EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS

Sinan Dündar

doi:10.30794/pausbed.1413500

Research Article

EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS

Year 2024, Issue: 61, 371 - 391, 22.03.2024

Sinan Dündar

https://doi.org/10.30794/pausbed.1413500

Abstract

The level of a country's entrepreneurship ecosystem is an important indicator that serves the economic development of that country. In today's world, governments resort to various instruments to strengthen the entrepreneurship infrastructure. In Türkiye, a significant part of these activities is implemented by KOSGEB. Since 2010, Hands-On Entrepreneurship Trainings are one of the initiatives that contribute to this objective. In this study, the performances of each province, NUTS-I regions and NUTS-II regions in Türkiye in terms of benefiting from entrepreneurship supports are analysed. The criteria used during the evaluation are weighted by Fuzzy BWM method where the most important criterion is determined as “number of enterprises supported following the trainings". In the performance ranking performed by AROMAN method TR6, TR3 and TR4 regions are ranked in the first three order as the most successful NUTS-I regions. In addition, a similar evaluation is carried out in terms of provinces and NUTS-II regions.

Keywords

Entrepreneurship, KOSGEB, MCDM, Fuzzy BWM, AROMAN

Ethical Statement

The research does not involve any content that requires the approval of the Ethics Committee.

References

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Amoozad Mahdiraji, H., Arzaghi, S., Stauskis, G., & Zavadskas, E. K. (2018). A Hybrid Fuzzy BWM-COPRAS Method for Analyzing Key Factors of Sustainable Architecture. Sustainability, 10(5). https://doi.org/10.3390/su10051626
Badi, I., Pamučar, D., Stević, Ž., & Muhammad, L. J. (2023). Wind farm site selection using BWM-AHP-MARCOS method: A case study of Libya. Scientific African, 19, e01511. https://doi.org/10.1016/j.sciaf.2022.e01511 Bakanlıklara Bağlı, İlgili, İlişkili Kurum ve Kuruluşlar ile Diğer Kurum ve Kuruluşların Teşkilatı Hakkında Cumhurbaşkanlığı Kararnamesi, 4 (2018). https://webdosya.kosgeb.gov.tr/Content/Upload/Dosya/Mevzuat/cbaskanligi_4_kararname.pdf
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Boldureanu, G., Ionescu, A. M., Bercu, A.-M., Bedrule-Grigoruță, M. V., & Boldureanu, D. (2020). Entrepreneurship Education through Successful Entrepreneurial Models in Higher Education Institutions. Sustainability, 12(3). https://doi.org/10.3390/su12031267
Bonab, S. R., Ghoushchi, S. J., Deveci, M., & Haseli, G. (2023). Logistic autonomous vehicles assessment using decision support model under spherical fuzzy set integrated Choquet Integral approach. Expert Systems with Applications, 214, 119205. https://doi.org/10.1016/j.eswa.2022.119205
Bošković, S., Švadlenka, L., Jovčić, S., Dobrodolac, M., Simić, V., & Bacanin, N. (2023). An Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN)—A Case Study of the Electric Vehicle Selection Problem. IEEE Access, 11, 39496–39507. https://doi.org/10.1109/ACCESS.2023.3265818
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Ecer, F., Murat, T., Dinçer, H., & Yüksel, S. (2024). A fuzzy BWM and MARCOS integrated framework with Heronian function for evaluating cryptocurrency exchanges: A case study of Türkiye. Financial Innovation, 10(1), 31. https://doi.org/10.1186/s40854-023-00543-w
Ferrandiz, J., Fidel, P., & Conchado, A. (2018). Promoting entrepreneurial intention through a higher education program integrated in an entrepreneurship ecosystem. International Journal of Innovation Science, 10(1), 6–21. https://doi.org/10.1108/IJIS-09-2017-0089
