The impact of the industrial Clusters on Regional Development Case Study: Stone Industrial Clusters of Isfahan Metropolitan Region

Authors

• Mohammad hosein Sharifzadegan
• Hoomayon Norayi

Abstract

Despite the formation of the largest production and processing of stone in the Isfahan metropolitan region in recent decades (including: Mahmmoudabad, Najafabad, Dolatabad, and Khomeinishahr industrial clusters), less detailed studies have been done about clustering, especially in relation to their role in the regional development of industrial areas. This study attempts to cover this gap by cluster analysis of the stone industrial of Isfahan metropolitan region impact on regional development in term of its intensity and desirability. A Mixed research paradigm (involving the mixed case study in quantitative and qualitative research methods) has been used. In this way, at first, the literature about “industrial clusters” and “the role of industrial clusters on the regional development” were reviewed to determin indexes. The second stage, the questionnaire was provided based on selected measures and multi stage sampling method (stratified random sampling for determiantion of sampling population and systematic sampling methods for sampling frame). Then, 223 persons who work in the selected industrial were selected among 1115 workers base on the clustering sample in order to complete the questionnaire and collect data. The third stage, the obtained data were entered into the SPSS software in which confirmatory factor analysis and linear scaling transformation technique were used for measuring selected clusters in term of its intensity and desirability, respectively. The results show that despite the potential influence of Mahmmoudabad, Najafabad, Dolatabad, and Khomeinishahr stone industrial clusters on the Isfahan metropolitan development in term of its intensity, the selected industrial clusters have not still a very desirable economic, social and physical impacts. Also, clusters have more impact on social regional development, internal relation of firm improvement, preventing management migration and increasing physical capital in comparison with to economic regional development, external relation of firm improvement, preventing staff migration and increasing human capital. Thus, stone industrial clusters in the Isfahan metropolitan region are stil in the embryonic stage of development and they are far from the theoretical industrial clusters which have high-intensity and desirable impact for their regions.

Keywords

• Industrial Clusters
• Regional Development
• Stone industry
• Isfahan metropolitan region

