Skip to main content

Advertisement

Log in

Geographical and cognitive proximity effects on innovation performance in SMEs: a way through knowledge acquisition

  • Published:
International Entrepreneurship and Management Journal Aims and scope Submit manuscript

Abstract

This study explores the relative influence of geographical and cognitive proximity to explain innovation performance. This paper deepens the controversy between the significance of both types of proximity, contributing to a better understand their interconnections. The study further analyzes to what extent knowledge acquisition provides a congruent explanation of the effectiveness of innovation in proximity contexts. The paper has tested a structural model based on a sample of 224 Spanish footwear firms. Footwear industry is a mature and traditional industry with a significant presence of the territorial agglomeration of firms all over Spain. Findings suggest both a direct and indirect effect of cognitive proximity on innovation performance. However, an excess of geographical proximity produces spatial lock-in, thus limiting the access to new knowledge and lowering innovations. By contrast, proximity in terms of goals and culture leads firms belonging to a territorial cluster to achieve knowledge acquisition resulting in relevant innovation. Findings suggest that although transferable valuable knowledge exists in clustered contexts firms should adopt a proactive behavior to have access common knowledge and in order to generate effective innovations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. In the context of this research, we define geographical proximity for membership of an industrial district. We consider the notions of district and cluster to be equivalent, although we are aware of the conceptual and methodological differences.

  2. Institutional proximity is associated with the institutional framework at the macro-level. This proximity may be helpful because sharing the same values and expectations with non-local organizations may be beneficial for interactive learning (Boschma 2005).

  3. This study is part of a broader Research Project of the Regional Plan of Scientific Research, Technological Development and Research of Castilla-La Mancha.

  4. Data from the General Section of Analysis, Strategy and Evaluation (2009).

  5. FICE is the Spanish footwear manufacturers federation. This institution seeks to promote the competitiveness of the footwear firms through internationalization strategies, promotion, training, information, marketing, quality, brand support, innovation… These activities are conducted directly and through INESCOP’s key support.

  6. INESCOP is the Technological Institute of Footwear. This institution provides direct services, transfers knowledge and research on topics of general interest.

  7. AICE is the local association of Elche and AIDECA is the local association of Almansa.

  8. Expenditure on innovative activities in the sector over the business volume of this sector.

  9. SABI is a directory of Spanish and Portuguese firms that provides financial data and general.

  10. The Camerdata database is a directory of all Spanish firms from the network of local Chambers of Commerce.

  11. For cognitive proximity, innovation performance and knowledge acquisition variables

  12. For the variable of geographical proximity

  13. When we test our hypotheses, we considered all firms that were members of any district to be in the same category. Through an ANOVA and a Scheffe’s test between firms belonging to each industrial district, we observed no differences in the mean of the variables of the study.

  14. The different items refer to the relationships with the firm’s contacts, which include people, firms or institutions of the same industry.

  15. We use PLS-Graph 3.0

  16. This value is computed by multiplying the significant structural paths.

References

  • Acs, Z. J., & Audretsch, D. B. (1988). Innovation in small and large firms: an empirical analysis. American Economic Review, 78, 678–690.

    Google Scholar 

  • Agrawal, A., Cockburn, I., & McHale, J. (2006). Gone but not forgotten: labor flows, knowledge spillovers, and enduring social capital. Journal of Economic Geography, 6, 571–591.

    Article  Google Scholar 

  • Antonelli, C. (2000). Collective knowledge communication and innovation: the evidence of technological districts. Regional Studies, 34, 535–547.

    Article  Google Scholar 

  • Armstrong, J. S., & Overton, T. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14, 396–402.

    Article  Google Scholar 

  • Asociación Española de Componentes del Calzado-AEC (2008). INFOAEC Report.Elche: AEC (www.aec.es).

  • Audretsch, D. (1998). Agglomeration and the location of economic activity. Oxford Review of Economic Policy, 14, 18–29.

    Article  Google Scholar 

  • Autio, E., Sapienza, H. J., & Almeida, J. (2000). Effects of age at entry, knowledge intensity and imitability on international growth. Academy of Management Journal, 43, 909–924.

    Article  Google Scholar 

  • Baptista, R., & Swann, P. (1998). Do firms in clusters innovate more? Research Policy, 27, 525–540.

    Article  Google Scholar 

  • Baron, R., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.

    Article  Google Scholar 

  • Becattini, G. (1979). Dal settore industriale al distretto industriale. Alcune considerazioni sull’unita di indagine dell’economia industriale. Rivista di Economia e Politica Industriale, 5(1), 7–21.

    Google Scholar 

  • Belso-Martínez, J. A. (2010). International outsourcing and partner location in the Spanish footwear sector: an analysis based in industrial district SMEs. European Urban and Regional Studies, 17, 65–82.

