The Baltic Region

2012 Issue №3(13)

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Clusters in the institutional perspective: on the theory and methodology of local socioeconomic development

DOI
10.5922/2079-8555-2012-3-1
Pages
4-24

Abstract

This article addresses the problem of definition and identification of clusters as localized mesoeconomic systems with fuzzy boundaries that stimulate the  development of these systems. The author analyses the influence of the inductive approach to the formation of cluster theory and juxtaposes different typologies of clusters and other types of localized economic systems. The article offers an overview of the existing methodological approaches to the problem of cluster identification and emphasises the major role of institutional dimension in the identification (and functioning) of clusters, especially in comparison to cluster formation theory based on the technological connection of adjacent units. The author comes to a conclusion that, without the inclusion of institutional factors, alongside localising and technological ones (demonstrated through different variables), it is virtually impossible to develop an independent cluster theory, different from the general  agglomeration theory. For the first time, a hierarchy of institutions affecting the formation of local economic systems is considered against the background of the identification of institutional levels, whose full development makes it possible to speak of the formation of clusters as most successful mesoeconomic systems. At the same time, the author emphasizes that, in economies gravitating towards the market type of organisation, the development of mesoeconomic systems is closely connected to competition for innovative rent. The article outlines the methodology for cluster studies, which makes it possible to consider such relatively new to the regional science phenomena as innovative and “transborder” clusters.

Reference

1. Gareev, T. R. 2007, «Voshodjawie» modeli regional'nogo razvitija, lokal'nye proizvodstvennye sistemy i razvitie malogo i srednego biznesa [«Rising» model of regional development, local production systems and development of small and medium
businesses]. In: Kaliningradskaja oblast': na puti k regional'nym programmam MBA/MPA [Kaliningrad region: towards regional programs MBA / MPA], Kaliningrad, Izd-vo RGU im. I. Kanta, p. 76—113.
2. Gareev, T. R. 2010, Instituty i jekonomicheskoe razvitie na subregional'nom (mezo-) urovne [Institutions and economic development at the subregional (meso) level], Obwestvennye nauki i sovremennost' [Social Sciences and the present], no. 5,
p. 45—58.
3. Gareev, T. R. 2010, Regional'nyj institucionalizm: terra incognita ili terra ficta? [Regional institutionalism: terra incognita or terra ficta? Journal of Institutional Studies, Vol. 2, no. 2, p. 27—37.
4. Kutsenko, E. S. 2009, Klastery v jekonomike: praktika vyjavlenija. Obobwenie zarubezhnogo opyta [Clusters in the economy: the practice of identification. Generalization of international experience], Obozrevatel' — Observer, no. 10 (237), p. 109—126.
5. Levin, S. N. 2007, Formirovanie konstitucionnyh pravil v jekonomike Rossii [The formation of the constitutional rules in the Russian economy], Kemerovo, Kuzbassvuzizdat.
6. Markov, L. S. 2010, Institucional'nye aspekty funkcionirovanija innovacionnogo klastera [Institutional aspects of the innovation cluster], Menedzhment innovacij [Management of innovation], no. 4.

7. Markov, L. S., Yagolnitser, M. A. 2008, Mezojekonomicheskie sistemy: problemy tipologii [Mesoeconomic system: problems of typology], Region: jekonomika i sociologija [Region: Economics and Sociology], no. 1, p. 18―44.
8. Mezojekonomika razvitija [Mezoekonomika development], 2011, CJeMI RAN, Moscow, Nauka.
9. Pilipenko, I. V. 2011, Klastery i territorial'no-proizvodstvennye kompleksy v regional'nom razvitii, Regional'noe razvitie i regional'naja politika Rossii v perehodnyj period [Clusters and territorial-industrial complexes in regional development, regional development and regional policy in Russia during the transition period], Moscow, Izd-vo MGTU im. N. Je. Baumana, p. 191―208.
10. Pilipenko, I. V. 2004, Principial'nye razlichija v koncepcii promyshlennyh klasterov i territorial'no-proizvodstvennyh kompleksov [The principal differences in the concept of industrial clusters and territorial production complexes], Vestnik Moskovskogo Universiteta. Ser. 5, Geografija [Moscow University Geography Bulletin], no. 5, p. 3―9.
11. Porter, M. 2006, Konkurentnye preimuwestva stran [The competitive advantages of countries]. In: Vehi jekonomicheskoj mysli, T. 6, Mezhdunarodnaja jekonomika [Landmarks of Economic Thought, T. 6, International Economics], Moscow, TEIS, p. 549—581.
12. Porter, M. 2003, Konkurencija [Сompetition], Moscow, Izdatel'skij dom «Vil'jams».
13. Shastitko, A. Ye. 2009, Clusters as a Form of Spatial Organisation of Economic Activity: Theory and Practical Observations, Baltic Region, no. 2, p. 7—25. doi: 10.5922/2079-8555-2009-2-2.
14. Bergman, E., Feser, E. 1999, Industrial and Regional Clusters: Concepts and Comparative Applications, Morgantown, Regional Research Institute, West Virginia University.
15. Berry, B. 1964, Approaches to regional analysis: A synthesis, Annals of the Association of American Geographers, no. 54, p. 2―11.
16. Brachert, M., Titze, M., Kubis, A. 2011, Identifying industrial clusters fr om a multidimensional perspective: Methodical aspects with an application to Germany, Papers in Regional Science, Vol. 90, no. 2, p. 419―439.
17. Boschma, R. 2005, Proximity and Innovation: A Critical Assessment, Regional Studies, Vol. 39 (1), p. 61―74.
18. Potter J., Miranda, G. (ed). 2009, Clusters, Innovation and Entrepreneurship, OECD.
19. Czamanski, S., Ablas, L. 1979, Identification of Industrial Clusters and Complexes: a Comparison of Methods and Findings, Urban Studies, no. 16, p. 61—80.
20. Diaz, B., Moniche, L., Morillas, A. 2006, A Fuzzy Clustering Approach to the Key Sectors of the Spanish Economy, Economic Systems Research, Vol. 18, no. 3, p. 299—318.
21. Diaz, B., Morillas, A. 2008, Robust Statistics and Fuzzy Industrial Clustering. In: Forging the New Frontiers: Fuzzy Pioneers II, Springer-Verlag, p. 219 —236.
22. Dridi, Ch., Hewings, G. 2003, Sectors associations and similarities in inputoutput systems: An application of dual scaling and fuzzy logic to Canada and the United States, The Annals of Regional Science, no. 37, p. 629―656.
23. Enright, M. 2000, Regional clusters and multinational enterprises: Independence, dependence or interdependence? International Studies of Management and Organization, no. 30(2), p. 114—138.
24. Feser, E. J., 2000, Bergman E. M. National Industry Cluster Templates: A Framework for Regional Cluster Analysis, Regional Studies, no. 34.1, p. 1―20.

