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Çok Kriterli Karar Verme Yöntemleri Kullanarak Spor Kulüplerinde Lojistik Kararların Verilmesi

Yıl 2019, Cilt: 7 Sayı: 1, 129 - 142, 30.06.2019
https://doi.org/10.17093/alphanumeric.425766

Öz

Son yıllarda, spor daha profesyonel ve endüstriyel bir sektör haline gelmiş ve spor kulüplerinde analitik karar verme yöntemlerinin kullanımı çok daha önemli hale gelmiştir. Spor kulüplerinde, takımın maçlara taşınmasına karar verilmesi dikkatle çözülmesi gereken karmaşık bir problemdir. Bu çalışmada, spor kulüplerinin maçlara ulaştırılması probleminin çözümü için bir çok kriterli karar verme yöntemi önerilmiştir. Bu problem, spor kulüpleri için literatürde daha önce ele alınmamıştır. Bu çalışmada, problemin çözümü için iki aşamalı bir yöntem önerilmiştir. Analitik Hiyerarşi Süreci kriterlerin ağırlıklarının belirlenmesinde kullanılmış ve ELECTRE de taşıma alternatiflerinin en iyiden en kötüye sıralanmasında kullanılmıştır. Önerilen yöntemi test etmek üzere, gerçek bir vaka çalışması sunulmuştur. Bu gerçek vaka çalışmasında, bir Türk spor kulübünün voleybol branşındaki üst yaş takımı için en iyi taşıma alternatifi büyük, orta boy veya küçük otobüslerin dış kaynak kullanımı veya satın alımı gibi bir çok alternatif arasından seçilmiştir. Kriterler maliyet, konfor düzeyi, zaman ve prestij olarak belirlenmiştir. Bu vaka çalışması, en iyi kararın otobüsleri maç başına kiralamak yerine büyük otobüs satın almak olması nedeniyle kulüpteki karar vericilerin lojistik kararlarını değiştirmelerinin gerektiğini ortaya çıkarmıştır.