    Article  Google Scholar 

  • Best, M., & Forrant, R. (1996). Creating industrial capacity: Pentagon-led versus production-led industrial policies. In J. Michie & J. G. Smith (Eds.), Creating industrial capacity: Towards full employment (pp. 225–254). New York: Oxford University Press.

    Google Scholar 

  • Boix, R., & Galletto, V. (2006). Sistemas locales de trabajo y distritos industriales marshallianos en España. Economía Industrial, 359, 165–184.

    Google Scholar 

  • Boschma, R. (2005). Proximity and innovation: a critical assessment. Regional Studies, 39, 61–74.

    Article  Google Scholar 

  • Cáceres, R., Guzmán, J., & Rekowsik, M. (2011). Firms as source of variety in innovation: influence of size and sector. International Entrepreneurship and Management Journal. doi:10.1007/s11365-011-0198-8.

  • Capello, R., & Faggian, A. (2005). Collective learning and relational capital in local innovation processes. Regional Studies, 39, 75–87.

    Article  Google Scholar 

  • Capó-Vicedo, J., Expósito-Langa, M., & Molina-Morales, F. X. (2008). Improving SME competitiveness reinforcing interorganisational networks in industrial clusters. International Entrepreneurship and Management Journal, 4, 147–169.

    Article  Google Scholar 

  • Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Sage University Paper Series on Quantitative Applications in the Social Sciences, N. 07–017. Sage, Beverly Hills, Cambridge.

  • Chen, C., & Huang, J. (2008). Strategic human resource practices and innovation performance—the mediating role of knowledge management capacity. Journal of Business Research, 62, 104–114.

    Article  Google Scholar 

  • Chin, W. W. (1998). Issues and opinion on structural equation modelling. MIS Quarterly, 22, 7–15.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absortive capacity: a new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152.

    Article  Google Scholar 

  • Correia, I. M., & Petiz, O. (2007). Firms and universities—do spillovers enhance firm’s performance? International Entrepreneurship and Management Journal, 3, 145–157.

    Article  Google Scholar 

  • Dakhli, M., & de Clercq, D. (2004). Human capital, social capital, and innovation: a multicountry study. Entrepreneurship & Regional Development, 16, 107–128.

    Article  Google Scholar 

  • DeCarolis, D. M., & Deeds, D. L. (1999). The impact of stocks and flows of organizational knowledge on firm performance: an empirical investigation of the biotechnology industry. Strategic Management Journal, 20, 953–968.

    Article  Google Scholar 

  • Dei Ottati, G. (2003). Trust, interlinking transactions and credit in the industrial district. In G. Becattini, M. Bellandi, G. Dei Ottati, & F. Sforzi (Eds.), From industrial district to local development. An itinerary of research. Cheltenham: Edward Elgar Publishing.

    Google Scholar 

  • Dyer, J., & Nobeoka, K. (2000). Creating and managing a high-performance knowledge-sharing network: the Toyota case. Strategic Management Journal, 21, 345–367.

    Article  Google Scholar 

  • Dyer, J., & Singh, H. (1998). The relational view: cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23, 660–679.

    Google Scholar 

  • Exposito-Langa, M., Molina-Morales, F. X., & Capó-Vicedo, J. (2011). New product development and absortive capability in industrial districts: a multidimensional approach. Regional Studies, 45, 319–331.

    Article  Google Scholar 

  • Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. Akron: The University of Akron.

    Google Scholar 

  • Feldman, M. (1994). The geography of innovation. Dordrecht: Kluwer Academic Publishers.

    Book  Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.

    Article  Google Scholar 

  • Fuentes, M. M., Ruiz, M., Bojica, A. M., & Fernandez, V. (2010). Prior knowledge and social networks in the exploitation of entrepreneurial opportunities. International Entrepreneurship and Management Journal, 6(4), 481–501.

    Article  Google Scholar 

  • General Section of Analysis, Strategy & Evaluation. (2009). El sector español del calzado. Boletín Económico de ICE, 2961, 3–18.

    Google Scholar 

  • Galende, J., & de la Fuente, J. M. (2003). Internal factors determining a firm’s innovative behaviour. Research Policy, 32, 715–736.

    Article  Google Scholar 

  • Galunic, C., & Rodan, D. (1998). Resource recombinations in the firms: knowledge structures and the potencial for Schumpeterian rents. Strategic Management Journal, 19, 1193–1202.

    Article  Google Scholar 

  • Giuliani, E., & Bell, M. (2005). The micro-determinants of meso-level learning and innovation: evidence from a Chilean wine cluster. Research Policy, 34, 47–68.

    Article  Google Scholar 

  • Grant, R. M. (2000). Shifts in the world economy: The drivers of knowledge management. In C. Despres & D. Chauvel (Eds.), Knowledge horizonts: The present and the promise of knowledge management (pp. 27–53). Massachusetts: Butterworth-Heinemann.

