Organisational modes for Open Innovation in the bio-pharmaceutical industry: An exploratory analysis

Technovation 31 (2011) 22–33

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Technovation journal homepage: www.elsevier.com/locate/technovation

Organisational modes for Open Innovation in the bio-pharmaceutical industry: An exploratory analysis Mattia Bianchi 1, Alberto Cavaliere 2, Davide Chiaroni 3, Federico Frattini n, Vittorio Chiesa 4 Politecnico di Milano, Department of Management, Economics and Industrial Engineering, Piazza L. da Vinci 32, 20133 Milano, Italy

a r t i c l e in f o

Keywords: Open Innovation Inbound Open Innovation Outbound Open Innovation Bio-pharmaceutical industry Biotechnology

a b s t r a c t This paper investigates the adoption of Open Innovation in the bio-pharmaceutical industry, studying through which organisational modes it is put into practice and how these modes are interwoven with the different phases of drug discovery and development process. Two rounds of interviews with industry experts were carried out to develop a model describing the adoption of Open Innovation by bio-pharmaceutical companies. This framework was then applied to an extensive and longitudinal empirical basis, which includes data about the adoption of Open Innovation by the top 20 worldwide industry players, in the time period 2000–2007. The paper provides a thorough discussion of how biopharmaceutical firms have used different organisational modes (i.e. licensing agreements, non-equity alliance, purchase and supply of technical and scientific services) to enter into relationship with different types of partners (i.e. large pharmaceutical companies, product biotech firms, platform biotech firms and universities) with the aim to acquire (Inbound Open Innovation) or commercially exploit (Outbound Open Innovation) technologies and knowledge. The implications of the study for Open Innovation research and possible avenues for future investigation are discussed at length in the paper. & 2010 Elsevier Ltd. All rights reserved.

1. Introduction Since the early work of Chesbrough (2003), Open Innovation has ranked very high on the agenda of innovation and technology management scholars (Christensen et al., 2005; Gassmann, 2006; Vanhaverbeke, 2006). According to Chesbrough (2003), firms have traditionally invested in large R&D functions with the aim to maximize innovation and to nurture their competitiveness and growth through the improvement of existing products, services and processes as well as the introduction of radically new ones. This ‘‘closed’’ approach to innovation is ‘‘a view that says successful innovation requires control. Companies must generate their own ideas, and then develop them, build them, market them, distribute them, service them, finance them, and support them on their own’’ (Chesbrough, 2003, p. 20). However, this framework has become no longer sustainable in several industries where some ‘‘erosion’’ factors are in place (i.e. the growing mobility of technical professionals and knowledge workers, the increasing role of private venture capital, the birth and expansion of a market

n

Corresponding author. Tel.: + 39 02 2399 2796; fax: + 39 02 2399 2720. E-mail addresses: [email protected] (M. Bianchi), [email protected] (A. Cavaliere), [email protected] (D. Chiaroni), [email protected] (F. Frattini), [email protected] (V. Chiesa). 1 Tel.: + 39 02 2399 3997; fax: + 39 02 2399 2720. 2 Tel.: + 39 02 2399 2797; fax: + 39 02 2399 2720. 3 Tel.: + 39 02 2399 2775; fax: + 39 02 2399 2720. 4 Tel.: + 39 02 2399 2761; fax: + 39 02 2399 2720. 0166-4972/$ - see front matter & 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.technovation.2010.03.002

for technologies). Here a new approach has emerged, which assumes that firms ‘‘can and should use external ideas as well as internal ones, and internal and external paths to market’’ to make the most out of their technologies (Chesbrough, 2003, p. 24). This model is based on the recognition that valuable technologies and pieces of knowledge may originate from both within and outside the firm’s boundaries, and that innovation can be commercially exploited both internally, in the forms of new products and services sold into the market, and externally, i.e. disembodied from physical artefacts. The Open Innovation model captures a number of changes in firms’ approach to strategic management of technology that have emerged over the years as a response to significant modifications in the competitive environment, e.g., increased dynamicity and turbulence (Wolf, 2006), the globalisation of markets and business activities, accrued competition (Gupta and Wilemon, 1996) and rapid advances in technology development (Bayus, 1994). These changes include the end of the linear model of innovation (Ortt and Smits, 2006), firms’ increased reliance on external sources of technology (Chatterji, 1996; Roberts, 2001), their enhanced attitude toward using multiple channels for technology exploitation (Lichtenthaler, 2004) and the internationalisation of industrial R&D and innovation activities (Jones and Teegen, 2002). This paper adds to our understanding of the Open Innovation paradigm investigating the adoption of this model by firms in the bio-pharmaceutical industry. This industry includes firms that carry out the research, development, manufacturing and

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commercialisation of pharmaceutical products having biological sources, usually involving live organisms or their active components, and being created by biotechnology methods (see also www.bio.org). In particular, this paper adopts a longitudinal perspective to study how bio-pharmaceutical companies have organised over time to exchange technologies and pieces of knowledge with different classes of external organisations (e.g., universities, competitors) along the different stages of the R&D and innovation development process (e.g., drug discovery and drug development). The analyses reported in the paper contribute to the existing research on Open Innovation, studying the adoption of this approach in an industry where the use of Open Innovation practices has been rather under-researched so far. Furthermore, managers will hopefully find the arguments developed in the paper useful to understand the potential of Open Innovation for bio-pharmaceutical firms and the organisational alternatives they could rely on. The paper is structured as follows. The next section reviews the relevant literature on the adoption and organisational implications of Open Innovation with a focus on the bio-pharmaceutical industry. The third section describes the research strategy adopted in the paper, whereas the fourth one reports and discusses the results of the empirical analyses. Finally, some conclusions and future directions of research are outlined.

2. Literature review and research framework As mentioned above, in the last section, Open Innovation is a largely debated issue in innovation and technology management literature. However, many topics related to Open Innovation remain largely unexplored and require further theoretical and empirical research to be fully understood. In particular, two gaps can be identified, which are relevant in the light of the purpose of this paper: (i) there is a paucity of contributions that analyse how and to what extent firms operating in a given industry implement Open Innovation and (ii) there are few contributions that look at how firms organise themselves to make the most out of Open Innovation, i.e. on the organisational implications of this emerging innovation management paradigm. 2.1. Literature review As far as the first gap in the literature is concerned, it should be noted that Chesbrough documented the emergence of Open Innovation mainly in high-technology industries, e.g., Lucent, 3Com, IBM, Intel, Millennium Pharmaceuticals (Chesbrough, 2003). Since then, there have been some attempts to investigate the adoption of Open Innovation in mature, asset intensive contexts. For instance, Chesbrough and Crowther (2006) surveyed 12 firms in the US, which were identified as ‘‘early adopters’’ of Open Innovation in the aerospace, chemicals, inks and coatings, and consumer packaged goods industries. They showed that Open Innovation practices are not widespread in use, although the sampled firms have sharply increased their attitude toward leveraging external sources of innovation to complement their internal R&D activities during the last years. Vanhaverbeke (2006) studied a sample of Dutch innovative SMEs working in mature industries and found that they often use processes for accessing external sources of technologies and knowledge, whereas they perceive relevant barriers when it comes to commercialize technologies disembodied from physical artefacts, e.g., through out-licensing agreements or sale of technologies. Finally, Chiaroni et al. (2010) described the anatomy of the organisational change process through which a sample of Italian firms working in mature, low-technology industries revolutionised their approach