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Ghorabaee, M. K., Amiri, M., Hashemi-Tabatabaei, M., & Ghahremanloo, M. (2021). Sustainable Public Transportation Evaluation using a Novel Hybrid Method Based on Fuzzy BWM and MABAC. The Open Transportation Journal, 15, 31–44. https://doi.org/10.2174/1874447802115010031
Ghoushchi, S. J., Yousefi, S., & Khazaeili, M. (2019). An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures. Applied Soft Computing, 81, 105505. https://doi.org/10.1016/j.asoc.2019.105505
Görçün, Ö. F., & Doğan, G. (2023). Mobile crane selection in project logistics operations using Best and Worst Method (BWM) and fuzzy Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS). Automation in Construction, 147, 104729. https://doi.org/10.1016/j.autcon.2022.104729
Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23–31. https://doi.org/10.1016/j.knosys.2017.01.010
Kara, K., Yalçın, G. C., Acar, A. Z., Simic, V., Konya, S., & Pamucar, D. (2024). The MEREC-AROMAN method for determining sustainable competitiveness levels: A case study for Turkey. Socio-Economic Planning Sciences, 91, 101762. https://doi.org/10.1016/j.seps.2023.101762
Khan, S., Haleem, A., & Khan, M. I. (2021). Assessment of risk in the management of Halal supply chain using fuzzy BWM method. Supply Chain Forum: An International Journal, 22(1), 57–73. https://doi.org/10.1080/16258312.2020.1788905
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Kumar, S., Maity, S. R., & Patnaik, L. (2023). A novel BWM integrated MABAC decision-making approach to optimize the wear parameter of CrN/TiAlSiN coating. Journal of Industrial and Management Optimization, 19(4), 2676–2703. https://doi.org/10.3934/jimo.2022061
Kurniawan, V. R. B., & Puspitasari, F. H. (2021). A Fuzzy BWM Method for Evaluating Supplier Selection Factors in a SME Paper Manufacturer. IOP Conference Series: Materials Science and Engineering, 1071, 012004. https://doi.org/10.1088/1757-899X/1071/1/012004
Mešić, A., Miškić, S., Stević, Ž., & Mastilo, Z. (2022). Hybrid MCDM Solutions for Evaluation of the Logistics Performance Index of the Western Balkan Countries. ECONOMICS, 10(1), 13–34. https://doi.org/10.2478/eoik-2022-0004
Mwatsika, C. (2016). Measuring the Number of Jobs Created through Entrepreneurship Training. International Journal of Academic Research in Business and Social Sciences, 6(7), 223–240. https://doi.org/10.6007/IJARBSS/v6-i7/2243
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UYGULAMALI GİRİŞİMCİLİK EĞİTİMLERİNİN İL, DÜZEY-I VE DÜZEY-II BÖLGELERİ BAZINDA BULANIK BWM VE AROMAN YÖNTEMLERİYLE DEĞERLENDİRİLMESİ

Year 2024, Issue: 61, 371 - 391, 22.03.2024

Sinan Dündar

https://doi.org/10.30794/pausbed.1413500

Abstract

Bir ülkenin girişimcilik ekosistemin seviyesi, o ülkenin ekonomik kalkınmasına hizmet eden önemli bir göstergedir. Günümüz dünyasında ise hükümetler, girişimcilik altyapısını güçlendirmek amacıyla çeşitli enstrümanlara başvurmaktadır. Türkiye’de ise bu konudaki faaliyetlerin önemli bir kısmı KOSGEB tarafından yürütülmektedir. 2010 yılından itibaren uygulanmaya başlanan Uygulamalı Girişimcilik Eğitimleri, bu amaca hizmet eden uygulamalardan birisidir. Bu araştırmada, Türkiye’deki her bir ilin, Düzey-I bölgelerinin ve Düzey-II bölgelerinin girişimcilik desteklerinden yararlanma açısından performansları incelenmiştir. Değerlendirme esnasında kullanılan kriterler Bulanık BWM yöntemiyle ağırlıklandırılmış olup en önemli ölçüt, “eğitim sonrası desteklenen işletme sayısı” olarak belirlenmiştir. AROMAN yöntemiyle gerçekleştirilen performans sıralamasında ise TR6, TR3 ve TR4 en başarılı Düzey-I bölgeleri olarak ilk üç sırada yer almıştır. Ayrıca, benzer bir değerlendirme il ve Düzey-II bölgeleri açısından da gerçekleştirilmiştir.

