E-Ticaretteki Pazaryeri Satıcı Seçimi Problemine Bulanık Hibrit Yaklaşım

Öz

Günümüz şartları göz önüne alındığında ve salgın hastalığın birden bire ortaya çıkması durumu internet ticaretini zorunlu olarak arttırmıştır. Bu durum satıcıların çeşitlenmesi ve farklı sektörlerde sayılarının artmasına sebep olmuştur. İnternet satıcılarının artması müşteriler için hangi ürünü hangi satıcıdan nasıl alacağı konusunda karar vermesini zorlaştırmıştır. Bu sebeple pazaryeri siteleri incelenmiş ve müşterilerin tercihini etkileyen en önemli kriterler belirlenmiştir. Bu kriterlerin çoğu, karar vericilerin bulanık ifadeler kullanarak ifade edebilecekleri dilsel terimlere dayanmaktadır. Bu çalışmada, Bulanık Analitik Hiyerarşi Prosesi ve Bulanık Hiyerarşik TOPSIS yöntemlerinin birleştirilmesiyle bir hibrit model kullanılarak satıcı seçim problemi çözülmüştür. Çalışmada, satıcı puanları, müşteri yorumları ve alanında uzman kişilerden görüş alınmıştır. Üç ana kriter ve on yedi alt kriter belirlenmiş ve Bulanık Hibrit Yaklaşıma uygulanmıştır. Uygulanan hibrit yöntemin sonuçlarına göre en etkili ana kriter 0,68 ağırlıkla satıcının genel özellikleri olarak bulunmuştur. Satıcı ile iletişim kolaylığı ise 0,30 ağırlıkla bu ana kriterin bir alt kriterinden elde edilmiştir. Böylelikle yapılan analizler sonucunda müşterilerin satıcının genel özelliklerine ve satış sonrası iletişime diğer kriterlere göre çok daha önem verdiği görüşüne varılmıştır. Önerilen hibrit model Türkiye'deki pazaryeri satıcı seçimi problemine başarıyla uygulanmıştır.

Anahtar Kelimeler

• Satıcı seçimi problemi
• Bulanık AHP
• Bulanık Hiyerarşik TOPSIS
• Pazaryeri
• İnternet alışverişi

A Fuzzy Hybrid Approach to The Marketplace Seller Selection Problem in E-Commerce

Öz

Considering today's conditions and the sudden emergence of an epidemic disease, internet commerce has necessarily increased. This situation has led to the diversification of vendors and an increase in their number in different sectors. The increase in internet sellers has made it difficult for customers to decide which product to buy from which seller and how. For this reason, the marketplace sites were examined and the most important criteria affecting the preferences of the customers were determined. Most of these criteria are based on linguistic terms that decision makers can express using fuzzy expressions. In this study, vendor selection problem is solved using a hybrid model by combining Fuzzy Analytical Hierarchy Process and Fuzzy Hierarchical TOPSIS methods. In the study, seller ratings, customer comments and opinions from experts in the field were taken. Three main criteria and seventeen sub-criteria were determined and applied to the Fuzzy Hybrid Approach. According to the results of the applied hybrid method, the most effective main criterion was found to be the general characteristics of the seller with a weight of 0.68. Ease of communication with the seller was obtained from a sub-criterion of this main criterion with a weight of 0.30. Thus, as a result of the analyzes made, it was concluded that the customers attach more importance to the general characteristics of the seller and to the after-sales communication than the other criteria. The proposed hybrid model has been successfully applied to the marketplace vendor selection problem in Turkey.

Anahtar Kelimeler

• Vendor selection problem
• Fuzzy AHP
• Fuzzy Hierarchical TOPSIS
• Marketplace
• Internet Shopping.

