What are university-industry research links about?
Structure of the LectureThe university-industry complex: A yet poorly understood system.University-industry relationships: The importance of searching, screening and signallingThe Governance of University-Industry Knowledge Transfer: Are Different Models Coexisting?
The university-industry complex*
*What do we know?30 years after the start of the institutionalisation (with policy support) of uni-ind relationships we know something but not yet enough to have a consolidated understanding (conflicting results):Field/sector effectResearcher characteristicsUniversity characteristicsFirm characteristics
*Field/sectorMost of the evidence is based on hightech industries and especially biomedical; in most recent years also other fields (engineering) have been increasingly studied; Fields with most intense collaborations.We still fail to recognize the importance of non hightech fields: see for example Food;We know very little of the interactions in services (important in the UK case);
Field/sectorAcross fields/sectors there are extremely important differences in: type of knowledge, the codification of knowledge, incentives and reward system, supply or demand led, etc
Researcher CharacteristicsRecent wave of studies at the individual level:Previous experience;Entrepreneurial capacity in raising funding (public and private);Seniority and tenure ~Male ~Teaching ?
University characteristicsMore likely to occur in some universities than in others due to differences in:Type (disciplinary orientation, local development focus) of the UNI;Environment of the UNI;Culture (more is done in the centre/department and more is accepted and more will be done . B. Clark entrepreneurial UNI);
University characteristicsQuality of the centre/department +/-Existence of formal infrastructure of KT ?Size ?
Firm Characteristics I Quantitative analysis based on surveys: Yale, Carnegie Mellon, PACE, CIS II-III-IV, KNOW, National surveys:Klevorick et al., 1995 USMeyer-Krahmer and Schmoch (1998) and Beise and Stahl (1999) national survey Germany;Arundel and Geuna (2004) PACE EU countries;Mohnen and Hoareau (2002) CIS II EU countries;Cohen, Nelson and Walsh (2002) CM USA;Swann (2002) and Laursen and Salter (2003) CIS III UK.
Firm Characteristics IIThe size of the firm affect collaboration:The larger the more collaboration. butSmall biotech firms and spin-offs. The R&D investment and/or R&D intensity:Absorptive capacity.
Firm Characteristics IIIOpenness of the firm (+):Searching, screening and signallingThe role of demand !!!Product versus process innovation:Mixed results.Independent (+) versus subsidiaries:The role of the headquarter.
Firm Characteristics IVCountries differences.Technological sector.Distance matters (but not always and not for all).
University-industry relationships: The importance of searching, screening and signalling
Roberto Fontana, Aldo Geuna, Mireille Matt
Contribution of the paperWe want to explain why certain firms do cooperate with universities while other dont (probability of cooperation yes/no);For the sample of firms that cooperated with university, we want to explain the number of R&D JV that firms had (intensity of cooperation how many times.We want to test if openess of the firm plays a role e.g. the role of demand
Literature and hypotheses (1)The degree of openness: import external knowledge and knowledge disclosure on a voluntary basis Search strategy: firms look for sources of knowledge (number of external knowledge channels) (Laursen & Salter 2003)Screening activity: selection of a specific relevant source (journals = source of open science, but also of info about scientists)Signalling activity: voluntary disclosure (Pnin 2004) trigger reciprocity, gain feedbacks, network, reputation, higher order knowledge, attract potential partners.H1: Openness should affect positively the probability and the intensity (different effects).
Literature and hypotheses (2)The size: Absolute - (Arundel & Geuna 2004, Mohnen & Hoareau 2003, Cohen et al 2002, etc.);Relative to R&D.
H2.1 Larger firms should have a higher probability to cooperate (internalisation of spillovers).H2.2. Firms with larger R&D investment should be involved in a greater # of R&D projects (spare resources).
Literature and hypotheses (3)R&D intensity Active at the technological frontier more reliant on science (Arundel & Geuna 2004, Schartinger et al. 2001); High R&D investment => high absorptive capacity (Cohen & Levinthal, 1990).
H3. The higher the R&D intensity, the higher the probability of cooperating and the greater the number of projects.
Literature and hypotheses (4)The legal status of the firm:R&D activities concentrated at a firms headquarter;Independent firms cooperate more with PROs than firms belonging to a large group (Mohnen & Hoareau 2003).
H4. Within multi-plan firms, headquarters mediate collaboration.
Literature and hypotheses (5)Type of innovative activities: contrasted results:Positive relation between radical product innovation and cooperation with PROs (Mohnen & Hoareau, 2003);Companies involved in process innovation are more likely to cooperate with PROs than those engaged in product innovation (Swann, 2002).
Data sourcesKNOW survey 2000 7 EU countries: Denmark, France, Germany, Greece, Italy, Netherlands, UK 5 sectors: food and beverages, chemicals excluding pharma, communications equipment, telecom services and computer services 2 size classes: (10-249 employees, 250-999 employees)Average response rate: 33% (minus UK) 50% of innovative firms (222) signed R&D cooperation with PROs in the 3 years before the survey.
The variables (1)Openness of the firm :Number of external sources (fairs and conferences, searching patent db, reverse engineering, internet) - SEARCHMean % of new innovations introduced in collaboration with partners - ExtCOLLScreening publications PUBLICATIONSGovernment R&D projects SUBSIDIESPatents - PATENTSSEARCHINGSCREENINGSIGNALLING
The variables (2)Firm size:Number of employees - EmployeesR&D employment R&D Firm R&D Activity: R&D intensity R&DINT Outsourcing R&D expenditures ExtR&D Headquarter - HEADQ
The variables (3)Firm innovative activityProcess innovation PROCINNProduct innovation PRODINN
Country and sector fixed effects COUNTRY, SECTOR.