Keywords

Girişimcilik, KOSGEB, ÇKKV, Bulanık BWM, AROMAN

Ethical Statement

Araştırmada, Etik Kurul kararı gerektiren herhangi bir içerik bulunmamaktadır.

References

Aksoy, B., Koçancı, M., & Namal, M. K. (2019). Girişimcilik Motivasyonu: Uygulamalı Girişimcilik Eğitimi Katılımcıları Örneği. Yönetim ve Ekonomi Dergisi, 26(1), 109–129. https://doi.org/10.18657/yonveek.526604
Altunay, K. (2020). Yeni Girişimci Desteği Nihai Değerlendirme Raporu (2020/02; p. 123). KOSGEB. https://webdosya.kosgeb.gov.tr/Content/Upload/Dosya/Kurumsal/Raporlar/Giri%C5%9Fimcilik_Destek_Program%C4%B1_Yeni_Giri%C5%9Fimci_Deste%C4%9Fi_Nihai_De%C4%9Ferlendirme_....pdf
Amiri, M., Hashemi-Tabatabaei, M., Ghahremanloo, M., Keshavarz-Ghorabaee, M., Zavadskas, E. K., & Banaitis, A. (2021). A new fuzzy BWM approach for evaluating and selecting a sustainable supplier in supply chain management. International Journal of Sustainable Development & World Ecology, 28(2), 125–142. https://doi.org/10.1080/13504509.2020.1793424
Amoozad Mahdiraji, H., Arzaghi, S., Stauskis, G., & Zavadskas, E. K. (2018). A Hybrid Fuzzy BWM-COPRAS Method for Analyzing Key Factors of Sustainable Architecture. Sustainability, 10(5). https://doi.org/10.3390/su10051626
Badi, I., Pamučar, D., Stević, Ž., & Muhammad, L. J. (2023). Wind farm site selection using BWM-AHP-MARCOS method: A case study of Libya. Scientific African, 19, e01511. https://doi.org/10.1016/j.sciaf.2022.e01511 Bakanlıklara Bağlı, İlgili, İlişkili Kurum ve Kuruluşlar ile Diğer Kurum ve Kuruluşların Teşkilatı Hakkında Cumhurbaşkanlığı Kararnamesi, 4 (2018). https://webdosya.kosgeb.gov.tr/Content/Upload/Dosya/Mevzuat/cbaskanligi_4_kararname.pdf
Biswas, T., Chatterjee, P., & Choudhuri, B. (2020). Selection of commercially available alternative passenger vehicle in automotive environment. Operational Research in Engineering Sciences: Theory and Applications, 3, 2620–1747. https://doi.org/10.31181/oresta200113b
Boldureanu, G., Ionescu, A. M., Bercu, A.-M., Bedrule-Grigoruță, M. V., & Boldureanu, D. (2020). Entrepreneurship Education through Successful Entrepreneurial Models in Higher Education Institutions. Sustainability, 12(3). https://doi.org/10.3390/su12031267
Bonab, S. R., Ghoushchi, S. J., Deveci, M., & Haseli, G. (2023). Logistic autonomous vehicles assessment using decision support model under spherical fuzzy set integrated Choquet Integral approach. Expert Systems with Applications, 214, 119205. https://doi.org/10.1016/j.eswa.2022.119205
Bošković, S., Švadlenka, L., Jovčić, S., Dobrodolac, M., Simić, V., & Bacanin, N. (2023). An Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN)—A Case Study of the Electric Vehicle Selection Problem. IEEE Access, 11, 39496–39507. https://doi.org/10.1109/ACCESS.2023.3265818
Bouraima, M. B., Tengecha, N. A., Stević, Ž., Simić, V., & Qiu, Y. (2023). An integrated fuzzy MCDM model for prioritizing strategies for successful implementation and operation of the bus rapid transit system. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05183-y
Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model. Journal of Cleaner Production, 266, 121981. https://doi.org/10.1016/j.jclepro.2020.121981
Ecer, F., & Pamucar, D. (2022). A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690
Ecer, F., Murat, T., Dinçer, H., & Yüksel, S. (2024). A fuzzy BWM and MARCOS integrated framework with Heronian function for evaluating cryptocurrency exchanges: A case study of Türkiye. Financial Innovation, 10(1), 31. https://doi.org/10.1186/s40854-023-00543-w
Ferrandiz, J., Fidel, P., & Conchado, A. (2018). Promoting entrepreneurial intention through a higher education program integrated in an entrepreneurship ecosystem. International Journal of Innovation Science, 10(1), 6–21. https://doi.org/10.1108/IJIS-09-2017-0089
Frederick, H., O’Connor, A., & Kuratko, D. D. (2019). Entrepreneurship: Theory/Process/Practice (5th ed.). Cengage Learning Inc.
Gan, J., Zhong, S., Liu, S., & Yang, D. (2019). Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment. Discrete Dynamics in Nature and Society, 2019, 2456260. https://doi.org/10.1155/2019/2456260
