Кластеры в институциональной проекции: к теории и методологии локального социально-экономического развития
Ключевые слова
Аннотация
Рассматривается проблема определения и идентификации кластеров как локализованных мезоэкономических систем с нечеткими границами, стимулирующими их развитие.Исследуется влияние индуктивного подхода на формирование теории кластеров, сравниваются различные типологии кластеров и других локализованных экономических систем. Дается обзор существующих методологических подходов к проблеме идентификации кластеров, обосновывается принципиальная роль институционального измерения в идентификации (и функционировании) кластеров, особенно в сравнении с теорией комплексообразования, основанной на тех-нологической связанности территориально близких единиц. Показано, что безвключения в анализ наряду с локационными и технологическими институциональных факторов (раскрываемых через различные переменные) практически не-возможно построить самостоятельную теорию кластеров, отличную от общей теории агломераций. Впервые анализируется иерархия институтов, влияющих на создание локальных экономических систем, и выделены институциональные уровни, по зрелости которых можно судить о формировании кластеров как наиболее успешных мезоэконмических систем. При этом отмечается, что в экономиках, тяготеющих крыночному типу организации, развитие мезоэкономических систем неразрывно связано с конкуренцией за инновационную ренту. Таким образом, обозначаются контуры методологии исследования кластеров, позволяющей рассматривать такие относительно новые в региональной науке феномены, как иннова-ционные и «трансграничные» кластеры.
This article addresses the problem of definition and identification of clusters as localised mesoeconomic systems with fuzzy boundaries that stimulate the development of these systems. The author analyses the influence of the inductive approach on the formation of cluster theory and juxtaposes different typologies of clusters and other types of localised economic systems. The article offers an overview of the existing methodological approaches to the problem of cluster identification and emphasizes 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 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.
2. Гареев Т. Р. Институты и экономическое развитие на субрегиональном (мезо)уровне // Общественные науки и современность. 2010. № 5. С. 45—58.
3. Гареев Т. Р. Региональный институционализм: terra incognita или terra ficta? // Journal of Institutional Studies. 2010. Т. 2, № 2. С. 27—37.
4. Куценко Е. С. Кластеры в экономике: практика выявления. Обобщение зарубежного опыта // Обозреватель — Observer. 2009. № 10 (237). C. 109—126.
5. Левин С. Н. Формирование конституционных правил в экономике России. Кемерово, 2007.
6. Марков Л. С. Институциональные аспекты функционирования инновационного кластера // Менеджмент инноваций. 2010. № 4.
7. Марков Л. С., Ягольницер М. А. Мезоэкономические системы: проблемы типологии // Регион: экономика и социология. 2008. № 1. С. 18―44.
8. Мезоэкономика развития / под ред. чл.-кор. РАН Г. Б. Клейнера; ЦЭМИ РАН. М., 2011.
9. Пилипенко И. В. Кластеры и территориально-производственные комплексы в региональном развитии // Региональное развитие и региональная политика России в переходный период / под общ. ред. С. С. Артоболевского, О. Б. Глезер. М., 2011. С. 191―208.
10. Пилипенко И. В. Принципиальные различия в концепции промышленных кластеров и территориально-производственных комплексов // Вестник Московского университета. Сер. 5. География. 2004. № 5. С. 3―9.
11. Портер М. Конкурентные преимущества стран // Вехи экономической мысли / под общ. ред. А. П. Киреева; Гос. ун-т — Высшая школа экономики, Институт «Экономическая школа». М., 2006. Т. 6 : Международная экономика. С. 549—581.
12. Портер М. Конкуренция / пер. с англ. М., 2003.
13. Шаститко А. Е. Кластеры как форма пространственной организации экономической деятельности: теория вопроса и эмпирические наблюдения //Балтийский регион. 2009. № 2. С. 9—32.
14. Bergman E., Feser E. Industrial and regional clusters: concepts and comparative applications / ed. by S. Loveridge. Morgantown : Regional Research Institute : West Virginia University, 1999.
15. Berry B. Approaches to regional analysis: a synthesis // Annals of the Association of American Geographers. 1964. № 54. P. 2―11.
