Business models in Italian biotechnology industry: a

Technovation 25 (2005) 1299–1306 www.elsevier.com/locate/technovation

Business models in Italian biotechnology industry: a quantitative analysis Barbara Bigliardia,1, Anna Nosellab,*, Chiara Verbanoa,1 b

a Dipartimento di Ingegneria Industriale, Universita` degli Studi di Parma, Viale delle Scienze 181/A, 43100 Parma, Italy Dip. Tecnica e Gestione dei Sistemi Industriali, Universita` degli Studi di Padova, Str.lla San Nicola 3, 36100 Vicenza, Italy

Abstract The aim of this research is to study the business models of the Italian biotechnological firms through a statistical analysis, using the data base made up in the previous work by the same authors of this paper. The results of the study show the existence of four clusters grouping biotechnological firms: ‘service companies’, ‘small research companies’ (NBFs), ‘Traditional integrated firms’, ‘Industrialized Integrated firms’. We then analyse the patterns of the development of biotechnological firms in Italy. q 2004 Elsevier Ltd. All rights reserved. Keywords: Biotechnology companies; Business models; Cluster analysis; Italy; Patterns of development

1. Introduction Biotechnologies represent one of the most significant emerging technologies, whose different applications can be used for the growth of knowledge-based industry. The business of biotechnologies has taken place in Italy later than in other countries (i.e. the United States and other European countries), and this consideration has led some experts to maintain that Italy has already missed the ‘train of biotechnologies’ (OPES, 2001). However, by a previous research made by the same authors of this paper, it turned out that recently there have been signals of development, especially in the pharmaceutical industry (Nosella et al., 2004). The objectives of the previous study can be explained as follow: † to undertake a census of Italian biotechnological companies, after having defined them as companies which are innovative and carry out R&D or at least industrial development; † to identify and to describe their strategic profile and innovative processes; * Corresponding author. Tel.: C39 444 998734; fax: C39 444 998888. E-mail addresses: [email protected] (B. Bigliardi), anna. [email protected] (A. Nosella), [email protected] (C. Verbano). 1 Tel.: C39 521 905860; fax C39 521 905705. 0166-4972/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.technovation.2004.10.013

† to identify the business models adopted by these companies. The aim of the present study is to examine in more details the previous research and to go on with it. From the previous study it resulted that the companies analyzed were positioned in different competitive segments; in other words, it turned out that these companies were different according to the type of product/service sold out on the market and to their innovative processes. In particular, it emerged that, due to the different competitive factors, these companies could be classified based on the predominant business model they use in five categories, described below: † companies (usually pharmaceutical) with an high level of scientific knowledge that operate predominantly in the applied research (NBFs): NBFs are typically young small companies that sell their product (research output) or set up partnership with larger companies able to produce and commercialize their products; † vertically integrated companies, that are established companies which have the resources and the capabilities needed from research through to commercialization. Both established companies (with their own inner department dedicated to the development of biotechnological products) and companies that are born and have been working only in the biotechno logical industry belong to this business model.

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These companies not only develop new products/processes internally, but also establish permanent collaborative relationships with other companies such as small research firms, with the purpose to share the risk of the failure on various projects and, most of all, to widen their own knowledge base; † companies whose major areas of business are industrial development, production and commercialization: they are generally manufacturing companies that ‘buy research’ carried out by other companies, usually by the small firms previously mentioned. The number of these companies (prevalently operating in pharmaceutical industry), is quite small. The challenges that these companies have to face with are, generally, further improvements of the production processes (in order to obtain higher standards of quality), and the manufacture of products in the respect of strict technical safetyoriented specifications, established by regulatory Bodies (Pisano and Wheelwright, 1995); † companies that produce and sell services, that are companies of recent constitution that provide research (e.g. chemical synthesis, cloning and sequencing) to other companies. Generally, the capital required to start up this type of entrepreneurial mission is lower than the capital required by other companies previously described; † integrated companies that sell their products to other companies: these are firms focused on the use of biotechnologies in the development of production processes (e.g. production of monoclonal antibodies, cells and proteins), often in collaboration with the customer, and that end their role with the supply of the product (Cockburn et al., 1999). In Italy, this type of business has not yet been adopted by a large number of companies, due to the fact that biotechnologies have been applied prevalently in research processes rather than in the new product development. The five categories described above resulted by a close review of the literature and, additionally, by an empirical survey. In particular, the hypothesis on the first four models arose for the most part by the analysis of the data collected, while for the fifth category it is resulted of more valuable the review of the actual literature. For this reason, it is not possible, with the data available up to now, to state some hypotheses on the fifth category; therefore, it will be the object of further study. The aim of the present work is to study in depth and to verify the results regarding the four emergent business models through a statistical analysis, using the database made up in the previous work by the same authors. Specifically, the objective of this research is, first, to verify the existence of clusters of companies with similar characteristics, that are internally homogeneous groups (but heterogeneous among them). These clusters will be then compared with the four models in order to check for

