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