and the biographical behaviour of individuals. For example, there are autobiographical inventories and behavioural inventories. In a fourth group would be the project tests (Tat, Rorscharch). In the Rorscharch test statistical frequency determines if the answer is original or not. In a fifth group would be performance tests, divided in two subgroups: tests of artistic abilities, which try to evaluate the capacity for appreciating and/or producing an artistic form, and psychometric tests of creative performance focused on evaluating the creative performance of individuals, their productions. In general, we can distinguish two main tendencies: there are tests that measure creativity through the ability to produce creative ‘answers’ when confronted with a specific stimulus, and those that measure characteristics (motivational, attitudinal, behavioural, etc.) that form the basis of the creative personality. In the Institute of Creativity we are in the development phase of creating a measuring instrument, the TSPC.

What aspects are measured by the TSPC? The approach adopted by the PECEI (Educational Program for the Development of Creativity and Innovation) model is to consider creativity as an acquirable skill, although some individuals possess this quality naturally. We understand creativity as a skill with which students are eventually able to find new ways of seeing and doing things and wager solutions to different problems posed. PECEI has, as a point of departure, the basic indicators of creativity gathered from the bibliographical index of the most representative authors 1. In order to evaluate creativity we concentrate on measuring the characteristics of the creative person through the perceptions these individuals have of themselves in relation to the indicators of creativity that are most relevant regarding mental and behavioural aspects: what they think and what they do. The objective is to create an instrument for the evaluation of creativity, using a series of indicators derived from a working definition of creativity. The basic indicators are categorised in terms of the subject, the process and the context. We understand as an indicator a meaningful variable with a normative character. More specifically, we understand as an indicator of creativity (in our case) a variable 1

Bibliographical corpus prepared from Valiente Berna, J. (2009); Martín Ibañez, R. (1996) ‘Indicators of Creativity,’ in Creativity: Assesment, Evaluation and Investigation, Madrid. UNEDS de la Torre (2006) ‘Reference Points and Indicators of Creativity,’ Torre and Morales (coord.) Understanding and Evaluating Creativity: A resourse for improving the quality of teaching. Málaga. Aljibe.

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that gathers traits characteristic of the creative person, the manifestations of individual subjects and who they perceive to be meaningful references in their environment. We also pay attention to the significant references of their environment and if they consider themselves creative or not; with special attention given, in reference to the product, to attributes of originality and suitability. We will afterwards complete this evaluation with behavioural and biographical inventories of those identified as creative through the questionnaire. These indicators will permit us, on the one hand, to assess creative realities, and on the other, to implement objectives to be achieved in the education of creativity.

Steps followed in the elaboration We have proceeded to analyse the bibliographical corpus of the authors, who, in recent years, have published papers on indicators of creativity, by carrying out a metaanalysis of what already exists. The most commonly used indicators we found included sensitivity, in general, and when faced with a problem. This is defined as knowing how to discover what is beyond the established information or insufficiently explained; it refers to the ability to detect problems and anticipate consequences. It involves fluency and productivity in the sense of not being content with the first results and continuing seeking alternatives. For this, it is crucial the ability to formulate new hypotheses and new approaches, to have mental flexibility, as opposed to rigidity and repetition and the capacity to change perspectives, having a unique character. Although these are the most common and most used indicators, there are others such as: self-confidence; capacity for synthesis, association, and analysis; the ability to redefine resources; imagination; desire for achievement; organisation; communication; proactivity; and the searching for experiences. Based on this information, we have defined a series of basic factors, which have served as the reference point for developing a measuring instrument (questionnaire) within the traditional theoretical structure of the construction of norm-referenced tests. The questionnaire was first pilot tested online with one hundred individuals in order to assess its adequacy, the comprehension of the questions and the coherence of the answers, and to obtain an initial evaluation regarding the reliability of the instrument (internal consistency) and initial evidence of its validity. We have extracted a series of factors that permit us the first working approximation of creativity without a consensual definition. Once the quality of the pilot test was evaluated, we drew up a definitive measurement tool to be used online for a survey of creative professionals (art, publicity, business, architecture, etc.) and the general population. 312


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The results of this survey will be analysed using classical statistics and complex mathematical models. Afterwards, we will try to establish a model of measurement by setting up diverse scales in various dimensions and components, in order to be able to collect the different aspects of creativity, as a single form of creativity does not exists. Subsequently, and from a perspective of (quantitative/qualitative) methodological complementarity, we will try to complete the definitive design of the instrument and its validation based on ethnographic strategies, which allow us to identify key biographical elements of the concept of creativity as it is revealed by people identified as creative. Once determined the pertinence of the measuring instrument from the research evidence, we will be able to lay the foundations of educational models for creative development with a general and/or sectored application and to develop experiments in educational contexts to study the educational potential of the model.

