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Türkiye Ulusal Spor Federasyonlarında Ters VZA İle Kaynak Tahsisi

Yıl 2021, Cilt: 7 Sayı: 1, 150 - 164, 31.07.2021
https://doi.org/10.22466/acusbd.935345

Öz

Sporcular, antrenörler, sponsorlar ve kamu otoritelerini içeren paydaşlarının beklentilerini karşılamak için ulusal spor federasyonlarının (NSF'ler) performans ölçüm modellerini üstlenmesi gerekmektedir. Bu çalışmada Ters Veri Zarflama Analizi(InDEA) modelleri kullanılarak 18. Akdeniz Oyunları'na katılan Türkiye'den 15 spor federasyonunun etkinlik analizi yapılmıştır. Sonuçlar, spor federasyonlarının ortalama verimliliğinin oldukça düşük olduğunu ortaya koymuştur. Önerilen InDEA modeli, NSF'lerin ve farklı organizasyonların yöneticilerine üretim analizi, performans ölçümü, kaynak planlama ve stratejik yönetim konusunda yardımcı olabilir.

Kaynakça

  • Abdollah, H., Ali, A. & Majid, S. (2008). A DEA model for resource allocation. Economic Modelling, 25(5), 983–993. https://doi.org/10.1016/j.econmod.2008.01.003
  • Banker, R. D., Charnes, A. & Cooper, W.W. (1984). Some models for the estimation of technical and scale inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078
  • Beasley, J.E. (2003). Allocating fixed costs and resources via data envelopment analysis. EJOR, 147(1), 198-216. https://doi.org/10.1016/S0377-2217(02)00244-8
  • Bernard, A. & Busse, M.R (2004). Who wins the Olympic Games: economic resources and medal totals? The Review of Economics and Statistics, 86(1), 413-417. https://doi.org/10.1162/003465304774201824
  • Carlos, P., Alén, E. & Perez-González, A. P (2017). Measuring the efficiency of the Spanish Olympic Sports Federations. European Sport Management Quarterly, 17(2), 210-225. https://doi.org/10.1080/16184742.2016.1245769
  • Charnes, A., Cooper, W. W. & Rhodes, E. L. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Condon, E. M., Golden, B. L. & Wasil, E. A. (1999). Predicting the success of nations at the summer Olympic using neural networks. Computers and Operations Research, 26(13), 1243-1265. https://doi.org/10.1016/S0305-0548(99)00003-9
  • Emrouznejad, A. & Yang G.L. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 61, 4-8. https://doi.org/10.1016/j.seps.2017.01.008
  • Gattoufi, S., Ami, G.R. & Emrouznejad, A. (2014). A new inverse DEA method for merging banks. IMA Journal of Management Mathematics, 25(1), 73–87. https://doi.org/10.1093/imaman/dps027
  • Ghiyasi, M. (2015). On inverse DEA model: the case of variable returns to scale. ComputersandIndustrial Engineering, 87, 407–409. https://doi.org/10.1016/j.cie.2015.05.018
  • Hadi-Vencheh, A., & Foroughi, A.A. (2006). A generalized DEA model for inputs/outputs estimation. Mathematical and Computer Modelling, 43(5-6), 447–457. https://doi.org/10.1016/j.mcm.2005.08.005
  • Hadi-Vencheh, A. Hatami-Marbini, A., Ghelej, B.Z. & Gholami. K. (2014). An Inverse Optimization Model for Imprecise Data Envelopment Analysis. Optimization, 64(11), 1-14. https://doi.org/10.1080/02331934.2014.974599
  • Hoffmann, R., Ging, L.C. & Ramasamy, B. (2004). Olympic Success and ASEAN Countries: Economic Analysis and Policy Implications. Journal of Sports Economics. 5(3), 262-276. https://doi.org/10.1177/1527002503261826
  • Jablonsky, J. (2018). Ranking of countries in sporting events using two-stage data envelopment analysis models: a case of Summer Olympic Games 2016. CEJOR, 26(4), 951–966. https://doi.org/10.1007/s10100-018-0537-8
  • Jahanshahloo, G. R., Hosseinzadeh, L.F., Rostamy-Malkhalifeh, M. & Ghobadi, S. (2014). Using enhanced Russell model to solve inverse data envelopment analysis problems. The Scientific World Journal, 4, 1-10. https://doi.org/10.1155/2014/571896
  • Lei, C., Li, Y., Xie, X. & Liang, L. (2015). Measuring Olympics achievements based on a parallel DEA approach. Annals of Operations Research, 226(1), 379–396. https://doi.org/10.1007/s10479-014-1708-1
  • Lertworasirikul, S., Charnsethikul, P. and Fang, S.C. (2011). Inverse Data Envelopment Analysis model to preserve relative efficiency values: the case of variable returns to scale. Computers and Industrial Engineering, 6(4), 1017-1023. https://doi.org/10.1016/j.cie.2011.06.014
  • Lim, D.J. (2016). Inverse DEA with frontier changes for new product target setting. European Journal of Operational Research, 254(2), 510-516. https://doi.org/10.1016/j.ejor.2016.03.059
  • Lin, Y., Yan, L. & Wang, Y.M (2019). Performance evaluation and investment analysis for container port sustainable development in china: an inverse DEA approach. Sustainability, 11(17), 4617. https://doi.org/10.3390/su11174617
  • Lins, M.P.E., Gomes, E.G., Mello, J.C.B.S. & Mello, A.J.R.S. (2003). Olympic ranking based on a zero sum gains DEA model. European Journal of Operational Research, 148(2), 312–322. https://doi.org/10.1016/S0377-2217(02)00687-2