consistency with our previous work and the emerging literature. If the results will confirm these hypothesis, it will represent a statistical evidence of the existence of these four business models, and the next step of the research will be the analysis of a single representative case, with the purpose to specify and outline in depth the features of each model.

2. The context The present study has analyzed the Italian companies that develop new biotechnological application in order to obtain new products/processes or to improve the existing ones (e.g. fermentation, DNA recombination techniques, etc.). According to the Organisation for Economic Cooperation and Development (OECD, 1989), biotechnology consists in the use of scientific and engineering principles (based on microbiology, genetic, biochemistry, chemical and biochemical engineering) to transform materials using biological agents, (such as micro organism, enzymes, animal or vegetable cells), with the purpose to obtain products and services. OECD, in order to make more understandable the different employments of biotechnologies, has classified it into three categories: † classic biotechnologies: age-old biotechnologies, such as fermentation; † recent biotechnologies, asserted after the industrial revolution: this type of biotechnology has allowed to obtain vaccines, enzymes and hybrids; † new biotechnologies, well-established after 1970, principally because of the discovery of techniques such as DNA recombination and cellular fusion. The recent discovery related to genetic engineering can be considered the ‘propelling element’ that has greatly increased and spread the possible uses of biotechnologies. In fact, the industries in which these technologies are at present developed are numerous and they mainly take in healthcare, agriculture and zootechny, feeding, fine chemistry, environment, instrumentation (see website: www.assobiotec.it; Spalla, 1996; Alberghina and Cernia, 1996; Nosella et al., 2004). The United States have been the pioneer country in the development of the new biotechnologies: in this country in fact, since the beginning of the 1980s, a network of small biotechnological firms (named NBFs), developing industrial applications out of genetic engineering started up. NBFs are small research firms interested, for example, in protein production, discovery of a new drug or in the supplier of some services. Usually, they are not able to complete the whole innovative path, and for this reason they create buyer-supplier relationships with larger firms, characterized by a consolidated presence into the industry (the so called


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Table 1 Main variables in the questionnaire Geographical location

Age (yr)

Type of biotechnology used

North

Traditional

Centre South

New

Turnover in 2002 (million of V)

No. of employees

Activities carried out

Main industries

Applied research and experimental development Clinic development Industrial development Production and commercialization

Pharmaceutical Diagnostic Agro-zootechny Food Chemical Instrumentation Services and environment

Established Company, EC) (Petroni and Verbano, 2001; Passaro and Vittoria, 2000; Powell, 1998; Cockburn et al., 1999). It is possible to maintain that the American biotechnological industry is organized according to a network model whose units are universities, private and public research institutes, small biotechnological and established firms. These organizations have to operate into a system of collaborations and interactions rather than into a system of competition. In particular, small firms represent the ‘trait d’union’ between the academic and the industrial world, because they link the scientific community (depository of knowledge) and the technological community (oriented to the possible industrial exploitation of scientific knowledge) (Buratti, 1991); most of these firms are academic spin-offs and, often, their founders go on in maintaining strong relationships with the academic research institutes (Buratti, 1991). In Europe, with the exception of the United Kingdom, the business of biotechnology is born later than in the United States. Also in Italy, although there has been over the last years an important tradition in the chemical-pharmaceutical and agriculture/food sectors, recent applications offered by biologic technology are spreading over the country lately compared with the United States and with the main European countries. Due to the dynamics that have characterized the development of biotechnological industry in the United States, it seems interesting to understand the way of biotechnologies’ diffusion in Italy, with particular regards to the different business models shown by domestic companies.