Kaynakça

  • Abdollahzadeh, G., Damalas, C. A., Sharifzadeh, M. S., & Ahmadi-Gorgi, H. (2016). “Selecting strategies for rice stem borer management using the Analytic Hierarchy Process (AHP)”. Crop Protection, 84, 27-36.
  • Atalay, Ö., Karakaş, A. & Akça, M. (2017). “Türkiye'de Lojistik Merkezi Yeri Seçiminde Kriterlerin AHP ile Ağırlıklandırılması: Kars İli Üzerine Bir Analiz”. Ataturk University Journal of Economics & Administrative Sciences, 607-626.
  • Balcı, V. (2003). “Avrupa Birliği ve Spor”. Gazi Beden Eğitimi ve Spor Bilimleri Dergisi 8(2), 53-66.
  • Benayoun, R., Roy, B., & Sussman, B. (1966). “ELECTRE: Une méthode pour guider le choix en présence de points de vue multiples”. Note de travail, 49.
  • Bouzon, M., Govindan, K., Rodriguez, C. M. T., & Campos, L. M. (2016). “Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP”. Resources, Conservation and Recycling, 108, 182-197.
  • Budak, G., Kara, İ., İç, Y. T., & Kasımbeyli, R. (2017). “Optimization of Harmony in Team Formation Problem for Sports Clubs: A real life volleyball team application”. In Proceedings of MathSport International 2017 Conference (p. 81)
  • Büyüközkan, G., & Çifçi, G. (2012). “A Novel Hybrid MCDM Approach Based on Fuzzy DEMATEL, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Suppliers”. Expert Systems with Applications, 39(3), 3000-3011.
  • Çati, K., Es, A., & Özevin, O. (2017). “Sportive and Financial Performance Analysis Of Football Team With Entropi And Topsis Methods: An Application On Major Europe's 5 Leagues And Turkey League”. International Journal of Management Economics & Business, 13(1), 199.
  • Dadelo, S., Turskis, Z., Zavadskas, E. K., & Dadeliene, R. (2014). “Multi-criteria Assessment and Ranking System of Sport Team Formation Based on Objective-Measured Values Of Criteria Set”. Expert Systems with Applications, 41(14), 6106-6113.
  • Devecioğlu, S. (2005). “Türkiye’de Spor Sektörü Stratejilerinin Geliştirilmesi”. Verimlilik Dergisi, 2, 117-134.
  • Ecer, F. (2017). “Third-party Logistics (3PLs) Provider Selection via Fuzzy AHP and EDAS Integrated Model”. Technological and Economic Development of Economy, 1-20.
  • Erdoğan, M., & Kaya, İ. (2016). “A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey”. Applied Soft Computing, 39, 84-93.
  • Ergul, N. (2010). “Analyzing of the effects of league performance of Turkish sport clubs over the financial performances of the corresponding sport companies”. China-USA Business Review, 9(12), 69.
  • Ergul, N. (2017)”The Investigation of the Relationship Between Financial Success of Sport Companies and Football Victories of Sports Clubs”. Hakenler/Referees 35(3), 44.
  • Falsini, D., Fondi, F., & Schiraldi, M. M. (2012). “A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration”. International Journal of Production Research, 50(17), 4822-4829.
  • Figueira, J. R., Greco, S., & Roy, B. (2009). “ELECTRE methods with interaction between criteria: An extension of the concordance index”. European Journal of Operational Research, 199(2), 478-495.
  • Gürcan, Ö. F., Beyca, Ö. F., Arslan, Ç. Y., & Eldemir, F. (2016). Third party logistics (3PL) provider selection with AHP application. Procedia-Social and Behavioral Sciences, 235, 226-234.
  • Karaatlı, M., Ömürbek, N., & Köse, G. (2014). “Analitik Hiyerarşi Süreci Temelli Topsis Ve Vikor Yöntemleri İle Futbolcu Performanslarinin Değerlendirilmesi”. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 29(1).
  • Karaman, A. S., & Akman, E. (2017). “Taking-off corporate social responsibility programs: An AHP application in airline industry”. Journal of Air Transport Management.
  • Kayikci, Y. (2010). “A conceptual model for intermodal freight logistics centre location decisions”. Procedia-Social and Behavioral Sciences, 2(3), 6297-6311.
  • Mavi, K. R., Mavi, K. N., & Kiani, L. (2012). “Ranking football teams with AHP and TOPSIS methods”. International Journal of Decision Sciences, Risk and Management, 4(1-2), 108-126.
  • Kökdemir, D. (2003). “Belirsizlik durumlarinda karar verme ve problem çözme [Making decisions and problem solving in uncertainty]”. Unpublished PhD thesis. Ankara: Ankara University, Institute of Social Sciences, Department of Social Psychology.
  • Lee, S., & Ross, S. D. (2012). “Sport sponsorship decision making in a global market: An approach of Analytic Hierarchy Process (AHP)”. Sport, Business and Management: An International Journal, 2(2), 156-168.
  • Mavi, N. K., & Mavi, R. K. (2014). Talent pool membership in sport organisations with fuzzy analytic hierarchy process. International Journal of Logistics Systems and Management, 17(1), 1-21.
  • Milani, A. S., Shanian, A., & El-Lahham, C. (2006). “Using different ELECTRE methods in strategic planning in the presence of human behavioral resistance”. Advances in Decision Sciences, 2006.
  • Nguyen, T., & Nahavandi, S. (2016). “Modified AHP for gene selection and cancer classification using type-2 fuzzy logic”. IEEE Transactions on Fuzzy Systems, 24(2), 273-287.
  • Ozceylan, E. (2016). “A mathematical model using AHP priorities for soccer player selection: a case study”. South African Journal of Industrial Engineering, 27(2), 190-205.
  • Önüt, S., Kara, S. S., & Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert systems with applications, 36(2), 3887-3895.
  • Pinnuck, M., & Potter, B. (2006). “Impact of on‐field football success on the off‐field financial performance of AFL football clubs”. Accounting & Finance, 46(3), 499-517.
  • Russell, R & Taylor, B.W. (2003). Operations Management 4th Edition. Upper Saddle River, New Jersey: Prentice Hall.
  • Saaty, R. W. (1987). “The analytic hierarchy process—what it is and how it is used”. Mathematical modelling, 9(3-5), 161-176.
  • Saaty, T. L. (1972). “An eigenvalue allocation model for prioritization and planning”. Energy Management and Policy Center, University of Pennsylvania, 28-31.
  • Saaty, T. L. (2008). “Decision making with the analytic hierarchy process”. International journal of services sciences, 1(1), 83-98.
  • Sakinc, I., Acikalin, S., & Soyguden, A. (2017). “Evaluation of the Relationship between Financial Performance and Sport Success in European Football”. Journal of Physical Education and Sport, 17, 16.
  • Singh, R. P., & Nachtnebel, H. P. (2016). “Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal”. Renewable and Sustainable Energy Reviews, 55, 43-58.
  • Tsoukias, A., Perny, P., & Vincke, P. (2002). “From concordance/discordance to the modelling of positive and negative reasons in decision aiding”. In Aiding decisions with multiple criteria (pp. 147-174). Springer, Boston, MA.
  • Tzeng, Gwo-Hshiung & Huan, Jih-Jeng. (2011) “Multiple Attribute Decision Making: Methods”. CRC Press.
  • Vieira, J. G. V., Toso, M. R., da Silva, J. E. A. R., & Ribeiro, P. C. C. (2017). “An AHP-based framework for logistics operations in distribution centres”. International Journal of Production Economics, 187, 246-259.
  • Vujanović, D., Momčilović, V., Bojović, N., & Papić, V. (2012). “Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP”. Expert Systems with Applications, 39(12), 10552-10563.
  • Wadhwa, S., Madaan, J., & Chan, F. T. S. (2009). “Flexible decision modeling of reverse logistics system: A value adding MCDM approach for alternative selection”. Robotics and Computer-Integrated Manufacturing, 25(2), 460-469.
  • Żak, J., & Węgliński, S. (2014). “The selection of the logistics center location based on MCDM/A methodology”. Transportation Research Procedia, 3, 555-564.

