Türkiye’de Şirket Kuruluş ve Kapanış Dinamiklerinin İller Bazında Analizi: Kümeleme, Entropi ve MAUT yaklaşımı

Abstract

Bu çalışma, Türkiye'de 81 il düzeyinde şirket kuruluş ve kapanış dinamiklerini analiz ederken, aynı zamanda bölgesel ekonomik kalkınma, girişimcilik ekosistemi ve yabancı sermaye etkilerini de değerlendirmektedir. Araştırmada, Türkiye Odalar ve Borsalar Birliği (TOBB), Türkiye Esnaf ve Sanatkârları Konfederasyonu (TESK) ve Türkiye Ticaret Sicil Gazetesi’nden elde edilen 2024 yılına ait veriler kullanılarak, 81 ilin şirketleşme oranları, kuruluş ve kapanış eğilimi gibi girişimcilik performansları incelenmiştir. Çalışmanın ilk aşamasında, illere özgü girişimcilik düzenini belirlemek amacıyla Kümeleme Analizi uygulanmıştır. Ardından, Çok Kriterli Karar Verme (ÇKKV) yöntemlerinden biri olan Entropi yöntemi ile kriterlerin ağırlıklar hesaplanmış ve MAUT (Multiple Attribute Utility Theory) yöntemi ile illerin girişimcilik ve ekonomik performanslarına göre sıralanmıştır. Elde edilen bulgular, Türkiye’de girişimcilik seviyelerinin iller arasında önemli farklılıklar gösterdiğini ortaya koymakta; özellikle düşük girişimcilik düzeyine sahip bölgeler için daha fazla bölgesel stratejilerin geliştirilmesi gerektiği tespit edilmiştir. Bu çalışma, iş kurma ve kapatma dinamiklerinin incelenmesi ve şirketlerin sürdürülebilirliğinin artırılması adına literatüre özgün katkılar sunmayı hedeflemektedir.

Keywords

• Şirket Dinamikleri
• Girişimcilik
• İl Bazında Analiz
• Kümeleme Analizi
• Entropi
• MAUT
• Bölgesel Kalkınma

Provincial Analysis of Company Establishment and Closure Dynamics in Türkiye: Clustering, Entropy and MAUT Approach

Abstract

This study analyzes the dynamics of company establishment and closure at the level of 81 provinces in C, while also assessing regional economic development, entrepreneurship ecosystem and foreign capital effects. Using data from the Union of Chambers and Commodity Exchanges of Türkiye (TOBB), the Confederation of Turkish Tradesmen and Craftsmen (TESK) and the Turkish Trade Registry Gazette for the year 2024, the study examines the entrepreneurial performances of 81 provinces, such as incorporation rates, establishment and closure trends. In the first stage of the study, Cluster Analysis was applied to identify province-specific entrepreneurship patterns. Then, the weights of the criteria were calculated with the Entropy method, one of the Multi-Criteria Decision Making (MCDM) methods, and the provinces were ranked according to their entrepreneurship and economic performance with the MAUT (Multiple Attribute Utility Theory) method. The findings reveal that there are significant differences in entrepreneurship levels among provinces in Türkiye and that more regional strategies should be developed especially for regions with low entrepreneurship levels. This study aims to make original contributions to the literature in order to analyze the dynamics of business start-up and closure and to increase the sustainability of companies.

Keywords

• Company Dynamics
• Entrepreneurship
• Provincial Analysis
• Cluster Analysis
• Entropy
• MAUT
• Regional Development

References

1. Aidis, R., Estrin, S., & Mickiewicz, T. (2012). Size matters: Entrepreneurial entry and government. Small Business Economics, 39(1), 119-139.
2. Aliusta, G. (2024). Socioeconomic determinants of firm establishment rates: The case of Turkiye. Anadolu University Journal of Social Sciences, 30(1), 45–63.
3. Alpar, R. (2011). Applied Multivariate Statistical Methods, (3th ed.). Detay Publishing.
4. Armington, C. & Acs, Z. J. (2002). The determinants of regional variation in new firm formation. Regional Studies, 36(1), 33-45.
5. Atamer, B. (1992). Cluster analysis and application of cluster analysis to pharmaceutical industry [Master Thesis]. Marmara University.
6. Audretsch, D. B. & Mahmood, T. (1995). New firm survival: New results using a hazard function. The Review of Economics and Statistics, 77(1), 97-103.
7. Chen, W., Feng, D. & Chu, X. (2015). Study of poverty alleviation effects for Chinese fourteen contiguous destitute areas based on entropy method. International Journal of Economics and Finance, 7(4), 89-98.
8. Confederation of Turkish Tradesmen and Craftsmen (TESK). (2024). Population and tradesmen data. www.tesk.org.tr (Access Date: 15.02.2025).