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to innovation from a ‘‘closed’’ to an ‘‘open’’ paradigm. A few contributions can be also found in the literature that attempt to unravel the adoption of Open Innovation in a specific industry. For instance, Christensen et al. (2005) studied Open Innovation from an evolutionary economic perspective, focusing on a specific sectoral system of innovation (i.e. consumer electronics) and studying the industrial dynamics associated with the development of the class D amplifier technology. Sarkar and Costa (2008) provided a review of the literature contributions that document the use of Open Innovation practices in the food industry, where firms have been increasingly opening up to external sources of knowledge in search of successful new products and technologies. Finally, a recent book by Fasnacht (2009) discussed the use of open business models and strategies in the context of the financial service industry. Besides these scattered contributions, literature has not systematically investigated so far how firms belonging to a given industry adhere to the Open Innovation paradigm, although this would be a fundamental prerequisite to enhance the external validity of the model, as noted by West et al. (2006) in the research agenda for Open Innovation that they put forward in the concluding chapter of their book. As a result of this gap in the literature, the adoption of Open Innovation in the bio-pharmaceutical industry has not been systematically documented so far. Besides sparse anecdotic evidence (e.g., the description, reported in Chesbrough (2003), of the innovation strategy adopted by Millennium Pharmaceuticals), and some contributions published in the specialistic and sectoral literature (e.g., Munos, 2006; Smits and Boon, 2008) to the best knowledge of the authors there is only one scholarly contribution (Fetterhoff and Voelkel, 2006), which adopts a managerial perspective to study Open Innovation in bio-pharmaceutical firms. The authors proposed a model of the external innovation value chain, which comprises the following five stages: (1) seeking opportunities; (2) evaluating their market potential and innovativeness; (3) recruiting potential partners for the development of the opportunity; (4) capturing value from commercialisation and (5) extending the innovation offering. This model is intended to be of help for bio-pharmaceutical firms to capture the full value of the inter-organisational relationships they establish with external technology providers, and is developed through examples drawn from Roche Diagnostics’s experience. Notwithstanding this limitation of the existing literature, it is believed that the bio-pharmaceutical industry has several features that make it a fertile ground for the adoption of Open Innovation and therefore for studying its managerial and organisational implications. This is clear if we consider its soaring technology intensity (DeCarolis and Deeds, 1999), the complexity of the bio-pharmaceutical innovation and technology development process, and the heterogeneity of the competences it requires (Koput et al., 1996), the importance of technology transfer for the development of the industry as a whole (Madhok and Osegowitsch, 2000), the intensity of relationships between bio-pharmaceutical firms, universities and research centres (Owen-Smith et al., 2002) and the birth of a venture capital market, at least in Anglo-Saxon countries, specialized in supporting biotech ventures (Powell et al., 2002). A recent paper by Xia and Roper (2008) further documents the critical role of alliances between bio-pharmaceutical firms in both US and European contexts. As far as the second gap in the literature is concerned, Open Innovation research has started only recently to investigate how firms organise themselves and modify their management practices to ease the implementation of the new innovation management paradigm. Mainly anecdotic and exploratory results have been produced so far on this topic. For instance, Huston and Sakkab (2006) documented the use of different forms of networks

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and illustrated the anatomy of the strategic planning process, which are at the heart of the Open Innovation approach of Procter & Gamble, also known as ‘‘Connect & Develop’’. Haour (2004) described the organisational modes used by Generics to support the operation of its ‘‘distributed innovation’’ system, whereas Kirschbaum (2005) explained how the multinational life science and material science firm DSM has built a teamwork and entrepreneurial culture for Open Innovation. Dittrich and Duysters (2007) studied how innovation networks can be used to cope with a changing technological environment, making explicit reference to the innovation networks leveraged by Nokia to develop the GSM and UMTS technologies. These firms appear to have developed superior network resource combination capabilities, a concept recently introduced by Tolstoy and Agndal (2010) to identify the capability that allows companies to draw on and combine complementary resources available in the networks. Furthermore, Laursen and Salter (2006) identified, through a survey of UK manufacturing firms, two variables that describe the characteristics of a network for innovation, namely its search breadth and its search depth. Finally, van de Vrande et al. (2006) studied the criteria affecting the choice of the governance modes for external technology sourcing under an Open Innovation perspective, whereas Huang et al. (2009) showed that the financial benefits of external technology sourcing depend on the type of incremental innovation developed by the acquiring firm, it being marginal or adaptive. From this brief literature analysis it clearly emerges that a structured theory of the managerial and organisational impact of Open Innovation has not been developed yet.

2.2. Research framework This paper contributes to fill these gaps in the extant literature, focusing on the organisational modes through which biopharmaceutical firms open up their innovation processes and enter into relationships with external organisation to exchange technologies and knowledge. As far as the organisational modes are concerned, it is necessary to distinguish two dimensions of the Open Innovation paradigm, namely ‘‘Inbound’’ and ‘‘Outbound’’ Open Innovation (Chesbrough and Crowther, 2006). Inbound Open Innovation is the practice of leveraging the technologies and discoveries of others, and it requires the opening up to, and the establishment of inter-organisational relationships with external organisation with the aim to access their technical and scientific competencies. Outbound Open Innovation is instead the practice of establishing relationships with external organisations to which proprietary technologies are transferred for commercial exploitation. Working on the concepts developed by March (1991), Inbound Open Innovation serves the purpose to improve the firm’s ‘‘exploration’’ capabilities in innovation management, whereas Outbound Open Innovation is very much related to the ‘‘exploitation’’ of the firm’s current basis of knowledge and technologies (He and Wong, 2004). Literature has documented the use of different organisational modes through which Inbound and Outbound Open Innovation can be put into practice (Grandstrand, 2004; Lichtenthaler, 2004, 2005). Widespread organisational modes for Inbound Open Innovation are: in-licensing, minority equity investments, acquisitions, joint ventures, R&D contracts and research funding, purchase of technical and scientific services and non-equity alliances. Typical organisational modes for Outbound Open Innovation are instead: licensing out, spinning out of new ventures, sale of innovation projects, joint venture for technology commercialisation, supply of technical and scientific services, corporate venturing investments and nonequity alliances.

Furthermore, literature has shown that these organisational modes are used by Open Innovation firms to establish relationships with a number of heterogeneous actors, as noted also in recent reports (OECD, 2008; von Hippel, 2005; Perkmann and Walsh, 2007; EmdenGrand et al., 2006). The taxonomy of partners for Open Innovation suggested in the OECD report comprises suppliers, customers, competitors, consultants, private R&D institutes, universities and other higher education, government and public research. Finally, the organisational modes that a firm selects and the type of partners with which it enters into relationships vary substantially along the phases of the R&D process (e.g., basic research, applied research, development, launch), because they are characterised by very dissimilar requirements in terms of level of investments, risk, uncertainty and need for exploring new knowledge rather than exploiting existing one (Chiesa, 2001). This is particularly true in the bio-pharmaceutical R&D process, which can be roughly divided into two stages, namely drug discovery and drug development (Muffatto and Giardina, 2003; Chiesa, 2003; Chiesa and Chiaroni, 2004; Gassmann and Reepmeyer, 2005; Chiaroni et al., 2007). Drug discovery includes the following activities: (i) target identification and validation, where a new gene or protein or a sequence of both (target) is selected for potentially being pathogenic of a selected disease, and it is then initially validated by searching extant data about interactions with the human organism and about previously filed patents that might eventually protect the target and (ii) lead identification and optimisation, where a new biological compound is identified for addressing the target and treating the related disease and it is chemically stabilised with the adjunct of excipients (i.e. substances included in the drug formulation) with the aim to turn it into the active principle of the future drug. At this point, the drug development process begins, which comprises the following three activities. (i) Pre-clinical tests, where the mechanisms of absorption, distribution, metabolism, excretion and toxicology of the new drug are studied and its effects are initially tested on animals. At the end of the pre-clinical tests a first approval by public authorities is needed to proceed with the development. (ii) Clinical tests, divided into Phase I, Phase II and Phase III (Muffatto and Giardina, 2003), where human patients are involved with the aim to test the safety and to assess the effectiveness of the new drug. If the response of these tests is positive, the new drug obtain the approval by public authorities to reach the market.