Using Multi-Criteria Decision Making Methods to Make Logistics Decisions in Sports Clubs

Yıl 2019, Cilt: 7 Sayı: 1, 129 - 142, 30.06.2019
https://doi.org/10.17093/alphanumeric.425766

Öz

Sports have evolved into a more professional and industrial sector in the last decades and the usage of analytical decision making methods in sports clubs has gained importance than ever. Decision makers in sports clubs have to make many decisions about their logistics activities. In sports clubs, decision making of transportation of a team to the games is a complex problem that needs to be solved carefully. In this study, a Multi-Criteria Decision Making method has been proposed to solve the transportation problem of sports clubs. This problem has not been addressed for sports clubs in the literature. In this study, a two-step method is proposed to solve the problem. Analytic Hierarchy Process (AHP) is used to determine the criteria weights and ELECTRE is used to order transportation alternatives from the best to the worst. To test the proposed method, a real-life case study is presented. In this real problem, the best transportation option among various alternatives such as outsourcing or buying large, medium or small sized buses for the senior team of a volleyball branch of a Turkish sports club is chosen. The criteria are determined as cost, comfort level, time and prestige. The case study revealed that the decision makers in the club should revise their logistics decisions as the best decision is to buy a large sized bus instead of outsourcing buses per game basis.