9. Çelik, U., Akçetin, E., & Gök, M. (2017). Applied data mining with rapidminer, (1st ed.) Pusula Publishing.
10. Çolak, B., Durdağ, Z. & Erdoğmuş, P. (2016). Automatic clustering with K-means algorithm. El-Cezeri Science and Engineering Journal, 3(2), 315-323.
11. Djankov, S., La Porta, R., Lopez-de-Silanes, F. & Shleifer, A. (2002). The regulation of entry. Quarterly Journal of Economics, 117(1), 1–37.
12. Duda, R.O., Hart, P.E., & Stork, D.G. (2001). Pattern Classification (2nd ed.). John Wiley & Sons.
13. Dunne, T., Roberts, M. J. & Samuelson, L. (1988). Patterns of firm entry and exit in US manufacturing industries. The RAND Journal of Economics, 19(4), 495-515.
14. DPT. (2006). Regional development and company dynamics in Türkiye. State Planning Organization Publications.
15. Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (5th ed.). Wiley.
16. Freitas, L. V., Freitas, A. P. B. R., Veraszto, E. V., Marins, F. A. S. & Silva, M. B. (2013). Decision-making with multiple criteria using AHP and MAUT: An industrial application. European International Journal of Science and Technology, 2(9), 93-100.
17. Haltiwanger, J. (2000). Firm dynamics and productivity growth. NBER Working Paper No. 7288. https://doi.org/10.3386/w7288.
18. Haltiwanger, J. (2012). Job creation and firm dynamics in the United States. In: Innovation Policy and the Economy, 12(1), 17-38.
19. Han, J., Pei, J., & Kamber, M. (2011). Data Mining: Concepts and techniques. Elsevier Science & Technology (3th ed.). San Francisco: Morgan Kaufmann.
20. Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag.
21. İslamoglu, M., Apan, M., & Öztel, A. (2015). An evaluation of the financial performance of REITs in Borsa Istanbul: A case study using the Entropy-Based TOPSIS Method. International Journal of Financial Research, 6(2), 124-138.
22. Kaufman, L., & Rousseeuw, P. J. (2005). Finding groups in data: An introduction to cluster analysis. John Wiley & Sons.
23. Kailiponi, P. (2010). Analyzing evacuation decisions using multi-attribute utility theory (MAUT). Procedia Engineering, 3(2010), 163-174.
24. Karakuş, C., & Baykasoğlu, A. (2022). Evaluation of innovation performance in manufacturing firms using Fuzzy TOPSIS. Gazi University Journal of Science, 35(1), 231–245.
25. Karami, A., & Johansson, R. (2014). Utilization of multi attribute decision making techniques to integrate automatic and manual ranking of options. Journal of Information Science and Engineering, 30(2), 519-534.
26. Ketchen, D. J., & Shook, C. L. (1996). The application of cluster analysis in strategic management research: An analysis and critique. Strategic Management Journal, 17(6), 441-458.
27. Kuckertz, A., Brändle, L., Gaudig, A., Hinderer, S., Reyes, C. A. M, Prochotta, A., Steinbrink, K. M., & Berger, E. S. C. (2020). Startups in times of crisis – A rapid response to the COVID-19 pandemic. Journal of Business Venturing Insights, 13, 1-13.
28. Mishra, A. R., Rani, P., & Verma, S. (2021). A hybrid fuzzy-AHP and K-means clustering approach for investment decision in industrial zones. Expert Systems with Applications, 178, 114976.
29. Norusis, M.J. (1993). SPSS for Windows advanced statistics release 6.0, SPSS Inc.
30. Olson, D. L. (1995). Decision aids for selection problems. Springer Science & Business Media.
31. Özdemir, M. ve Seçkin, Z. (2023). Türkiye’de dijital eşitsizlik ve girişimcilik ilişkisi: Panel veri analizi. İktisat ve Finans Araştırmaları Dergisi, 7(1), 31–48.
32. Özkan, Y. (2013). Data mining methods. Papatya Publishing.
33. Pektas, A.O. (2013). Data mining with SPSS. Vertical Publishing Distribution.
34. Rao, M. R. (1971). Cluster analysis and mathematical programming. Journal of the American Statistical Association, 66(335), 622-626.
35. Salehi, A. & Izadikhah, M. (2014). A novel method to extend SAW for decision-making problems with interval data. Decision Science Letters, 3(2), 225–236.
36. Schumpeter, J. A. (1934). The theory of economic development: an inquiry into profits, capital, credit, interest, and the business cycle. Harvard University Press.
37. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423; 623–656.
38. Siffert, M. & Guimarães, L. (2020). Entrepreneurial ecosystem and sustainability as catalysts for regional development: Proposition of a theoretical framework. Journal of the Knowledge Economy, 21(4), 1-23.
39. State Planning Organization (DPT). (2006). Regional Development National Strategy (BGUS) 2007-2013. DPT Publications.
40. Taymaz, E., Voyvoda, E., & Yılmaz, K. (2008). Structural transformation, productivity and technological change dynamics in Turkish manufacturing industry (ERC Working Papers in Economics No. 08/04). Middle East Technical University, Center for Economic Research.
41. The Economic Policy Research Foundation of Turkiye (TEPAV). (2005). Turkiye investment climate assessment (Vol. 2). TEPAV Publications.
42. The Union of Chambers and Commodity Exchanges of Turkiye (TOBB). (2024). Data on Established and Closed Companies by Province. www.tobb.org.tr
43. TUİK, Türkiye İstatistik Kurumu (Nisan, 2024). Regional economic data. TÜİK Official Database. www.tuik.gov.tr (Access Date: 08.02.2025).
44. TUİK, Türkiye İstatistik Kurumu (Nisan, 2024). Regional Indicators Database. www.tuik.gov.tr (Access Date: 08.02.2025).
45. Ulutaş, A., Özkan, A. M., & Tağaf, H. (2018). Personnel selection using Fuzzy Analytic Hierarchy Process and Fuzzy Grey Relational Analysis methods. Electronic Journal of Social Sciences, 17(65), 223-232.
46. Wang, M., Lin, S. J., & Lo, Y. C. (2010, December 7-10). The comparison between MAUT and PROMETHEE [Conference presentation]. 2010 IEEE International Conference on Industrial Engineering and Engineering Management, Macao, China.
47. Winterfeldt, D. Von, & Edwards W. (1986). Decision analysis and behavioral research. Cambridge University Press.