Types of partners

Organisational modes Phases of the R&D process

Time Fig. 1. Schematic representation of the research framework.

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(iii) Post-approval activities, where the new drug is actually produced, marketed and sold and where additional information on its risks, benefits and optimal use in the middle-term are collected through the so called post-marketing tests. This brief analysis suggests that in order to address the research question of the paper the framework underlying our research should comprise three main variables: organisational modes for Open Innovation, types of partners and phases of the R&D process. As indicated in Fig. 1, our empirical analysis will attempt to explore how the relationships between the three variables have evolved over time in the bio-pharmaceutical industry. In the next section, the methodology of our empirical analysis will be described in depth.

Table 1 List of participants in the expert interviews. Position

Organisation

Corporate Affaire Director Director

Amgen Assobiotech—Italian association of biotech companies ATA—Advanced Technology Assessment

Life Science Senior Consultant Chief Executive Officer Business Development Manager Chief Executive Officer Chief Executive Officer Full Professor Director

3. Research methodology The research strategy devised to pursue the paper’s objective is made of two steps with the following purposes: (i) to operationalize the research framework presented in the last section in the bio-pharmaceutical industry, taking into account the peculiarities of R&D and innovation activities carried out by bio-pharmaceutical firms and (ii) to use the framework developed in the previous step to collect and interpret data in the scope of a longitudinal study involving a number of leading bio-pharmaceutical companies. As far as the first step of the research is concerned, two rounds of expert interviews were organised and carried out with 20 key informants (business development managers, R&D directors, Chief Executive Officers of bio-pharmaceutical companies, as well as academics and consultants with a significant experience in the field), who are among the most knowledgeable Italian experts of the bio-pharmaceutical industry. The list of the participants who took part in each round of interviews is reported in Table 1. The interviews have been conducted directly by the authors. The experts were provided with the list of the organisational modes for Open Innovation and the types of partners developed through the literature analysis and are presented in the last section of the paper. They were asked to discuss through which organisational modes and with which partners bio-pharmaceutical firms are used to enter into relationships along the different phases of the drug discovery and development process. Moreover, they were asked to identify any contextual variables that could explain how bio-pharmaceutical firms interact with external organisations. It should be noted that the Open Innovation concept has not been superimposed to the experts involved in the analysis but our research was presented as an investigation of the patterns of inter-organisational collaborations in the bio-pharmaceutical industry. Only at the end of the second round of interviews, the Open Innovation model was presented to the interviewees, most of which were already familiar with the concept. Interestingly, it emerged from the interviews that bio-pharmaceutical firms have developed over time several characteristics that can be interpreted as signs of the emergence of the Open Innovation paradigm: (i) they have deliberately established as a strategic priority to improve their relationships with external organisation in both Inbound and Outbound Open Innovation processes; (ii) they have often introduced a dedicated budget for the establishment and management of these external collaborations and partnerships and (iii) they have very often undergone a reorganisation of internal processes and practices to improve their ability to manage collaborative innovation activities. Further evidence corroborating the idea that bio-pharmaceutical firms have indeed conformed themselves to the principles of Open Innovation is presented in Section 4 and discussed in the conclusions of the paper. The information collected during the first interviews

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Senior Industrial Specialist—Health Sciences Chairman and Chief Executive Officer Manager Chief Executive Officer Business Development Manager Director R&D Chief Executive Officer Chief Executive Officer Head of External R&D Policy Chairman and Chief Executive Officer Business Development Manager

Axxam Bioindustry Park Canavese Bioxell Blossom Associates Department of Biotechnology—Universita degli Studi di Milano-Bicocca Department of Pharmacological Sciences—Universita degli Studi di Milano Ernst&Young

Gentium GlaxoSmithKline MolMed MolMed MolMed Newron NicOx Roche Siena Biotech Toscana Life Sciences

was compared and critically examined and the emerging interpretative model was provided to the key informants during the second round of interviews for validation. The definitive model was further discussed with two different experts (the Head of Business Development of Nerviano Medical Sciences and the Director of Business Development and Licensing of Nycomed, who were not involved in the two rounds of expert interviews) for external corroboration. Therefore, this first step of the research allowed the authors to develop a framework for investigating the organisational modes of Open Innovation in the bio-pharmaceutical industry, which will be presented at the beginning of the next section. In the second phase of the research, we identified the first 20 bio-pharmaceutical companies worldwide (on the basis of their market capitalisation at the end of December 2006, see Table 2) and, for each firm, we collected data about the Open Innovation modes they have been using in the different phases of the drug discovery and development process over time. Further details about the empirical analysis and, in particular: (i) the selection of the sample; (ii) the time period covered in the analysis, (iii) the type of data collected and (iv) the sources of the data, are provided in the following. First, it should be noted that the decision to focus on the top 20 biotech firms on the basis of their market capitalisation is consistent with the aim of the article. On one hand, companies listed on public stock exchange markets are required to disclose information about their R&D activities and this gives the authors the opportunity to access critical information about the organisational modes for Open Innovation they have been employing over the years. On the other hand, the firms included in our sample represent the top players in the industry and hence are more suitable to anticipate relevant trends and best practices in the management of innovation. Second, the time period covered by our study includes the years 2000–2007. This was done in the attempt to improve the relevance of the information gathered for

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M. Bianchi et al. / Technovation 31 (2011) 22–33

Table 2 List of companies in the sample. Name

Market capitalization, 29th December 2006 ($billion)

Genentech Amgen Gilead Sciences Celgene Genzyme Biogen Idec Serono Medimmune Elan Pharmaceuticals Amylin Pharmaceuticals Vertex Pharmaceuticals Cephalon Millennium Pharmaceuticals ImClone Systems PDL BioPharma Human Genome Sciences Medarex Alkermes BioMarin Pharmaceuticals MGI Pharma

85.8 85.7 32.0 19.8 17.7 17.7 12.7 7.9 5.8 5.6 5.0 4.8 3.6 2.7 2.6 1.7 1.7 1.6 1.6 1.5

the research with the efficiency of the data collection procedures. Moreover, 2000 is often the earliest year for which internal documentation and archival reports are available for the firms in the sample. The data that we collected concerned:

 The pipeline of innovation projects and new drugs under development for the firms in the sample.

