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GIDA SEKTÖRÜNDE ÜÇÜNCÜ PARTİ LOJİSTİK FİRMA SEÇİMİNDE BULANIK ÇOK KRİTERLİ KARAR VERME TEKNİKLERİYLE ENTEGRE BİR MODEL YAKLAŞIMI

Yıl 2023, Cilt: 10 Sayı: 1, 57 - 80, 29.03.2023
https://doi.org/10.30798/makuiibf.979840

Öz

Bu çalışmanın amacı, üçüncü parti lojistik firma seçimi ve değerlendirme kriterlerini belirlemek ve gıda sektöründeki alternatifler arasından en uygun seçimin yapılmasına yardımcı olmaktır. Diğer bir amaç ise, üçüncü parti lojistik firma seçim sürecinde bulanık çok kriterli karar verme yöntemlerini entegre ederek karma bir model sunmaktır. Bu çalışmada bulanık DEMATEL, bulanık ANP ve bulanık TOPSIS yöntemlerinin kombinasyonu kullanılmıştır. Karar amacına bağlı olarak belirlenen kriterler arasındaki etkileşimler değerlendirilerek bir karar ağı oluşturulmuştur. Bu çalışma gıda sektöründe süt ve süt ürünleri üreten büyük ölçekli bir firmada yapılmıştır. Yapılan analizler ve elde edilen bulgular sonucunda teknoloji, teslimat performansı ve kalite en çok etkileyen kriterler olarak bulunmuştur. Bununla birlikte kriterler arasından en çok etkilenen kriterin de firma imajı olduğu tespit edilmiştir. S2 olarak isimlendirilen firma, alternatiflerin değerlendirilmesi sonucunda en iyi üçüncü parti lojistik firması olarak önerilmiştir. Bu çalışmada kullanılan bütünleşik bulanık yöntemler üçüncü parti lojistik firmalarının seçiminde ve değerlendirilmesinde ilk kez kullanılmıştır. Ayrıca bu çalışmada literatürde rastlanmamış üç adet yeni kriter tespit edilmiş ve ilgili literatüre ufak da olsa katkıda bulunulmaya çalışılmıştır. Bu kriterler; hamaliye bedeli, hijyen ve araç tedarik yeteneğidir.