  • Lozano, S., Villa, G., Guerrero, F., & Cortés, P. (2002). Measuring the performance of nations at the Summer Olympics using data envelopment analysis. Journal of the Operational Research Society, 53(5), 501-511. https://doi.org/10.1057/palgrave.jors.2601327
  • Madella, A., Bayle, E. & Tome, J. (2005). The organisational performance of national swimming federations in Mediterranean countries: A comparative approach. European Journal of Sport Science, 5(4), 207-220. https://doi.org/10.1080/17461390500344644
  • MBS, (2021). Gençlik ve Spor Hizmetleri Kanunu. Erişim: 19.04.2021, https://www.mevzuat.gov.tr/mevzuat?Mevz uatNo=3289&MevzuatTur=1&MevzuatTertip=5
  • Meza, L.A., Valério, R., P., João Carlos, C. B. & Mello, S. (2015). Assessing the efficiency of sports in using financial resources with DEA models. Procedia Computer Science, 55, 1151-1159. https://doi.org/10.1016/j.procs.2015.07.086
  • Moosa, I. A. & Smith, L. (2004). Economic development indicators as determinants of medal winning at the Sydney Olympics: an extreme bound analysis. Australian Economic Papers, 43(3), 288–301. https://doi.org/10.1111/j.1467-8454.2004.00231.x
  • Siegfried, N, Schlesinger, T. Bayle, E. & Giauque, D. (2015). Professionalization of sport federations-a multi-level framework for analysing forms, causes and consequences. European Sport Management Quarterly, 15(4), 407-433. https://doi.org/10.1080/16184742.2015.1062990
  • O'Boyle, I. & Hassan, D. (2014). Performance management and measurement in national-level non-profit sport organizations. European Sport Management Quarterly, 14(3), 299–314. https://doi.org/10.1080/16184742.2014.898677
  • Ramanathan, R. (2003). An introduction to Data Envelopment Analysis: a tool for performance measurement. Sage Publications.
  • Shirouyehzad, H. & Yazdani, F. (2014). Performance evaluation and ranking of participation Asian countries in 2012 London Olympic Games through Data Envelopment Analysis. Journal of Data Envelopment Analysis and Decision Science 2014, 1-11. https://doi.org/10.5899/2014/dea-00065
  • Steuer, R.E. (1986). Multiple Criteria Optimization Theory, Computation and Application. 2nd ed. Malabar, Krieger.
  • Taghizadeh, K., Bagherpour, M. & Mahdavi, I. (2011). Application of fuzzy multi-objective linear programming model in a multi-period multi-product production-planning problem. International Journal of Computational Intelligence Systems, 4(2), 228-243. https://doi.org/10.1080/18756891.2011.9727779
  • Valenti, M., Scelles, N. & Morrow, S. (2019). Elite sport policies and international sporting success: a panel data analysis of European women’s national football team performance. European Sport Management Quarterly, 20(3), 300-320. https://doi.org/10.1080/16184742.2019.1606264
  • Valério, R.P. and Meza, L.A. (2013). A data envelopment analysis evaluation and financial resources reallocation for Brazilian Olympic sports. Wseas Transactions on Systems, 12(12), 627-636.
  • Wegener, M. & Âmin, G.R. (2019). Minimizing greenhouse gas emissions using inverse DEA with an application in oil and gas. Expert Systems with Applications, 122, 369-375. https://doi.org/10.1016/j.eswa.2018.12.058
  • Wei, Q.L., Zhang, J. & Zhang, X. (2000). An inverse DEA model for inputs/outputs estimate. European Journal of Operational Research, 121(1), 151–163. https://doi.org/10.1016/S0377-2217(99)00007-7
  • Winand, M., Rihoux, B., Qualizza, D. & Zintz, T. (2010). Combinations of key determinants of performance in sport governing bodies. Sport, Business and Management: An International Journal, 1(3), 234-251. https://doi.org/10.1108/20426781111162657
  • Wolstencroft, E. (2002). Talent identification and development: An academic review. Sportscotland.
  • Wu, J., Zhou, Z. & Liang, L. (2010). Measuring the performance of nations at Beijing Summer Olympics using integer-valued DEA model. Journal of Sports Economics, 11(5), 549-566. https://doi.org/10.1177/1527002509352619
  • Wu, H., Chen, B., Xia, Q. & Zhou, H. (2013). Ranking and benchmarking of the Asian games achievements based on DEA: The case of Guangzhou 2010. Asia-Pacific Journal of Operational Research, 30(6), 1350028. https://doi.org/10.1142/S0217595913500280
  • Yan, H., We, Q. & Hao. G. (2002). DEA models for resource reallocation and production input/output estimation. European Journal of Operational Research, 136(1), 19–31. https://doi.org/10.1016/S0377-2217(01)00046-7
  • Yetim, A. A. (2019). Yönetim ve Spor (Genişletilmiş 2. Baskı). Gazi Kitapevi
  • Zhang, D., Li, X., Meng, W. & Liu, W. (2009). Measuring the performance of nations at the Olympic Games using DEA models with different preferences. Journal of the Operational Research Society, 60(7), 983-990. https://doi.org/10.1057/palgrave.jors.2602638
  • Zhang, M. & Cui. J.J. (2016). The extension and integration of the inverse DEA method. Journal of the Operational Research Society, 67(9), 1212-1220. https://doi.org/10.1057/jors.2016.2