 The number and typology of different organisational modes (as   



identified in the interpretative framework developed through the expert interviews) adopted by the firms. The phase of drug discovery and development process (as described in the relevant literature) that each of the above mentioned organisational modes refers to. The typology of partners involved (as identified in the interpretative framework developed through the expert interviews). The therapeutic area within which the object of each interorganisational relationship established by the firms in our sample can be classified (i.e. the target disease of a new drug). This was identified by our key informants as a relevant variable to explain the adoption of Open Innovation by bio-pharmaceutical companies. The size of the firms in the sample, measured through their market capitalisation and annual sales in 2006, which is a further firm-level, contextual variable suggested by the expert interviews.

As a primary source of information, the annual reports of the selected firms in the time period 2000–2007 have been analysed. Nevertheless, in order to validate the collected data, they have been triangulated with information taken from professional databases and reports (i.e. Recombinant Capital, Biospace Directory, Canadian Biotech). In particular, these databases were used to corroborate information about the pipeline of innovation projects and new drugs under development, the typology of partners involved in each inter-organisational relationship established by the firms in the sample and the phase of drug discovery and development process the organisational modes for Open Innovation refer to. Finally, it is necessary to notice that, for the purpose of the article, the identification of general trends is far more important than the completeness of the data collected for each firm in the sample. Indeed, even if comprehensiveness

might be ensured by the fact that the firms in the sample are listed on public stock exchanges, it is however reasonable to expect that, if omissions have occurred, they are randomly distributed in the sample, and hence they do not undermine the results of the analysis.

4. Results and discussion In this section we present the results of the empirical investigation. First, the framework of analysis developed with the help of the expert interviews is discussed. Then, the outcome of the longitudinal analysis is discussed at length. 4.1. Results from the expert interviews As a first step, the interviewed experts were asked to identify in which phases of the drug discovery and development process Inbound and Outbound Open Innovation dimensions are more likely to be implemented by bio-pharmaceutical firms. It emerged from our interviews that Inbound Open Innovation is likely to take place mainly in the first three phases of the drug discovery and development process, i.e. target identification and validation, lead identification and optimisation, and pre-clinical tests. It is chiefly in these stages that bio-pharmaceutical firms that are not able to master all the tasks and do not possess all the competencies required to undertake these activities enter into relationships with external organisations, either to leverage their innovation efforts or to access highly specialised knowledge and competencies. On the other hand, Outbound Open Innovation occurs mainly in the second part of the process, i.e. during clinical tests and post-approval activities. In these phases, bio-pharmaceutical firms are more likely to open up their boundaries to external organisations for exploiting the results of their innovation activities, ensuring a quicker and wider access to the market. Because of the intrinsic characteristics of the bio-pharmaceutical innovation process, it is only with the beginning of the clinical tests that the ‘‘candidate’’ drug reaches a stage of development that allows it to be commercially exploited. Before this point, the drug discovery and development process is mainly a ‘‘trial-anderror’’ activity, characterised by extremely high uncertainty and unpredictable outcomes. In clinical tests the development risk lowers and the process becomes much more formalised and externally visible. It is from this point, therefore, that opportunities for external commercial exploitation can be identified and pursued. In some cases, as noticed by our experts, commercial exploitation may start earlier than the end of pre-clinical tests (e.g., through out-licensing a candidate who has not yet completed these tests). Similarly, external organisations may be accessed for contributing to the generation of innovation even later on in the process (e.g., through in-licensing a candidate who has already entered the clinical tests phase). Nevertheless, as we wanted to investigate where Inbound or Outbound Open Innovation is ‘‘more likely’’ to take place, we set the distinction between these two dimensions of Open Innovation at the end of preclinical tests. Fig. 2 summarizes these discussions. The experts were then provided with the list of the organisational modes for Open Innovation developed through the literature analysis and they were asked to identify which of them, and others that could be missing from our taxonomy, bio-pharmaceutical firms are more likely to adopt in each phase of their innovation process. Furthermore, they discussed, starting from the taxonomy of partners for Open Innovation presented in Section 2, which types of external organisations bio-pharmaceutical firms are more likely to leverage along their innovation process. As far as

M. Bianchi et al. / Technovation 31 (2011) 22–33

OUTBOUND

INBOUND

TARGET IDENTIFICATION AND VALIDATION

27

LEAD IDENTIFICATION AND OPTIMISATION

CLINICAL TESTS PRE-CLINICAL TESTS

POST-APPROVAL ACTIVITIES Phase I

Phase II

Phase III

Fig. 2. Inbound and Outbound Open Innovation in the bio-pharmaceutical drug discovery and development process

SMALLMEDIUM PRODUCT BIOTECHFIRMS

OUT-LICENSING SUPPLY OF SCIENTIFIC SERVICES

TARGET IDENTIFICATION AND VALIDATION

LEAD IDENTIFICATION AND OPTIMISATION

ALLIANCE FOR GENERATION

PURCHASE OF SCIENTIFIC SERVICES

UNIVESITY AND RESEARCH CENTRES

CLINICAL TESTS PRE-CLINICAL TESTS

PLATFORM BIOTECHFIRMS

POST-APPROVAL

Phase I

IN-LICENSING

LARGE PRODUCT BIOTECHFIRMS

Phase II

Phase III

ACTIVITIES

ALLIANCE FOR EXPLOITATION

PHARMACEUTICAL FIRMS

Fig. 3. Open Innovation modes and partners along the phases of the drug discovery and development process.

the types of partners for Open Innovation are concerned, the experts suggested distinguishing between:

 Pharmaceutical firms, i.e. firms involved in the research,







development, production and commercialisation of drugs and with a portfolio of products already marketed, which is primarily made of ‘‘traditional’’, non-biotech products. They are usually large companies with a long history in the industry and a worldwide geographical presence. Product biotech firms, i.e. firms involved in the research and development (and in some cases also in the production and commercialisation) of new drugs and therapeutics based on biotechnology. They are relatively young firms all established after 1980. Platform biotech firms, i.e. specialized firms focused on the development and commercialisation of new biotech-based technologies (e.g., High Throughput Screening) and devices (e.g., diagnostic tools) used in the drug discovery and development process. Universities and public research centres, which carry out research in biotech-related disciplines or technologies.

As far as the organisational modes for Open Innovation are concerned, three viable alternatives have been identify for both

Inbound and Outbound Open Innovation. They are depicted in Fig. 3. Open Innovation modes used to implement Inbound Open Innovation are:

 Alliance, usually taking place in the target identification and





validation phases. Bio-pharmaceutical companies establish partnerships (without equity involvement) with other biotech firms, pharmaceutical companies, universities or public research centres with the aim to pursue a common innovative objective (e.g., the validation of a genetic target). Purchase of scientific services, usually related to the lead identification and optimisation phases. Through this organisational mode bio-pharmaceutical firms externalise to specialised players, usually platform biotech firms and, although less frequently, universities and research centres, a specific phase of their innovation process (e.g., the lead optimisation activity), under a well-defined contractual agreement (for further details on the role of technical and scientific services in the biotech industry see Chiaroni et al., 2007). In-licensing, usually taking place during pre-clinical tests. Bio-pharmaceutical firms acquire the rights to use a specific candidate typically from another biotech firm, a pharmaceutical company or, although less frequently, from a university.

