Innovation indicators and policy - Some reflections on limitations and potentialities of innovation surveys Eduardo B Viotti
EXTENDED ABSTRACT The possibility to improve the innovation policymaking process depends on the ability to better understand and gauge the nature and evolution of national innovation systems. Traditional S&T indicators constitute an insufficient basis for this purpose. The relatively recent development of indicators derived from innovation surveys represents a promising step forward in that direction. However, as pointed out by [1], innovation surveys have had not much impact on innovation policy thus far. Scientific and technological (S&T) policies during the postwar period were dominated by the perspective that innovation would be a natural consequence of investments made in research and development (R&D), especially in basic research and in R&D personnel. From this perspective, which came to be known as the linear model [2], [3], universities and public research institutions occupied the center stage of S&T policy because they were thought to be responsible for the advancement of knowledge necessary for initiating a process that would eventually lead to innovation. Research aimed at advancing the knowledge frontier and with no consideration for any practical purpose – basic research – was seen as the most important engine of the advance of knowledge and, therefore, eventually, of innovation. The main source of S&T policy inspiration was the linear model, and it ruled almost absolutely in most countries during the postwar period. It is true that there were very significant exceptions (like, for instance, the promotion of innovations by US space and defense policies), but they were not usually seen as a challenge to the linear model tenets because they were not considered S&T policies as such. Since the last decade of the 20th Century, however, a more sophisticated and complex understanding of the innovation process started to have a growing influence, initially, in S&T policy analysis and, later, in policymaking. Nowadays, this systemic model of innovation, expressed in the so-called National Innovation Systems (NIS) approach [4]-[9] has a Manuscript received December 13, 2007. Eduardo B Viotti is legislative advisor on scientific and technological policy for the Brazilian Senate (on leave), and associate researcher and lecturer at the Center for Sustainable Development (CDS), University of Brasilia, Brasilia, DF, Brazil. (e-mail:
[email protected]).
relatively large influence on policy discourse, but its actual impact on policymaking remains to be verified. The systemic approach supports diagnosis of NIS strengths and weaknesses and determination of policy objectives or targets, but sometimes the simple and straightforward rules of thumb that used to guide S&T policies in the past, inspired by the linear model, still seem to creep into modern innovation policies through a backdoor. The Lisbon Strategy, set by the European Union (EU) in 2000, for example, seems to have become, to a certain extent, a victim of this problem. The Lisbon objective to transform the EU into “the most competitive and dynamic knowledge-based economy in the world by the year 2010” could be seen as a manifestation of the influence of the systemic approach on policymaking. After the Barcelona European Council 2002, however, this objective ended up by having as its most visible policy motto the target to raise the level of EU R&D investment from 1.9% to 3% of GDP by 2010. As a matter of fact, setting a national target for R&D spending is a policy practice that is almost universal. OECD Science, Technology and Industry Outlook 2006 [10], for instance, lists the specific national R&D targets for 19 countries, and there are certainly many more countries, both developed and developing, that follow this same practice. The strength of that type of target as a policy tool lies in its simplicity, ease of understanding and measurement, and also to its enticing subjacent association with the allocation of more money, especially public money, to R&D practitioners, who are the main constituencies of STI policies. That target is a clear-cut example of the usefulness of an S&T indicator for policymaking. However, the reduction of the whole picture to a single R&D indicator would be better suited to a policy inspired by a linear model of innovation than by one using the systemic approach. The multiple aspects or variables involved in systemic analysis will surely require a complex set of indicators to better gauge any NIS. The indicators derived from innovation surveys naturally emerge as the indicators par excellence of the systemic approach, even though it will be wrong to claim any exclusivity for them. This is so because, among other things, they represent a way of looking directly at the innovation system core. Surveys of innovation collect information from enterprises, which are the actual locus where innovation happens, and they also try to measure innovations themselves, their determinants and their consequences for
enterprises. The objective of these surveys is not to collect information about any variable believed to be the “pacemaker” of innovation and, to indirectly infer what happens to innovation. Collection of surveys of innovation evolved greatly in the last few years. A large number of countries have already carried out one or more surveys of innovations. The 25 member countries of the European Union are collecting, during 2007, data for the fifth round of Community Innovation Surveys (CIS) of innovation. Every two years a new survey is carried out in these 25 countries. Canada, Japan, Australia, Thailand, South Africa, South Korea, Uruguay, Chile, Colombia, Mexico, Argentina and Brazil have already had one or more rounds of surveys. It seems to be about time for indicators like rates of innovation and percentages of new products in the total turnover of firms or industries to be emerging as targets in science, technology and innovation (STI) policies. It is about time also for results of surveys of innovation to occupy an important position in policy evaluation and analysis, standing alongside the most traditional indicators like R&D expenditures and personnel, and publications or scientific production. However, this does not seem to be happening. Besides the presentation and introduction, this paper includes three main sections. The first discusses the relevance of innovation indicators for policymaking, and it gives strong evidences of how it is being poorly used. The second section analyses the reasons for this almost lack of use of innovation indicators, and the last section presents ways to improve the usefulness of innovation surveys for policymaking.
Index Terms—innovation, science and technology policy, policymaking, innovation surveys and indicators.
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