Resource Allocation of the National Sport Federations of Turkey with Inverse DEA

Yıl 2021, Cilt: 7 Sayı: 1, 150 - 164, 31.07.2021
https://doi.org/10.22466/acusbd.935345

Öz

In order to meet the expectations of their stakeholders involving athletes, coaches, sponsors and public authorities, national sport federations (NSFs) need to undertake performance measurement models. In this study, using inverse Data Envelopment Analysis (InDEA) models, an efficiency analysis of 15 sports federations of Turkey which participated in the 18th Mediterranean Games was performed. The results revealed that the average efficiency of the sports federations was considerably low. The suggested InDEA model can help managers of NSFs and different organizations with production analysis, performance measurement, resource planning and strategic management.

Kaynakça

  • Abdollah, H., Ali, A. & Majid, S. (2008). A DEA model for resource allocation. Economic Modelling, 25(5), 983–993. https://doi.org/10.1016/j.econmod.2008.01.003
  • Banker, R. D., Charnes, A. & Cooper, W.W. (1984). Some models for the estimation of technical and scale inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078
  • Beasley, J.E. (2003). Allocating fixed costs and resources via data envelopment analysis. EJOR, 147(1), 198-216. https://doi.org/10.1016/S0377-2217(02)00244-8
  • Bernard, A. & Busse, M.R (2004). Who wins the Olympic Games: economic resources and medal totals? The Review of Economics and Statistics, 86(1), 413-417. https://doi.org/10.1162/003465304774201824
  • Carlos, P., Alén, E. & Perez-González, A. P (2017). Measuring the efficiency of the Spanish Olympic Sports Federations. European Sport Management Quarterly, 17(2), 210-225. https://doi.org/10.1080/16184742.2016.1245769
  • Charnes, A., Cooper, W. W. & Rhodes, E. L. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Condon, E. M., Golden, B. L. & Wasil, E. A. (1999). Predicting the success of nations at the summer Olympic using neural networks. Computers and Operations Research, 26(13), 1243-1265. https://doi.org/10.1016/S0305-0548(99)00003-9
  • Emrouznejad, A. & Yang G.L. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 61, 4-8. https://doi.org/10.1016/j.seps.2017.01.008
  • Gattoufi, S., Ami, G.R. & Emrouznejad, A. (2014). A new inverse DEA method for merging banks. IMA Journal of Management Mathematics, 25(1), 73–87. https://doi.org/10.1093/imaman/dps027
  • Ghiyasi, M. (2015). On inverse DEA model: the case of variable returns to scale. ComputersandIndustrial Engineering, 87, 407–409. https://doi.org/10.1016/j.cie.2015.05.018
  • Hadi-Vencheh, A., & Foroughi, A.A. (2006). A generalized DEA model for inputs/outputs estimation. Mathematical and Computer Modelling, 43(5-6), 447–457. https://doi.org/10.1016/j.mcm.2005.08.005
  • Hadi-Vencheh, A. Hatami-Marbini, A., Ghelej, B.Z. & Gholami. K. (2014). An Inverse Optimization Model for Imprecise Data Envelopment Analysis. Optimization, 64(11), 1-14. https://doi.org/10.1080/02331934.2014.974599
  • Hoffmann, R., Ging, L.C. & Ramasamy, B. (2004). Olympic Success and ASEAN Countries: Economic Analysis and Policy Implications. Journal of Sports Economics. 5(3), 262-276. https://doi.org/10.1177/1527002503261826
  • Jablonsky, J. (2018). Ranking of countries in sporting events using two-stage data envelopment analysis models: a case of Summer Olympic Games 2016. CEJOR, 26(4), 951–966. https://doi.org/10.1007/s10100-018-0537-8