Ghorabaee, M. K., Amiri, M., Hashemi-Tabatabaei, M., & Ghahremanloo, M. (2021). Sustainable Public Transportation Evaluation using a Novel Hybrid Method Based on Fuzzy BWM and MABAC. The Open Transportation Journal, 15, 31–44. https://doi.org/10.2174/1874447802115010031
Ghoushchi, S. J., Yousefi, S., & Khazaeili, M. (2019). An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures. Applied Soft Computing, 81, 105505. https://doi.org/10.1016/j.asoc.2019.105505
Görçün, Ö. F., & Doğan, G. (2023). Mobile crane selection in project logistics operations using Best and Worst Method (BWM) and fuzzy Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS). Automation in Construction, 147, 104729. https://doi.org/10.1016/j.autcon.2022.104729
Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23–31. https://doi.org/10.1016/j.knosys.2017.01.010
Kara, K., Yalçın, G. C., Acar, A. Z., Simic, V., Konya, S., & Pamucar, D. (2024). The MEREC-AROMAN method for determining sustainable competitiveness levels: A case study for Turkey. Socio-Economic Planning Sciences, 91, 101762. https://doi.org/10.1016/j.seps.2023.101762
Khan, S., Haleem, A., & Khan, M. I. (2021). Assessment of risk in the management of Halal supply chain using fuzzy BWM method. Supply Chain Forum: An International Journal, 22(1), 57–73. https://doi.org/10.1080/16258312.2020.1788905
Küçük ve Orta Ölçekli İşletmeleri Geliştirme ve Destekleme İdaresi Başkanlığı Teşvik ve Muafiyetleri Kanunu, 3624 (1990). https://webdosya.kosgeb.gov.tr/Content/Upload/Dosya/Mevzuat/2019_KOSGEB_Kanunu.pdf
Kumar, S., Maity, S. R., & Patnaik, L. (2023). A novel BWM integrated MABAC decision-making approach to optimize the wear parameter of CrN/TiAlSiN coating. Journal of Industrial and Management Optimization, 19(4), 2676–2703. https://doi.org/10.3934/jimo.2022061
Kurniawan, V. R. B., & Puspitasari, F. H. (2021). A Fuzzy BWM Method for Evaluating Supplier Selection Factors in a SME Paper Manufacturer. IOP Conference Series: Materials Science and Engineering, 1071, 012004. https://doi.org/10.1088/1757-899X/1071/1/012004
Mešić, A., Miškić, S., Stević, Ž., & Mastilo, Z. (2022). Hybrid MCDM Solutions for Evaluation of the Logistics Performance Index of the Western Balkan Countries. ECONOMICS, 10(1), 13–34. https://doi.org/10.2478/eoik-2022-0004
Mwatsika, C. (2016). Measuring the Number of Jobs Created through Entrepreneurship Training. International Journal of Academic Research in Business and Social Sciences, 6(7), 223–240. https://doi.org/10.6007/IJARBSS/v6-i7/2243
Puška, A., Božanić, D., Nedeljković, M., & Janošević, M. (2022). Green Supplier Selection in an Uncertain Environment in Agriculture Using a Hybrid MCDM Model: Z-Numbers–Fuzzy LMAW–Fuzzy CRADIS Model. Axioms, 11(9). https://doi.org/10.3390/axioms11090427
Qahtan, S., Alsattar, H. A., Zaidan, A. A., Deveci, M., Pamucar, D., Delen, D., & Pedrycz, W. (2023). Evaluation of agriculture-food 4.0 supply chain approaches using Fermatean probabilistic hesitant-fuzzy sets based decision making model. Applied Soft Computing, 138, 110170. https://doi.org/10.1016/j.asoc.2023.110170
Qian, S., Brannon, D. L., & Tabak, F. (2022). Exploring Mechanisms in the Entrepreneurial Passion–Entrepreneurial Behavior Relationship: Mediating Role of Growth-Oriented Intentions. Journal of Career Development, 49(4), 922–933. https://doi.org/10.1177/08948453211005848
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Ringo Ho, M.-H., Uy, M. Y., Kang, B., & Chan, K.-Y. (2018). Impact of Entrepreneurship Training on Entrepreneurial Efficacy and Alertness among Adolescent Youth. Frontiers in Education, 3(13), 1–10. https://doi.org/10.3389/feduc.2018.00013
Roy, P., & Shaw, K. (2022). An integrated fuzzy credit rating model using fuzzy-BWM and new fuzzy-TOPSIS-Sort-C. Complex & Intelligent Systems, 9(4). https://doi.org/10.1007/s40747-022-00823-5
Schumpeter, J. A. (1951). Change and the Entrepreneur. In Essays of J.A. Schumpeter (1st ed., p. 325). Addison-Wesley Press, Inc.
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There are 41 citations in total.