Kaynakça

  • Abdollahzadeh, G., Damalas, C. A., Sharifzadeh, M. S., & Ahmadi-Gorgi, H. (2016). “Selecting strategies for rice stem borer management using the Analytic Hierarchy Process (AHP)”. Crop Protection, 84, 27-36.
  • Atalay, Ö., Karakaş, A. & Akça, M. (2017). “Türkiye'de Lojistik Merkezi Yeri Seçiminde Kriterlerin AHP ile Ağırlıklandırılması: Kars İli Üzerine Bir Analiz”. Ataturk University Journal of Economics & Administrative Sciences, 607-626.
  • Balcı, V. (2003). “Avrupa Birliği ve Spor”. Gazi Beden Eğitimi ve Spor Bilimleri Dergisi 8(2), 53-66.
  • Benayoun, R., Roy, B., & Sussman, B. (1966). “ELECTRE: Une méthode pour guider le choix en présence de points de vue multiples”. Note de travail, 49.
  • Bouzon, M., Govindan, K., Rodriguez, C. M. T., & Campos, L. M. (2016). “Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP”. Resources, Conservation and Recycling, 108, 182-197.
  • Budak, G., Kara, İ., İç, Y. T., & Kasımbeyli, R. (2017). “Optimization of Harmony in Team Formation Problem for Sports Clubs: A real life volleyball team application”. In Proceedings of MathSport International 2017 Conference (p. 81)
  • Büyüközkan, G., & Çifçi, G. (2012). “A Novel Hybrid MCDM Approach Based on Fuzzy DEMATEL, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Suppliers”. Expert Systems with Applications, 39(3), 3000-3011.
  • Çati, K., Es, A., & Özevin, O. (2017). “Sportive and Financial Performance Analysis Of Football Team With Entropi And Topsis Methods: An Application On Major Europe's 5 Leagues And Turkey League”. International Journal of Management Economics & Business, 13(1), 199.
  • Dadelo, S., Turskis, Z., Zavadskas, E. K., & Dadeliene, R. (2014). “Multi-criteria Assessment and Ranking System of Sport Team Formation Based on Objective-Measured Values Of Criteria Set”. Expert Systems with Applications, 41(14), 6106-6113.
  • Devecioğlu, S. (2005). “Türkiye’de Spor Sektörü Stratejilerinin Geliştirilmesi”. Verimlilik Dergisi, 2, 117-134.
  • Ecer, F. (2017). “Third-party Logistics (3PLs) Provider Selection via Fuzzy AHP and EDAS Integrated Model”. Technological and Economic Development of Economy, 1-20.
  • Erdoğan, M., & Kaya, İ. (2016). “A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey”. Applied Soft Computing, 39, 84-93.
  • Ergul, N. (2010). “Analyzing of the effects of league performance of Turkish sport clubs over the financial performances of the corresponding sport companies”. China-USA Business Review, 9(12), 69.
  • Ergul, N. (2017)”The Investigation of the Relationship Between Financial Success of Sport Companies and Football Victories of Sports Clubs”. Hakenler/Referees 35(3), 44.
  • Falsini, D., Fondi, F., & Schiraldi, M. M. (2012). “A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration”. International Journal of Production Research, 50(17), 4822-4829.
  • Figueira, J. R., Greco, S., & Roy, B. (2009). “ELECTRE methods with interaction between criteria: An extension of the concordance index”. European Journal of Operational Research, 199(2), 478-495.
  • Gürcan, Ö. F., Beyca, Ö. F., Arslan, Ç. Y., & Eldemir, F. (2016). Third party logistics (3PL) provider selection with AHP application. Procedia-Social and Behavioral Sciences, 235, 226-234.
  • Karaatlı, M., Ömürbek, N., & Köse, G. (2014). “Analitik Hiyerarşi Süreci Temelli Topsis Ve Vikor Yöntemleri İle Futbolcu Performanslarinin Değerlendirilmesi”. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 29(1).
  • Karaman, A. S., & Akman, E. (2017). “Taking-off corporate social responsibility programs: An AHP application in airline industry”. Journal of Air Transport Management.
  • Kayikci, Y. (2010). “A conceptual model for intermodal freight logistics centre location decisions”. Procedia-Social and Behavioral Sciences, 2(3), 6297-6311.
  • Mavi, K. R., Mavi, K. N., & Kiani, L. (2012). “Ranking football teams with AHP and TOPSIS methods”. International Journal of Decision Sciences, Risk and Management, 4(1-2), 108-126.