Kaynakça

  • Aguezzoul, A., Rabenasoloo, B. & Jolly-Desodt, A. M., (2006). Multicriteria decision aid tool for third-party logistics providers’ selection, In International Conference Service Systems and Service Management (ICSSSM).
  • Akman, G. & Alkan, A., (2006). Measurement of supplier performance at supply chain management by using fuzzy AHP method: a study at automotive subcontractor industry, Istanbul Ticaret University Journal of science, 5(9), 23-46.
  • Alkhatib, S. F., Darlington, R. & Nguyen, T. T., (2015). Logistics service providers (lsps) evaluation and selection: literature review and framework development, Strategic Outsourcing: An International Journal, 8(1), 102-134.
  • Altan, S., & Karaş Aydın, E. (2015). An Integrated model approach with fuzzy DEMATEL and fuzzy TOPSIS methods for the selection of third party logistic firm, Suleyman Demirel University, Journal of Faculty of Economics & Administrative Sciences, 20(3), 99-119.
  • Bajec, P., & Tuljak-Suban, D. (2019). An Integrated Analytic Hierarchy Process-Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria, Sustainability, 11(8),
  • Bianchini, A., (2018). 3PL Provider Selection by AHP and TOPSIS methodology, Benchmarking: An International Journal, (just-accepted), 235-252.
  • Bottani, E. & Rizzi, A., (2006). A fuzzy TOPSIS methodology to support outsourcing of logistics services, Supply Chain Management: An International Journal, 11(4), 294-308.
  • 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, 9(3), 3000-3011.
  • Chang, B., Chang, C.W. & Wu, C.H., (2011). Fuzzy DEMATEL method for developing supplier selection criteria, Expert Systems with Applications, 38(3), 1850-1858.
  • Chen, C. T., (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114(1), 1-9.
  • Chen, J.K. & Chen, S., (2010). Using A novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education, Expert Systems with Applications, 37, 1981-1990.
  • Cheng, E. W., & Li, H. (2004). Contractor selection using the analytic network process, Construction Management and Economics, 22(10),1021-1032.
  • Chiang, Z., & Tzeng, G. H. (2009). A third party logistics provider for the best selection in fuzzy dynamic decision environments, International Journal of Fuzzy Systems, 11(1)
  • Çakır, E., Tozan, H. & Vayvay, O., (2009). A method for selecting third party logistic service provider using fuzzy AHP, Journal of Naval Science and Engineering, 5(3), 38-54.
  • Çelebi, D., Bayraktar, D., & Bingol, L. (2010). Analytical network process for logistics management: a case study in a small electronic appliances manufacturer, Computers & Industrial Engineering, 58(3), 432-441.
  • Daim, T. U., Udbye, A. & Balasubramanian, A., (2012). Use of analytic hierarchy process (AHP) for selection of 3PL providers, Journal of Manufacturing Technology Management, 24(1), 28-51.
  • Değermenci, A. & Ayvaz, B., (2016). Fuzzy environment multi criteria decision making techniques personnel selection: participation in an application in banking sector, Istanbul Commerce University Journal of Science, 15(30), 77-93.
  • Ecer, F. (2018). Third-party logistics (3PL) provider selection via fuzzy AHP and EDAS integrated model, Technological and Economic Development of Economy, 24(2), 615-634.
  • Fu, K., Xu, J., Zhang, Q., & Miao, Z. (2010). An AHP-based decision support model for 3PL evaluation, In 2010 7th International Conference on Service Systems and Service Management pp. 1-6. IEEE.
  • Govindan, K., Grigore, M. C., & Kannan, D. (2010). Ranking of third party logistics provider using fuzzy electre II, In the 40th International Conference on Computers & Indutrial Engineering, 1-5. IEEE.
  • Govindan, K., Khodaverdi, R. & Vafadarnikjoo, A., (2016). A grey DEMATEL approach to develop third-party logistics provider selection criteria, Industrial Management & Data Systems, 16(4), 690-722.
  • Gök, A. C., & Perçin, S. (2016). DEMATEL-ANP-VIKOR approach for assessing the e-service quality of electronic shopping (E-shopping) sites, Anadolu University Journal of Social Sciences, 16(2), 131-144.
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  • Gümüüay, S. A. & Berberoğlu, N., (2011). Decision making process of logistics outsourcing and criteria for 3PL provider selection, Online Academic Journal of Information Technology, 2(5), 33-50.
  • Gürcan, O. F., Yazıcı, I., Beyza, O. F., Arslan, C. Y., & Eldemir, F. (2016). Third party logistics (3PL) provider selection with AHP application, Procedia-Social and Behavioral Sciences, 235, 226-234.
  • Hwang, B. N. & Shen, Y. C., (2015). Decision making for third party logistics supplier selection in semiconductor manufacturing industry: a nonadditive fuzzy ıntegral approach, Mathematical Problems in Engineering,
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  • Jovčić, S., Průša, P., Dobrodolac, M., & Švadlenka, L., (2019). A proposal for a decision-making tool in third-party logistics (3PL) provider selection based on multi-criteria analysis and the fuzzy approach, Sustainability, 11(15)
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  • Kulak, O. & Kahraman, C., (2005). Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process, Information Sciences, 170(2-4), 191-210.
  • Kuo, R. J., Hsu, C. W. & Chen, Y. L., (2015). Integration of Fuzzy ANP and Fuzzy TOPSIS for Evaluating Carbon Performance of Suppliers, International Journal of Environmental Science and Technology, 12(12), 863-3876.
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  • Lixin, D., Ying, L., & Zhiguang, Z. (2008). Selection of logistics service provider based on analytic network process and VIKOR algorithm, In 2008 IEEE International Conference on Networking, Sensing and Control, 1207-1210. IEEE.
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  • Montanari, R., (2008). “Cold chain tracking: a managerial perspective”, Trends in Food Science & Technology, 19, 425-431.
  • Narkhede, B. E., Raut, R., Gardas, B., Luong, H. T., & Jha, M., (2017). Selection and evaluation of third party logistics service provider (3PLSP) by using an ınterpretive ranking process (IRP). Benchmarking: An International Journal, 24(6), 1597-1648.
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  • Özbek, A., & Eren, T. (2012). Selecting the third party logistic (3PL) firm through the analytic hierarchy process (AHP), International Journal of Engineering Research and Development, 4(2), 46-54.
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  • Özçakar, N., & Demir, H. (2011). Supplier selection by using the fuzzy TOPSIS method, Istanbul Management Journal, 22(69), 25-44.
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AN INTEGRATED MODEL APPROACH WITH FUZZY MULTI CRITERIA DECISION MAKING METHODS FOR THE SELECTION OF THIRD PARTY LOGISTICS FIRM IN THE FOOD INDUSTRY

