Aija Leiponen Imperial College London and Cornell University

Transcription

1 Aija Leiponen Imperial College London and Cornell University

2 Research design How does the breadth of innovation approach matter for innovation performance? Objectives Sources of knowledge Geographic location Finnish CIS and R&D survey + employment register (skills data) Cross-sectional with lagged explanatory variables Collaborative work with Constance Helfat (Dartmouth College)

3 R&D survey Collected by Statistics Finland Targeting all Finnish R&D performing manufacturing firms, plus a set of (R&D performing) service firms Data on R&D investments, employees, units and location; commercialization of innovations Every 2 years 3

4 Community Innovation Survey Collected by Statistics Finland Survey instrument and data collection techniques developed by Eurostat All Finnish manufacturing firms with more than 100 employees, plus random sample stratified by size and industry of the remainder 72 percent response rate in 1997 Data on commercialization of innovations, innovation objectives, knowledge sources in innovation, R&D, other information 4

5 Advantages Representative data for manufacturing (not just pharmaceuticals!) Innovation outcomes (not intermediate outputs such as patents!) Uniquedata from Finland: innovation objectives (CIS 2); domestic R&D units Disadvantages Cross sectional setup (with lags) difficult to argue exogeneity Limited set of organizational variables

6 Aija Leiponen, Cornell University Constance Helfat, Dartmouth College 6

7 1. Parallel paths and sampling Nelson 1961; Evenson & Kislev 1976; Baldwin and Clark 2003 Technological opportunity is characterized as a distribution of innovation outcomes E.g. balls in an urn Each innovation project is a draw from the distributionib i The more times you draw, more likely to find good outcome Probability of success is improved by conducting multiple parallel searches, but there are decreasing returns to draws/projects

8 2. Cognition and uncertainty Prahalad & Bettis; Gavetti & Levinthal; Tversky & Kahneman Dominant logic constrains innovative search and makes local search more likely than distant search Availability heuristic: rely on easy to retrieve information Adjustment and anchoring: estimate uncertain events by adjusting an initial value/reference point People (and firms) tend to search narrowly

9 3. Innovative search March: Exploration and exploitation (OS 1991) Katila and Ahuja (AMJ 2002) Search depth (reuse) and scope (breadth) and their interaction are pos. related to new product introductions Decreasing returns to depth, not breadth Laursen and Salter (SMJ 2006) Broad search facilitates incremental improvement; search hdepth this associated with new-to-the-world th innovation Decreasing returns to both types of search

10 What about breadth in innovation objectives? Objective: a technical goal (Cohen and Malerba, 2001) A research program or project With a particular objective, e.g., develop a new product, reducelabor costs Analogy to technical trials and potential routes to a singleinnovation innovation (Nelson, 1961; Evenson and Kislev, 1976) 10

11 CIS Innovation Objectives 1. Replace outdated 6. Increase flexibility of products production 2. Improve product quality 7. Reduce labor costs 3. Expand product 8. Rd Reduce use of materials il assortment 9. Reduce use of energy 4. Enter newmarkets or 10. Mitigate environmental increase market share damage 5. Fulfill government regulation lti or standards d Scale: not important/not requirements used very important (0 3) 11

12 Hypotheses 1. Firms that have greater breadth of innovation objectives experience greater innovation success. Multiple draws increases probability of success Multiple objectives counteracts diminishing returns within each objective 2. Firms that have greater breadth of knowledge sources for innovation experience greater innovation success. As the number of innovation objectives or knowledge sources increases, the positive impact on innovation success diminishes. 12

13 Innovation Success (R&D survey) INNOVATION Binary (0,1) variable indicating whether the firm introduced any new to the firm the technological product or process innovations in Probit regression NEW PRODUCT SALES Percentage of firm sales revenue in 1998 from technologically new products introduced in Tobit regression 13

14 Objectives and Sources (CIS) OBJECTIVES Sum of the binary scores for innovation objectives that obtain an evaluation of 2 or 3 on a scale of 0 3 SOURCES Sum of the binary scores for knowledge sources that obtain an evaluation of 2 or 3 on a scale of

15 PRODUCT PROCESS

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17 Control Variables Log of number of firm employees Log of R&D expenditures Business group (0,1 subsidiary of larger firm) Ratio of export to total sales revenues % employees with PhDs % employees with technical college degrees Industry dummy variables 17

18 Results OBJECTIVES is significant in tobit for product sales; SOURCESissignificantinboth significant in probitfor prob(innovation) and tobit for product sales multicollinearity Diminishing returns not very clear; stronger for knowledge sources than objectives Optimal breadth is quite high! and many firms don t seem to reach it cognitive limitations? i i Sensitivity analyses with product and process objectives; individual objectives 18

19 Implications Innovation objectives (and objectives more generally) matter Tend to be overlooked in innovation research Need to decompose innovation activity into underlying components Provides greater precision regarding the determinants of innovation success Improves the ability to derive meaningful managerial implications 19

20 Aija Leiponen, Cornell University Constance Helfat, Dartmouth College 20

21 What Does Multilocation of R&D Entail? Multiple geographic locations of R&D activity within a single firm Geographically separated from headquarters some degree of organizational decentralization GEOGRAPHIC DECENTRALIZATION 21

22 Benefits vs. costs of geographic decentralization 1. International Business/FDI and Knowledge- Based View (KBV): Focus on benefits 2. Organizational Economics (organization form and incentives): Focus on costs 22

