Stephen Roper CSME, Warwick Business School, UK Stephen.roper@wbs.ac.uk Jun Du and Jim Love

1. Knowledge Pathways and Innovation: How do R&D and Skills Enable Knowledge Acquisition from Different Sources? Stephen Roper CSME, Warwick Business School, UK Stephen.roper@wbs.ac.uk Jun Du and Jim Love Economics and Strategy Group Aston Business School

2. Introductory remarks • Key objective of paper is to explore how external knowledge and internal competencies interact in helping firms to innovate • In particular, to identify those internal competences – elements of absorptive capacity (ACAP)– which help firms to benefit from particular sources of external knowledge • In other words we are interested in the pathways through which knowledge flows from external sources into firms innovations • Research Question: Which specific aspects of ACAP are important in enabling firms to take advantage of different types of external knowledge for innovation?

3. Context • Open innovation models stress importance of different sources of external knowledge for innovation and considerable empirical evidence that firms which use external knowledge in their innovation activities have higher innovation outputs. • By external knowledge we mean firms’ links to different types of external organisations as part of their innovation activity. In particular firms’ links to: • Universities – public knowledge linkages • Suppliers - backwards • Customers - forwards • Competitors or joint ventures - horizontal • Absorptive capacity literature stresses importance of internal competencies and external knowledge in general terms but tends to regard external knowledge as uniform • But external knowledge – from universities, firms, consultants - will differ considerably in nature and may require specific internal competencies – something of a gap in the literature

4. Absorptive capacity • Notion from Cohen and Levinthal (1989, 1990) roughly – firms’ ability to evaluate, absorb and exploit external knowledge. • More recent writers have tended to focus on the more functional elements of ACAP focussing on processes of : • knowledge acquisition (Zahra and George, 2002) • knowledge assimilation (Zahra and George, 2002) • knowledge transformation (Kim, 1998) • Developments tend to have been in this process area though rather than focussing on the ‘nature ‘ of the knowledge involved. One example where this is not the case is Schmidt (2005).

5. Empirical Hypotheses • Key indicator of absorptive capacity since C&L has been has been R&D spending, stocks or intensities (Cassiman and Veugelers 2002). • More recent studies have also suggested importance of tacit knowledge gained by experience or more ad hoc R&D activity etc. (Rosenberg, 1982; Dosi, 1988; Senker, 1995) • Hypothesis 1: R&D (Direct effect) • Both formal and informal aspects of firms’ R&D activity may contribute to ACAP and have positive effects on innovation outputs.

6. Empirical Hypotheses • Human capital indicators also tend to be used as indicators of absorptive capacity – may reflect both effectiveness and network competencies or relationships (Mangematin and Nesta, 1999). • Both graduate and intermediate skills may also be important … • Hypothesis 2: Workforce skills (Direct effect) • Workforce skills both at graduate and intermediate levels will contribute to ACAP and will have positive effects on innovation outputs.

7. Empirical Hypotheses • Of course key interest here is complementarity between external knowledge sources and internal capabilities and here have little previous literature on which to base hypotheses. • Schmidt (2005) for Germany finds that R&D is more important for university knowledge and – to a lesser extent – skills are important for knowledge absorption from other firms • Hypothesis 3: R&D complementarities • Firms’ internal R&D capabilities will have stronger complementarity with public knowledge sourcing for innovation than other forms of external knowledge sourcing activity. • Hypothesis 4: Skill complementarities • Workforce skills will have stronger complementarity with horizontal, forwards and backwards knowledge sourcing for innovation than for other forms of external knowledge sourcing

8. Test bed – the innovation production function • Firm-level knowledge or innovation production function of the form: • Where: • I is an innovation output measure, • ACAPi are a series of R&D and skills-based ACAP indicators, • KSj, j=1, 4 are knowledge sourcing indicators, • RI is a vector of indictors of firms’ resource base • MKT is a vector of indicators relating to firms’ market environment.

9. Test bed – the innovation production function • Firm-level knowledge or innovation production function of the form: • Where: • I is an innovation output measure, • ACAPi are a series of R&D and skills-based ACAP indicators, • KSj, j=1, 4 are knowledge sourcing indicators, • RI is a vector of indictors of firms’ resource base • MKT is a vector of indicators relating to firms’ market environment. Hypotheses 1 and 2

10. Test bed – the innovation production function • Firm-level knowledge or innovation production function of the form: • Where: • I is an innovation output measure, • ACAPi are a series of R&D and skills-based ACAP indicators, • KSj, j=1, 4 are knowledge sourcing indicators, • RI is a vector of indictors of firms’ resource base • MKT is a vector of indicators relating to firms’ market environment. Hypotheses 3 and 4

11. Data Source • Irish Innovation Panel (IIP) • Provides information on the innovation, technology adoption, networking and performance of manufacturing plants throughout Ireland and Northern Ireland over the period 1995-2005 • 4 waves, 3600 observations (i.e. 4x900) • Each survey covers the innovation activities of manufacturing plants with 10 or more employees over a three year period • Average survey response rate of 34.5 per cent • Present study uses 2nd , 3rd, 4th and 5th waves

12. Descriptives (IIP waves 2 to 5 – 1994 to 2005)

13. Control variables

14. Illustrative Models: Probability of engaging in product innovation (Probit)

15. Illustrative Models: Probability of engaging in product innovation (Probit)

16. Illustrative Models: Probability of engaging in product innovation (Probit)

17. Empirical results • Results suggest strong support for hypotheses 1 and 2 of the significance of the direct effects on innovation of both R&D (formal and informal) and graduate skills indicator • Evidence for hypotheses 3 and 4 on interactions is weaker but find partial support for each hypothesis: • R&D as element of ACAP more important for product innovation • Skills indicators prove more significant for process change • Empirical evidence for complementarities is weaker than would anticipate from theoretical discussion of ACAP. • Direct effects much more important than ‘absorption’ effects.

18. Implications • Key knowledge pathways between external knowledge and innovation are therefore ‘direct’ rather than mediated significantly by internal capabilities • External knowledge sources and ACAP indicators seem largely independent or additive in the innovation production function • But….Schmidt (2005) suggests stronger links between external knowledge sources and ACAP for Germany than we find here. • Why might this be?

19. Discussion • Irish context marked by very specific knowledge eco-system marked by: • Low levels of interaction • Lack of positive university-industry linkages • Large-scale inward technology transfer • Leads to marked duality – some firms have few external links for innovation, others (externally-owned) have knowledge injections. • Both situations would tend to reduce importance of complementarities • Suggests importance of: • Potential repeat in different international contexts • Use of broader ranges of indicators (of innovation, knowledge sourcing and ACAP).