Conclusions Creativity is a trait which all humans possess to a greater or lesser extent, although it needs to be cultivated; experience leads us to automated responses and we stop being creative. Teaching creativity is a strategy for the future because humans need, more and more, to be creative in order to face the challenges that arise in the different domains of reality. The education of creativity is a strategy for the future because we live in a changing society. In the same way, investigating and measuring creativity is a strategy for the future because evaluation, which forms part of the educational programs of creative development, introduces analysis and provides information for educational improvement. Education and the measurement of creativity require starting from models, which justify the establishment of educational criteria for quality in its basic dimensions. The measurement of creativity has implications for the processes of education in relation to the student, the teacher and the process itself. Education is a double-edged sword that can be used to either cultivate or stifle creativity. The teacher is the fundamental reference point in the school: their role is of prime importance in promoting creativity in his students. The problem of the evaluation of creativity is tied to that of its definition, the indicators which allow for its measurement and the instruments of measurement. Although the scientific production in this field is substantial, unanimity does exist regarding neither the concept of creativity nor its measurement. The measuring instrument TSPC, in the development phase at the Institute of Creativity, has as its point of departure the basic indicators of creativity collected in the bibliographical index of the most representative authors. It has as its objective the 313


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measurement of traits of the creative person through the perceptions that subjects have of themselves in relation to the indicators of creativity. The TSPC works within a structure of classical theory on the manufacturing of norm-referenced tests. From the start, the indicators are categorised around the subject, process and context. From a perspective of methodological complementarity (quantitative and qualitative), we will complete the definitive design of the questionnaire and its validation; with the aim of being able to define the characteristics of the creative person in relation to his creative products, as it is the creative person who carries out creative production. For this reason, the biographical study of the creative projects of individuals is fundamental to the measurement of creativity. Finally, it is on this basis that educational models for creative development are elaborated (applicable to various sectors) as well as experiments in educational contexts, which will permit us to know the potential of the models. References Barrón, F. (1976). Personalidad creadora y proceso educativo. Madrid: Marova. Castells, M. and Villaseca, J. (2007). Entorno innovador, iniciativa emprendedora y desarrollo local. Barcelona: Octaedro. Castillejo, J. L. (1981). Nuevas perspectivas de las ciencias de la educación. Madrid: Anaya. De Bono, E. (1998). El pensamiento lateral. Barcelona: Paidós. De Bono, E. (1997). Seis sombreros para pensar. Barcelona: Editorial Granica. Getzels, J. W., Jackson, P. W. (1962). Creativity and intelligence. New york: John Wiley. Guilford, J. P. (1968). Intelligence, creativity and their educational implications. San Diego, CA: Kirapp. Guilford, J. P. (1971). The structure of intellect. New York: McGraw Hill. Guilford, J. P. (1977). La naturaleza de la inteligencia humana. Buenos Aires: Paidós. Guilford, J. P. (1978). Creatividad y educación. Buenos Aires: Paidós. Marín, R. (1995). La creatividad: diagnóstico, evaluación e investigación. Madrid: UNED. Nickerson, R., Perckins, D., and Smith, E. (1987). Enseñar a pensar. Barcelona: Paidós. Portman, A. (1969). Biologische Fragmente zu einer Lehre. Basel-Stuttgart: Menschen. Torrance, E. P. and Myers R. E. (1977). Educación y capacidad creative. Madrid: Marova. Wallach, M. A. and Kogan, N. (1965). Modes of thinking in young children, A Study of the creativity-intelligence. New York: Holt.