16. Brachert M., Titze M., Kubis A. Identifying industrial clusters from a multidimensional perspective: methodical aspects with an application to Germany // Papers in Regional Science. 2011. Vol. 90, № 2. P. 419―439.
17. Boschma R. Proximity and innovation: a critical assessment // Regional Studies. 2005. Vol. 39(1). P. 61―74.
18. Clusters, innovation and entrepreneurship / ed. by J. Potter, G. Miranda. OECD, 2009.
19. Czamanski S., Ablas L. Identification of industrial clusters and complexes: a comparison of methods and findings // Urban Studies. 1979. № 16. P. 61—80.
20. Diaz B., Moniche L., Morillas A. A fuzzy clustering approach to the key sectors of the Spanish economy // Economic Systems Research. 2006. Vol. 18, № 3.P. 299—318.
21. Diaz B., Morillas A. Robust statistics and fuzzy industrial clustering / forging the new frontiers: fuzzy pioneers II / ed. by M. Nikravesh [et al.]. Springer-Verlag, 2008. P. 219 —236.
22. Dridi Ch., Hewings G. Sectors associations and similarities in input-output systems: an application of dual scaling and fuzzy logic to Canada and the United States // The Annals of Regional Science. 2003. № 37. P. 629―656.
23. Enright M. Regional clusters and multinational enterprises: independence, dependence or interdependence? // International Studies of Management and Organization. 2000. № 30(2). P 114—138.
24. Feser E. J., Bergman E. M. National industry cluster templates: a framework for regional cluster analysis // Regional Studies. 2000. Vol. 34(1). P. 1―20.
25. Feser E., Renski H., Goldstein H. Clusters and economic development outcomes:an analysis of the link between clustering and industry growth // Economic Development Quarterly. 2008. № 22. P. 324―344.
26. Iammarino S., McCann Ph. The structure and evolution of industrial clusters: transactions, technology and knowledge spillovers // Research Policy. 2006.Vol. 35(7). P. 1018―1036.
27. Lagendijk A. Towards conceptual quality in regional studies: the need for subtle critique — a response to markusen // Regional Studies. 2003. Vol. 37(6—7).P. 719—727.
28. Manning S. Customizing clusters: on the role of western multinational corporations in the formation of science and engineering clusters in emerging economies// Economic Development Quarterly. 2008. Vol. 22, № 4. P. 316—323.
29. Markusen A. Fuzzy concepts, scanty evidence, policy distance: the case for rigour and policy relevance in critical regional studies // Regional Studies. 1999.Vol. 33(9). P. 869—884.
30. Markusen A. Sticky places in slippery space: a typology of industrial districts// Economic Geography. 1996. Vol. 72(3). P. 293―313.
31. Martin P., Mayer T., Mayneris F. Public support to clusters: a firm level study of French «Local Productive Systems» // Regional Science and Urban Economics.2011. № 41. P. 108—123.
32. Martin R., Sunley P. Deconstructing clusters: chaotic concepts or policy panacea? // Journal of Economic Geography. 2003. № 3. P. 5—35.
33. Morillas A., Robles L., Diaz B. I-O coefficients importance: a fuzzy logic approach // International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 2011. Vol. 19, № 6. P. 1013−1031.
34. Moulaert F., Sekia F. Territorial innovation models: a critical survey // Regional Studies. 2003. Vol. 37(3). P. 289—302.
35. Oksanen E., Williams J. An alternative factor-analytic approach to aggregation of input-output tables // Econiomic Systems Research. 1992. № 4(3).P. 245―256.
36. Pickernell D., Rowe P., Christie M., Brooksbank D. Developing a framework for network and cluster identification for use in economic development policymaking// Entrepreneurship and Regional Development. 2007. № 19. P. 339―358.
37. Porter M. The economic performance of regions // Regional Studies. 2003.Vol. 37( 6—7). P. 549—578.
38. Rugman A., Verbeke A. Multinational enterprises and clusters: an organizing framework // MIR : Management International Review. 2003. Vol. 43, № 3.P. 151―169.
39. Schenk K.-E. Economic institutions and complexity: structures, interactions, and emergent Properties. Edward Elgar Publishing Limited, 2003.
