organisational modes for open innovation in the bio-pharmaceutical industry: an exploratory analysis

Technovation 31 (2011) 22–33

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Technovation

0166-49

doi:10.1

n Corr

E-m

alberto.

federico1 Te2 Te3 Te4 Te

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

Organisational modes for Open Innovation in the bio-pharmaceuticalindustry: 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 i n f o

Keywords:

Open Innovation

Inbound Open Innovation

Outbound Open Innovation

Bio-pharmaceutical industry

Biotechnology

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ail addresses: [email protected] (M

[email protected] (A. Cavaliere), davide.chia

[email protected] (F. Frattini), vittorio.chiesa

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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 bio-

pharmaceutical 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 Innovationhas ranked very high on the agenda of innovation and technologymanagement scholars (Christensen et al., 2005; Gassmann, 2006;Vanhaverbeke, 2006). According to Chesbrough (2003), firms havetraditionally invested in large R&D functions with the aim tomaximize innovation and to nurture their competitiveness andgrowth through the improvement of existing products, servicesand processes as well as the introduction of radically new ones.This ‘‘closed’’ approach to innovation is ‘‘a view that sayssuccessful innovation requires control. Companies must generatetheir own ideas, and then develop them, build them, market them,distribute them, service them, finance them, and support them ontheir own’’ (Chesbrough, 2003, p. 20). However, this frameworkhas become no longer sustainable in several industries wheresome ‘‘erosion’’ factors are in place (i.e. the growing mobility oftechnical professionals and knowledge workers, the increasingrole of private venture capital, the birth and expansion of a market

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. Bianchi),

[email protected] (D. Chiaroni),

@polimi.it (V. Chiesa).

.

.

.

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for technologies). Here a new approach has emerged, whichassumes that firms ‘‘can and should use external ideas as well asinternal ones, and internal and external paths to market’’ to makethe most out of their technologies (Chesbrough, 2003, p. 24). Thismodel is based on the recognition that valuable technologies andpieces of knowledge may originate from both within and outsidethe firm’s boundaries, and that innovation can be commerciallyexploited both internally, in the forms of new products andservices sold into the market, and externally, i.e. disembodiedfrom physical artefacts.

The Open Innovation model captures a number of changes infirms’ approach to strategic management of technology that haveemerged over the years as a response to significant modificationsin the competitive environment, e.g., increased dynamicity andturbulence (Wolf, 2006), the globalisation of markets andbusiness activities, accrued competition (Gupta and Wilemon,1996) and rapid advances in technology development (Bayus,1994). These changes include the end of the linear model ofinnovation (Ortt and Smits, 2006), firms’ increased reliance onexternal sources of technology (Chatterji, 1996; Roberts, 2001),their enhanced attitude toward using multiple channels fortechnology exploitation (Lichtenthaler, 2004) and the internatio-nalisation of industrial R&D and innovation activities (Jones andTeegen, 2002).

This paper adds to our understanding of the Open Innovationparadigm investigating the adoption of this model by firms in thebio-pharmaceutical industry. This industry includes firmsthat carry out the research, development, manufacturing and

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M. Bianchi et al. / Technovation 31 (2011) 22–33 23

commercialisation of pharmaceutical products having biologicalsources, usually involving live organisms or their active compo-nents, and being created by biotechnology methods (see alsowww.bio.org). In particular, this paper adopts a longitudinalperspective to study how bio-pharmaceutical companies haveorganised over time to exchange technologies and pieces ofknowledge with different classes of external organisations(e.g., universities, competitors) along the different stages of theR&D and innovation development process (e.g., drug discoveryand drug development). The analyses reported in the papercontribute to the existing research on Open Innovation, studyingthe adoption of this approach in an industry where the use ofOpen Innovation practices has been rather under-researched sofar. Furthermore, managers will hopefully find the argumentsdeveloped in the paper useful to understand the potential of OpenInnovation for bio-pharmaceutical firms and the organisationalalternatives they could rely on. The paper is structured as follows.The next section reviews the relevant literature on the adoptionand organisational implications of Open Innovation with a focuson the bio-pharmaceutical industry. The third section describesthe research strategy adopted in the paper, whereas the fourthone reports and discusses the results of the empirical analyses.Finally, some conclusions and future directions of research areoutlined.

2. Literature review and research framework

As mentioned above, in the last section, Open Innovation is alargely debated issue in innovation and technology managementliterature. However, many topics related to Open Innovationremain largely unexplored and require further theoretical andempirical research to be fully understood. In particular, two gapscan be identified, which are relevant in the light of the purpose ofthis paper: (i) there is a paucity of contributions that analyse howand to what extent firms operating in a given industry implementOpen Innovation and (ii) there are few contributions that look athow firms organise themselves to make the most out of OpenInnovation, i.e. on the organisational implications of thisemerging innovation management paradigm.

2.1. Literature review

As far as the first gap in the literature is concerned, it should benoted that Chesbrough documented the emergence of OpenInnovation mainly in high-technology industries, e.g., Lucent,3Com, IBM, Intel, Millennium Pharmaceuticals (Chesbrough,2003). Since then, there have been some attempts to investigatethe adoption of Open Innovation in mature, asset intensivecontexts. For instance, Chesbrough and Crowther (2006) surveyed12 firms in the US, which were identified as ‘‘early adopters’’ ofOpen Innovation in the aerospace, chemicals, inks and coatings,and consumer packaged goods industries. They showed that OpenInnovation practices are not widespread in use, although thesampled firms have sharply increased their attitude towardleveraging external sources of innovation to complement theirinternal R&D activities during the last years. Vanhaverbeke (2006)studied a sample of Dutch innovative SMEs working in matureindustries and found that they often use processes for accessingexternal sources of technologies and knowledge, whereas theyperceive relevant barriers when it comes to commercializetechnologies disembodied from physical artefacts, e.g., throughout-licensing agreements or sale of technologies. Finally, Chiaroniet al. (2010) described the anatomy of the organisational changeprocess through which a sample of Italian firms working inmature, low-technology industries revolutionised their approach

to innovation from a ‘‘closed’’ to an ‘‘open’’ paradigm. A fewcontributions can be also found in the literature that attempt tounravel the adoption of Open Innovation in a specific industry. Forinstance, Christensen et al. (2005) studied Open Innovation froman evolutionary economic perspective, focusing on a specificsectoral system of innovation (i.e. consumer electronics) andstudying the industrial dynamics associated with the develop-ment of the class D amplifier technology. Sarkar and Costa (2008)provided a review of the literature contributions that documentthe use of Open Innovation practices in the food industry, wherefirms have been increasingly opening up to external sources ofknowledge in search of successful new products and technologies.Finally, a recent book by Fasnacht (2009) discussed the use ofopen business models and strategies in the context of thefinancial service industry. Besides these scattered contributions,literature has not systematically investigated so far how firmsbelonging to a given industry adhere to the Open Innovationparadigm, although this would be a fundamental prerequisite toenhance the external validity of the model, as noted by West et al.(2006) in the research agenda for Open Innovation that they putforward in the concluding chapter of their book.