    Chapter  Google Scholar 

  • Gulati, R., Nohria, N. A., & Zaheer, A. (2000). Strategic networks. Strategic Management Journal, 21, 203–215.

    Article  Google Scholar 

  • Gupta, A. K., & Govindarajan, V. (1984). Business unit strategy, managerial characteristics and business unit effectiveness at strategy implementation. Academy of Management Journal, 27, 25–41.

    Article  Google Scholar 

  • Haenlein, M., & Kaplan, A. M. (2004). A beginner’s guide to partial least squares analysis. Understanding Statistics, 3, 283–297.

    Article  Google Scholar 

  • Hundley, G., & Jacobson, C. (1998). The effects of the keiretsu on the export performance of Japanese companies: help or hindrance? Strategic Management Journal, 19, 927–937.

    Article  Google Scholar 

  • Inkpen, A., & Tsang, E. (2005). Social capital, networks, and knowledge transfer. Academy of Management Review, 30, 146–165.

    Article  Google Scholar 

  • James, L. R., Mulaik, S. A., & Brett, J. M. (2006). A tale of two methods. Organizational Research Methods, 9, 233–244.

    Article  Google Scholar 

  • Kale, P., Singh, H., & Pelmutter, H. (2000). Learning and protection of proprietary assets in strategic alliances: building relational capital. Strategic Management Journal, 21, 217–237.

    Article  Google Scholar 

  • Knoben, J., & Oerlemans, L. A. G. (2006). Proximity and inter-organizational collaboration: a literature review. International Journal of Management Reviews, 8, 71–89.

    Article  Google Scholar 

  • Krause, D. R., Handfield, R. B., & Tyler, B. B. (2007). The relationships between supplier development, commitment, social capital accumulation and performance improvement. Journal of Operations Management, 25, 528–545.

    Article  Google Scholar 

  • Laursen, K., & Salter, A. (2006). Open innovation: the role of openness in explaining innovation performance among U.K. manufacturing firms. Strategic Management Journal, 27, 131–150.

    Article  Google Scholar 

  • Marshall, A. (1925). Principles of economics (8th ed.). London: Macmillan.

    Google Scholar 

  • Martin, R., & Sunley, P. (2003). Deconstructing clusters: chaotic concept or policy panacea? Journal of Economic Geography, 3, 5–35.

    Article  Google Scholar 

  • Maula, M., Autio, E., & Murray, G. (2003). Prerequisites for the creation of social capital and subsequent knowledge acquisition in corporate venture capital. Venture Capital, 35, 117–134.

    Article  Google Scholar 

  • McEvily, B., & Zaheer, A. (1999). Bridging ties: a source of firm heterogeneity in competitive capabilities. Strategic Management Journal, 20, 1133–1156.

    Article  Google Scholar 

  • Mistri, M., & Solari, S. (2001). Social networks and productive connectance: modeling the organizational form of the industrial district. Human System Management, 20, 223–236.

    Google Scholar 

  • Molina-Morales, F. X., & Martínez-Fernández, M. T. (2010). Social networks: effects of social capital on firm innovation. Journal of Small Business Management, 48(2), 258–279.

    Article  Google Scholar 

  • Mowery, D. C., Oxley, J. E., & Silverman, B. S. (1996). Strategic alliances and inter-firm knowledge transfer. Strategic Management Journal, 17, 77–92.

    Google Scholar 

  • Muscio, A. (2006). Patterns of innovation in industrial districts: an empirical analysis. Industry and Innovation, 13, 291–312.

    Article  Google Scholar 

  • Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5, 14–37.

    Article  Google Scholar 

  • Nooteboom, B. (2000). Learning and innovation in organizations and economies. Oxford: Oxford University Press.

    Google Scholar 

  • Nunnally, J. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Parra-Requena, G., Molina-Morales, F. X., & García-Villaverde, P. M. (2010). The mediating effect of cognitive social capital on knowledge acquisition in clustered firms. Growth and Change, 41, 59–84.

    Article  Google Scholar 

  • Porter, M. (1998). Cluster and the economics of competition. Harvard Business Review, 76, 77–91.

    Google Scholar 

  • Rowley, T. (1997). Moving beyond dyadic ties: a network theory of stakeholder influences. Academy Management Review, 22, 887–910.

    Google Scholar 

  • Simonin, B. L. (1999). Ambiguity and the process of knowledge transfer in strategic alliances. Strategic Management Journal, 20, 595–623.

    Article  Google Scholar 

  • Spanos, Y. E., & Lioukas, S. (2001). An examination into the causal logic of rent generation: contrasting Porter’s competitive strategy framework and the resource based perspective. Strategic Management Journal, 22, 907–934.