Estimation: models & results (1)Negative Binomial Models.Zero Inflated Negative BinomialNumber of R&D Projects = extent of collaboration;Propensity for firms to engage in R&D Project = existence of a relationship (Logit Selection)
Type of Innovative Activity
Type of Innovative Activity
Estimation: models & results (2)Propensity for firms to engage in R&D Projects with PROs: Absolute Size (+) Openness (+): screening (publications + subsidies) Absorptive capacity (+) Headquarter (+)
Estimation: models & results (3)Number of collaborations : Relative Size: R&D employment (+) Openness (+): signalling (patents), outsourcing Absorptive capacity (+)
Estimation: models & results (4)As in previous literature, the type of innovative activity (process versus product) does not provide any definitive result may be also due to the fact that the large majority of respondents do both.Country dummies are significant to explain the number of collaborations, not so much the selection. Sector dummies are not significant except in the case of food and chemicals in the selection model.
Conclusion (1) The role of size and R&D activity:Larger firms have a higher probability to engage in formal agreements with PROs but the number of R&D project signed depends on the size of the R&D department (do I have enough R&D people).Firms with important absorptive capacity (being near the technological frontier) have a higher chance to cooperate and conclude more R&D projects with PROs.
Conclusion (2) The role of openness of firms:Acquiring external knowledge via the screening of publications and the involvement in public policies affects the probability to cooperate with PROs.Signalling competencies via patenting and R&D outsourcing affects the level of collaboration.Policy implication:Demand pool policies informed by the idea of firm openness (in its various specific aspects) as a major driving force.
The Governance of University-Industry Knowledge Transfer: Are Different Models Coexisting?Isabel Bodas Freitas Aldo GeunaFederica Rossi
*Research questionsWhat is the relative importance of the two governance models? Do firm differ according to the governance model they choose?Do proximity and collaboration objective explain the importance of institutional collaborations?
None of these questions have yet been addressed by the literature in an exhaustive way
Data & Methodology
*Data The questionnaire was circulated in October/November 2008 1052 valid responses (representative sample validated by the local Chamber of the Commerce)Survey asked aboutwhether firms engaged in institutional or personal collaborations in the last three yearsfor non-collaborators: reasons for not collaboratingfor institutional collaborators: which universities they collaborated with, objectives of the collaboration, amount of money spent
Table 1. Share of companies that have collaborated with universities (institutional collaborations only) in the previous three years
*Personal contractual collaborationsOverall 17.5% of the sample has had a collaboration with at least one univ
Table 16. Reasons for which firms do not engage in institutional collaborations with universities
% of companies that do not collaborate with universities
There was no need
The firm already has the advanced internal competences it needs
The firm acquires the necessary knowledge from other partner firms
The firm collaborates with external non-university research centres
The firm may be interested in collaborating with universities, but it lacks the resources for this kind of investment
The firm only engages in collaborations with individual researchers (payment is made directly to the researcher or to his/her own firm)
It is difficult to develop contacts with the UNI
*Methodology: Models 1&2A firm does not decide to collaborate and then select the best governance structure to collaborate, institutional or personal.A firm may not collaborate (either it has internal competences to solve the technological problem or does collaborate with other partners);Collaborate with a personal contract with a researcher;Develop an institutional collaboration.We start by running a series of Logit models (to exploit the larger number of observation) then we check our results with a Multinomial Logit model.
*Methodology: Model 3For those firms that engaged in institutional collaborationsfactors that explain the financial investment in institutional collaborations Tobinon the logarithm of one plus the total amount spent in the collaborationRegressors as in Model 2 with the addition of:The objective of the collaboration (R&D, testing, organisation, marketing, etc)The location of the university (in the region, in neighbouring regions, in Italy abroad)
*Methodology: Model 1For those firms that did not engage in institutional collaborations with universities in the last three years:the choice of establishing personal collaborations vs. not collaboratingLogit modeldependent variable: personal collaboration vs. no collaboration at allSize, Innovative effort, Sourcing knowledge outside, organizational characteristics (outsource, multinational, expert)
Table 5. Reasons for not collaborating with universities: distribution of answers*
Table 6. Rotated Loading factors of reasons for not having participated in institutional collaborations with universities in the previous 3 years*
*Table 6. Logit Model Estimation of Probability of non-institutional collaborators to engage in personal collaborations with Universities
Methodology: Model 2Are firms engaging in institutional collaborations with universities significantly different from those that either do not cooperate or cooperate with university researchers through personal contract?2 Logit modelDependent variable: institutional collaboration vs. no institutional collaboration,Dependent variable: institutional collaborations vs personal collaboration.*
*Table 7. Logit Model Institutional Collaboration with Universities
Model 3Total investment*
*Table 9. Tobit model of the logarithm of total investment
Summary of results
*ResultsIn line with results from other empirical literaturelarge firms making innovative efforts (R&D or design activities) are generally more likely to collaborate with universities.however, by distinguishing between institutional and personal collaborations, we find that they are both important channels of knowledge transferthey seem to involve firms with different research strategies
*ResultsFirms that maintained only contractual personal collaboration with university researchers were found: to invest more into the acquisition of external knowledge than firms that collaborated institutionally, and to be more likely to rely on external sources of technological knowl...