As a result of this gap in the literature, the adoption of OpenInnovation in the bio-pharmaceutical industry has not beensystematically documented so far. Besides sparse anecdoticevidence (e.g., the description, reported in Chesbrough (2003),of the innovation strategy adopted by Millennium Pharmaceu-ticals), and some contributions published in the specialistic andsectoral literature (e.g., Munos, 2006; Smits and Boon, 2008) tothe best knowledge of the authors there is only one scholarlycontribution (Fetterhoff and Voelkel, 2006), which adopts amanagerial perspective to study Open Innovation in bio-pharma-ceutical firms. The authors proposed a model of the externalinnovation value chain, which comprises the following fivestages: (1) seeking opportunities; (2) evaluating their marketpotential and innovativeness; (3) recruiting potential partners forthe development of the opportunity; (4) capturing value fromcommercialisation and (5) extending the innovation offering. Thismodel is intended to be of help for bio-pharmaceutical firms tocapture the full value of the inter-organisational relationshipsthey establish with external technology providers, and is devel-oped through examples drawn from Roche Diagnostics’s experi-ence. Notwithstanding this limitation of the existing literature, itis believed that the bio-pharmaceutical industry has severalfeatures that make it a fertile ground for the adoption of OpenInnovation and therefore for studying its managerial andorganisational implications. This is clear if we consider its soaringtechnology intensity (DeCarolis and Deeds, 1999), the complexityof the bio-pharmaceutical innovation and technology develop-ment process, and the heterogeneity of the competences itrequires (Koput et al., 1996), the importance of technologytransfer for the development of the industry as a whole (Madhokand Osegowitsch, 2000), the intensity of relationships betweenbio-pharmaceutical firms, universities and research centres(Owen-Smith et al., 2002) and the birth of a venture capitalmarket, at least in Anglo-Saxon countries, specialized in support-ing biotech ventures (Powell et al., 2002). A recent paper by Xiaand Roper (2008) further documents the critical role of alliancesbetween bio-pharmaceutical firms in both US and Europeancontexts.

As far as the second gap in the literature is concerned, OpenInnovation research has started only recently to investigate howfirms organise themselves and modify their managementpractices to ease the implementation of the new innovationmanagement paradigm. Mainly anecdotic and exploratory resultshave been produced so far on this topic. For instance, Huston andSakkab (2006) documented the use of different forms of networks

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M. Bianchi et al. / Technovation 31 (2011) 22–3324

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 supportthe operation of its ‘‘distributed innovation’’ system, whereasKirschbaum (2005) explained how the multinational life scienceand material science firm DSM has built a teamwork andentrepreneurial culture for Open Innovation. Dittrich andDuysters (2007) studied how innovation networks can be usedto cope with a changing technological environment, makingexplicit reference to the innovation networks leveraged by Nokiato develop the GSM and UMTS technologies. These firms appear tohave developed superior network resource combination capabil-ities, a concept recently introduced by Tolstoy and Agndal (2010)to identify the capability that allows companies to draw on andcombine complementary resources available in the networks.Furthermore, Laursen and Salter (2006) identified, through asurvey of UK manufacturing firms, two variables that describe thecharacteristics of a network for innovation, namely its searchbreadth and its search depth. Finally, van de Vrande et al. (2006)studied the criteria affecting the choice of the governance modesfor external technology sourcing under an Open Innovationperspective, whereas Huang et al. (2009) showed that thefinancial benefits of external technology sourcing depend onthe type of incremental innovation developed by the acquiringfirm, it being marginal or adaptive. From this brief literatureanalysis it clearly emerges that a structured theory of themanagerial and organisational impact of Open Innovation hasnot been developed yet.

Organisational modes

Types of partners

Phases of theR&D process

Time

Fig. 1. Schematic representation of the research framework.

2.2. Research framework

This paper contributes to fill these gaps in the extant literature,focusing on the organisational modes through which bio-pharmaceutical firms open up their innovation processes andenter into relationships with external organisation to exchangetechnologies and knowledge. As far as the organisational modesare concerned, it is necessary to distinguish two dimensions of theOpen Innovation paradigm, namely ‘‘Inbound’’ and ‘‘Outbound’’Open Innovation (Chesbrough and Crowther, 2006). InboundOpen Innovation is the practice of leveraging the technologies anddiscoveries of others, and it requires the opening up to, and theestablishment of inter-organisational relationships with externalorganisation with the aim to access their technical and scientificcompetencies. Outbound Open Innovation is instead the practiceof establishing relationships with external organisations to whichproprietary technologies are transferred for commercial exploita-tion. Working on the concepts developed by March (1991),Inbound Open Innovation serves the purpose to improve thefirm’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 andtechnologies (He and Wong, 2004). Literature has documentedthe use of different organisational modes through which Inboundand Outbound Open Innovation can be put into practice (Grand-strand, 2004; Lichtenthaler, 2004, 2005). Widespread organisa-tional modes for Inbound Open Innovation are: in-licensing,minority equity investments, acquisitions, joint ventures, R&Dcontracts and research funding, purchase of technical andscientific services and non-equity alliances. Typical organisationalmodes for Outbound Open Innovation are instead: licensing out,spinning out of new ventures, sale of innovation projects, jointventure for technology commercialisation, supply of technical andscientific services, corporate venturing investments and non-equity alliances.

Furthermore, literature has shown that these organisationalmodes are used by Open Innovation firms to establish relation-ships with a number of heterogeneous actors, as noted also inrecent reports (OECD, 2008; von Hippel, 2005; Perkmann andWalsh, 2007; EmdenGrand et al., 2006). The taxonomy of partnersfor Open Innovation suggested in the OECD report comprisessuppliers, customers, competitors, consultants, private R&Dinstitutes, universities and other higher education, governmentand public research.