  • Jahanshahloo, G. R., Hosseinzadeh, L.F., Rostamy-Malkhalifeh, M. & Ghobadi, S. (2014). Using enhanced Russell model to solve inverse data envelopment analysis problems. The Scientific World Journal, 4, 1-10. https://doi.org/10.1155/2014/571896
  • Lei, C., Li, Y., Xie, X. & Liang, L. (2015). Measuring Olympics achievements based on a parallel DEA approach. Annals of Operations Research, 226(1), 379–396. https://doi.org/10.1007/s10479-014-1708-1
  • Lertworasirikul, S., Charnsethikul, P. and Fang, S.C. (2011). Inverse Data Envelopment Analysis model to preserve relative efficiency values: the case of variable returns to scale. Computers and Industrial Engineering, 6(4), 1017-1023. https://doi.org/10.1016/j.cie.2011.06.014
  • Lim, D.J. (2016). Inverse DEA with frontier changes for new product target setting. European Journal of Operational Research, 254(2), 510-516. https://doi.org/10.1016/j.ejor.2016.03.059
  • Lin, Y., Yan, L. & Wang, Y.M (2019). Performance evaluation and investment analysis for container port sustainable development in china: an inverse DEA approach. Sustainability, 11(17), 4617. https://doi.org/10.3390/su11174617
  • Lins, M.P.E., Gomes, E.G., Mello, J.C.B.S. & Mello, A.J.R.S. (2003). Olympic ranking based on a zero sum gains DEA model. European Journal of Operational Research, 148(2), 312–322. https://doi.org/10.1016/S0377-2217(02)00687-2
  • Lozano, S., Villa, G., Guerrero, F., & Cortés, P. (2002). Measuring the performance of nations at the Summer Olympics using data envelopment analysis. Journal of the Operational Research Society, 53(5), 501-511. https://doi.org/10.1057/palgrave.jors.2601327
  • Madella, A., Bayle, E. & Tome, J. (2005). The organisational performance of national swimming federations in Mediterranean countries: A comparative approach. European Journal of Sport Science, 5(4), 207-220. https://doi.org/10.1080/17461390500344644
  • MBS, (2021). Gençlik ve Spor Hizmetleri Kanunu. Erişim: 19.04.2021, https://www.mevzuat.gov.tr/mevzuat?Mevz uatNo=3289&MevzuatTur=1&MevzuatTertip=5
  • Meza, L.A., Valério, R., P., João Carlos, C. B. & Mello, S. (2015). Assessing the efficiency of sports in using financial resources with DEA models. Procedia Computer Science, 55, 1151-1159. https://doi.org/10.1016/j.procs.2015.07.086
  • Moosa, I. A. & Smith, L. (2004). Economic development indicators as determinants of medal winning at the Sydney Olympics: an extreme bound analysis. Australian Economic Papers, 43(3), 288–301. https://doi.org/10.1111/j.1467-8454.2004.00231.x
  • Siegfried, N, Schlesinger, T. Bayle, E. & Giauque, D. (2015). Professionalization of sport federations-a multi-level framework for analysing forms, causes and consequences. European Sport Management Quarterly, 15(4), 407-433. https://doi.org/10.1080/16184742.2015.1062990
  • O'Boyle, I. & Hassan, D. (2014). Performance management and measurement in national-level non-profit sport organizations. European Sport Management Quarterly, 14(3), 299–314. https://doi.org/10.1080/16184742.2014.898677
  • Ramanathan, R. (2003). An introduction to Data Envelopment Analysis: a tool for performance measurement. Sage Publications.
  • Shirouyehzad, H. & Yazdani, F. (2014). Performance evaluation and ranking of participation Asian countries in 2012 London Olympic Games through Data Envelopment Analysis. Journal of Data Envelopment Analysis and Decision Science 2014, 1-11. https://doi.org/10.5899/2014/dea-00065
  • Steuer, R.E. (1986). Multiple Criteria Optimization Theory, Computation and Application. 2nd ed. Malabar, Krieger.