a questionnaire was sent to each company in order to gather information regarding the aspects shown in Table 1, where a list of the corresponding variables is also shown. All of the companies in the sample returned a questionnaire, for a return rate of 100%, even if some questionnaires were not complete. As regards the geographical distribution, 74% of the companies are located in the Northern Italy (34% in the Lombardia district alone), 11% in Southern Italy and the remainder 15% in Central Italy. The companies taken into consideration are young companies, in fact 30 and 59% have been founded in the last 6 and 10 years, respectively, while only 15 are 20 years old or older. Size is consistent with age: it was pointed out that 59% of companies has less than 50 employees. Finally, as concerns the field of activity, the most important one is the pharmaceutical industry (53%), followed by the diagnostic industry (31%), agriculture-zootechny and food industry (20%) and service industries (only 15%). For further details about the database see the previous work of the same authors (Nosella et al., 2004). 3.2. Cluster analysis As specified in the first paragraph, the aim of this study was to answer two research questions: † Can the Italian biotechnological companies be grouped into clusters characterized by internal homogeneity and external heterogeneity? † If it is possible, do these clusters outline the four theoretical business models hypothesized at the end of the first study?

3. Methodology 3.1. The database As already said, the group of companies examined was built up in the previous research, using a census of Italian entrepreneurial organizations that develop new industrial applications out of biotechnologies in order to obtain new products/processes or to improve existing ones (Nosella et al., 2004). This census identifies 100 companies and

In order to answer these questions, we have applied a cluster analysis using the software SPSS: this statistical technique makes it possible to group the analyzed subjects (the companies) on the base of the likelihood of values scored by a set of variables (called grouping variables) The grouping variables that have been considered are five: age, size, degree of newness of the biotechnologies used, level of R&D integration and level of industrialization/services of the sector. In order to define the grouping variables,

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Table 2 Definition and codification of grouping variables Grouping variables (1) Age (2) Size (3) Degree of newness of biotechnology used (4) Level of R&D integration (5) Level of industrialization/ services of the sector

Codified values 1

2

3

Less than 5 years Less than 20 employees Traditional

Between 6–10 years Between 21–50 employees Traditional and new

More than 10 years More than 50 employees New

NBF Food and zootechny

Manufacturer Pharmaceutical, pharmaceutical and diagnostic

Integrated Environment, services, diagnostic

the variables gathered into the database have been recodified as shown in Table 2. It is suitable, as far as the level of R&D integration is concerned, to specify that: † the New Biotechnology Firms (NBFs) are companies whose main activities are Applied Research and/or Clinic Development (if they belong to the pharmaceutical industry), and/or Industrial Development. In other words, NBFs are specialized research-based companies that typically offer a prototype or a pre-prototype (to be developed and sold out on the market) to firms that belong to the same industry; † the manufacturer companies operate in the last stage of the innovative process: industrial development, production and commercialization, and even some stages related to the clinic development if they belong to the pharmaceutical industry; moreover, they often outsource applied research; † the integrated companies carry out the whole chain of activities from applied research to production and commercialization. With the purpose explained above in mind, hierarchical clustering analysis was conducted in order to identify the critical features of homogeneous firms and intergroup differences. A set of clustering criteria were carefully considered in order to select the most appropriate one: the hierarchical method, and in particular a complete linkage’s method, proved to be particularly effective for differentiation. Agglomerative hierarchical algorithm starts with n clusters, where n is the number of observations. The distance between observations is calculated and the two closest points are merged into a cluster. The process iterates until all observations are included in one cluster. Distances among clusters were measured using the Euclidean distances. Four clusters emerged from the statistical analysis. The criteria adopted for settling down for a four-clusters solution are both statistical and conceptual, in that it is selected analysing the resulting dendogram and, moreover, it provides a deeper understanding of business models investigated, compared with a three-clusters solution.

As a validity check we verified that the results provided by the complete linkage’s methods are similar to the cluster solutions produced by the Ward’s method, in terms of cluster centroid.