Finally, the organisational modes that a firm selects and thetype of partners with which it enters into relationships varysubstantially along the phases of the R&D process (e.g., basicresearch, applied research, development, launch), because theyare characterised by very dissimilar requirements in terms of levelof investments, risk, uncertainty and need for exploring newknowledge rather than exploiting existing one (Chiesa, 2001). Thisis particularly true in the bio-pharmaceutical R&D process, whichcan be roughly divided into two stages, namely drug discoveryand drug development (Muffatto and Giardina, 2003; Chiesa,2003; Chiesa and Chiaroni, 2004; Gassmann and Reepmeyer,2005; Chiaroni et al., 2007). Drug discovery includes the followingactivities: (i) target identification and validation, where a newgene or protein or a sequence of both (target) is selected forpotentially being pathogenic of a selected disease, and it is theninitially validated by searching extant data about interactionswith the human organism and about previously filed patents thatmight eventually protect the target and (ii) lead identification andoptimisation, where a new biological compound is identified foraddressing the target and treating the related disease and it ischemically stabilised with the adjunct of excipients (i.e. sub-stances included in the drug formulation) with the aim to turn itinto the active principle of the future drug. At this point, the drugdevelopment process begins, which comprises the following threeactivities. (i) Pre-clinical tests, where the mechanisms ofabsorption, distribution, metabolism, excretion and toxicology ofthe new drug are studied and its effects are initially tested onanimals. At the end of the pre-clinical tests a first approval bypublic authorities is needed to proceed with the development. (ii)Clinical tests, divided into Phase I, Phase II and Phase III (Muffattoand Giardina, 2003), where human patients are involved with theaim to test the safety and to assess the effectiveness of the newdrug. If the response of these tests is positive, the new drug obtainthe approval by public authorities to reach the market.

Table 1List of participants in the expert interviews.

Position Organisation

Corporate Affaire Director Amgen

Director Assobiotech—Italian association of biotech

companies

Life Science Senior

Consultant

ATA—Advanced Technology Assessment

Chief Executive Officer Axxam

Business Development

Manager

Bioindustry Park Canavese

Chief Executive Officer Bioxell

Chief Executive Officer Blossom Associates

Full Professor Department of Biotechnology—Universit �a degli

Studi di Milano-Bicocca


(iii) Post-approval activities, where the new drug is actuallyproduced, marketed and sold and where additional informationon its risks, benefits and optimal use in the middle-term arecollected through the so called post-marketing tests.

This brief analysis suggests that in order to address theresearch question of the paper the framework underlying ourresearch should comprise three main variables: organisationalmodes for Open Innovation, types of partners and phases of theR&D process. As indicated in Fig. 1, our empirical analysis willattempt to explore how the relationships between the threevariables have evolved over time in the bio-pharmaceuticalindustry.

In the next section, the methodology of our empirical analysiswill be described in depth.

Director Department of Pharmacological

Sciences—Universit�a degli Studi di Milano

Senior Industrial

Specialist—Health

Sciences

Ernst&Young

Chairman and Chief

Executive Officer

Gentium

Manager GlaxoSmithKline

Chief Executive Officer MolMed


Manager

MolMed

Director R&D MolMed

Chief Executive Officer Newron

Chief Executive Officer NicOx

Head of External R&D Policy Roche

Chairman and Chief

Executive Officer

Siena Biotech


Manager

Toscana Life Sciences

3. Research methodology

The research strategy devised to pursue the paper’s objective ismade of two steps with the following purposes: (i) to operationalizethe research framework presented in the last section in thebio-pharmaceutical industry, taking into account the peculiaritiesof R&D and innovation activities carried out by bio-pharmaceuticalfirms and (ii) to use the framework developed in the previous step tocollect and interpret data in the scope of a longitudinal studyinvolving a number of leading bio-pharmaceutical companies.

As far as the first step of the research is concerned, two roundsof expert interviews were organised and carried out with 20 keyinformants (business development managers, R&D directors, ChiefExecutive Officers of bio-pharmaceutical companies, as well asacademics and consultants with a significant experience in thefield), who are among the most knowledgeable Italian experts ofthe bio-pharmaceutical industry. The list of the participants whotook 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 organisationalmodes for Open Innovation and the types of partners developedthrough the literature analysis and are presented in the lastsection of the paper. They were asked to discuss through whichorganisational modes and with which partners bio-pharmaceu-tical firms are used to enter into relationships along the differentphases of the drug discovery and development process. Moreover,they were asked to identify any contextual variables that couldexplain how bio-pharmaceutical firms interact with externalorganisations. It should be noted that the Open Innovationconcept has not been superimposed to the experts involved inthe analysis but our research was presented as an investigation ofthe patterns of inter-organisational collaborations in thebio-pharmaceutical industry. Only at the end of the second roundof interviews, the Open Innovation model was presented tothe interviewees, most of which were already familiar with theconcept. Interestingly, it emerged from the interviews thatbio-pharmaceutical firms have developed over time severalcharacteristics that can be interpreted as signs of the emergenceof the Open Innovation paradigm: (i) they have deliberatelyestablished as a strategic priority to improve their relationshipswith external organisation in both Inbound and Outbound OpenInnovation processes; (ii) they have often introduced a dedicatedbudget for the establishment and management of these externalcollaborations and partnerships and (iii) they have very oftenundergone a reorganisation of internal processes and practices toimprove their ability to manage collaborative innovation activities.Further evidence corroborating the idea that bio-pharmaceuticalfirms have indeed conformed themselves to the principles of OpenInnovation is presented in Section 4 and discussed in the conclusionsof the paper. The information collected during the first interviews

was compared and critically examined and the emerging inter-pretative model was provided to the key informants during thesecond round of interviews for validation. The definitive model wasfurther discussed with two different experts (the Head of BusinessDevelopment of Nerviano Medical Sciences and the Director ofBusiness Development and Licensing of Nycomed, who were notinvolved in the two rounds of expert interviews) for externalcorroboration. Therefore, this first step of the research allowed theauthors to develop a framework for investigating the organisationalmodes 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 20bio-pharmaceutical companies worldwide (on the basis of theirmarket capitalisation at the end of December 2006, see Table 2)and, for each firm, we collected data about the Open Innovationmodes they have been using in the different phases of the drugdiscovery and development process over time. Further detailsabout the empirical analysis and, in particular: (i) the selection ofthe sample; (ii) the time period covered in the analysis, (iii) thetype of data collected and (iv) the sources of the data, areprovided in the following.

First, it should be noted that the decision to focus on the top 20biotech firms on the basis of their market capitalisation isconsistent with the aim of the article. On one hand, companieslisted on public stock exchange markets are required to discloseinformation about their R&D activities and this gives the authorsthe opportunity to access critical information about the organisa-tional modes for Open Innovation they have been employing overthe years. On the other hand, the firms included in our samplerepresent the top players in the industry and hence are moresuitable to anticipate relevant trends and best practices in themanagement of innovation. Second, the time period covered byour study includes the years 2000–2007. This was done in theattempt to improve the relevance of the information gathered for

Table 2List of companies in the sample.