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Creative Learning Assessment

20. Creative Learning Assessment (CLA): a framework for developing and assessing children’s creative learning

Sue Ellis , (Center for Literacy in Primary Education (CLPE))

Abstract When the research team at CLPE set out to develop an assessment focusing on creative learning, initially with a focus on the creative arts, we were aware of the controversial and complex nature of the task. Creativity is a slippery concept to pin down. Attempts to assess it are seen by some as impossible, counterproductive and unwise. It is difficult to assess any complex learning, but assessing ‘creative learning’ is particularly challenging: if creativity involves originality and the use of the individual imagination, how can these qualities be judged against a set of predetermined criteria? Creative learning is multidimensional. It challenges established thinking and practice in assessment, requiring a creative solution. Working with teachers from a group of schools in inner-city London, we found that it is both possible and desirable to assess creative work and creative learning in order to promote it. This paper describes the elements and impact of the Creative Learning Assessment (CLA) as a means of evidencing and enabling children’s creative learning.

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Sue Ellis

Introduction What is creativity? Is it more helpful to think in terms of ‘creative learning and is this distinct from other kinds of learning? How can we help teachers to describe and evaluate the complexity of children’s progress as creative learners and are there common threads which link creative learning across subjects? Should we be attempting to assess creativity at all? Do we risk losing it if we do? These are questions that need to be considered in any attempt to measure children’s creative achievement. The development of the CLA was the response to a request from a group of primary school head teachers who needed a way to systematically observe, describe and evaluate children’s creative learning in their schools. They believed that by focusing assessment on creative learning they could more fully represent pupils’ progress to colleagues, parents, governors, and inspectors and, by doing so, demonstrate the benefits of a curriculum that encouraged children’s creativity. The Lambeth head teachers had also asked for some means of relating achievement in creative learning to progress in academic areas. We aimed to provide them with ways of assessing literacy which would be compatible with their assessments of creative learning. The CLA research project, developed in collaboration with Lambeth EAZ/CLC schools, aimed to provide teachers with a view of creative learning and development, a framework for observation-based assessment, and information to feedback into planning a creative curriculum which would be responsive to individual and group needs. It was an opportunity for a group of researchers at CLPE (Sue Ellis, Myra Barrs and Jane Bunting) to work in partnership with a group of interested schools, many of them in areas of social deprivation, willing to give time and support to an extended development project to provide an innovative and workable solution to a real and complex problem. The initiative was helped by a changing context of government initiatives and welcome statements on creativity (Robinson 1999, DCMS 2002, DFES 2003, 2005, Ofsted 2003, QCA 2000) which provided a opportunity for the valuing of creative and arts learning. This had long been submerged by a curriculum and pedagogy dominated by the core subjects and their assessment by high-stakes, standardised testing. However, creativity represents a precious area of freedom within the curriculum and there was an understandable desire to protect it from attempts at measurement, particularly when there was a shared perception that assessment often leads to a narrowed curriculum and view of the learner. We wanted to develop a model of assessment that opened up possibilities to learners, informed teachers about the creative learning process, and encouraged them to be creative and reflective practitioners (Schon, 1987) in developing a curricu316


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lum and pedagogy that placed creativity at the centre. CLPE had an established track record in teacher assessment of language, literacy and learning (CLPE 1988, 1990, 1993, 2007), and we were well aware that assessment influences practice and creates backwash into the curriculum (Barrs, 1990). In developing the Creative Learning Assessment (CLA), we were concerned to create a positive backwash, influencing teaching and learning in constructive and supportive ways. Using an informing assessment structure, we believed, would help teachers to focus both on ways of analysing, and opportunities for developing, children’s creative work in schools.

What are we measuring? To assess creative learning we needed to evolve and develop a shared understanding of what we thought it was. An explicit description would help teachers to notice and record the different kinds of learning within a ‘creative spectrum’. Our model of assessment also needed to reflect the complexity of creative learning and enable teachers to look closely at the whole of children’s creative learning: both the process and the end products of their activity.

The CLA continuum The CLA Creative Learning Continuum, with cross-curricular and cross-age dimensions of learning, proved a clear, informing and open structure for reflecting on progress. Based on CLPE’s Patterns of Learning continuum (1990), it comprised: (i) confidence, independence and enjoyment (ii) collaboration and communication (iii) creativity (iv) strategies and skills (v) knowledge and understanding (vi) reflection and evaluation.