4. Results: description of clusters In Fig. 1 the dendrogram is reported: it shows the hierarchical clustering obtained using the method previously described. In abscissa it is reported the quadratic Euclidean distance between clusters, while the first column reports the identification’s code of each company grouped with the complete linkage’s method (vertical line). As shown in Fig. 1, it emerges the existence of four clusters: each cluster takes in 23, 19, 14 and 22 firms, respectively. The four clusters show, for each grouping variables, the average values reported in Table 3. Table 4 shows the analysis of variance between clusters and within cluster (Cluster means square and error mean square), F value and P value (Significance): the results show that all clusters are statistically different each other in four out of five cases, with a P value equal to 99%, and for all the variables with a significance level of 95%. From Table 4 we can also postulate that the variables ‘level of R&D integration’ and ‘level of industrialization/services of the sector’ are the most influencing the profile of clusters (FZ 438.163 and FZ49.908, respectively), while age is the less influencing variable. The distinct characteristics of the firms belonging to the four clusters are summarized in Table 5 and described below: † Firms belonging to cluster 1 operate in different industries (services, environment, diagnostic), are very small (up to 20 employees) and were set up less than 10 years ago (between 6 and 10 years); they use both new and traditional biotechnologies and carry out all the stages of innovative path internally (integrated). Then, they can be defined ‘Services Companies’. † Taking a closer look at Table 5, it emerges that the firms belonging to cluster 2 are specialized in the early stages of the innovative process. These firms are


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Fig. 1. Dendrogram resulting from the hierarchical cluster analysis using with the complete linkage’s method.

mainly young (average age !6 years), of small size (staffing between 21 and 50 employees), and use both traditional and new biotechnologies. As far as the industry is concerned, they operate mostly in the pharmaceutical and, often, in both pharmaceutical and diagnostic industries. Thus, they could been termed ‘Research Companies’ (NBF). † Clusters 3 and 4 are both characterized by vertically integrated and fairly established firms, but they result different because of various reasons:

† firms in cluster 3 are characterized by larger size (more than 50 employees), operate in the pharmaceutical or pharmaceutical and diagnostic industry, and they mostly use traditional and new biotechnologies. This cluster identifies a subcategory of the business model termed ‘Integrated Firms’, the so called ‘Industrialized Integrated Firms’; † on the contrary, firms in cluster 4 are smaller (between 21 and 50 employees), they are less industrialized than firms belonging to cluster 3, operate in traditional

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Table 3 The clusters obtained and average values of grouping variables Cluster

No. of cases

1 2 3 4 Total a

24 19 25 10 78a

Grouping variables 1

2

3

4

5

Age

Size (no. of employees)

Degree of newness of the BT used

Level of R&D integration

Level of industrialization/services of the sector

2.1 1.7 2.4 2.4 2.2

1.0 1.9 2.8 2.0 2.0

1.7 1.9 1.8 1.0 1.7

3.0 1.0 3.0 2.7 2.5

2.8 1.9 2.3 1.0 2.2

F

Sig.a

It has been excluded by the analysis the cases with missing data.

Table 4 Analysis of variance (ANOVA) between and within clusters Cluster

Age Size Degree of newness of the BT used Level of R&D integration Level of industrialization/services of the sector a

Error

Mean square between groups

df

Mean square within groups

df

2.278 13.206 2.176

3 3 3

0.622 0.368 0.314

74 74 74

3.665 35.842 6.922

0.016 0.000 0.000

18.109

3

0.041

74

438.163

0.000

8.057

3

0.161

74

49.908

0.000

Probability at one tail that the variances of the cluster are not sensibilly different.

industries (such as agro-zootechny and food), and use mostly traditional biotechnologies. Then, this cluster has been named ‘Traditional Integrated Firms’, and belong to the business model ‘Integrated Firms’.

5. Discussion and conclusions This study has helped to get a better insight into the characteristics of biotechnological firms in Italy. By analyzing the results of this study, it emerges the existence of four clusters grouping biotechnological firms; these clusters have proved to be statistically different in terms of the defined grouping variables (geographical location, age, size, level of newness of the biotechnologies used, level of R&D integration and level of industrialization/services

of the sector). The statistical evidence confirms the existence of the three business models hypothesized, that is ‘Services Companies’, ‘Small Research Firms’, named NBFs, and ‘Integrated Companies’. The latter cluster (‘Integrated Firms’), can be further split into two distinct subgroups named ‘Traditional Integrated Firms’ and ‘Industrialized Integrated Firms’, respectively. The fourth business model, ‘Manufacturing Firms’, has not shown statistical significance due to the limited presence of this type of firms in Italy. By analyzing the characteristics of these clusters, we can maintain that the development of biotechnological industry in Italy has followed principally two patterns: † the first involves the integrated firms that have often introduced, by using new biotechnologies, new products or manufacturing processes in support of their traditional