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The organisational modes used to implement Outbound Open Innovation are instead:

 Alliance. Bio-pharmaceutical firms partner with another





company (a biotech firm or, more often, a big pharmaceutical company) for accessing some complementary assets (e.g., production capacity or distribution channels) required to commercially exploit the new drug. Supply of scientific services, usually related to the finalisation of pre-clinical tests and the first tasks of clinical tests. Biopharmaceutical firms provide to third parties (typically other biotech firms) technical and scientific services, which leverage the outcome of their discovery efforts. Out-licensing, usually taking place during clinical tests. Bio-pharmaceutical firms license out, generally to big pharmaceutical companies, the rights to use a new candidate they have discovered and developed.

The relationships between the organisational modes for Open Innovation, the types of partners and the phases of the drug discovery and development process were investigated empirically through the longitudinal study of the top 20 bio-pharmaceutical companies. The moderating impact of two contextual variables suggested by the experts was explored. Besides the firm’s size, they suggested taking into account of whether the bio-pharmaceutical company used a specific organisational mode for Open Innovation to develop a new drug in a core or a non-core therapeutic area. By core area we mean a therapeutic area where the firm either generates more than 50% of its overall revenues or focus more than half of its research projects (as emerging from the analysis of its innovation pipeline). A non-core area is a therapeutic area that has not been explored yet by the firm or has only a marginal role in its product portfolio and pipeline. 4.2. Results from the longitudinal analysis The analysis of the data about the top 20 bio-pharmaceutical firms has produced interesting results on the adoption of Open Innovation in the industry. Table 3 provides an overview of the organisational modes for Open Innovation recorded in our sample, distinguishing between those employed for Inbound Open Innovation and those for Outbound Open Innovation. The studied firms, in the period 2000–2007, put into action as a whole 1072 organisational modes for Open Innovation, on average about 54 for each firm. It clearly emerges from the analysis of Table 3 that organisational modes for Inbound Open Innovation are prevalent. They account indeed for about 62% of the total organisational modes collected in our sample and show a relatively stable trend, whereas Outbound Open Innovation modes account for the remaining 38%, reaching the peak (43.2%) in 2006. This indicates that bio-pharmaceutical firms open up their innovation process especially for Inbound Open Innovation, where the quest for innovative products (and enabling technologies) able to support business development of top players is the

main purpose. This is fairly more evident if we take into account also the size of the firms. The results of this analysis are reported in Table 4. The smallest among the studied firms (i.e. those with a market capitalisation lower than $2 billion and annual revenues below $200 millions) implement organisational modes for Inbound Open Innovation in about 70% of the registered cases, whereas in the largest firms (i.e. those with a market capitalisation higher that $10 billion or annual revenues above $1500 millions) the relative weight of Outbound Open Innovation reaches its maximum at about 44%. On one side, this is due to the relative greater maturity of the largest firms, most of which have a product pipeline (i.e. the number of new drugs under development in the different phases of the process) and a market coverage that is rather similar to those of large, ‘‘traditional’’ pharmaceutical firms. The largest firms have therefore relatively more chances to access external actors for commercially exploiting innovation. On the other side, and more interestingly, Table 4 supports the idea that size matters when Open Innovation is concerned. The largest firms implemented in the period under analysis on average 71 organisational modes of Open Innovation, 1.5 times more than the mediumsized (i.e. those with a market capitalisation between $10 billion and $2 billion or annual revenues between $1500 millions and $200 millions) and the smallest firms (45 and 44, respectively). This is consistent with many literature contributions in the field of Open Innovation (Chesbrough, 2003; Chesbrough and Crowther, 2006), which indicates that the new innovation management paradigm is more intensively adopted by large firms, whereas its diffusion among small- and medium-size firms is still being questioned (see, e.g., van de Meer, 2007). Table 5 reports the results of the analysis about the object of the different organisational modes for Open Innovation, whether it is related to a new drug that is within the firm’s core therapeutic areas or not. There clearly emerges a growing use, both in Inbound and Outbound Open Innovation, of organisational modes involving innovations that are outside the firm’s core business (i.e. core therapeutic areas). Starting in 2000, from around 35% for both Inbound and Outbound Open Innovation, the relative weight of non-core organisational modes has increased over time, reaching in the last 2 years covered by our analysis more than 60% of the sampled organisational modes for Inbound Open Innovation and 50% for Outbound Open Innovation. This trend is even more evident if we take into account only the largest firms in our Table 4 Organisational modes for Open Innovation by firm’s size (total numbers). Organisational modes Number (percentage)

Largest firms

Medium firms

Smallest firms

Inbound Open Innovation

278 (56.3%) 216 (43.7%) 494

228 (63.3%) 132 (36.7%) 360

151 (69.3%) 67 (30.7%) 218

Outbound Open Innovation Total

Table 3 Organisational modes for Open Innovation by year. Organisational modes Number (percentage)

2000

2001

2002

2003

2004

2005

2006

2007

Inbound Open Innovation

97 (57.7%) 71 (42.3%) 168

85 (62.0%) 52 (38.0%) 137

71 (59.2%) 49 (40.8%) 120

79 (63.7%) 45 (36.3%) 124

85 (64.4%) 47 (35.6%) 132

76 (67.3%) 37 (32.7%) 113

84 (56.8%) 64 (43.2%) 148

80 (61.5%) 50 (38.5%) 130

Outbound Open Innovation Total

M. Bianchi et al. / Technovation 31 (2011) 22–33

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Table 5 Organisational modes for Open Innovation by object (core vs. non-core therapeutic area). 2000 Organisational modes

Core

2001 Noncore

Core

2002 Noncore

Core

2003 Noncore

Core

2004 Noncore

Core

2005 Noncore

Core

2006 Noncore

Core

2007 Noncore

Core

Noncore

Number (percentage) Inbound Open 64 33 53 32 41 30 39 40 36 49 35 41 33 51 32 48 Innovation (66.0%) (34.0%) (62.4%) (37.6%) (57.7%) (42.3%) (49.4%) (50.6%) (42.4%) (57.6%) (46.1%) (53.9%) (39.3%) (60.7%) (40.0%) (60.0%) Outbound Open 45 26 33 19 31 18 27 18 26 21 20 17 33 31 24 26 Innovation (63.4%) (36.6%) (63.5%) (36.5%) (63.3%) (36.7%) (60.0%) (40.0%) (55.3%) (44.7%) (54.1%) (45.9%) 51,6% (48.4%) (48.0%) (52.0%) Total 109 59 86 51 72 48 66 58 62 70 55 58 66 82 56 74

Table 6 Organisational modes for Open Innovation by typology. Organisational modes Number (percentage) Inbound Open Innovation Alliances Purchase of scientific services In-licensing Outbound Open Innovation Alliances Supply of scientific services Out-licensing Total

2000

2001

2002

2003

2004

2005

2006

2007

54 (55.7%) 25 (25.8%) 18 (18.6%)

41 (48.2%) 25 (29.4%) 19 (22.4%)

30 (42.3%) 23 (32.4%) 18 (25.4%)

28 (35.4%) 25 (31.6%) 26 (32.9%)

34 (40.0%) 31 (36.5%) 20 (23.5%)

28 (36.8%) 25 (32.9%) 23 (30.3%)

48 (57.1%) 20 (23.8%) 16 (19.0%)

44 (55.0%) 12 (15.0%) 24 (30.0%)