Details

Primary Language	English
Subjects	Regional Economy, Manufacturing and Industrial Engineering (Other)
Journal Section	Research Article
Authors	Sinan Dündar 0000-0001-8061-3322
Early Pub Date	March 22, 2024
Publication Date	March 22, 2024
Submission Date	January 2, 2024
Acceptance Date	February 9, 2024
Published in Issue	Year 2024 Issue: 61

Cite

APA	Dündar, S. (2024). EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(61), 371-391. https://doi.org/10.30794/pausbed.1413500
AMA	Dündar S. EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS. PAUSBED. March 2024;(61):371-391. doi:10.30794/pausbed.1413500
Chicago	Dündar, Sinan. “EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, no. 61 (March 2024): 371-91. https://doi.org/10.30794/pausbed.1413500.
EndNote	Dündar S (March 1, 2024) EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 61 371–391.
IEEE	S. Dündar, “EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS”, PAUSBED, no. 61, pp. 371–391, March 2024, doi: 10.30794/pausbed.1413500.
ISNAD	Dündar, Sinan. “EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 61 (March 2024), 371-391. https://doi.org/10.30794/pausbed.1413500.
JAMA	Dündar S. EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS. PAUSBED. 2024;:371–391.
MLA	Dündar, Sinan. “EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, no. 61, 2024, pp. 371-9, doi:10.30794/pausbed.1413500.
Vancouver	Dündar S. EVALUATION OF HANDS-ON ENTREPRENEURSHIP TRAININGS ON THE BASIS OF PROVINCES, NUTS-I AND NUTS-II REGIONS BY FUZZY BWM AND AROMAN METHODS. PAUSBED. 2024(61):371-9.

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