The CLA observation framework The interdependent and non-hierarchical strands of the continuum form the key headings within the CLA observation framework which, together with examples, help guide teacher observation and reflection on the creative learning process. They are not exhaustive, but indicative, and provide useful prompts for observation and analysis. Teachers responded positively to these descriptions, finding them recognisable and helpful. 317


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Sue Ellis

Table 1:The Creative Learning Observation Framework Teacher/TA

Year

Date

Date

Date

Name(s) Creative context (i) confidence, independence, enjoyment, e.g. developing pleasure and enjoyment engagement and focus empathy and emotional involvement self-motivation (ii) collaboration and communication, e.g. works effectively in a team contributes to discussion, makes suggestions listens and responds to others perseveres, overcomes problems communicates and presents ideas (iii) creativity, e.g. is imaginative and playful generates ideas, questions and makes connections risk-takes and experiments expresses own creative ideas using a range of artistic elements (iv) strategies and skills, e.g. identifies issues and explores options plans and develops a project demonstrates a growing range of artistic/creative skills uses appropriate subject specific skills with increasing control (v) knowledge and understanding, e.g. awareness of different forms, styles, artistic and cultural traditions, creative techniques uses subject specific knowledge and language with understanding (vi) reflection and evaluation, e.g. responds to and comments on own and others’ work responds to artistic/creative experiences analyses and constructively criticises work reviews and evaluates own progress Areas for further development

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The CLA observation framework allows teachers space to record what they are noticing while children are working on a creative project. It asks questions like: ‘In what ways are children able to take risks and experiment in their learning?’, ‘Do they generate ideas, questions and make connections?’, ‘Are there examples of responding to and commenting on their own and other people’s work?’ Teachers found the open framework flexible yet supportive in helping them to look closely at how children were learning in different arts subjects (classroom projects included the visual arts, animation, drama, dance, technology, history and literature). They saw it as an opportunity to find out what children know and can do, and as a way of developing a deeper knowledge and understanding of individuals and their approaches to learning. Prompts for observation can be seen in Table 1 which shows the ‘creative observation framework that the teachers used’. The significant role of reflection (Black, 2004) was highlighted by teachers as a part of the process. Through using the CLA framework, teachers decided to create specific time and emphasis within the curriculum for children’s self-reflection and peer evaluation, and drew on portfolios of work as a rich source of evidence to focus children’s discussion about their creative learning and work. Portfolios and e.portfolios (Barrett, 2000), together with the CLA observation framework and a scale of progress (see Figure 2), created a powerful element within the model of assessment. They provided a record of children’s work, both process and product, and included multimedia evidence. Whilst many elements within these headings are generic, we recognise that for the ‘Strategies and skills’ and ‘Knowledge and understanding’ strands, there are also subject-specific elements that teachers need to consider in addition to the generic features described. One teacher using the CLA commented: The framework helps you to view children’s learning through a different lens: ‘the doing’, listening to them as it happens, and the product ‘the done’. It’s a more balanced approach than just assessing the outcome. You learn so much more about the child that you can use to help them move forward. Teacher BL

The CLA Scale The CLA Scale provides teachers with a view of progress and development, and suggests ways they can support development. It shows, for example, children progressing across the scale to become more conscious, deliberate and critically reflective in their experimenting. 319


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Sue Ellis

The CLA Scale provides a tool for summative assessment. The five point scale is used by teachers at the end of the year to arrive at judgements of progress, drawing on the range of observation, portfolio and e.portfolio evidence gathered. The moderation process (Hallam, 2000) gives added validity to their judgements and in successive moderations resulted in a very high level of agreement by teacher moderators (CLPE, 2007): The moderation process was confirming. I felt more confident about my judgements afterwards. Teacher NF It made you appreciate other people’s observations — how accurate observations that were related to the elements of the scale could record and convey to others a clear picture of a child’s progress. Teacher AC

Figure 1: CLA scales

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During the year-long pilot, the revised CLA was road-tested thoroughly in real time, in real classrooms, in a range of primary schools, with teachers informing revisions along the way and helping to shape the final instrument. It was important that we developed a manageable assessment tool that could be readily taken on by other teachers. Pilot teachers were interviewed about the impact of the CLA on their practice: I could see what I was aiming for. It drew my attention to the different ‘parts’ of creativity. The scale has made me more aware of planning time for reflection, evaluation and commenting on others’ work. Teacher KS

