Trends in R&D internationalisation

1. The impact of internationalisation of research on firm market valuePaola CriscuoloTanaka Business SchoolImperial College London

2. Trends in R&D internationalisation Source: National Science Foundation “Science and Engineering Indicators”

3. Motivations for R&D internationalisation process • Home-base exploiting • To support local production • Home-base augmenting • To tap into local pockets of excellence (Florida, 1997, Kuemmerle 1999, Patel and Vega 1999)

4. New R&D organizational structures Each R&D unit assumes a leading role in the creation of technological assets in a particular area(Chiesa,1996, Gassmann & von Zedtwitz 1999 Criscuolo & Narula, 2007) New technologies are mostly created at centre

5. Global R&D networks: Novartis

6. Why MNEs are adopting this complex structure? • The assumption is that MNE can “efficiently fish for knowledge in a global pool, harness that knowledge for innovation, and then harvest its value for its stakeholders” Doz et al. (2001) “From Global to Metanational”

7. But firms are struggling... • Doz et al. (2006) found that: • coordination across research sites is weak; the number of cross-border projects is relatively low; foreign subsidiaries are not tapping into a broad range of external partners • As one of Siemens’ CEO acknowledged: • “we still need much more co-operation with outstanding universities around the globe: our research co-operation still has a distinctly German flavour” • Cross-borders knowledge transfer and integration are hindered by organizational and technological distance and MNEs suffer from organizational inertia (Criscuolo and Narula, 2007)

8. Are MNEs benefiting from global R&D strategies? • Impact on innovative performance (mixed evidence): • Japanese Pharmaceutical MNEs with foreign R&D produce more patents (Penner-Hahn & Shaver, 2005) • Pharmaceutical MNEs with a greater number of R&D locations produce less patents (Furman et al. 2006) • Dispersing R&D has negative impact on patents quality, however when innovative teams build on knowledge from different locations come up with patents with higher value (Singh 2007)

9. Are MNEs benefiting from global R&D strategies? What is the impact on financial performance of dispersing R&D?

10. Internationalisation of production and firm performance • Internalization theory(Buckley & Casson, 1976):FDI occurs when firms can maximize profits by creating internal markets for intangible assets • Mixed empirical evidence • But evidence that R&D intensity has a moderating impact: • Mock and Young (1991) state: “the value of multinationality stems from the possession of intangible assets and the value of these intangible assets increases with the degree of multinationality” • Benefits of internationalization are linked to R&D internationalization

11. Organizational learning perspective • Focus on learning opportunities generated by a geographically dispersed network of operation(Hitt et al. 1997, Barkema & Vermeulen 1998, Zahra et al. 2000) • Ability to absorb external knowledge depends on existing R&D capabilities (Cohen & Levintahl, 1990) • Thus need to have a geographically dispersed network of R&D facilities

12. Market value & R&D • Technological activities  intangible capital  future profits  reflected in market valuation • Markets value R&D stock, innovation output, but also innovation quality(Hall et al. 2005)and coherence of firm knowledge base (Nesta & Saviotti, 2006) • Investors appear to value not only quantity but also nature and properties of firm knowledge capital

13. Hypotheses • H1: Geographical dispersion of research activities has a positive impact on firm market value • H2: The higher the level of firms local embeddedness in host regions scientific community the higher their market value • H3: The more that firms are able to integrate knowledge from foreign locations the higher their market value

14. Embeddedness • Concept initially defined at the level of the individual • Granovetter (1985): most individual behaviours are closely embedded in networks of interpersonal relationships. The strength of these trust-based relationships in a social network is defined as embeddedness • Uzzi (1996) and Gulati (1999) applied the concept of embeddedness to firms • Key elements of an embeddeded relationship (Gordon and McCann 2000) • firms are more willing to engage in risky co-operative projects • firms may act as a group in order to support and achieve a common and mutually beneficial objective

15. Local embeddedness • Foreign subsidiaries are outsiders in the host region (Solvell & Zander, 1995) • Crucial to be embedded in the local network to access information & knowledge, especially if tacit • Local embeddedness has positive impact on foreign subsidiary performance and innovation (Andersson, Forsgren & Holm, 2002)