Yıl 2023, Cilt: 10 Sayı: 1, 57 - 80, 29.03.2023
https://doi.org/10.30798/makuiibf.979840

Öz

The purpose of this study was to determine third party logistics company selection and evaluation criteria and to help make the most suitable selection among the alternatives in the food sector. Another purpose was to present a mixed model by integrating fuzzy multi criteria decision making methods in third-party logistics company selection process. The combination of fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS methods were used in this study. A decision network was created by evaluating the interactions between the criteria determined depending on the decision goal. This study was conducted in a large scale company producing milk and dairy products in food sector. As a result of the analyses made and the findings obtained, technology, delivery performance and quality were found as the criteria having the highest scores in terms of effectiveness. In addition, it was also determined that the most affected criterion among the criteria was the company image. The S2 Company was selected as the best third-party logistics company as a result of the evaluation of alternatives. The integrated fuzzy methods used in this study were used for the first time in the selection and evaluation of third-party logistics companies. And three new criteria; namely, portage price, hygiene and vehicle were added to the related literature which did not exist before.

Kaynakça

  • Aguezzoul, A., Rabenasoloo, B. & Jolly-Desodt, A. M., (2006). Multicriteria decision aid tool for third-party logistics providers’ selection, In International Conference Service Systems and Service Management (ICSSSM).
  • Akman, G. & Alkan, A., (2006). Measurement of supplier performance at supply chain management by using fuzzy AHP method: a study at automotive subcontractor industry, Istanbul Ticaret University Journal of science, 5(9), 23-46.
  • Alkhatib, S. F., Darlington, R. & Nguyen, T. T., (2015). Logistics service providers (lsps) evaluation and selection: literature review and framework development, Strategic Outsourcing: An International Journal, 8(1), 102-134.
  • Altan, S., & Karaş Aydın, E. (2015). An Integrated model approach with fuzzy DEMATEL and fuzzy TOPSIS methods for the selection of third party logistic firm, Suleyman Demirel University, Journal of Faculty of Economics & Administrative Sciences, 20(3), 99-119.
  • Bajec, P., & Tuljak-Suban, D. (2019). An Integrated Analytic Hierarchy Process-Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria, Sustainability, 11(8),
  • Bianchini, A., (2018). 3PL Provider Selection by AHP and TOPSIS methodology, Benchmarking: An International Journal, (just-accepted), 235-252.
  • Bottani, E. & Rizzi, A., (2006). A fuzzy TOPSIS methodology to support outsourcing of logistics services, Supply Chain Management: An International Journal, 11(4), 294-308.
  • 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, 9(3), 3000-3011.
  • Chang, B., Chang, C.W. & Wu, C.H., (2011). Fuzzy DEMATEL method for developing supplier selection criteria, Expert Systems with Applications, 38(3), 1850-1858.
  • Chen, C. T., (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114(1), 1-9.
  • Chen, J.K. & Chen, S., (2010). Using A novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education, Expert Systems with Applications, 37, 1981-1990.
  • Cheng, E. W., & Li, H. (2004). Contractor selection using the analytic network process, Construction Management and Economics, 22(10),1021-1032.
  • Chiang, Z., & Tzeng, G. H. (2009). A third party logistics provider for the best selection in fuzzy dynamic decision environments, International Journal of Fuzzy Systems, 11(1)