  • Taghizadeh, K., Bagherpour, M. & Mahdavi, I. (2011). Application of fuzzy multi-objective linear programming model in a multi-period multi-product production-planning problem. International Journal of Computational Intelligence Systems, 4(2), 228-243. https://doi.org/10.1080/18756891.2011.9727779
  • Valenti, M., Scelles, N. & Morrow, S. (2019). Elite sport policies and international sporting success: a panel data analysis of European women’s national football team performance. European Sport Management Quarterly, 20(3), 300-320. https://doi.org/10.1080/16184742.2019.1606264
  • Valério, R.P. and Meza, L.A. (2013). A data envelopment analysis evaluation and financial resources reallocation for Brazilian Olympic sports. Wseas Transactions on Systems, 12(12), 627-636.
  • Wegener, M. & Âmin, G.R. (2019). Minimizing greenhouse gas emissions using inverse DEA with an application in oil and gas. Expert Systems with Applications, 122, 369-375. https://doi.org/10.1016/j.eswa.2018.12.058
  • Wei, Q.L., Zhang, J. & Zhang, X. (2000). An inverse DEA model for inputs/outputs estimate. European Journal of Operational Research, 121(1), 151–163. https://doi.org/10.1016/S0377-2217(99)00007-7
  • Winand, M., Rihoux, B., Qualizza, D. & Zintz, T. (2010). Combinations of key determinants of performance in sport governing bodies. Sport, Business and Management: An International Journal, 1(3), 234-251. https://doi.org/10.1108/20426781111162657
  • Wolstencroft, E. (2002). Talent identification and development: An academic review. Sportscotland.
  • Wu, J., Zhou, Z. & Liang, L. (2010). Measuring the performance of nations at Beijing Summer Olympics using integer-valued DEA model. Journal of Sports Economics, 11(5), 549-566. https://doi.org/10.1177/1527002509352619
  • Wu, H., Chen, B., Xia, Q. & Zhou, H. (2013). Ranking and benchmarking of the Asian games achievements based on DEA: The case of Guangzhou 2010. Asia-Pacific Journal of Operational Research, 30(6), 1350028. https://doi.org/10.1142/S0217595913500280
  • Yan, H., We, Q. & Hao. G. (2002). DEA models for resource reallocation and production input/output estimation. European Journal of Operational Research, 136(1), 19–31. https://doi.org/10.1016/S0377-2217(01)00046-7
  • Yetim, A. A. (2019). Yönetim ve Spor (Genişletilmiş 2. Baskı). Gazi Kitapevi
  • Zhang, D., Li, X., Meng, W. & Liu, W. (2009). Measuring the performance of nations at the Olympic Games using DEA models with different preferences. Journal of the Operational Research Society, 60(7), 983-990. https://doi.org/10.1057/palgrave.jors.2602638
  • Zhang, M. & Cui. J.J. (2016). The extension and integration of the inverse DEA method. Journal of the Operational Research Society, 67(9), 1212-1220. https://doi.org/10.1057/jors.2016.2
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Tüm Bölümler
Yazarlar

Gökhan Çakır 0000-0002-6800-9816

Süleyman Çakır 0000-0003-0334-8777

Yayımlanma Tarihi 31 Temmuz 2021
Gönderilme Tarihi 9 Mayıs 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 7 Sayı: 1

Kaynak Göster

APA Çakır, G., & Çakır, S. (2021). Türkiye Ulusal Spor Federasyonlarında Ters VZA İle Kaynak Tahsisi. Artvin Çoruh Üniversitesi Uluslararası Sosyal Bilimler Dergisi, 7(1), 150-164. https://doi.org/10.22466/acusbd.935345

Artvin Çoruh Üniversitesi Uluslararası Sosyal Bilimler Dergisi

ACUSBDCreative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY-NC) ile lisanslanmıştır.