40. Sonis M., Hewings J., Guo D. Industrial clusters in the input-output economic system // Handbook of Research on Cluster Theory / ed. by Ch. Karlsson. Edward Elgar, 2008. P. 153―168.
41. Steiner M., Hartmann C. Organizational learning in clusters: a case study on material and immaterial dimensions of cooperation // Regional Studies. 2006.Vol. 40(7). P. 493―506.
42. Sweeney S., Feser E. Plant size and clustering of manufacturing activity //Geographical Analysis. 1998. Vol. 30, № 1. P. 45―64.
43. Titze M., Brachert M., Kubis A. The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis (QIOA) // Regional Studies. 2011.Vol. 45( 1). P. 89―102.
44. Vishvanath A., Chen H. Technology Clusters: Using Multidimensional Scaling
to Evaluate and Structure Technology Clusters // Journal Of The American Society
For Information Science And Technology. 2006. № 57(11). P. 1451―1460.
45. Yang G., Stough R., Haynes K. Spatial and functional clustering: a comparative analysis of the Baltimore and Washington DC metropolitan regions in the US /
Handbook of Research on Innovation and Clusters: Cases and Policies / ed. by Ch. Karlsson. Edward Elgar, 2008. P. 343―358.
References
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, pp. 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,pp. 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, pp. 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),
pp. 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, pp. 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, pp. 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, pp. 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. E. 2009, Klastery kak forma prostranstvennoj organizacii jekonomicheskoj dejatel'nosti: teorija voprosa i jempiricheskie nabljudenija [Clusters as a Form of Spatial Organisation of Economic Activity: Theory and Practical Observations], Baltijskij region [Baltic Region], no. 2, pp. 9—32. doi: 10.5922/2074-9848-2009-2-2.
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, pp. 2―11.
16. Brachert, M., Titze, M., Kubis, A. 2011, Identifying industrial clusters from a multidimensional perspective: Methodical aspects with an application to Germany, Papers in Regional Science, Vol. 90, no. 2, pp. 419―439.
17. Boschma, R. 2005, Proximity and Innovation: A Critical Assessment, Regional Studies, Vol. 39(1), pp. 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, pp. 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, pp. 299—318.
21. Diaz, B., Morillas, A. 2008, Robust Statistics and Fuzzy Industrial Clustering. In: Forging the New Frontiers: Fuzzy Pioneers II, Springer-Verlag, pp. 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, pp. 629―656.
23. Enright, M. 2000, Regional clusters and multinational enterprises: Independence, dependence or interdependence? International Studies of Management and Organization, no. 30(2), pp. 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, pp. 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), pp.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), pp. 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, pp. 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), pp. 869—884.
30. Markusen, A. 1996, Sticky places in slippery space: a typology of industrial districts, Economic Geography,Vol. 72(3), pp. 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, pp. 108—123.
32. Martin, R., Sunley, P. 2003, Deconstructing clusters: chaotic concepts or policy panacea? Journal of Economic Geography, no. 3, pp. 5—35.
33. Morillas, A., Robles, L., Diaz, B. 2011, I-O coefficients importance: a fuzzy logic approach, International Journal of Uncertainty, Fuzziness and KnowledgeBased Systems,Vol. 19, no. 6, pp. 1013−1031.
34. Moulaert, F., Sekia, F. 2003,Territorial innovation models: a critical survey, Regional Studies, Vol. 37(3), pp. 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), pp. 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, № 19, pp. 339―358.
37. Porter, M. 2003, The Economic Performance of Regions, Regional Studies, Vol. 37, no. 6—7, pp. 549—578.
38. Rugman, A., Verbeke, A. 2003, Multinational Enterprises and Clusters: An Organizing Framework, MIR: Management International Review,Vol. 43, no. 3,pp. 151―169.
39. Schenk, K.-E. 2003, Economic institutions and complexity: structures, interactions, and emergent Properties, Edward Elgar Publishing Limited.
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,pp. 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 (July), pp. 493―506.
42. Sweeney, S., Feser, E. 1998, Plant size and clustering of manufacturing activity, Geographical Analysis, Vol. 30, no. 1, pp. 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, pp. 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),pp. 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, pp. 343―358.