Positive impacts of assessing creative learning using the CLA Our findings from the project showed that the CLA provided a valuable and practical tool for assessing and extending creative learning in classrooms. For example: Assessment Teachers found the CLA both manageable and informative. The clear structure of the observation headings enabled them to quickly internalise the criteria and use them to ‘notice’ and support the learning of each child in their class from a more knowledgeable perspective. Focusing on a few children informed their observation of all children and fed directly into their planning. The observation process had powerful effects on teachers who had experienced didactic training or practice and recognised they had lost focus on individual children’s learning in favour of transmission teaching and a delivery approach to the curriculum. Teachers recognised the elements of creativity described in the CLA framework and scale, and used these to observe, assess and develop children’s creative learning. The drama sessions were videoed and the difference between the first and third sessions were fascinating, from a riot of noise and movement to cathedral-like silence as children watched each other move with poise and expression. Following this, children’s writing became far more expansive and vivid. It was drama that supported them in writing more powerfully and convincingly, from inside the text. Teacher BL Creative learning and achievement The development of a more negotiated, workshop/atelier model enabled children to work with more autonomy, making more choices and decisions and generating more productive talk and discussion. The focus on creative learning showed that creative contexts empower children who are not revealed as ‘achieving’ in academic subjects 321


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Sue Ellis

or through current testing systems. Reflection and evaluation was key in promoting children’s critical reflection on their own and others’ work. ‘Reflective time’ encouraged children to review their own learning and teachers recognised the need to build into the curriculum time for reflection. I like being allowed to choose what we make because then everyone does different things. Jess, age 7 Pedagogy The CLA had a distinct effect on pedagogy, which moved from a more didactic, delivered curriculum to one that was negotiated and collaborative. This contributed to better relationships within the class. By closely observing children, teachers reorientated their teaching to focus on individual children’s learning experience and this helped them to move children on. Teachers felt supported in their planning and provision and developed a more reflective practice. The clear model of creative learning supported the explicit discussion of the creative process with children, enabling children to better understand what they needed to do. Teacher knowledge Though considered a difficult area to define and pin down (Craft 2005, Craft, Burnard and Grainger, 2005), the moderation process showed that teachers recognised the elements of creativity described in the CLA framework. The explicit headings for observation and descriptions of progress in the scale enhanced teachers’ knowledge of the different aspects of creative learning, promoting understanding of creative learning development for individual teachers and across the whole school. The framework helped me to look at how children were learning An understanding of creative learning gave rigour to my practice. Teacher MH Curriculum change Teachers’ observations demonstrated that children need time, space and a more integrated curriculum to make the important connections necessary to make real progress as learners. They saw the value of reflective time and created regular, planned opportunities for this. Teachers recognised that the model of learning transfers across other curriculum areas. The focus on creative learning enabled teachers to see the links with the rest of children’s learning where, for example, risk-taking, making choices, reflection and persistence transfer across subjects. The CLA provided me with a clear framework for thinking about what I needed to build into my planning. Teacher BL 322


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Figure 2: The impact of the Creative Learning assessment (CLA)

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Sue Ellis

Implications of measuring creativity Our experience of developing the CLA leads us to believe that measuring creativity provides a real opportunity to create a shift in our vision of education for the 21st century. It is a portal for change in the way we view: yy the learner as an active participant, who is experimental and critically reflective; yy the role of the teacher and other partners in schools, creating a culture of shared enquiry; yy the curriculum, as more integrated, dynamic and inclusive; and yy assessment as a means of recognising and valuing the diversity of talents. Assessing creativity is an ally in the process of transforming education as a creative enterprise. It is an important means by which we can make visible the impact of creative teaching on children’s willingness and ability to take creative leaps in their learning: Without some form of assessment and evaluation the teacher cannot know what the consequences of teaching have been. Not to know, or at least not to try to know, is professionally irresponsible. And to claim that such consequences cannot in principle be known is to ask people to support educational programs on faith. (Eisner, 2000) References Barrett, H. (2000). The REFLECT Initiative: Researching electronic portfolios and learner engagement. Winter/Spring 2000. Retrieved May 2009 from: http://electronicportfolios.org/reflect/index.html Barrs, M., Ellis S., Hester, H. and Thomas, A. (1988). The Primary Language Record Handbook for teachers. London: Centre for Language in Primary Education. Barrs, M., Ellis S., Hester, H. and Thomas, A. (1990). Patterns of Learning. London: Centre for Language in Primary Education. Black, P. et al. (2004). Assessment for Learning – Putting it into practice. Maidenhead: Open University Press. Craft, A. (2005). Creativity in Schools. Tensions and Dilemmas. Abingdon: Routledge. Craft, A. 2005; Craft, A., Burnard, P. and Grainger, T. (2005), Progression in Creative Learning (PICS) Open University Press. DCMS (2002). Creative Partnerships Mission Statement. London: DCMS. DfES (2003). Excellence and Enjoyment: a strategy for primary schools. London: DfES. DfES (2005). Every Child Matters. London: HMSO. Eisner, E. (2000). The Arts and the Creation of Mind. New Haven, CT: Yale University Press. 324