Kaynakça

1. Abdel-Basset M., Gunasekaran M., Mohamed M., Chilamkurti N. A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain, Future Generation Computer Systems 2019; 90: 489-502.
2. Akkaya G., Turanoğlu B., Öztaş S. An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert Systems with Applications, 2015; 42(24): 9565-9573.
3. Alizadeh, S. Rad, M.M.S. and Bazzazi, A.A.,2016. Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment. International Journal of Mining Science and Technology 2016; 26(6):1017-1023.
4. Amiri M.P. Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods. Expert Systems with Applications 2010; 37(9) : 6218-6224.
5. Beşikçi E.B., Kececi T., Arslan O., Turan O, An application of fuzzy-AHP to ship operational energy efficiency measures. Ocean Engineering 2016; 12: 392-402.
6. Buckley J.J. Fuzzy hierarchical analysis. Fuzzy Set Systems 1985; 17(3):233-247.
7. Calabrese A., Costa R., Levialdi N., Menichini T. Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues. Technological Forecasting and Social Change 2018; 139: 155-168. Chan B., Al‐Hawamdeh S. The development of e‐commerce in Singapore: The impact of government initiatives. Business process management journal 2002; 8(3): 278-288.
8. Chang D.Y. Applications of the extent analysis method on fuzzy AHP. European journal of operational research 1996; 95(3): 649-655.

9. Dožić S., Lutovac T., Kalić M. Fuzzy AHP approach to passenger aircraft type selection, Journal of Air Transport Management (2018). 68:165-175.
10. Gupta H. Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS. Journal of environmental management 2018; 226: 201-216.
11. Güler M.E. Prioritization of Revenue Management Factors: A Synthetic Extent Analysis Approach/ Prioritization of Yield Management Factors: Synthetic Scope Analysis Approach. Ege Academic Perspective 2012; 12(2): 161-170.
12. Heo E., Kim J., Boo K.-J. Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renewable and Sustainable Energy Reviews 2010; 14 (8): 2214-2220.
13. Hwang C.L. Yoon K. Multiple Attributes Decision Making Methods and Applications, Springer, 1981, Berlin Heidelberg.
14. Junior F.R.L., Osiro L., Carpinetti L.C.R. A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing 2014; 21: 194-209.
15. Li P., Zhang L., Dai L., Zou Y., Li X. An assessment method of operator’s situation awareness reliability based on fuzzy logic-AHP. Safety Science 2018; 119: 330-343. Li S., Wei Z. A hybrid approach based on the analytic hierarchy process and 2-tuple hybrid ordered weighted averaging for location selection of distribution centers. PloS one 2018; 13 ,11.
16. Ligus M., Peternek P. Determination of most suitable low-emission energy technologies development in Poland using integrated fuzzy AHP-TOPSIS methotds. Energy Procedia 2018; 153: 101-106.
17. Ly P.T.M., Lai W.H., Hsu C.W., Shih F.Y. Fuzzy AHP analysis of Internet of Things (IoT) in enterprises. Technological Forecasting and Social Change 2018; 136: 1-13.
18. Mandic K., Delibasic B., Knezevic S., Benkovic S. Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods. Economic Modelling 2014; 43: 30-37.
19. Mardani A., Jusoh A., Zavadskas E.K. Fuzzy multiple criteria decision-making techniques and applications–Two decades review from 1994 to 2014. Expert Systems with Applications 2015; 42(8); 4126-4148.
20. Pandey A., Kumar A. Commentary on Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach. Applied Soft Computing 2017; 51: 351-352. Saaty, T., 1989. Hierarchical-multiobjective systems, Control-Theory and Advanced Technology 5, 4, 485-489.
21. Sharma Y.K., Yadav A.K., Mangla S.K., Patil P.P. Ranking the Success Factors to Improve Safety and Security in Sustainable Food Supply Chain Management Using Fuzzy AHP. Materials Today: Proceedings 2018; 5(5): 12187-12196.
22. Sirisawat P,. Kiatcharoenpol, T. Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers. Computers & Industrial Engineering 2018; 117: 303-318.
23. Taylan O., Bafail A.O., Abdulaal R.M., Kabli M.R., Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing 2014; 17:105-116.
24. Wichapa N., Khokhajaikiat P. Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal centers. Operations Research Perspectives 2017; 4: 39-48.
25. Zadeh L.A. Fuzzy sets. Information and control 1965; 8(3): 338-353.
26. Zile M. Occupational Safety Risk Assessment Analysis Modeling and Software Development with Fuzzy Logic, Çukurova University Journal of Faculty of Engineering and Architecture 2015; 30(2), 267-274.