34 (47.9%) 11 (15.5%) 26 (36.6%) 168

25 (48.1%) 13 (25.0%) 14 (26.9%) 137

17 (34.7%) 4 (8.2%) 28 (57.1%) 120

12 (26.7%) 4 (8.9%) 29 (64.4%) 124

23 (48.9%) 3 (6.4%) 21 (44.7%) 132

21 (56.8%) 3 (8.1%) 13 (35.1%) 113

30 (46.9%) 2 (3.1%) 32 (50.0%) 148

26 (52.0%) 2 (4.0%) 22 (44.0%) 130

sample, for which the percentage of non-core organisational modes for Open Innovation increased from about 40% in 2000 to nearly 70% (for Inbound Open Innovation) and 60% (for Outbound Open Innovation) in 2007. Bio-pharmaceutical companies have increasingly looked outside the boundaries of their core therapeutic areas for in-sourcing and out-sourcing innovation. This intensified search for new partners in new therapeutic areas clearly indicates that firms are increasingly conforming to the new Open Innovation paradigm (Chesbrough, 2003; Dittrich and Duysters, 2007). Taking a closer look at the different organisational modes for Open Innovation, some interesting insights emerge (see Tables 6 and 7). For both Inbound and Outbound Open Innovation dimensions, alliances have the lion’s share with a relatively stable trend over the years. However, if we take into account their object, it is interesting to notice that in Inbound Open Innovation 63.5% of the alliances refer to non-core therapeutic areas, whereby the bio-pharmaceutical firm enters into relationship with a partner holding very dissimilar competencies. In this respect, alliances are a clear example of those weak ties (Granovetter, 1973) used to capture new ideas from new partners, which are at the very heart of Open Innovation strategies (Dittrich and Duysters, 2007). In Outbound Open Innovation, on the contrary, alliances (mostly co-manufacturing and co-marketing agreements) largely refer to core therapeutic areas, where biopharmaceutical firms need to expand their geographical coverage so as to reach customers on a worldwide basis. In- and out-licensing have experienced a growing trend, moving from about 19% to 30%, and from about 37% to 44%, respectively, for Inbound and Outbound Open Innovation. As far as the Inbound dimension is concerned, top bio-pharmaceutical firms need to continuously fill in their product pipelines in order to remain competitive in the market and sustain their growth

Table 7 Organisational modes for Open Innovation by typology and object (core vs. noncore therapeutic area). Organisational modes Number (percentage) Inbound Open Innovation Alliances Purchase of scientific services In-licensing Outbound Open Innovation Alliances Supply of scientific services Out-licensing

Core

Non-core

112 (36.5%) 107 (58.2%) 114 (69.5%)

195 (63.5%) 77 (41.8%) 50 (30.5%)

112 (60.2%) 35 (83.3%) 92 (49.2%)

74 (39.8%) 7 (16.7%) 95 (50.8%)

against large, traditional pharmaceutical firms. As long as their maturity increases over the years and they are able to use revenues from directly marketed drugs to finance their own R&D activities, they tend to establish more in-licensing agreements, thus allowing reduction of the risk of competence spill-over, to better protect intellectual property, and to ensure a tighter control and independence in the management of drug discovery and development process. Not surprisingly, the large majority of the in-licensing agreements (69.5%) refer to products in core therapeutic areas, where competition with large traditional pharmaceutical and other biotech firms is the most fierce and where the above mentioned advantages are most valued.

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M. Bianchi et al. / Technovation 31 (2011) 22–33

On the Outbound side, out-licensing is equally employed for innovation projects in core and non-core areas. However, the reasons for adopting out-licensing are rather different in the two cases. In the former, bio-pharmaceutical firms use out-licensing as a second-best strategy after alliances when they are not able to reach autonomously the market or are unable to find a suitable partner, whereas in the latter case bio-pharmaceutical firms adopt out-licensing to profit (in a typical Open Innovation approach) out of products whose development is not consistent with their main business focus, i.e. with their orientation in terms of therapeutic areas. A final remark is due on the purchase and supply of scientific services, whose relative weight has clearly declined over time. As far as the reduction in the purchase of scientific services is concerned, the underlying reason is mainly related to the progressive evolution toward the maturity stage of some basic technologies (e.g., gene mapping and analysis and production of monoclonal antibodies), which can be therefore implemented internally by top bio-pharmaceutical firms. On the contrary, for the supply of scientific services the observed trend is due to the natural evolution of bio-pharmaceutical firms: in the first stages of their life cycle, they are forced to supply technology-intensive services (e.g., High Throughput Screening or lead optimisation services) to create a stream of cash flow that supports internal R&D activities. Once their products have reached the market, the revenue stream from ancillary activities becomes less relevant and firms tend to concentrate their efforts on the drug discovery and development process for new products. Table 8 reports the results of the analysis about the different typologies of partners involved in the organisational modes for Open Innovation, distinguishing between large (i.e. with more than $150 million of annual revenues and more than 1000 employees) and small–medium companies. Moreover, as

suggested by the interviewed experts, biotech firms are divided into product biotech and platform (i.e. technology and scientific services suppliers) companies. No relevant changes have occurred over the years as far as the relationships with small biotech (both product and platform) firms and universities are concerned. It appears that establishing organisational modes for Open Innovation with universities and research centres is not a relevant phenomenon (with a 6% weight on the total), despite some literature contributions in the field (e.g., Owen-Smith et al., 2002), which claimed a pivotal role for these actors in fostering bio-pharmaceutical innovation projects. It should be noticed that our sample includes only top players in the industry, which are used to partner with other firms that have already started the process of development of the new product, rather than with universities and research centres, usually focused on basic research. This approach, on one side, reduces the overall risk of the development process (which has been already completed at least in part) and, on the other side, it allows top players to equally profit from marketed products. From the analysis of Table 8 there clearly emerges a growing involvement of large pharmaceutical firms, which increased from about 26% to more than 35% of the cases. This increase is counterbalanced by a weakening of the role of large product biotech firms, which in 2007 were involved in less than 10% of the organisational modes for Open Innovation implemented by top bio-pharmaceutical firms. In order to better understand these trends it is useful to distinguish the organisational modes for Open Innovation with an object related to the firm’s core therapeutic areas and those outside them (see Table 9). The involvement of large companies is mostly related to the former, whereas small and medium firms, as well as universities and research centres, are largely partnered with where an innovation in a non-core area is pursued. Indeed, as far as core areas are concerned, top bio-pharmaceutical firms mostly benefit from the

Table 8 Partners involved in the organisational modes for Open Innovation. Organisational modes Number (percentage) Large companies Pharmaceutical firms Product biotech firms Small–medium companies Product biotech firms Platform biotech firms Universities and research centres

2000

2001

2002

2003

2004

2005

2006

2007

44 (26.2%) 28 (16.7%)

36 (26.3%) 28 (20.4%)

31 (25.8%) 18 (15.0%)

23 (18.5%) 24 (19.4%)

33 (25.0%) 26 (19.7%)

20 (17.7%) 28 (24.8%)

45 (30.4%) 20 (13.5%)

46 (35.4%) 12 (9.2%)

65 (38.7%) 20 (11.9%) 11 (6.5%)

48 (35.0%) 16 (11.7%) 9 (6.6%)

43 (35.8%) 23 (19.2%) 5 (4.2%)

54 (43.5%) 17 (13.7%) 6 (4.8%)

49 (37.1%) 20 (15.2%) 4 (3.0%)