20.1001.1.22516735.1395.6.24.3.7

---

References

1. Amin, A. (2003). Chapter 10: Industrial Distrits. In E. Sheppard and T. J. Barnes. (eds). A companion to economic geography. Blackwell Companions to Geography.
2. Asheim, B. (1996). Industrial districts as learning regions: a condition for prosperity?, European Planning Studies 4, pp. 379–400.
3. Aydalot, P. (1986). Milieux Innovateurs en Europe. Groupe de Recherche Europe´en sur les Milieux Innovateurs (GREMI), Paris.
4. Beccattini, G., (1990), The Marshallian district as a socioeconomic notion, Industrial Districts and Inter-Firm Cooperation in Italy, F. Pyke, G. Becattini, and W. Sengenberger, eds., 37-51. International Institute for Labour Studies, Geneva.
5. Booysen, F. (2002). An overview and evaluation of composite indices of development. Social Indicators Research, No. 59, pp. 115–151.
6. Bresnahan, T., Gambardell, A. and Saxenian, A. (2001). Old economy’ inputs for ‘New economy’ outcomes: cluster formation in the New Silicon Valleys, Industrial and Corporate Change 10, pp. 835–860.
7. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models. Beverly Hills: Sage Publications.
8. Commission of the European Communities. (2008). The Concept of Clusters and Cluster Policies and their Role for Competitiveness and Innovation: Main Statistical Results and Lessons Learned. Commission Staff Working Paper Number SEC (2008) 2637. Commission of the European Communities, Brussels.
9. Cruz, S. C. S. and Teixeira, A. A. C. (2010). The Evolution of the Cluster Literature: Shedding Light on the Regional Studies–Regional Science Debate. Regional Studies, Vol. 44.9, pp. 1263–1288.
10. Dadashpoor, H. (2007). Learning, Innovation and Regional Economic Development: Empirical evidence of industrial clustering in the electronics and software industries in the Tehran metropolitan region. Studies in Regional Science, Vol. 37, No. 2, pp. 471-499.
11. Dadashpoor, H. (2010). Industrial Clustering, Innovation and competitive advantage in Tehran metropolitan region: Evidence of Auto-parts cluster in Iran. The Journal of Humanities, Vol. 17, No. 1, pp. 19-46.
12. Dadashpoor, H. (2011). Analyzing the Determinants of Locational Advantages in the Tehran Metropolitan Regions: Empirical Evidences of the Four Industrial Sectors, Quarterly journal of environment based territorial planning, 14, pp. 91- 117. [In Persian].
13. Dadashpoor, H., and Dadejani, M., (2015). Identyfing and prioritizing the radical factors influencing regional competitiveness; case study: Kurdistan Province. Jurnal of Regional Planning, 5(19), pp. 27-42. [In Persian].
14. Ghasemi, V. (2010). Structural equation modeling in social researches using AMOS graphic. Jameashenasan Press. [In Persian].
15. Hussey, D. M. & Eagan, P. D. (2007). Using structural equation modeling to test environmental performance in small and medium-sized manufacturers: can SEM help SMEs? Journal of Cleaner Production, Vol. 15, pp. 303–312.
16. INTERNAZIONALE MARMI E MACCHINE CARRARA S.P.A. (2014). Stone Sector 2014: Annual Report and Prospects for the International Stone Trade. Italian Trade Agency.
17. Johnson, R. B. and Christensen, L. (2014). Educational Research: Quantitative, Qualitative, and Mixed Approaches. 4th Edition. SAGE Publications, Inc.
18. Kalantari, Kh. (2009). Structural equation modeling in socio-economic research (with LISREL and SIMPLIS software). Farhange Saba Press. [In Persian].
19. Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling (Methodology in the Social Sciences). 3rd edition, Guilford Press.
20. Lee, Y. J. (2008). Subjective quality of life measurement in Taipei. Building and Environment, 43, pp. 1205– 1215.
21. MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149.
22. Mahdavi, M. T. (2007). Industrial clusters. Special association of industry and mining research and development. Tehran. [In Persian].
23. Marshall, A., (1890). Principles of Economics, London: Macmillan.
24. Maskell, P. (2001). Towards a knowledge-based theory of the geographical cluster, Industrial and Corporate Change 10, pp. 919–941.
25. Martin, R. and Sunley, P. (2003). Deconstructing clusters: chaotic concept or policy panacea?, Journal of Economic Geography, Vol. 3, pp. 5–35.
26. Maskell, P. and Lorenzen, M. (2004). The cluster as market organization, Urban Studies 41, pp. 991–1009.
27. Morgan, J. Q. (2004). The Role of Regional Industry Clusters in Urban Economic Development: An Analysis of Process and Performance. A dissertation submitted to the Graduate Faculty of  North Carolina State University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Public administration.
28. Morgan, J. Q. (2007). Industry Clusters and Metropolitan Economic Growth and Equality. International Journal of Economic Development, Volume 9, Number 4, pp. 307-375.
29. Naghsh-e-Jahan Consulting Engineers. (2010). Isfahan metropolitan plan, Volume 1: Introduction and determination of metropolitan position. Housing and urban planning ministry. [In Persian].
30. Oakey, R., Kipling, M. and Wildgust, S. (2001). Clustering among firms in the non-broadcast visual communications (NBVC) sector, Regional Studies 35, pp. 401–414.
31. OhUallachain, B. and Satterwhite, M. (1992). Sectoral Growth Patterns at the Metropolitan Level: An Evaluation of Economic Development Incentives. Journal of Urban Economics, Vol. 31: pp. 25-58.
32. Piore, M. J., Sabel, Ch. F., (1984). The Second Industrial Divide: Possibilities for Prosperity. New York: Basic Books.
33. Porter, M. (1990). The Competitive Advantage of Nations. New York, NY: The Free Press.
34. Porter, M. (1998). Clusters and the new economics of competition, Harvard Business Review 11, pp. 77–98.
35. Rabelotti, R. (1997). External Economies and Cooperation on Industrial Districts: A Comparison of Italy and Mexico.  St. Martin's Press.
36. Riggi, M. R. Maggioni, M. A. (2004). Labour Market Dynamics and Industrial Clusters: an Ecological Based Approach. XIX National Conference of Labour Economics.
37. Romer, P. (1986). Increasing Returns and Long-Run Growth. Journal of Political Economy, Vol. 94: pp. 1002-1037.
38. Rosenfeld, S. (2005) Industry clusters: business choice, policy outcome, or branding strategy?, Journal of New Business Ideas and Trends 3, pp. 4–13.
39. Saxenian, A. (1994). Regional Advantage: Culture and Competition in Silicon Valley and Route 128. Harvard University Press, Cambridge, MA.
40. Scott, A. J., (1988). New industrial spaces. London: Pergamon.
41. Sedighi, M. Y. (2010). The development of stone industrial clusters of Isfahan: Final report. Industry mining and trading Ministry. Isfahan. [In Persian].
42. Sideridis, G., Simos, P., Papanicolaou, A., & Fletcher, J. (2014). Using Structural Equation Modeling to Assess Functional Connectivity in the Brain Power and Sample Size Considerations. Educational and Psychological Measurement, Vol. 74, No. 5, pp. 733-758.
43. Soja, E. W. (2009). Regional Planning and Development Theories. In. Kitchin, R. and Thrift, N. (eds). International Encyclopedia of Human Geography. Elsevier.
44. Stropper, M. and Scott, A. (1989) The geographical foundations and social regulation of flexible production complexes, in Wolsh, J. and Dear, M. (Eds) The Power of Geography: How Territory Shapes Social Life, pp. 21–40. Allen & Unwin, Boston, MA.
45. Sölvell, Ö. and Williams, M. (2013). Building the Cluster Commons: An Evaluation of 12 Cluster Organizations in Sweden 2005-2012. Stockholm: Ivory Tower Publishers.
46. The World Bank. (2009). Clusters for Competitiveness: A Practical Guide & Policy Implications for Developing Cluster Initiatives. International Trade Department of the World Bank.
47. Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models an evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 73(6), pp. 913-934.