Name Market capitalization,

29th December 2006 ($billion)

Genentech 85.8

Amgen 85.7

Gilead Sciences 32.0

Celgene 19.8

Genzyme 17.7

Biogen Idec 17.7

Serono 12.7

Medimmune 7.9

Elan Pharmaceuticals 5.8

Amylin Pharmaceuticals 5.6

Vertex Pharmaceuticals 5.0

Cephalon 4.8

Millennium Pharmaceuticals 3.6

ImClone Systems 2.7

PDL BioPharma 2.6

Human Genome Sciences 1.7

Medarex 1.7

Alkermes 1.6

BioMarin Pharmaceuticals 1.6

MGI Pharma 1.5


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

�
The pipeline of innovation projects and new drugs underdevelopment for the firms in the sample. � The number and typology of different organisational modes (as
identified in the interpretative framework developed throughthe expert interviews) adopted by the firms.
� The phase of drug discovery and development process (as
described in the relevant literature) that each of the abovementioned organisational modes refers to.
� The typology of partners involved (as identified in the
interpretative framework developed through the expert inter-views).
� The therapeutic area within which the object of each inter-
organisational relationship established by the firms in oursample can be classified (i.e. the target disease of a new drug).This was identified by our key informants as a relevantvariable to explain the adoption of Open Innovation bybio-pharmaceutical companies.
� The size of the firms in the sample, measured through their
market capitalisation and annual sales in 2006, which is afurther firm-level, contextual variable suggested by the expertinterviews.

As a primary source of information, the annual reports of theselected firms in the time period 2000–2007 have been analysed.Nevertheless, in order to validate the collected data, they havebeen triangulated with information taken from professionaldatabases and reports (i.e. Recombinant Capital, BiospaceDirectory, Canadian Biotech). In particular, these databases wereused to corroborate information about the pipeline of innovationprojects and new drugs under development, the typology ofpartners involved in each inter-organisational relationshipestablished by the firms in the sample and the phase of drugdiscovery and development process the organisational modes forOpen Innovation refer to. Finally, it is necessary to notice that,for the purpose of the article, the identification of general trends isfar more important than the completeness of the data collectedfor each firm in the sample. Indeed, even if comprehensiveness

might be ensured by the fact that the firms in the sample arelisted on public stock exchanges, it is however reasonable toexpect that, if omissions have occurred, they are randomlydistributed in the sample, and hence they do not undermine theresults of the analysis.

4. Results and discussion

In this section we present the results of the empiricalinvestigation. First, the framework of analysis developed withthe help of the expert interviews is discussed. Then, the outcomeof the longitudinal analysis is discussed at length.

4.1. Results from the expert interviews

As a first step, the interviewed experts were asked to identifyin which phases of the drug discovery and development processInbound and Outbound Open Innovation dimensions are morelikely to be implemented by bio-pharmaceutical firms. It emergedfrom our interviews that Inbound Open Innovation is likely totake place mainly in the first three phases of the drug discoveryand development process, i.e. target identification and validation,lead identification and optimisation, and pre-clinical tests. It ischiefly in these stages that bio-pharmaceutical firms that are notable to master all the tasks and do not possess all thecompetencies required to undertake these activities enter intorelationships with external organisations, either to leverage theirinnovation efforts or to access highly specialised knowledge andcompetencies. On the other hand, Outbound Open Innovationoccurs mainly in the second part of the process, i.e. during clinicaltests and post-approval activities. In these phases, bio-pharma-ceutical firms are more likely to open up their boundaries toexternal organisations for exploiting the results of their innova-tion activities, ensuring a quicker and wider access to the market.Because of the intrinsic characteristics of the bio-pharmaceuticalinnovation process, it is only with the beginning of the clinicaltests that the ‘‘candidate’’ drug reaches a stage of developmentthat allows it to be commercially exploited. Before this point, thedrug discovery and development process is mainly a ‘‘trial-and-error’’ activity, characterised by extremely high uncertainty andunpredictable outcomes. In clinical tests the development risklowers and the process becomes much more formalised andexternally visible. It is from this point, therefore, that opportu-nities for external commercial exploitation can be identified andpursued. In some cases, as noticed by our experts, commercialexploitation may start earlier than the end of pre-clinical tests(e.g., through out-licensing a candidate who has not yetcompleted these tests). Similarly, external organisations may beaccessed for contributing to the generation of innovation evenlater on in the process (e.g., through in-licensing a candidate whohas already entered the clinical tests phase). Nevertheless, as wewanted to investigate where Inbound or Outbound Open Innova-tion is ‘‘more likely’’ to take place, we set the distinction betweenthese two dimensions of Open Innovation at the end of pre-clinical tests. Fig. 2 summarizes these discussions.

The experts were then provided with the list of the organisa-tional modes for Open Innovation developed through theliterature analysis and they were asked to identify which ofthem, and others that could be missing from our taxonomy,bio-pharmaceutical firms are more likely to adopt in each phase oftheir innovation process. Furthermore, they discussed, starting fromthe taxonomy of partners for Open Innovation presented in Section2, which types of external organisations bio-pharmaceutical firmsare more likely to leverage along their innovation process. As far as

TARGET IDENTIFICATION

AND VALIDATION

LEADIDENTIFICATION

AND OPTIMISATION

PRE-CLINICALTESTS

POST-APPROVALACTIVITIES

CLINICAL TESTS

PhaseI

PhaseII

PhaseIII

INBOUND OUTBOUND

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

ALLIANCE FOR GENERATION

PURCHASE OF SCIENTIFIC SERVICES

IN-LICENSING

SUPPLY OF SCIENTIFIC SERVICES

OUT-LICENSING

ALLIANCE FOR EXPLOITATION

TARGET IDENTIFICATION

ANDVALIDATION

LEADIDENTIFICATION

ANDOPTIMISATION

PRE-CLINICALTESTS

POST-APPROVALACTIVITIES

CLINICAL TESTS

PhaseI

PhaseII

PhaseIII

PHARMACEUTICALFIRMS

LARGEPRODUCT

BIOTECHFIRMSPLATFORM

BIOTECHFIRMS

SMALL-MEDIUMPRODUCT

BIOTECHFIRMS

UNIVESITYAND

RESEARCH CENTRES

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 expertssuggested distinguishing between:

�
Pharmaceutical firms, i.e. firms involved in the research,development, production and commercialisation of drugs andwith a portfolio of products already marketed, which isprimarily made of ‘‘traditional’’, non-biotech products. Theyare usually large companies with a long history in the industryand a worldwide geographical presence. � Product biotech firms, i.e. firms involved in the research and
development (and in some cases also in the production andcommercialisation) of new drugs and therapeutics based onbiotechnology. They are relatively young firms all establishedafter 1980.
� Platform biotech firms, i.e. specialized firms focused on the
development and commercialisation of new biotech-basedtechnologies (e.g., High Throughput Screening) and devices(e.g., diagnostic tools) used in the drug discovery anddevelopment 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 areconcerned, three viable alternatives have been identify for both

Inbound and Outbound Open Innovation. They are depicted inFig. 3.

