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İşletme Kümelerinin Belirlenmesinde Yararlanılan Yöntemlere İlişkin Bir Literatür İncelemesi

Year 2023, Volume: 21 Issue: 1, 153 - 170, 30.04.2023
https://doi.org/10.33688/aucbd.1150602

Abstract

Bu çalışmanın amacı, işletme kümelerini belirlemek için kullanılan yöntemlere ilişkin bir literatür incelemesi sunmak ve yöntemlerin ürettiği enformasyonu ve kısıtlarını kümelerin kavramsal nitelikleri kapsamında değerlendirmektir. Literatürde yer alan tüm yöntemlerin kendilerine özgü sınırlılıklara sahip olduğu görülmektedir. Bununla birlikte karma yaklaşımların, nicel yöntemlerden yararlanan yukarıdan aşağı yaklaşımlar ve nitel yöntemlerden yararlanan aşağıdan yukarı yaklaşımların tek başına benimsenmesinin neden olduğu sınırlılıkları ortadan kaldırabildiği görülmektedir. Kümelerin en temel niteliği olan etkileşim/bağlantısallık düzeyinin tespit edilmesinde ise sosyal ağ analizinden yararlanılabilir. İşletme kümelerinin ekonomik sistemler içinde belirlenebilmesi kümelere özgü politika önerilerinin geliştirilebilmesi için önem taşımaktadır.

Supporting Institution

Anadolu Üniversitesi

Project Number

1408E367

Thanks

Çalışma, 03/09/2020-05/09/2020 tarihleri arasında gerçekleştirilen 28. Ulusal Yönetim ve Organizasyon Kongresinde sunulmuştur. Görüş ve önerileri ile çalışmanın geliştirilmesine katkıda bulunan kongre katılımcılarına teşekkür ederim.

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A Literature Review on Methods Used For Determining Business Clusters

Year 2023, Volume: 21 Issue: 1, 153 - 170, 30.04.2023
https://doi.org/10.33688/aucbd.1150602

Abstract

The aim of this paper is to present a literature review on the methods used to identify business clusters and to evaluate the information and constraints produced by the methods within the scope of the conceptual characteristics of the clusters. All methods have their own limitations. However, mixed approaches can eliminate the limitations caused by adopting top-down approaches using quantitative methods and bottom-up approaches using qualitative methods alone. Social network analysis can be used to determine the level of interaction/connectivity, which is the most basic feature of clusters. Identifying business clusters within economic systems is important for developing cluster-specific policy recommendations.