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Ellis, S., Barrs, M. and Bunting, J. (2007). Assessing Communication and Learning in Creative Contexts. London: CLPE/CfBT

Hallam, P.J. (2000). Reliability and validity of teacher-based reading assessment: Application of “Quality Assurance for Teacher-based Assessment” (QATA) to California Learning Record moderations. Doctoral dissertation. Berkeley, CA: UC Berkeley. NACCE (1999). All Our Futures: creativity, culture and education. London: DfEE. Ofsted. QCA. (2000) The National Curriculum for England. London: QCA Safford, K. and Barrs, M. (2006). Many Routes to Meaning. London: Centre for Literacy in Primary Education. Schon, D. (1987). Educating the Reflective Practitioner. San Francisco: Jossey-Bass Publishers.

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Promoting creativity in education

21. Promoting creativity in education and the role of measurement

Marilyn Fryer (The Creative Centre Ltd)

Abstract This paper outlines some of the factors involved in promoting creativity in education. Of particular interest is how teachers’ attitudes and their perceptions of creativity are linked to their preferred ways of teaching and assessment. The role of measurement generally in enhancing creativity is briefly explored. Finally, it is argued that insufficient is known about cross-cultural differences in creative education and that a Europe-wide study would be desirable.

Introduction Creativity, like education, is a complex, multidimensional concept which means that the simple question, How can creativity be promoted in education? begs further questions. These can be answered in a variety of ways depending on how these concepts are defined and which criteria are adopted as yardsticks of success. Published definitions of creativity vary in a number of ways, such as the extent to which they: yy Focus on the individual, the creative process, product or idea, environment — or a combination of these. Examples of the latter include: The creative process … is the emergence in action of a novel relational product, growing out of the uniqueness of the individual on the one hand, and the materials, events, people, or circumstances of his life on the other (Rogers, 1954, quoted in Vernon, 1970, p. 139). 327


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Marilyn Fryer

Creativity is a process that results in novelty which is accepted as useful, tenable, or satisfying by a significant group of others at some point in time. (Stein, 1984, p.1.). yy Differ with regard to the level of creativity regarded as legitimate. For Ausubel (1978) only high levels of creativity count; Fabun (1969) views virtually everything invented as creative, but Ghiselin (1963) acknowledges both. yy Differ in terms of their discipline or theoretical perspective; within psychology this includes Behaviourist, Freudian, Humanistic, Piagetian and Cognitive approaches (Fryer, 1989).

Factors involved in promoting creativity in education The capacity to be creative is an intensely human capacity. In this section the focus is on how students can be enabled to function as more creative individuals.

Valuing creativity Firstly it is important to make it clear that creativity is valued. As a result of his research investigations across a variety of cultures (Torrance, 1995; 1965) concluded that creativity tends to flourish where it is valued. Similarly, I found that those UK teachers who were most keen to promote students’ creativity also stressed the value of a whole school commitment to creative education. They particularly valued their head teacher’s commitment (Fryer, 1996). The designation of 2009 as the European Year of Creativity and Innovation is to be especially welcomed since it is likely to have a really positive effect. This is in contrast to the situation in mid 1980s UK when I began my investigations into UK teacher’s views on creativity, teaching and learning. At that time, creative education was virtually a non-issue in Britain and the political climate was not at all favourable.

Inter-group differences in perspectives on creativity Secondly, it cannot be assumed that everyone involved in promoting creativity in education sees creativity in the same way. For example, in my earliest research, Project 1000, I discovered clear and highly significant inter-group differences in perceptions of creativity between men and women, and when controlling for gender, between teachers of different subjects. These differences were also evident in the criteria the teachers preferred to use for assessing the creativity of their students’ work.

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Promoting creativity in education

For example, as a group, the female teachers were more inclined to see creativity in very personal terms — for example, as self-expression (p