Open Innovation modes used to implement Inbound OpenInnovation are:

�
Alliance, usually taking place in the target identification andvalidation phases. Bio-pharmaceutical companies establishpartnerships (without equity involvement) with other biotechfirms, pharmaceutical companies, universities or public re-search centres with the aim to pursue a common innovativeobjective (e.g., the validation of a genetic target). � Purchase of scientific services, usually related to the lead
identification and optimisation phases. Through this organisa-tional mode bio-pharmaceutical firms externalise to specia-lised players, usually platform biotech firms and, although lessfrequently, universities and research centres, a specific phaseof their innovation process (e.g., the lead optimisationactivity), under a well-defined contractual agreement (forfurther details on the role of technical and scientific services inthe biotech industry see Chiaroni et al., 2007).
� In-licensing, usually taking place during pre-clinical tests.
Bio-pharmaceutical firms acquire the rights to use aspecific candidate typically from another biotech firm, apharmaceutical company or, although less frequently, from auniversity.


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

TabOrg

O

N

In

O

T

Alliance. Bio-pharmaceutical firms partner with anothercompany (a biotech firm or, more often, a big pharmaceuticalcompany) for accessing some complementary assets (e.g.,production capacity or distribution channels) required tocommercially exploit the new drug.
� Supply of scientific services, usually related to the finalisation
of pre-clinical tests and the first tasks of clinical tests. Bio-pharmaceutical firms provide to third parties (typically otherbiotech firms) technical and scientific services, which leveragethe outcome of their discovery efforts.
�
Table 4Organisational modes for Open Innovation by firm’s size (total numbers).

Organisational modes Largest firms Medium firms Smallest firms

Number (percentage)

Inbound Open Innovation 278 228 151

(56.3%) (63.3%) (69.3%)

Outbound Open Innovation 216 132 67

(43.7%) (36.7%) (30.7%)

Total 494 360 218

Out-licensing, usually taking place during clinical tests.Bio-pharmaceutical firms license out, generally to bigpharmaceutical companies, the rights to use a new candidatethey have discovered and developed.

The relationships between the organisational modes for OpenInnovation, the types of partners and the phases of the drugdiscovery and development process were investigated empiricallythrough the longitudinal study of the top 20 bio-pharmaceuticalcompanies. The moderating impact of two contextual variablessuggested by the experts was explored. Besides the firm’s size, theysuggested taking into account of whether the bio-pharmaceuticalcompany used a specific organisational mode for Open Innovation todevelop a new drug in a core or a non-core therapeutic area. By corearea we mean a therapeutic area where the firm either generatesmore than 50% of its overall revenues or focus more than half of itsresearch projects (as emerging from the analysis of its innovationpipeline). A non-core area is a therapeutic area that has not beenexplored yet by the firm or has only a marginal role in its productportfolio and pipeline.

4.2. Results from the longitudinal analysis

The analysis of the data about the top 20 bio-pharmaceuticalfirms has produced interesting results on the adoption of OpenInnovation in the industry. Table 3 provides an overview of theorganisational modes for Open Innovation recorded in our sample,distinguishing between those employed for Inbound OpenInnovation and those for Outbound Open Innovation.

The studied firms, in the period 2000–2007, put into action asa whole 1072 organisational modes for Open Innovation, onaverage about 54 for each firm. It clearly emerges from theanalysis of Table 3 that organisational modes for Inbound OpenInnovation are prevalent. They account indeed for about 62% ofthe total organisational modes collected in our sample and show arelatively stable trend, whereas Outbound Open Innovationmodes account for the remaining 38%, reaching the peak (43.2%)in 2006. This indicates that bio-pharmaceutical firms open uptheir innovation process especially for Inbound Open Innovation,where the quest for innovative products (and enabling technol-ogies) able to support business development of top players is the

le 3anisational modes for Open Innovation by year.

rganisational modes 2000 2001 2002

umber (percentage)

bound Open Innovation 97 85 71

(57.7%) (62.0%) (59.2%)

utbound Open Innovation 71 52 49

(42.3%) (38.0%) (40.8%)

otal 168 137 120

main purpose. This is fairly more evident if we take into accountalso the size of the firms. The results of this analysis are reportedin Table 4.

The smallest among the studied firms (i.e. those with a marketcapitalisation lower than $2 billion and annual revenues below$200 millions) implement organisational modes for Inbound OpenInnovation in about 70% of the registered cases, whereas in thelargest firms (i.e. those with a market capitalisation higher that$10 billion or annual revenues above $1500 millions) the relativeweight of Outbound Open Innovation reaches its maximum atabout 44%. On one side, this is due to the relative greater maturityof the largest firms, most of which have a product pipeline (i.e. thenumber of new drugs under development in the different phasesof the process) and a market coverage that is rather similar tothose of large, ‘‘traditional’’ pharmaceutical firms. The largestfirms have therefore relatively more chances to access externalactors for commercially exploiting innovation. On the other side,and more interestingly, Table 4 supports the idea that size matterswhen Open Innovation is concerned. The largest firms imple-mented in the period under analysis on average 71 organisationalmodes of Open Innovation, 1.5 times more than the medium-sized (i.e. those with a market capitalisation between $10 billionand $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 fieldof Open Innovation (Chesbrough, 2003; Chesbrough andCrowther, 2006), which indicates that the new innovationmanagement paradigm is more intensively adopted by largefirms, whereas its diffusion among small- and medium-size firmsis still being questioned (see, e.g., van de Meer, 2007).

Table 5 reports the results of the analysis about the object ofthe different organisational modes for Open Innovation, whetherit is related to a new drug that is within the firm’s coretherapeutic areas or not.

There clearly emerges a growing use, both in Inbound andOutbound Open Innovation, of organisational modes involvinginnovations that are outside the firm’s core business (i.e. coretherapeutic areas). Starting in 2000, from around 35% for bothInbound and Outbound Open Innovation, the relative weight ofnon-core organisational modes has increased over time, reachingin the last 2 years covered by our analysis more than 60% of thesampled organisational modes for Inbound Open Innovation and50% for Outbound Open Innovation. This trend is even moreevident if we take into account only the largest firms in our

2003 2004 2005 2006 2007

79 85 76 84 80

(63.7%) (64.4%) (67.3%) (56.8%) (61.5%)

45 47 37 64 50

(36.3%) (35.6%) (32.7%) (43.2%) (38.5%)

124 132 113 148 130

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

2000 2001 2002 2003 2004 2005 2006 2007

Organisational

modes

Core Non-

core

Core Non-

core

Core Non-

core

Core Non-

core

Core Non-

core

Core Non-

core

Core Non-

core

Core Non-

core

Number

(percentage)

Inbound Open

Innovation

64 33 53 32 41 30 39 40 36 49 35 41 33 51 32 48

(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

Innovation

45 26 33 19 31 18 27 18 26 21 20 17 33 31 24 26

(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 6Organisational modes for Open Innovation by typology.