  • Çakır, E., Tozan, H. & Vayvay, O., (2009). A method for selecting third party logistic service provider using fuzzy AHP, Journal of Naval Science and Engineering, 5(3), 38-54.
  • Çelebi, D., Bayraktar, D., & Bingol, L. (2010). Analytical network process for logistics management: a case study in a small electronic appliances manufacturer, Computers & Industrial Engineering, 58(3), 432-441.
  • Daim, T. U., Udbye, A. & Balasubramanian, A., (2012). Use of analytic hierarchy process (AHP) for selection of 3PL providers, Journal of Manufacturing Technology Management, 24(1), 28-51.
  • Değermenci, A. & Ayvaz, B., (2016). Fuzzy environment multi criteria decision making techniques personnel selection: participation in an application in banking sector, Istanbul Commerce University Journal of Science, 15(30), 77-93.
  • Ecer, F. (2018). Third-party logistics (3PL) provider selection via fuzzy AHP and EDAS integrated model, Technological and Economic Development of Economy, 24(2), 615-634.
  • Fu, K., Xu, J., Zhang, Q., & Miao, Z. (2010). An AHP-based decision support model for 3PL evaluation, In 2010 7th International Conference on Service Systems and Service Management pp. 1-6. IEEE.
  • Govindan, K., Grigore, M. C., & Kannan, D. (2010). Ranking of third party logistics provider using fuzzy electre II, In the 40th International Conference on Computers & Indutrial Engineering, 1-5. IEEE.
  • Govindan, K., Khodaverdi, R. & Vafadarnikjoo, A., (2016). A grey DEMATEL approach to develop third-party logistics provider selection criteria, Industrial Management & Data Systems, 16(4), 690-722.
  • Gök, A. C., & Perçin, S. (2016). DEMATEL-ANP-VIKOR approach for assessing the e-service quality of electronic shopping (E-shopping) sites, Anadolu University Journal of Social Sciences, 16(2), 131-144.
  • Göl, H. & Çatay, B., (2007). Third-party logistics provider selection: insights from A Turkish automotive company, Supply Chain Management: An International Journal, 12(6), 379-384.
  • Gümüüay, S. A. & Berberoğlu, N., (2011). Decision making process of logistics outsourcing and criteria for 3PL provider selection, Online Academic Journal of Information Technology, 2(5), 33-50.
  • Gürcan, O. F., Yazıcı, I., Beyza, O. F., Arslan, C. Y., & Eldemir, F. (2016). Third party logistics (3PL) provider selection with AHP application, Procedia-Social and Behavioral Sciences, 235, 226-234.
  • Hwang, B. N. & Shen, Y. C., (2015). Decision making for third party logistics supplier selection in semiconductor manufacturing industry: a nonadditive fuzzy ıntegral approach, Mathematical Problems in Engineering,
  • Jharkharia, S. & Shankar, R., (2007). Selection of logistics service provider: an analytic network process (ANP) approach, Omega, 35(3), 274-289.
  • Jovčić, S., Průša, P., Dobrodolac, M., & Švadlenka, L., (2019). A proposal for a decision-making tool in third-party logistics (3PL) provider selection based on multi-criteria analysis and the fuzzy approach, Sustainability, 11(15)
  • Kang, H. Y., Lee, A. H. & Yang, C. Y., (2012). A fuzzy ANP model for supplier selection as applied to IC packaging, Journal of Intelligent Manufacturing, 23(5), 1477-1488.
  • Karagül, H., & Albayrako*lu, M. M. (2007). “Selecting a third-party logistics provider for an automotive company: an analytic hierarchy process model”. ISAHP 2007, 3-6.
  • Kashi, K., (2015). DEMATEL method in practice: finding the causal relations among key competencies, The 9th International Days of Statistics and Economics, Prague, 723-732.
  • Ku, C. Y., Chang, C. T. & Ho, H. P., (2010). Global supplier selection using fuzzy analytic hierarchy process and fuzzy goal programming, Quality & Quantity, 44(4), 623-640.
  • Kulak, O. & Kahraman, C., (2005). Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process, Information Sciences, 170(2-4), 191-210.