    Article  Google Scholar 

  • Staber, U. (2001). Spatial proximity and firm survival in a declining industrial district: the case of knitwear firms in Baden-Württemberg. Regional Studies, 35, 329–341.

    Article  Google Scholar 

  • Storper, M. (1992). The limits to globalization: technology districts and international trade. Economic Geography, 68, 60–93.

    Article  Google Scholar 

  • Stuart, T., & Sorenson, O. (2003). The geography of opportunity: spatial heterogeneity in founding rates and the performance of biotechnology firms. Research Policy, 32, 229–253.

    Article  Google Scholar 

  • Torre, A., & Rallet, A. (2005). Proximity and localization. Regional Studies, 39, 47–59.

    Article  Google Scholar 

  • Tortajada, E., Fernandez, I., & Ybarra, J. (2005). Evolución de la industria española del calzado: factores relevantes en las últimas décadas. Economía Industrial, 355, 211–227.

    Google Scholar 

  • Tsai, W., & Ghoshal, S. (1998). Social capital, and value creation: the role of intrafirm networks. Academy of Management Journal, 41, 464–478.

    Article  Google Scholar 

  • Utterback, J. (1974). Innovation in industry and the diffusion of technology. Science, 183, 620–626.

    Article  Google Scholar 

  • Warren, L., Patton, D., & Bream, D. (2009). Knowledge acquisition processes during the incubation of new high technology firms. International Entrepreneurship and Management Journal, 5(4), 481–495.

    Article  Google Scholar 

  • Wuyts, S., Colomb, M. G., Dutta, S., & Nooteboom, B. (2005). Empirical tests of optimal cognitive distance. Journal of Economic Behavior & Organization, 58, 277–302.

    Article  Google Scholar 

  • Ybarra, J. (2006). Los distritos industriales en el desarrollo local valenciano, XIV International EconomicHistoryCongress, Helsinki, 21–25 August.

  • Yeoh, P., & Roth, K. (1999). An empirical analysis of sustained advantage in the U.S. pharmaceutical industry: impact of firms resources and capabilities. Strategic Management Journal, 20, 637–653.

    Article  Google Scholar 

  • Yli-Renko, H., Autio, E., & Sapienza, H. (2001). Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firm. Strategic Management Journal, 22, 587–613.

    Article  Google Scholar 

  • Young-Ybarra, D., & Wiersema, M. (1999). Strategic flexibility in information technology alliances: the influence of transaction cost economics and social exchange theory. Organization Science, 10, 439–459.

    Article  Google Scholar 

  • Zahra, S. A. (1996). Technology strategy and new venture performance: a study of corporate–sponsored and independent biotechnology ventures. Journal of Business Venturing, 11, 289–321.

    Article  Google Scholar 

  • Zhang, J., Di Benedetto, A., & Hoenig, S. (2009). Product development strategy, product innovation performance, and the mediating role of knowledge utilization: evidence from subsidiaries in China. Journal of International Marketing, 17, 42–58.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pedro Manuel García-Villaverde.

Appendix I

Appendix I

Please, show your level of agree with the next assertions about the shared elements with your contacts (1 = totally disagree; 7 = totally agree)

Cognitive social capital (shared goals)

 We share the same ambition and vision as our contacts1.

 My firm is enthusiastic about pursuing the collective goals and missions of our relationships. We share our goals and objectives with our contacts.

 We understand our contacts’ strategy and needs.

 My firm’s employees and my contacts’ employees have positive attitudes toward a cooperative relationship.

 My firm and my contacts tend to agree on how to make the relationship work.

Cognitive social capital (shared culture)

 The business practices and operational mechanisms of your contacts are very similar to yours.

 The corporate culture and management style of your contacts is very similar to yours.

Please, show your level of agree with the next assertions about the acquisition of knowledge (1 = totally disagree; 7 = totally agree)

Knowledge acquisition

 Your company has learnt or acquired new or important information from your contacts.

 Your company has learnt or acquired critical capability or skill from your contacts.

 Your relationships or contacts have helped your company to enhance its existing capabilities/skills.

 Your contacts have been an important source of information/know-how for you on customer needs and trends.

 Your contacts have been an important source of information/know-how for you on competition.

 Your contacts have been an important source of information/know-how for you in technical issues.

Please, show your level of agree with the next assertions both how important is this objective for the firm and how successful is the achievement of this objective in relation to the expected results in the innovation performance (1 = totally disagree; 7 = totally agree)

 Profitability of new products

 Sales of new products

Rights and permissions

Reprints and permissions

About this article

Cite this article

Molina-Morales, F.X., García-Villaverde, P.M. & Parra-Requena, G. Geographical and cognitive proximity effects on innovation performance in SMEs: a way through knowledge acquisition. Int Entrep Manag J 10, 231–251 (2014). https://doi.org/10.1007/s11365-011-0214-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11365-011-0214-z

Keywords

Navigation