Organisational modes 2000 2001 2002 2003 2004 2005 2006 2007

Number (percentage)


Alliances 54 41 30 28 34 28 48 44

(55.7%) (48.2%) (42.3%) (35.4%) (40.0%) (36.8%) (57.1%) (55.0%)

Purchase of scientific services 25 25 23 25 31 25 20 12

(25.8%) (29.4%) (32.4%) (31.6%) (36.5%) (32.9%) (23.8%) (15.0%)

In-licensing 18 19 18 26 20 23 16 24

(18.6%) (22.4%) (25.4%) (32.9%) (23.5%) (30.3%) (19.0%) (30.0%)


Alliances 34 25 17 12 23 21 30 26

(47.9%) (48.1%) (34.7%) (26.7%) (48.9%) (56.8%) (46.9%) (52.0%)

Supply of scientific services 11 13 4 4 3 3 2 2

(15.5%) (25.0%) (8.2%) (8.9%) (6.4%) (8.1%) (3.1%) (4.0%)

Out-licensing 26 14 28 29 21 13 32 22

(36.6%) (26.9%) (57.1%) (64.4%) (44.7%) (35.1%) (50.0%) (44.0%)

Total 168 137 120 124 132 113 148 130

Table 7Organisational modes for Open Innovation by typology and object (core vs. non-

core therapeutic area).

Organisational modes Core Non-core

Number (percentage)


Alliances 112 195

(36.5%) (63.5%)

Purchase of scientific services 107 77

(58.2%) (41.8%)

In-licensing 114 50

(69.5%) (30.5%)


Alliances 112 74

(60.2%) (39.8%)

Supply of scientific services 35 7

(83.3%) (16.7%)

Out-licensing 92 95

(49.2%) (50.8%)


sample, for which the percentage of non-core organisationalmodes for Open Innovation increased from about 40% in 2000 tonearly 70% (for Inbound Open Innovation) and 60% (for OutboundOpen Innovation) in 2007. Bio-pharmaceutical companies haveincreasingly looked outside the boundaries of their core ther-apeutic areas for in-sourcing and out-sourcing innovation. Thisintensified search for new partners in new therapeutic areasclearly indicates that firms are increasingly conforming to thenew Open Innovation paradigm (Chesbrough, 2003; Dittrich andDuysters, 2007).

Taking a closer look at the different organisational modes for OpenInnovation, 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 theyears. However, if we take into account their object, it is interesting tonotice that in Inbound Open Innovation 63.5% of the alliances refer tonon-core therapeutic areas, whereby the bio-pharmaceutical firmenters into relationship with a partner holding very dissimilarcompetencies. In this respect, alliances are a clear example of thoseweak ties (Granovetter, 1973) used to capture new ideas from newpartners, which are at the very heart of Open Innovation strategies(Dittrich and Duysters, 2007). In Outbound Open Innovation, on thecontrary, alliances (mostly co-manufacturing and co-marketingagreements) largely refer to core therapeutic areas, where bio-pharmaceutical firms need to expand their geographical coverage soas 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 faras the Inbound dimension is concerned, top bio-pharmaceuticalfirms need to continuously fill in their product pipelines in orderto remain competitive in the market and sustain their growth

against large, traditional pharmaceutical firms. As long as theirmaturity increases over the years and they are able to userevenues from directly marketed drugs to finance their own R&Dactivities, they tend to establish more in-licensing agreements,thus allowing reduction of the risk of competence spill-over, tobetter protect intellectual property, and to ensure a tightercontrol and independence in the management of drug discoveryand development process. Not surprisingly, the large majority ofthe in-licensing agreements (69.5%) refer to products in coretherapeutic areas, where competition with large traditionalpharmaceutical and other biotech firms is the most fierce andwhere the above mentioned advantages are most valued.


On the Outbound side, out-licensing is equally employed forinnovation projects in core and non-core areas. However, thereasons for adopting out-licensing are rather different in the twocases. In the former, bio-pharmaceutical firms use out-licensingas a second-best strategy after alliances when they are not able toreach autonomously the market or are unable to find a suitablepartner, whereas in the latter case bio-pharmaceutical firmsadopt out-licensing to profit (in a typical Open Innovationapproach) out of products whose development is not consistentwith their main business focus, i.e. with their orientation in termsof therapeutic areas.

A final remark is due on the purchase and supply of scientificservices, whose relative weight has clearly declined over time. Asfar as the reduction in the purchase of scientific services isconcerned, the underlying reason is mainly related to theprogressive evolution toward the maturity stage of some basictechnologies (e.g., gene mapping and analysis and production ofmonoclonal antibodies), which can be therefore implementedinternally by top bio-pharmaceutical firms. On the contrary, forthe supply of scientific services the observed trend is due to thenatural evolution of bio-pharmaceutical firms: in the first stagesof their life cycle, they are forced to supply technology-intensiveservices (e.g., High Throughput Screening or lead optimisationservices) to create a stream of cash flow that supports internalR&D activities. Once their products have reached the market, therevenue stream from ancillary activities becomes less relevantand firms tend to concentrate their efforts on the drug discoveryand development process for new products.

Table 8 reports the results of the analysis about the differenttypologies of partners involved in the organisational modes forOpen Innovation, distinguishing between large (i.e. with morethan $150 million of annual revenues and more than 1000employees) and small–medium companies. Moreover, as

Table 8Partners involved in the organisational modes for Open Innovation.


Number (percentage)

2000 2001 2002

Large companies

Pharmaceutical firms 44 36 31

(26.2%) (26.3%) (25.8%)

Product biotech firms 28 28 18

(16.7%) (20.4%) (15.0%)

Small–medium companies

Product biotech firms 65 48 43

(38.7%) (35.0%) (35.8%)

Platform biotech firms 20 16 23

(11.9%) (11.7%) (19.2%)

Universities and research centres 11 9 5

(6.5%) (6.6%) (4.2%)

Table 9Partners by object of the organisational mode (core vs. non-core therapeutic area).