  • Kuo, R. J., Hsu, C. W. & Chen, Y. L., (2015). Integration of Fuzzy ANP and Fuzzy TOPSIS for Evaluating Carbon Performance of Suppliers, International Journal of Environmental Science and Technology, 12(12), 863-3876.
  • Li, X. & Wang, Q., (2007). Coordination Mechanisms of Supply Chain Systems, European Journal of Operational Research, 179(1), 1-16.
  • Li, Y. L., Ying, C. S., Chin, K. S., Yang, H. T., & Xu, J. (2018). Third-Party Reverse Logistics Provider Selection Approach Based on Hybrid-Information MCDM and Cumulative Prospect Theory, Journal of Cleaner Production, 195,573-584.
  • Liou, J. H., Tzeng, G. H., & Chang, H. C., (2007). Airline Safety Measurement Using A Hybrid Model, Journal of Air Transport Management, 13, 243-249.
  • Lixin, D., Ying, L., & Zhiguang, Z. (2008). Selection of logistics service provider based on analytic network process and VIKOR algorithm, In 2008 IEEE International Conference on Networking, Sensing and Control, 1207-1210. IEEE.
  • Meade, L. & Sarkis, J., (2002). A conceptual model for selecting and evaluating thirdparty reverse logistics providers, Supply Chain Management: An International Journal, 7(5), 283-295.
  • Meng, X. (2008). Study of evaluation and selection on third party reverse logistics providers, In 2008 International Seminar on Business and Information Management, 1, 518-521. IEEE.
  • Moberg, C. R. & Speh, T. W., (2004). Third-party warehousing selection: a comparison of national and regional firms, American Journal of Business, 19(2), 71-76.
  • Montanari, R., (2008). “Cold chain tracking: a managerial perspective”, Trends in Food Science & Technology, 19, 425-431.
  • Narkhede, B. E., Raut, R., Gardas, B., Luong, H. T., & Jha, M., (2017). Selection and evaluation of third party logistics service provider (3PLSP) by using an ınterpretive ranking process (IRP). Benchmarking: An International Journal, 24(6), 1597-1648.
  • Ocampo, L. A., Tan, T. A. G. & Sia, L. A., (2018). Using fuzzy DEMATEL in modeling the causal relationships of the antecedents of organizational citizenship behavior (OCB) in the hospitality ındustry: a case study in the philippines, Journal of Hospitality and Tourism Management, 34, 11-29.
  • Organ, A., (2013). Evaluation of machine selection criteria by method of fuzzy DEMATEL, Cukurova University, Journal of Social Sciences Institute, 22(1), 157-172.
  • Özbek, A., & Eren, T. (2012). Selecting the third party logistic (3PL) firm through the analytic hierarchy process (AHP), International Journal of Engineering Research and Development, 4(2), 46-54.
  • Özbek, A., (2013). Third party logistics (3PL) company selection with analytical network process approach, Atatürk University, Journal of Economics and Administrative Sciences, 27(1), 95-113.
  • Özçakar, N., & Demir, H. (2011). Supplier selection by using the fuzzy TOPSIS method, Istanbul Management Journal, 22(69), 25-44.
  • Özçifçi, V. & Arsu, T., (2013). Application of AHP selecting logistic service provider, Journal of Social Sciences and Humanities, 5(1), 309‐8012.
  • Paksoy, S., (2017). Current approaches in multi criteria decision making, Karahan Publisher, 1. Edition, Adana.
  • Ramik, J., (2007). A decision system using anp and fuzzy inputs, International Journal of Innovative Computing, Information and Control, 3(4), 825-837.
  • Raut, R., Kharat, M., Kamble, S. & Kumar, C. S., (2018). Sustainable evaluation and selection of potential third party logistics providers (3PL): an integrated MCDM approach, Benchmarking: An International Journal, (just-accepted)
  • Rijswijk, W. V., & Frewer, L. J. (2008). Consumer perceptions of food quality and safety and their relation to traceability, British Food Journal, 110(10), 1034-46.