  • Kökdemir, D. (2003). “Belirsizlik durumlarinda karar verme ve problem çözme [Making decisions and problem solving in uncertainty]”. Unpublished PhD thesis. Ankara: Ankara University, Institute of Social Sciences, Department of Social Psychology.
  • Lee, S., & Ross, S. D. (2012). “Sport sponsorship decision making in a global market: An approach of Analytic Hierarchy Process (AHP)”. Sport, Business and Management: An International Journal, 2(2), 156-168.
  • Mavi, N. K., & Mavi, R. K. (2014). Talent pool membership in sport organisations with fuzzy analytic hierarchy process. International Journal of Logistics Systems and Management, 17(1), 1-21.
  • Milani, A. S., Shanian, A., & El-Lahham, C. (2006). “Using different ELECTRE methods in strategic planning in the presence of human behavioral resistance”. Advances in Decision Sciences, 2006.
  • Nguyen, T., & Nahavandi, S. (2016). “Modified AHP for gene selection and cancer classification using type-2 fuzzy logic”. IEEE Transactions on Fuzzy Systems, 24(2), 273-287.
  • Ozceylan, E. (2016). “A mathematical model using AHP priorities for soccer player selection: a case study”. South African Journal of Industrial Engineering, 27(2), 190-205.
  • Önüt, S., Kara, S. S., & Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert systems with applications, 36(2), 3887-3895.
  • Pinnuck, M., & Potter, B. (2006). “Impact of on‐field football success on the off‐field financial performance of AFL football clubs”. Accounting & Finance, 46(3), 499-517.
  • Russell, R & Taylor, B.W. (2003). Operations Management 4th Edition. Upper Saddle River, New Jersey: Prentice Hall.
  • Saaty, R. W. (1987). “The analytic hierarchy process—what it is and how it is used”. Mathematical modelling, 9(3-5), 161-176.
  • Saaty, T. L. (1972). “An eigenvalue allocation model for prioritization and planning”. Energy Management and Policy Center, University of Pennsylvania, 28-31.
  • Saaty, T. L. (2008). “Decision making with the analytic hierarchy process”. International journal of services sciences, 1(1), 83-98.
  • Sakinc, I., Acikalin, S., & Soyguden, A. (2017). “Evaluation of the Relationship between Financial Performance and Sport Success in European Football”. Journal of Physical Education and Sport, 17, 16.
  • Singh, R. P., & Nachtnebel, H. P. (2016). “Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal”. Renewable and Sustainable Energy Reviews, 55, 43-58.
  • Tsoukias, A., Perny, P., & Vincke, P. (2002). “From concordance/discordance to the modelling of positive and negative reasons in decision aiding”. In Aiding decisions with multiple criteria (pp. 147-174). Springer, Boston, MA.
  • Tzeng, Gwo-Hshiung & Huan, Jih-Jeng. (2011) “Multiple Attribute Decision Making: Methods”. CRC Press.
  • Vieira, J. G. V., Toso, M. R., da Silva, J. E. A. R., & Ribeiro, P. C. C. (2017). “An AHP-based framework for logistics operations in distribution centres”. International Journal of Production Economics, 187, 246-259.
  • Vujanović, D., Momčilović, V., Bojović, N., & Papić, V. (2012). “Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP”. Expert Systems with Applications, 39(12), 10552-10563.
  • Wadhwa, S., Madaan, J., & Chan, F. T. S. (2009). “Flexible decision modeling of reverse logistics system: A value adding MCDM approach for alternative selection”. Robotics and Computer-Integrated Manufacturing, 25(2), 460-469.
  • Żak, J., & Węgliński, S. (2014). “The selection of the logistics center location based on MCDM/A methodology”. Transportation Research Procedia, 3, 555-564.
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Uğur Orhan Karaköprü 0000-0002-1974-7134

Özgür Kabadurmuş 0000-0002-1974-7134

Yayımlanma Tarihi 30 Haziran 2019
Gönderilme Tarihi 21 Mayıs 2018
Yayımlandığı Sayı Yıl 2019 Cilt: 7 Sayı: 1

Kaynak Göster

APA Karaköprü, U. O., & Kabadurmuş, Ö. (2019). Using Multi-Criteria Decision Making Methods to Make Logistics Decisions in Sports Clubs. Alphanumeric Journal, 7(1), 129-142. https://doi.org/10.17093/alphanumeric.425766

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