23 1. International Business & Knowledge- Based View of the Firm Firms need information about foreign markets, technologies This knowledge is often tacit Requires that firms co-locate geographically Technology transfer is associated with substantial transaction costs (Teece 1977) The multinational corporation arises out of superior efficiency in knowledge transfer across borders (Kogut & Zander 1992, 1993) Reference point: outsourcing or alliances (communication across org. boundaries) 23

24 Implications of FDI + KBV Clear advantages for knowledge acquisition of multiple R&D locations Access to more knowledge sources Greater likelihood of successful innovation Wider range of innovation output 24

25 2. Organizational Economics Geographic distance requires at least some delegation and decentralization ti At least of day-to-day operations And perhaps strategically as well This increases the costs of monitoring and coordination Knowledge transfer itself is costly too. Reference point: single R&D location 25

26 When is it advantageous to decentralize? More market- and customer-specific (more applied) R&D Less need to transfer knowledge within the firm (and bear the associated costs) Decentralized incentives, decision making 26

27 Benefits AND Costs: Hypotheses 1. Firms that have multiple locations of R&D activity experience greater innovation success, but there are diminishing returns to the number of R&D locations - FDI/KBV + costs of organization 2. (Conditional on H1) Any positive association between multilocation of R&D activity and innovation o success reflects ects access to a larger number of different sources of knowledge outside of the organization - FDI/KBV (vs. org. form/incentive arguments) 27

28 Benefits vs. Costs: Hypotheses 3. (a) Firms that have multiple R&D locations generate a wider range of innovation output than firms that have a single R&D unit (KBV) Vs. (b) Firms that have multiple R&D locations generate a narrower range of innovation output (org. form + incentives) 4. Multilocation of R&D activity is associated with greater innovation success for imitative than novel innovations (org. form + incentives) - Implications for research on patents, which reflect novel innovations 28

29 Empirical setting Manufacturing sector in Finland Uniquely detailed data on innovation outcomes and R&D locations of individual firms No information on command and control structure within firms Arguments apply within as well as between countries 29

30 Can we study geographic decentralization within one small country? Yes! Finland is geographically and economically diverse Long distances between major cities and hot spots surface area about the same as CA; 50% larger than the UK A few specialized hot spots electronics in the North; pulp, paper & machinery in South East; medical research on the West coast 4 technical universities, 10 universities in distinct locations Helsinki metro area = largest market; two other major industrial concentrations (Turku, Tampere) 30

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32 Primary sources of data An almost representative sample of R&D performing manufacturing firms R&D survey 1998 R&D locations R&D spending Size (employees) Other controls: firm structure (business group; M&A activity; divestments), exports Innovation survey Innovation output measures Importance of knowledge sources Customers, suppliers, competitors, universities, government research institutes, patents and databases, trade and professional meetings Technological innovations only 32

33 Characteristics of the sample 469 R&D-performing manufacturing firms 354 employees on average in 1998 (5 22,000) R&D/sales average 4.3% in 1998 (0 93%) 67% product innovators ( new to the firm ) 46% process innovators 13% had multiple R&D locations in Finland (in 2000) 2 locations: 7.5% 3 or more locations: 5.3% 33

34 Dependent variables Binary indicators of innovation success Indicate whether the firm introduced at least one innovation Any type of innovation: process, new-to-themarket product, new-to-the-firm product Product sales revenue from innovation All types of products, new-to-the-market, or new- to-the-firm th only Breadth of innovation impact 1. BOTH product and process innovations 2. Innovation impact survey measures (product range, quality, market share, new markets, production flexibility, capacity, costs, environmental effects, regulations and standards) 34

35 Explanatory variables Number of R&D locations 2 locations; 3 or more locations Number of important external knowledge sources Original responses on a Likert scale 35

36 Control variables Firm size (log employees) R&D expenditures (log) Business group subsidiary or parent Export revenues (log) Sales growth from M&A or sales reduction from divestment Foreign subsidiaries (log) Industry 36

37 Findings 1. Multiple R&D locations are associated with greater innovation success Diminishing returns to multiple locations 2. Effect of multiple R&D locations on innovation success is correlated with that of external sources of knowledge Consistent with mediation 3. Multiple R&D locations are associated with a broad impact of innovations 4. Multiple R&D locations are associated with new-to-the-firm th (imitative) it ti but not new-to-the- th world innovations 37

38 Conclusion: Towards a Nuanced Approach to R&D Location R&D multilocation is associated with: Greater innovation success but diminishing returns Both information benefits and organizational costs matter Wider access to external sources of knowledge, and Wider applicability of resulting innovations Consistent with KBV Benefits from R&D multilocation for imitative innovations As predicted by org form/incentives 38

39 Contributions of the study 1. Bring together two largely separate literatures regarding geographic decentralization of R&D Organizational economics and international business/kbv 2. Measures of innovation success beyond patents Across many industries; representative sample Compare novel (new-to-the-world) vs. imitative(new-to-the-firm) innovation 3. Test whether access to more external knowledge sources explains the effects of R&D multilocation on innovation outcomes Prediction of the knowledge-based view 39

40 Methodological issues Measurement survey data Cross-sectional setup (with lagged explanatory variables) endogeneity issues A lagged dependent variable biased coefficients

41 What really causes innovation? Not search Not location Not R&D should h we focus more on institutions, incentives, opportunities, cost of resources for innovation?

42 Research opportunities Combine CIS with other sources of representative data Need conceptual/theoretical novelty to break through to major journals Geography is a hot (overheated?) area How do firms (other than pharma, software) deal with globalization? Service innovation may respond differently? Cognition: Apply insights from behavioral econ, psych into empirical research on innovation