Project Number

1408E367

References

  • Ache, P. (2000). Cities in old industrial regions between local innovative milieu and urban governance reflections on city region governance. European Planning Studies, 8 (6), 693-709. doi:10.1080/713666434
  • Akgüngör, S., Kumral, N., Lenger, A. (2003). National industry clusters and regional specializations in Turkey. European Planning Studies, 11 (6), 647-669. doi.10.1080/0965431032000108378
  • Akgüngör, S. (2004). Industry clusters in Turkey: Identifying regional highpoints. Yapı Kredi Economic Review, 15 (2), 69-90.
  • Alcacer, J., Zhao, M. (2013). Zooming in: A practical manual for identifying geographic clusters. Harward Business School Working Paper, 1-28. doi:10.1002/smj.2451
  • Asheim, B.T. (2000). Industrial districts: The contributions of Marshall and beyond. In: Clark, G. L., Gertler, M. S., Feldman, M. P. (Eds.), The Oxford handbook of economic geography (pp. 413-431). Oxford University Press.
  • Asheim, B., Gertler, M. (2006). The geography of innovation: Regional innovation systems. In J. Fagerberg, D. Mowery, R. Nelson (Eds.), The Oxford Handbook of Innovation (pp. 291–317). Oxford: Oxford University Press.
  • Barabasi, A. (2010). İş Hayatında, Bilimde ve Günlük Yaşamda Bağlantılar. (Çev. N. Elhüseyni). İstanbul: Optimist Yayınları.
  • Barkley, D., Kim, Y., Henry, M. (2001). Do manufacturing plants cluster across rural areas? Evidence from a probabilistic modeling approach. REDRL Research Report 10-2001-01. Regional Economic Development Research Laboratory Clemson University, Clemson, South Carolina.
  • Bathelt, H., Malmberg, A., Maskell, P. (2004). Clusters and knowledge: Local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 28 (1), 31–56. doi:10.1191/0309132504ph469oa
  • Becattini, G. (1990). The Marshallian industrial district as a socio-economic notion. In: F. Pyke, G. Becattini and W. Sengenberger (Eds.), Industrial Districts and Inter-Firm Cooperation In Italy (pp. 37–51). Geneva: International Institute for Labour Studies.
  • Bell, G. (2005). Clusters, networks, and firm innovativeness. Strategic Management Journal, 26, 287–295. doi:10.1002/smj.448
  • Bell, G., Zaheer, A. (2007). Geography, networks and knowledge flow. Organization Science, 18 (6), 955–972. doi:10.1287/orsc.1070.0308
  • Benita, F., Sarica, S., Bansal G. (2020). Testing the static and dynamic performance of statistical methods for detection of national industrial clusters. Pap Reg Sci., 99, 1137–1157. doi:10.1007/s41685-022-00272-5
  • Bergman, E.M., Feser, E. J. (1999). Industry clusters: A methodology and framework for regional development policy in the United States. In: Boosting Innovation: The Cluster Approach. Oecd Proceedings (pp 243-268).
  • Bergman, E. M., Feser, E. J. (2020). Industrial and regional clusters: concepts and comparative applications. Reprint. Edited by Scott Loveridge and Randall Jackson. WVU Research Repository.
  • Boschma, R., Wall, A. (2005). Knowledge networks and innovative performance in an industrial district: The case of a footwear district in the south of Italy. Papers in Evolutionary Economic Geography. Utrecht University.
  • 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, 90 (2), 419-437. doi:10.1111/j.1435-5957.2011.00356.x
  • Bramanti, A., Ratti, R. (1997). The multi-faced dimensions of local development. In: Ratti, R., Bramanti, A., Gordon, R. L. (Eds.), The dynamics of innovative regions: The GREMI approach (pp. 3-46).
  • Brown, R. (2000). Cluster dynamics in theory and practice with application to Scotland. Regional and Industrial Policy Research Paper Number: 38. Published by: European Policies Research Centre ISBN: 1-871130-16-6.
  • Brusco, S. (1990). The idea of industrial districts: Its genesis. In: F. Pyke, G. Becattini and W. Sengenberger (Eds.), Industrial districts and inter-firm cooperation in Italy (pp. 10–20). Geneva: International Institute for Labour Studies
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  • Carlino, G., Kerr, W. (2105). Agglomeration and innovation. In: Duranton, G., Henderson, V. J., Strange, W. C. (Eds.), Handbook of regional and urban economics (pp 349-404).
  • Carroll, M. C., Reid, N., Bruce W., Smith, B. W. (2008). Location quotients versus spatial autocorrelation in identifying potential cluster regions. Ann Reg Sci, 42, 449–463. doi: 10.1007/s00168-007-0163-1
  • Casanueva, C., Castro, I., Galan, J. (2013). Informational networks and innovation in mature industrial clusters. Journal of Business Research, 66, 603–613. doi:10.1016/j.jbusres.2012.02.043
  • Catini, R., Karamshuk, D., Penner, O., Riccaboni, M. (2015). Identifying geographic clusters: A network analytic approach. Research Policy, 44, 1749–1762. doi:10.1016/j.respol.2015.01.011
  • Chain, C.P., Santos, A.C.d., Castro, L.G.d., Júnior, Prado, J.W.d. (2019). Bibliometric analysis of the quantitative methods applied to the measurement of industrial clusters. Journal of Economic Surveys, 33: 60-84. doi:10.1111/joes.12267
  • Cruz, C. S., Teixeira, A. C. (2010). The evolution of the cluster literature: Shedding light on the regional studies–regional science debate. Regional Studies, 44 (9), 1263-1288. doi:10.1080/00343400903234670
  • Cortright, J. (2006). Making sense of clusters: Regional competitiveness and economic development. A Discussion Paper Prepared for the The Brookings Institution Metropolitan Policy Program.
  • Creswell, J. W. (2017). Araştırma Deseni: Nitel, Nicel ve Karma Yöntem Yaklaşımları. (Çev. Ed. Demir, S. B.) Ankara: Eğiten Kitap.
  • Delgado, M., Porter, M., Stern, S. (2014). Defining clusters of related industries. NBER Working Paper Series. http://www.nber.org/papers/w20375. adresinden edinilmiştir.
  • Duranton, G., Overman, H. G., (2005). Testing for localisation using micro-geographic data. Review of Economic Studies, 72 (4), 1077–1106.doi:10.1111/0034-6527.00362
  • Egeraat, C., Morgenroth, E., Kroes, R., Curran, D., Gleeson, J. (2015). A measure for identifying substantial geographic concentrations. MPRA Paper No. 65954. Retrieved from https://mpra.ub.uni-muenchen.de/65954/1/MPRA_paper_65954.pdf
  • Ellison, G., Glaeser, E. (1997). Geographic concentration in U.S. manufacturing industries: A dartboard approach. Journal of Political Economy, 105 (5), 889-927.
  • Feser, E., Bergman, E. (2000). National industry cluster templates: A framework for applied regional cluster analysis. Regional Studies, 34 (1), 1-19. doi:10.1080/00343400050005844
  • Feser E, Sweeney S, Renski H. (2005). A descriptive analysis of discrete U.S. industrial complexes. Journal of Regional Science, 45, 395–419. doi:10.1111/j.0022-4146.2005.00376.x
  • García-Lillo, F., Claver-Cortés, E., Marco-Lajara, B., Úbeda-García, M., Seva-Larrosa, P. (2018) On clusters and industrial districts: A literature review using bibliometrics methods, 2000–2015. Papers in Regional Science, 97: 835– 861. doi:10.1111/pirs.12291
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Details

Primary Language Turkish
Subjects Human Geography
Journal Section Derleme
Authors

Gökhan Önder 0000-0002-0936-4076

Project Number 1408E367
Early Pub Date April 30, 2023
Publication Date April 30, 2023
Published in Issue Year 2023 Volume: 21 Issue: 1

Cite

APA Önder, G. (2023). İşletme Kümelerinin Belirlenmesinde Yararlanılan Yöntemlere İlişkin Bir Literatür İncelemesi. Coğrafi Bilimler Dergisi, 21(1), 153-170. https://doi.org/10.33688/aucbd.1150602