Table 5 The profile of the clusters obtained Cluster

Age

Size (no. of employees)

Degree of newness of the BT used

Level of R&D integration

Level of industrialization/ services of the sector

Business models

1 2 3 4

Young Very young Older Older

Very small Small Medium and big Small

Traditional and new Traditional and new Traditional and new Traditional

Low (integrated) High (NBF) Low (Integrated) Low (integrated)

High (terziary) Medium (secondary) Medium (secondary) Low (traditional primary and secondary)

Services companies NBF Integrated companies Traditional Integrated companies


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core business. These are frequently large firms that diversified their consolidated distinctive competences through massive investment in innovative biotechnologies. In this context, an impulse, even if moderate, to the development of biotechnological industry, has come also by the integrated firms operating in more traditional biotechnologies such as the agriculture-zootechny and the food ones with less innovative product-embodied technologies. † The second is, vice versa, characterized by the presence of new firms, mainly focused on development stages. Among this group, in fact, we can find a considerable number of companies (29.5% of the total number) of smaller size belonging to the services sector. These firms could be depicted as specialized suppliers of services towards large customers that outsource these activities. More recently, small research companies (24% over the total) have appeared on the competitive arena, whose innovative capabilities are based on broader knowledge heritage and a superior technical–scientific competences. They, consequently, need a start up capital higher than services companies. This phenomenon, that has taken place only in the last years, has been stimulated by the dynamics of merge and acquisitions that have characterized the industry (Orsenigo, 2001) and, on the other hand, by the slow diffusion of new financing instruments, supporting the growth of new entrepreneurial initiatives (Lee et al., 2001).

entrepreneurship could be the capabilities of Universities and public research centres to generate spin-offs and new business ventures able to operate autonomously on the marketplace. Further research efforts will be aimed towards deepening of the business models that have been identified and, with the present study, also statistically validated. One possible research rout will address the study of distinctive competences of firms belonging to the different business models. In this way, the analysis will be focused on the individuation of core capabilities that make it possible for these firms to reach a lasting competitive advantage. Then, the identification of successful strategic competences and the mechanisms of their generation may help both researchers and practitioners to get an insight on entrepreneurial patterns, innovative processes and capability-building paths within this industry. Last but not least, possible feature guidelines of research could include the investigation of the last business model (‘Integrated Companies that sell their products to the other companies’), that was identified in the previous work through a close review of the literature but that did not empirically emerged from the present analysis.

A comparison of the Italian model of industry development with that of the main industrialized countries (Allansdottir et al., 2001), highlights the singularity of the role played by the ‘Industrialized Integrated Companies’. In the main Industrialized Countries innovative path is, typically, the result of a marked division of activities and discipline-related specialization. According to this model in fact the network of firms operates as a whole but it shares competences and business related risks. In this perspective, the experience of United States emerges as emblematic: virtuous network between Universities and research institutes has forced the establishment of NBFs, specialized in the introduction of innovative biotechnological products/ processes, and also of big companies, able to carry out meaningful process innovations (Buratti, 1991; Gambardella, 1996). Another distinctive feature is that in the US and in some European countries new biotechnologies firms are, in most cases, academic spin-offs that exploit the scientific knowledge and competences available in research centres to deploy new business. In Italy, this phenomenon is still negligible (Alberghina and Chiesa, 2002), despite it is widely acknowledged the presence of a noteworthy scientific knowledge base in different research institutes. Thus, the theoretical debate on the development of biotechnology in Italy almost unanimously agrees that one of the major drivers for the birth and growth of

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Barbara Bigliardi graduated in Engineering Management cum laude from the Faculty of Engineering of the University of Parma. She is studying for a Ph.D in Industrial Engineering at the Department of Industrial Engineering in the same faculty. Her major research interests are in the areas of Human Resources Management and Innovation Management.

Anna Nosella is a research fellow at the Department of Management and Engineering. She received her PhD in Engineering Management and Economics; her main research interests are on Human Resources Management and Innovation Management.

Chiara Verbano is a Researcher at the Department of Industrial Engineering at the University of Parma. She received her PhD in Engineering Management and Economics from the University of Padua. Her major research interests are in the areas of R&D management and innovation management.