16. Hypotheses • H1: Geographical dispersion of research activities has a positive impact on firm market value • H2: The higher the level of firms’ local embeddedness in host-region scientific communities the higher their market value • H3: The more that firms are able to integrate knowledge from foreign locations the higher their market value

17. Knowledge integration • Knowledge integration is crucial to create value • “the critical source of competitive advantage is knowledge integration rather than knowledge itself” (Grant, 1996) • Synergies between R&D sites and international cross-fertilization of knowledge might lead to technological upgrading (Bartlett & Ghoshal 1990, Zander 1999)

18. Hypotheses • H1: Geographical dispersion of research activities has a positive impact on firm market value • H2: The higher the level of firms local embeddedness in host regions scientific community the higher their market value • H3: The more that firms are able to integrate knowledge from foreign locations the higher their market value

19. Data: Publications • Scientific publications by the 1998 Fortune 500 pharmaceutical and chemical MNEs (29 firms) between 1990 - 2005 • To capture the geography of their research activities • In science-based sectors firms publish selected results to increase their visibility and to be ‘plugged’ into the scientific community (Cockburn & Henderson, 1998, Tijssen 2004)

20. Data: Co-authorship • Co-authorship behaviour by foreign subsidiaries scientists • To capture both local embeddedness and knowledge integration from multiple locations • Co-authorship captures knowledge exchanges since it often entails face-to-face interactions, extensive discussions, joint problem solving, exchanges of information and tacit knowledge • CHI indicator to assign each publication to a particular sub-discipline (e.g. Microbiology, Pharmacology)

21. Publication & co-authorship trends

22. The model • vlog of Tobin’s Q proxied by ratio of market capitalisation divided by total assets • rda (R&D intensity)logR&D expenditure over total assets • inta (Intangible assets)loginvestments in other intangible assets over total assets • X control variables: firm size (log sales), financial leverage (log ratio total liabilities over total assets), publication intensity (log ratio publications over R&D expenditure), time dummies

23. Geographical dispersion Herfindahl-based index of geographic distribution of firm i publications in countries n at time t. If equals to 0 publications concentrated in one country

24. Local embeddedness • Weighted average of subsidiaries’ co-publications with local counterparts Weights: share of co-authorships in region n, in discipline k and year t over total number of co-authorships in that region

25. What do I mean by local co-authorship? • A publication that includes two scientists from GSK subsidiary in Research Triangle Park (North Caroline), two scientists from the University of Duke (North Caroline), and one scientist from the University of Wisconsin, would generate six co-authorships but only four will be considered as local

26. Knowledge integration indicator Novartis intra-firm co-authorship network in 2005 density of intra-firm co-authorship network

27. Econometric issues • Problems of heteroskedasticity and autocorrelation • Kmenta (1986) autoregressive heteroskedastic model • But suitable only when N, the number of firms, is lower than T, the number of periods • Fixed effect AR(1) and adjust for panel heteroskedasticity using the White’s correction

28. Results from fixed effect Kmenta (1986) autoregressive heteroskedastic model H1 H2 H3

29. Findings • Investors seem to perceive the creation of a global network of research facilities as an opportunity to increase future profits • Higher levels of local embeddedness are associated to higher market values • Investors do not to value positively efforts to achieve synergies across geographical boundaries

30. Implications • Global R&D strategy • Broaden the search outside the national boundaries • Being open and connected to the local scientific community • Do not ‘desperately seek synergy’ (Goold & Cambell 1998, Kretschmer & Puranam, 2007) • Support for the organizational learning perspective on internationalisation • Extend our understanding of the relationship between multinationality and firm performance

31. Limitations • Econometric issues: • R&D intensity is predetermined rather than exogenous • persistence in market value shocks requires lagged values of Tobin’s Q and generalised method of moments (GMM) estimator • Local embeddedness is a characteristic of the subsidiary not of the MNE • Local embeddedness captured with a very crude indicator

32. Future research • Increase the sample of firms • Identify collaborative partners and develop a better measure of embeddedness • Explore impact of local vs non-local scientific collaborations by foreign subsidiaries