Number (percentage)

Large companies Pharmaceutical firms

Product biotech firms

Small–medium companies Product biotech firms

Platform biotech firms

Universities and research cen

suggested by the interviewed experts, biotech firms are dividedinto product biotech and platform (i.e. technology and scientificservices suppliers) companies.

No relevant changes have occurred over the years as far as therelationships with small biotech (both product and platform)firms and universities are concerned. It appears that establishingorganisational modes for Open Innovation with universities andresearch centres is not a relevant phenomenon (with a 6% weighton the total), despite some literature contributions in the field(e.g., Owen-Smith et al., 2002), which claimed a pivotal role forthese actors in fostering bio-pharmaceutical innovation projects.It should be noticed that our sample includes only top players inthe industry, which are used to partner with other firms that havealready started the process of development of the new product,rather than with universities and research centres, usuallyfocused on basic research. This approach, on one side, reducesthe overall risk of the development process (which has beenalready completed at least in part) and, on the other side, it allowstop players to equally profit from marketed products.

From the analysis of Table 8 there clearly emerges a growinginvolvement of large pharmaceutical firms, which increased fromabout 26% to more than 35% of the cases. This increase is counter-balanced by a weakening of the role of large product biotech firms,which in 2007 were involved in less than 10% of the organisationalmodes for Open Innovation implemented by top bio-pharmaceuticalfirms. In order to better understand these trends it is useful todistinguish the organisational modes for Open Innovation with anobject related to the firm’s core therapeutic areas and those outsidethem (see Table 9). The involvement of large companies is mostlyrelated to the former, whereas small and medium firms, as well asuniversities and research centres, are largely partnered with where aninnovation in a non-core area is pursued. Indeed, as far as core areasare concerned, top bio-pharmaceutical firms mostly benefit from the

2003 2004 2005 2006 2007

23 33 20 45 46

(18.5%) (25.0%) (17.7%) (30.4%) (35.4%)

24 26 28 20 12

(19.4%) (19.7%) (24.8%) (13.5%) (9.2%)

54 49 47 55 52

(43.5%) (37.1%) (41.6%) (37.2%) (40.0%)

17 20 11 20 12

(13.7%) (15.2%) (9.7%) (13.5%) (9.2%)

6 4 7 8 8

(4.8%) (3.0%) (6.2%) (5.4%) (6.2%)

Non-core Core

103 175

(37.1%) (62.9%)

69 115

(37.5%) (62.5%)

268 145

(64.9%) (35.1%)

86 53

(61.9%) (38.1%)

tres 46 12

(79.3%) (20.7%


expertise in ‘‘downstream’’ activities (e.g., clinical tests and post-approval activities) of large pharmaceutical companies, which canleverage their long lasting presence in the industry. When newresearch areas are addressed, on the contrary, they rather choose toinvolve smaller and more innovative firms and leading edgeuniversities and research centres, increasing the chances foraccessing new technological and scientific capabilities, which is atypical behaviour of Open Innovation companies (Perkmann andWalsh, 2007).

Further analyses have been performed on the types of partnersby looking at their cross-relationships with both the phases of thedrug discovery and development process and the organisationalmodes for Open Innovation in which they are involved. Theresults of these analyses are reported in Tables 10 and 11.

The aforementioned role of small and medium biotech firms insupporting Inbound Open Innovation is corroborated by the datain Table 10. These firms partner with the top bio-pharmaceuticalfirms in our sample in more than 51% of the organisational modesfor Open Innovation implemented in the first phase of the drugdiscovery and development process, i.e. in the identification andvalidation of the target. Similarly, the pivotal role of largepharmaceutical firms in downstream activities clearly emergesfrom the fact that they account for the large majority (64.5%) ofthe organisational modes for Open Innovation in the post-approval activities. The technical and scientific expertise ofplatform biotech firms is, on the contrary, crucial in the leadidentification and optimisation tasks, where large scale and high

Table 10Partners involved in the organisational modes for Open Innovation by phase of the dru

Large companies

Organisational modes Pharmaceutical firms Product biotech firms


Target identification and validation 60 74

(14.7%) (18.2%)

Lead identification and optimisation 23 13

(14.2%) (8.0%)

Pre-clinical tests 17 12

(19.3%) (13.6%)


Clinical tests 87 68

(31.8%) (24.8%)

Post-approval activities 91 17

(64.5%) (12.1%)

Table 11Partners involved by organisational modes for Open Innovation.

Large companies

Organisational modes Pharmaceutical

firms

Product biotech

firms


Alliances 50 49

(16%) (16%)

Purchase of technical and scientific

services

30 28

(16%) (15%)

In-licensing 28 28

(17%) (17%)


Alliances 64 28

(34%) (15%)

Supply of technical and scientific services 17 12

(40%) (29%)

Out-licensing 89 39

(48%) (21%)

speed sampling analysis (HTS—High Throughput Screening) isneeded. Table 11, moreover, further supports the finding that inInbound Open Innovation, alliances are used as weak ties(Granovetter, 1973) for accessing new areas of expertise, thisresulting again in a strong involvement (49%) of small- andmedium-sized product biotech firms. On the contrary, in Out-bound Open Innovation, the involvement of large firms (with theircomplementary assets) clearly prevails.

It is interesting to notice that the framework developedthrough the expert interviews documenting the use of differentorganisational modes along the phases of the drug discovery anddevelopment process (see Fig. 3) appears to be corroborated bythese empirical analyses. Looking at Inbound Open innovation, itemerges indeed that: (i) nearly 50% of the alliances for InboundOpen Innovation are concentrated in the phase of targetidentification and validation; (ii) purchase of scientific servicesis prevalent (48%) in lead identification and optimisation stage,where it typically allows the bio-pharmaceutical firm to accessrelevant technological platforms and (iii) in-licensing is focused in61% of the reported cases in the pre-clinical tests and, in theremaining 39%, in the first steps of the clinical tests. As far asOutbound Open Innovation is concerned: (i) about 55% of thealliances are related to post-approval activities, where bio-pharmaceutical firms mostly need, as already mentioned, toexpand their market coverage; (ii) supply of scientific services,even if marginal, is concentrated almost only in the pre-clinicaland clinical tests phases and (iii) out-licensing is almost equally

g discovery and development process.