47 (41.6%) 11 (9.7%) 7 (6.2%)

55 (37.2%) 20 (13.5%) 8 (5.4%)

52 (40.0%) 12 (9.2%) 8 (6.2%)

Table 9 Partners by object of the organisational mode (core vs. non-core therapeutic area). Organisational modes Number (percentage) Large companies

Pharmaceutical firms Product biotech firms

Small–medium companies

Product biotech firms Platform biotech firms Universities and research centres

Non-core

Core

103 (37.1%) 69 (37.5%) 268 (64.9%) 86 (61.9%) 46 (79.3%)

175 (62.9%) 115 (62.5%) 145 (35.1%) 53 (38.1%) 12 (20.7%

M. Bianchi et al. / Technovation 31 (2011) 22–33

expertise in ‘‘downstream’’ activities (e.g., clinical tests and postapproval activities) of large pharmaceutical companies, which can leverage their long lasting presence in the industry. When new research areas are addressed, on the contrary, they rather choose to involve smaller and more innovative firms and leading edge universities and research centres, increasing the chances for accessing new technological and scientific capabilities, which is a typical behaviour of Open Innovation companies (Perkmann and Walsh, 2007). Further analyses have been performed on the types of partners by looking at their cross-relationships with both the phases of the drug discovery and development process and the organisational modes for Open Innovation in which they are involved. The results of these analyses are reported in Tables 10 and 11. The aforementioned role of small and medium biotech firms in supporting Inbound Open Innovation is corroborated by the data in Table 10. These firms partner with the top bio-pharmaceutical firms in our sample in more than 51% of the organisational modes for Open Innovation implemented in the first phase of the drug discovery and development process, i.e. in the identification and validation of the target. Similarly, the pivotal role of large pharmaceutical firms in downstream activities clearly emerges from the fact that they account for the large majority (64.5%) of the organisational modes for Open Innovation in the postapproval activities. The technical and scientific expertise of platform biotech firms is, on the contrary, crucial in the lead identification and optimisation tasks, where large scale and high

31

speed sampling analysis (HTS—High Throughput Screening) is needed. Table 11, moreover, further supports the finding that in Inbound Open Innovation, alliances are used as weak ties (Granovetter, 1973) for accessing new areas of expertise, this resulting again in a strong involvement (49%) of small- and medium-sized product biotech firms. On the contrary, in Outbound Open Innovation, the involvement of large firms (with their complementary assets) clearly prevails. It is interesting to notice that the framework developed through the expert interviews documenting the use of different organisational modes along the phases of the drug discovery and development process (see Fig. 3) appears to be corroborated by these empirical analyses. Looking at Inbound Open innovation, it emerges indeed that: (i) nearly 50% of the alliances for Inbound Open Innovation are concentrated in the phase of target identification and validation; (ii) purchase of scientific services is prevalent (48%) in lead identification and optimisation stage, where it typically allows the bio-pharmaceutical firm to access relevant technological platforms and (iii) in-licensing is focused in 61% of the reported cases in the pre-clinical tests and, in the remaining 39%, in the first steps of the clinical tests. As far as Outbound Open Innovation is concerned: (i) about 55% of the alliances are related to post-approval activities, where biopharmaceutical firms mostly need, as already mentioned, to expand their market coverage; (ii) supply of scientific services, even if marginal, is concentrated almost only in the pre-clinical and clinical tests phases and (iii) out-licensing is almost equally

Table 10 Partners involved in the organisational modes for Open Innovation by phase of the drug discovery and development process. Large companies Organisational modes Inbound Open Innovation Target identification and validation Lead identification and optimisation Pre-clinical tests Outbound Open Innovation Clinical tests Post-approval activities

Small–medium companies

Pharmaceutical firms

Product biotech firms

Product biotech firms

Platform biotech firms

Univesity and research centres

60 (14.7%) 23 (14.2%) 17 (19.3%)

74 (18.2%) 13 (8.0%) 12 (13.6%)

210 (51.6%) 39 (24.1%) 38 (43.2%)

32 (7.9%) 81 (50.0%) 9 (10.2%)

31 (7.6%) 6 (3.7%) 12 (13.6%)

87 (31.8%) 91 (64.5%)

68 (24.8%) 17 (12.1%)

105 (38.3%) 21 (14.9%)

8 (2.9%) 9 (6.4%)

6 (2.2%) 3 (2.1%)

Table 11 Partners involved by organisational modes for Open Innovation. Large companies Organisational modes

Inbound Open Innovation Alliances Purchase of technical and scientific services In-licensing Outbound Open Innovation Alliances Supply of technical and scientific services Out-licensing

Small–medium companies

Pharmaceutical firms

Product biotech firms

Product biotech firms

Platform biotech firms

Univesity and research centres

50 (16%) 30 (16%) 28 (17%)

49 (16%) 28 (15%) 28 (17%)

151 (49%) 54 (29%) 75 (46%)

29 (9%) 69 (37%) 19 (12%)

28 (9%) 5 (3%) 14 (9%)

64 (34%) 17 (40%) 89 (48%)

28 (15%) 12 (29%) 39 (21%)

71 (38%) 10 (24%) 52 (28%)

17 (9%) 2 (5%) 3 (2%)

8 (4%) 1 (2%) 2 (1%)

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M. Bianchi et al. / Technovation 31 (2011) 22–33

distributed between pre-clinical and clinical tests. More in particular, out-licensing for products in non-core areas tends to concentrate in pre-clinical tests (from 42% in 2000 to about 73% in 2007), this reducing the financial effort (and risk) for biopharmaceutical firms in developing products which are outside their main business scope. Consistently with the Open Innovation philosophy, these products are developed outside the boundaries of the firm, which however finds a way to profit from them. Outlicensing products in core areas, on the contrary, is even more intensely pursued in the later steps of the clinical tests, thus highlighting the attempt from bio-pharmaceutical firms to reach autonomously (i.e. with their own products) mainstream markets.

5. Conclusions The paper represents one of the first attempts to systematically and longitudinally analyse how firms in a given industry organise themselves to implement Open Innovation. In particular, it investigates the case of the bio-pharmaceutical industry as it represents a fertile ground for the adoption of the Open Innovation philosophy. Relying on two rounds of expert interviews, a framework of analysis has been developed that identifies different organisational modes for Open Innovation through which bio-pharmaceutical firms exchange technologies and knowledge with different types of partners along the phases of the drug discovery and development process. This framework has been applied to an extensive and longitudinal empirical basis, which includes data about the adoption of Open Innovation by the top 20 worldwide industry players, in the time period 2000–2007. Bio-pharmaceutical firms have traditionally made an extensive use of technological collaborations to support their new product development process (Niosi, 2003; Baum et al., 2000; Salman and Saives, 2005). Our analysis documents at least two changes in their approach to inter-organisational exchange of technologies and knowledge that are consistent with the Open Innovation paradigm: (i) the firms in our sample have gradually modified their innovation network by including more and more external partners operating outside their core areas, thus supporting the idea that a different and more ‘‘agnostic’’ Open Innovation approach (West et al., 2006) about the sources and uses of innovation has been adopted and (ii) alliances play an increasing role among the organisational modes implemented by firms in our sample in both Inbound and Outbound Open Innovation, thus supporting the idea that firms are more and more intensely searching for weak ties linking their innovation process to external actors in a typical Open Innovation approach (Dittrich and Duysters, 2007). Furthermore, the paper explains how bio-pharmaceutical firms have used, during the years covered by the analysis, different organisational modes (i.e. licensing agreements, non-equity alliances and supply/provision of technical and scientific services) to enter into relationship with different types of partners (i.e. large pharmaceutical companies, product biotech firms, platform biotech firms and universities) with the aim to acquire (Inbound Open Innovation) or commercially exploit (Outbound Open Innovation) technologies and knowledge. A tentative interpretation of how the characteristics of the bio-pharmaceutical industry (e.g., the structure of the innovation process and its typical risk pattern, the business focus of industry players on major therapeutic areas, the problems related to the management of Intellectual Property) impact on how firms implement Open Innovation has been advanced as well. In this respect, the article supports the idea that the lack of similar contributions in the literature is a major gap in the current research on the implementation of the Open Innovation paradigm. As far as the limitations of the paper are concerned, it is necessary to notice that the analysis it is built on is exploratory in nature. A