  • Qureshi, M. N., Kumar, D., & Kumar, P. (2007). Selection of potential 3PL services providers using TOPSIS with interval data. In 2007 IEEE International Conference on Industrial Engineering and Engineering Management, 1512-1516. IEEE.
  • Saaty, T. L., (2008). Decision making with the analytic hierarchy process, International Journal Services Sciences, 1(1), 83-98.
  • Saen, R. F., (2007). A new mathematical approach for suppliers selection: accounting for non-homogeneity is important, Applied Mathematics and Computation, 185(1), 84-95.
  • Sahu, N. K., Datta, S. & Mahapatra, S. S., (2015). Fuzzy based appraisement module for 3PL evaluation and selection, Benchmarking: An International Journal, 22(3), 354-392.
  • Samantra, C., Datta, S., Mishra, S., & Mahapatra, S. S. (2013). Agility appraisal for integrated supply chain using generalized trapezoidal fuzzy numbers set, The International Journal of Advanced Manufacturing Technology, 68(5-8), 1491-1503.
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  • Soba M. & Simsek, A. (2019). Selection of a company that provides third party logistics (3PL) service with fuzzy TOPSIS method, International Journal of Social Sciences and Humanities, 33,380-399.
  • Soh, S., (2010). A decision model for evaluating third-party logistics providers using fuzzy analytic hierarchy process, African Journal of Business Management, 4(3), 339-349.
  • Sun, C., Pan, Y., & Bi, R. (2010). Study on Third-Party Logistics Service Provider Selection Evaluation Indices System Based on Analytic Network Process with BOCR, In 2010 International Conference on Logistics Systems and Intelligent Management (ICLSIM), 2, 1013-1017. IEEE.
  • Tabares-Urrea, N., Ramírez-Flòrez, G., Osorio-Gómez, J.C., (2020). Diffuse AHP and TOPSIS for the selection of a third-party provider considering operational risk, Revista EIA, 17(33), 89-105.
  • Tzeng, G. H., Chiang, C. H. & Li, C. W., (2007). Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL, Expert Systems with Applications, 32(4), 1028-1044.
  • Vijayvargiya, A., & Dey, A. K. (2010). An analytical approach for selection of a logistics provider, Management Decision, 48(3), 403-418.
  • Wang, Z., Leung, K. S. & Wang, J., (1999). A genetic algorithm for determining nonadditive set functions in information fusion, Fuzzy Sets and Systems, 102(3), 463-469.
  • Wu, W. W. & Lee, Y. T., (2007). Developing global managers’ competencies using the fuzzy DEMATEL method, Expert Systems With Applications, 32(2), 499-507.
  • Yadav, S., Garg, D., & Luthra, S. (2020). Selection of third-party logistics services for internet of things-based agriculture supply chain management, International Journal of Logistics Systems and Management, 35(2), 204-230.
  • Yang, J. L., Chiu, H. N., Tzeng, G. H. & Yeh, R. H., (2008). Vendor selection by integrated fuzzy MCDM techniques with independent and interdependent relationships, Information Sciences, 178(21), 4166-4183.
  • Zhang, H., Li, X., Liu, W., Li, B., & Zhang, Z. (2004). An application of the AHP in 3PL vendor selection of a 4PL system, In 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No. 04CH37583) 2, 1255-1260. IEEE.
Toplam 73 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Araştırma Makaleleri
Yazarlar

Mehri Banu Erdem 0000-0002-9763-3271

Nusret Göksu 0000-0003-3455-6982

Nuri Özgür Doğan 0000-0002-7892-1550

Yayımlanma Tarihi 29 Mart 2023
Gönderilme Tarihi 6 Ağustos 2021
Yayımlandığı Sayı Yıl 2023 Cilt: 10 Sayı: 1

Kaynak Göster

APA Erdem, M. B., Göksu, N., & Doğan, N. Ö. (2023). AN INTEGRATED MODEL APPROACH WITH FUZZY MULTI CRITERIA DECISION MAKING METHODS FOR THE SELECTION OF THIRD PARTY LOGISTICS FIRM IN THE FOOD INDUSTRY. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, 10(1), 57-80. https://doi.org/10.30798/makuiibf.979840