Product biotech firms Platform biotech firms Univesity and research centres

210 32 31

(51.6%) (7.9%) (7.6%)

39 81 6

(24.1%) (50.0%) (3.7%)

38 9 12

(43.2%) (10.2%) (13.6%)

105 8 6

(38.3%) (2.9%) (2.2%)

21 9 3

(14.9%) (6.4%) (2.1%)


Product biotech

firms

Platform biotech

firms

Univesity and research

centres

151 29 28

(49%) (9%) (9%)

54 69 5

(29%) (37%) (3%)

75 19 14

(46%) (12%) (9%)

71 17 8

(38%) (9%) (4%)

10 2 1

(24%) (5%) (2%)

52 3 2

(28%) (2%) (1%)


distributed between pre-clinical and clinical tests. More inparticular, out-licensing for products in non-core areas tends toconcentrate in pre-clinical tests (from 42% in 2000 to about 73% in2007), this reducing the financial effort (and risk) for bio-pharmaceutical firms in developing products which are outsidetheir main business scope. Consistently with the Open Innovationphilosophy, these products are developed outside the boundariesof the firm, which however finds a way to profit from them. Out-licensing products in core areas, on the contrary, is even moreintensely pursued in the later steps of the clinical tests, thushighlighting the attempt from bio-pharmaceutical firms to reachautonomously (i.e. with their own products) mainstream markets.

5. Conclusions

The paper represents one of the first attempts to system-atically and longitudinally analyse how firms in a given industryorganise themselves to implement Open Innovation. In particular,it investigates the case of the bio-pharmaceutical industry as itrepresents a fertile ground for the adoption of the OpenInnovation philosophy. Relying on two rounds of expert inter-views, a framework of analysis has been developed that identifiesdifferent organisational modes for Open Innovation throughwhich bio-pharmaceutical firms exchange technologies andknowledge with different types of partners along the phases ofthe drug discovery and development process. This framework hasbeen applied to an extensive and longitudinal empirical basis,which includes data about the adoption of Open Innovation by thetop 20 worldwide industry players, in the time period 2000–2007.

Bio-pharmaceutical firms have traditionally made an extensiveuse of technological collaborations to support their new productdevelopment process (Niosi, 2003; Baum et al., 2000; Salman andSaives, 2005). Our analysis documents at least two changes in theirapproach to inter-organisational exchange of technologies andknowledge that are consistent with the Open Innovation paradigm:(i) the firms in our sample have gradually modified their innovationnetwork by including more and more external partners operatingoutside their core areas, thus supporting the idea that a different andmore ‘‘agnostic’’ Open Innovation approach (West et al., 2006) aboutthe sources and uses of innovation has been adopted and (ii)alliances play an increasing role among the organisational modesimplemented by firms in our sample in both Inbound and OutboundOpen Innovation, thus supporting the idea that firms are more andmore intensely searching for weak ties linking their innovationprocess to external actors in a typical Open Innovation approach(Dittrich and Duysters, 2007). Furthermore, the paper explains howbio-pharmaceutical firms have used, during the years covered by theanalysis, different organisational modes (i.e. licensing agreements,non-equity alliances and supply/provision of technical and scientificservices) to enter into relationship with different types of partners(i.e. large pharmaceutical companies, product biotech firms, plat-form biotech firms and universities) with the aim to acquire(Inbound Open Innovation) or commercially exploit (OutboundOpen Innovation) technologies and knowledge. A tentative inter-pretation of how the characteristics of the bio-pharmaceuticalindustry (e.g., the structure of the innovation process and its typicalrisk pattern, the business focus of industry players on majortherapeutic areas, the problems related to the management ofIntellectual Property) impact on how firms implement OpenInnovation has been advanced as well. In this respect, the articlesupports the idea that the lack of similar contributions in theliterature is a major gap in the current research on the implementa-tion of the Open Innovation paradigm.

As far as the limitations of the paper are concerned, it is necessaryto notice that the analysis it is built on is exploratory in nature. A

promising avenue for future research could be a systematicinvestigation of the variables that have determined the observedtemporal evolution in the organisational modes for Open Innovationadopted by bio-pharmaceutical firms. In order to pursue thisobjective, it could be useful to adopt the approach suggested byPettigrew (1990) in his primer on longitudinal multiple case studyresearch. He suggests that ‘‘theoretically and practically soundresearch on change should explore the context, content and processof change’’ (Pettrigrew, 1990, p. 268). This paper has focused simplyon the ‘‘content’’ of change, documenting how the organisationalmodes used to implement Open Innovation by bio-pharmaceuticalcompanies have evolved over time, although some insight about therole of industry-level and firm-level variables have been presented. Inorder to systematically identify the antecedents and determinants ofthis evolution, it would be necessary to adopt the methodologicalperspective suggested by Pettigrew (known as ‘‘contextualism’’),which combines a vertical (i.e. focused on the impact of inner andouter contextual variable) and horizontal (i.e. focused on the causesand consequences of the observed phenomena) analysis. Further-more, it could be interesting to further investigate whether and howthe composition of the sample, which includes only large productbiotech firms (i.e. firms developing new drugs), affects the results ofthe present analysis. It might be possible to argue, for example, thatplatform biotech firms are less compelled with the need to fill in theirproduct pipeline and therefore have a different approach to OpenInnovation, or that smaller firms adopt in- and out-licensing strategiesthat are different (or even exactly the opposite) to those of large firms.The authors believe, however, that this paper represents a valuablebasis for future research and managerial discussions in the field.

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Mattia Bianchi holds a Ph.D. in Management, Economicsand Industrial Engineering from Politecnico di Milano. Heteaches Business Economics and Innovation Managementat Politecnico di Milano and at University of Bergamo. Hismain research areas are licensing strategies, OpenInnovation and energy markets.

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

Davide Chiaroni is Assistant Professor of BusinessEconomics and Organisation at Politecnico di Milano. Heholds a Ph.D. in Management, Economics and IndustrialEngineering from Politecnico di Milano. He was pre-viously Research Assistant at University of Milano-Bicocca, Department of Biotechnology and Biosciences.His research area is strategy and strategic management inhigh-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 BusinessEconomics and Organisation at Politecnico di Milano. Heholds a Ph.D. in Management, Economics and IndustrialEngineering from Politecnico di Milano. He was lecturerin Business Economics and Organization at Universit�aVita-Salute San Raffaele (Milano). His research interestsconcern the management and organisation of R&Dactivities, R&D performance measurement and the com-mercialisation of innovation in high-technology markets.He has written more than 60 papers published in leadinginternational journals and proceedings of internationalconferences.

Vittorio Chiesa is Full Professor of R&D Strategy andOrganisation at Politecnico di Milano. He is member ofthe Management Council and the Faculty of MIP (theBusiness School of Politecnico di Milano), where he isHead of the Technology Strategy Area. He is a member ofthe Steering Committee on Biotechnology of the ItalianMinistry of Industry and of the Network of BiotechOfficials at the European Commission. He is author ofseveral books and more than 100 publications in thefields of R&D management, R&D internationalization andtechnology strategy.

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organisational modes for open innovation in the bio-pharmaceutical industry: an exploratory analysis

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