promising avenue for future research could be a systematic investigation of the variables that have determined the observed temporal evolution in the organisational modes for Open Innovation adopted by bio-pharmaceutical firms. In order to pursue this objective, it could be useful to adopt the approach suggested by Pettigrew (1990) in his primer on longitudinal multiple case study research. He suggests that ‘‘theoretically and practically sound research on change should explore the context, content and process of change’’ (Pettrigrew, 1990, p. 268). This paper has focused simply on the ‘‘content’’ of change, documenting how the organisational modes used to implement Open Innovation by bio-pharmaceutical companies have evolved over time, although some insight about the role of industry-level and firm-level variables have been presented. In order to systematically identify the antecedents and determinants of this evolution, it would be necessary to adopt the methodological perspective suggested by Pettigrew (known as ‘‘contextualism’’), which combines a vertical (i.e. focused on the impact of inner and outer contextual variable) and horizontal (i.e. focused on the causes and consequences of the observed phenomena) analysis. Furthermore, it could be interesting to further investigate whether and how the composition of the sample, which includes only large product biotech firms (i.e. firms developing new drugs), affects the results of the present analysis. It might be possible to argue, for example, that platform biotech firms are less compelled with the need to fill in their product pipeline and therefore have a different approach to Open Innovation, or that smaller firms adopt in- and out-licensing strategies that are different (or even exactly the opposite) to those of large firms. The authors believe, however, that this paper represents a valuable basis for future research and managerial discussions in the field. References Baum, J.A.C., Calabrese, T., Silverman, B.S., 2000. Don’t go it alone: alliance network composition and startups’ performance in Canadian biotechnology. Strategic Management Journal 21 (3), 267–294. Bayus, B.L., 1994. Are product life cycles really getting shorter? Journal of Product Innovation Management 11 (4) 300–308. Chatterji, D., 1996. Accessing external sources of technology. Research–Technology Management 39 (2), 49–56. Chesbrough, H., 2003. Open Innovation: the new imperative for creating and profiting from technology. Harvard Business School Press, Boston. Chesbrough, H., Crowther, A.K., 2006. Beyond high-tech: early adopters of Open Innovation in other industries. R&D Management 36 (3), 229–236. Chiaroni, D., Chiesa, V., De Massis, A., Frattini, F., 2007. The knowledge bridging role of technical and scientific services in knowledge-intensive industries. International Journal of Technology Management 41 (3/4), 249–272. Chiaroni, D., Chiesa, V., Frattini, F., 2010. Unravelling the process from Closed to Open Innovation: evidence from mature, asset-intensive industries. R&D Management, forthcoming. Chiesa, V., 2001. R&D Strategy and Organisation: Managing Technical Change in Dynamic Contexts. Imperial College Press. Chiesa, V., 2003. La Bioindustria. Strategie competitive e organizzazione industriale nel settore delle biotecnologie farmaceutiche. ETAS, Milano. Chiesa, V., Chiaroni, D., 2004. Industrial Clusters in Biotechnology, Driving Forces, Development Processes and Management Practices. Imperial College Press, London. Christensen, J.F., Olesen, M.H., Kjaer, J.S., 2005. The industrial dynamics of Open Innovation—evidence from the transformation of consumer electronics. Research Policy 34, 1533–1549. DeCarolis, D., Deeds, D., 1999. The impact of stocks and flows of organizational knowledge on firm performance: an empirical investigation of the biotechnology industry. Strategic Management Journal 20 (10), 953–968. Dittrich, K., Duysters, G., 2007. Networking as a means to strategy change: the case of Open Innovation in mobile telephony. Journal of Product Innovation Management 24 (6), 510–521. EmdenGrand, Z., Calantone, R.J., Droge, C., 2006. Collaborating for new product development: selecting the partner with the maximum potential to create value. Journal of Product Innovation Management 23 (4), 330–341. Fasnacht, D., 2009. Open Innovation in the Financial Services. Springer-Verlag, Berlin Heidelberg. Fetterhoff, T.J., Voelkel, D., 2006. Managing Open Innovation in biotechnology. Research–Technology Management 49 (3), 14–18. Gassmann, O., 2006. Opening up the innovation process: towards and agenda. R&D Management 36 (3), 223–226. Gassmann, O., Reepmeyer, G., 2005. Organizing pharmaceutical innovation: from science-based knowledge creators to drug-oriented knowledge brokers. Creativity and Innovation Management 14 (3), 233–245.

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Mattia Bianchi holds a Ph.D. in Management, Economics and Industrial Engineering from Politecnico di Milano. He teaches Business Economics and Innovation Management at Politecnico di Milano and at University of Bergamo. His main research areas are licensing strategies, Open Innovation and energy markets.

Alberto Cavaliere is a Ph.D. candidate in Management, Economics and Industrial Engineering at Politecnico di Milano. He teaches Business Economics and Organisation at Politecnico di Milano. His research area is management of innovation and performance measurement of R&D and technological innovation projects.

Davide Chiaroni is Assistant Professor of Business Economics and Organisation at Politecnico di Milano. He holds a Ph.D. in Management, Economics and Industrial Engineering from Politecnico di Milano. He was previously Research Assistant at University of MilanoBicocca, Department of Biotechnology and Biosciences. His research area is strategy and strategic management in high-technology industries. He is author of the book ‘‘Industrial Clusters in Biotechnology—Driving Forces, Development Processes and Management Practices’’ (with V. Chiesa), Imperial College Press, 2004.

Federico Frattini is Assistant Professor of Business Economics and Organisation at Politecnico di Milano. He holds a Ph.D. in Management, Economics and Industrial Engineering from Politecnico di Milano. He was lecturer in Business Economics and Organization at Universita Vita-Salute San Raffaele (Milano). His research interests concern the management and organisation of R&D activities, R&D performance measurement and the commercialisation of innovation in high-technology markets. He has written more than 60 papers published in leading international journals and proceedings of international conferences.

Vittorio Chiesa is Full Professor of R&D Strategy and Organisation at Politecnico di Milano. He is member of the Management Council and the Faculty of MIP (the Business School of Politecnico di Milano), where he is Head of the Technology Strategy Area. He is a member of the Steering Committee on Biotechnology of the Italian Ministry of Industry and of the Network of Biotech Officials at the European Commission. He is author of several books and more than 100 publications in the fields of R&D management, R&D internationalization and technology strategy.

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