25. Feser, E., Renski, H., Goldstein, H. 2008, Clusters and Economic Development Outcomes: An Analysis of the Link between Clustering and Industry Growth, Economic Development Quarterly, no. 22, p. 324―344.
26. Iammarino, S., McCann, Ph. 2006, The structure and evolution of industrial clusters: Transactions, technology and knowledge spillovers, Research Policy, Vol. 35 (7), p. 1018―1036.
27. Lagendijk, A. 2003, Towards Conceptual Quality in Regional Studies: The Need for Subtle Critique — A Response to Markusen, Regional Studies, Vol. 37 (6—7), p. 719—727.
28. Manning, S. 2008, Customizing Clusters: On the Role of Western Multinational Corporations in the Formation of Science and Engineering Clusters in Emerging Economies, Economic Development Quarterly,Vol. 2, no. 4, p. 316—323.
29. Markusen, A. 1999, Fuzzy concepts, scanty evidence, policy distance: the case for rigour and policy relevance in critical regional studies, Regional Studies, no. 33(9), p. 869—884.
30. Markusen, A. 1996, Sticky places in slippery space: a typology of industrial districts, Economic Geography,Vol. 72 (3), p. 293―313.
31. Martin, P., Mayer, T., Mayneris, F. 2011, Public support to clusters: a firm level study of French «Local Productive Systems», Regional Science and Urban Economics, no. 41, p. 108—123.
32. Martin, R., Sunley, P. 2003, Deconstructing clusters: chaotic concepts or policy panacea? Journal of Economic Geography, no. 3, p. 5—35.
33. Morillas, A., Robles, L., Diaz, B. 2011, I-O coefficients importance: a fuzzy logic approach, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems,Vol. 19, no. 6, p. 1013−1031.
34. Moulaert, F., Sekia, F. 2003,Territorial innovation models: a critical survey, Regional Studies, Vol. 37(3), p. 289—302.
35. Oksanen, E., Williams, J. 1992, An Alternative Factor-analytic Approach to Aggregation of Input—Output Tables, Econiomic Systems Research, no. 4(3), p. 245―256.
36. Pickernell, D., Rowe, P., Christie, M., Brooksbank, D. 2007, Developing a Framework for Network and Cluster Identification for Use in Economic Development Policy-Making, Entrepreneurship and Regional Development, no. 19, p. 339―358.
37. Porter, M. 2003, The Economic Performance of Regions, Regional Studies, Vol. 37, no. 6—7, p. 549—578.
38. Rugman, A., Verbeke, A. 2003, Multinational Enterprises and Clusters: An Organizing Framework, MIR: Management International Review,Vol. 43, no. 3, p. 151―169.
39. Schenk, K.-E. 2003, Economic institutions and complexity: structures, interactions, and emergent Properties, Edward Elgar Publishing Lim ited.
40. Sonis, M., Hewings, J., Guo, D. 2008, Industrial clusters in the input—output economic system. In: Handbook of Research on Cluster Theory, Edward Elgar, p. 153―168.
41. Steiner, M., Hartmann, C. 2006, Organizational learning in clusters: A case study on material and immaterial dimensions of cooperation, Regional Studies, Vol. 40, p. 493―506.
42. Sweeney, S., Feser, E. 1998, Plant size and clustering of manufacturing activity, Geographical Analysis, Vol. 30, no. 1, p. 45―64.

43. Titze, M., Brachert, M., Kubis, A. 2011, The Identification of Regional Industrial Clusters Using Qualitative Input—Output Analysis (QIOA), Regional Studies, Vol. 45, no. 1, p. 89―102.
44. Vishvanath, A., Chen, H. 2006, Technology Clusters: Using Multidimensional Scaling to Evaluate and Structure Technology Clusters, Journal Of The American Society For Information Science And Technology, no. 57(11), p. 1451―1460.
45. Yang, G., Stough, R., Haynes, K. 2008, Spatial and functional clustering: a comparative analysis of the Baltimore and Washington DC metropolitan regions in the US. In: Handbook of Research on Innovation and Clusters: Cases and Policies, Edward Elgar, p. 343―358.