Integrated Approach Of Fuzzy AHP and Grey Relational Analysis For Logistic Performance Evaluation

Abstract

In recent years, a complex logistics service approach has forced logistics service providers to produce more customer-focused services. Using integrated systems with information technologies to compete in the logistics sector improves customer satisfaction while increasing efficiency and productivity. Service providers that can effectively assess the knowledge and transportation infrastructure they have, with their human resources, logistics performances are also quite high. Delivery of products at scheduled time is one of the most important elements of logistics performance. Logistic performance assessments based on these factors can be global or local. In this study, logistic performance evaluation was carried out for 10 OECD member countries. The weights of the evaluation criteria for this were calculated by the fuzzy AHP method from the multi-criteria decision making techniques and then the ranking was done by grey relational analysis method according to the country's logistic performance. The logistics performances of the countries are primarily attributed to the lead time of import and export and then to the quality of trade and transport-related infrastructure.

Keywords

• Logistics Performance,Fuzzy AHP,Grey Relational Analysis

Lojistik Performans Değerlendirmesi İçin Bulanık AHP ve Gri İlişkisel Analiz Yöntemleri İle Bütünleşik Bir Yaklaşım

Öz

Son yıllarda hızlıca gelişme gösteren lojistik hizmet anlayışı, lojistik servis sağlayıcılarını gittikçe daha fazla müşteri odaklı hizmet üretmeye itmektedir. Lojistik sektöründe rekabet edebilmek için bilgi teknolojileriyle entegre sistemler kullanmak etkinlik ve verimliliği artırırken müşteri memnuniyetini de geliştirmektedir. Sahip olunan bilişim ve ulaştırma altyapılarını, kalifiye insan kaynağı ile etkin bir şekilde değerlendiren servis sağlayıcılarının lojistik performanslarının da oldukça yüksek olduğu görülmektedir. Bu çalışmada OECD üyesi 10 ülke için lojistik performans değerlendirmesi yapılmıştır.  Bunun için ele alınan değerlendirme kriterlerine ait ağırlıklar, çok kriterli karar verme tekniklerinden bulanık AHP metodu ile hesaplanmış daha sonra ülkelerin lojistik performansına göre sıralama gri ilişkisel analiz metoduyla gerçekleştirilmiştir. Ülkelerin lojistik performanslarının öncelikle ithalat ve ihracat teslim sürelerine daha sonra ise kullandıkları altyapıların kalitesine bağlı olduğu sonucuna erişilmiştir.

Anahtar Kelimeler

• Lojistik Performans,Bulanık AHP,Gri İlişkisel Analiz

References

1. Andersson, P., Aronsson, H. ve Storhagen, N. G. (1989). Measuring Logistics Performance. Engineering Costs and Production Economics, 17(1-4), 253-262.
2. Ahi, P. & Searcy, C. (2015). An Analysis of Metrics Used to Measure Performance in Green and Sustainable Supply Chains. Journal of Cleaner Production, 86,360-377.
3. Avelar-Sosa, L., García-Alcaraz, J. L., Vergara-Villegas, O. O., Maldonado-Macías, A. A. ve Alor-Hernández, G. (2015). Impact of Traditional and international logistic policies in supply chain performance. Int J Adv Manuf Technol, 76:913–925.
4. Bayraktutan, Y., Özbilgin, M. (2015). Lojistik Maliyetler ve Lojistik Performans Ölçütleri. Maliye Araştırmaları Dergisi,1-2, 95-112.
5. Cagliano, A.C. & Rafele, C. (2006). Using System Dynamics to Evaluate Logistic Performance. International Meetings for Research in Logistics, 445-457.
6. Caplice, C. & Sheffi, Y. (1995). A Review and Evaluation of Logistics Performance Measurement Systems. The International Journal of Logistics Management,6,1, 61-74.
7. Chan, F. T. S., Chan, H.K., Lau, H. C. W., ve Ip, R. W. L. (2006). An AHP Approach in Benchmarking Logistics Performance of the Postal Industry, Benchmarking: An International Journal, 13 (6), 636-661.
8. Chang, D. Y. (1996). Applications of the Extent Analysis Method on Fuzzy AHP. Eur J Oper Res, 95, 649–655.

9. Deng Julong (1982). Control Problems of Grey Systems, Systems and Control Letters, 5, 288-294.
10. Dünya Bankası. 2016. Lojistik Performans İndeksi. Erişim ( 30.08.2018) https://data.worldbank.org/indicator/LP.LPI.OVRL.XQ?view=chart
11. Erkan, B. (2014). The Importance and Determinants of Logistics Performance of Selected Countries, Journal of Emerging Issues in Economics, Finance and Banking, 3(6), 1237-1254.
12. Fawcett, S. E. & Cooper, M. B. (1998). Logistics Performance Measurement and Customer Success. Industrial Marketing Management, 27(4), 341-357.
13. Fugate, B. S., Autry, C. W., Davis-Sramek, B. ve Germain, R. N. (2012). Does Knowledge Management Facilitate Logistics-Based Differentiation? The Effect of Global Manufacturing Reach. International Journal of Production Economics, 139(2), 496-509.
14. Hanaoka, S. & Kunadhamraks, P. (2009). Multiple Criteria and Fuzzy Based Evaluation of Logistics Performance for Intermodal Transportation. Journal of Advanced Transportation, 43(2), 123-153.
15. Hsiao, H., Kemp, R. G. M., Van der Vorst, J. G. A. J. ve Omta, S. O. (2010). A Classification of Logistic Outsourcing Levels and Their Impact on Service Performance: Evidence 117 from the Food Processing Industry. International Journal of Production Economics, 124(1), 75-86.
16. Jothimani, D. & Sarmah, S. P. (2014). Supply Chain Performance Measurement for Third Party Logistics, Benchmarking: An International Journal, 21(6), 944-963. J. J. Buckley. (1985). Ranking Alternatives Using Fuzzy Numbers, Fuzzy Sets Systems,15(1), 21-31.
17. Kazancoglu, Y., Kazancoglu, I. ve Sagnak, M. (2018) Fuzzy DEMATEL-Based Green Supply Chain Management Performance: Application in Cement Industry. Industrial Management & Data Systems, 118(2), 412-431.
18. Korpela, J. & Tuominen, M. (1996). Benchmarking Logistics Performance with an Application of the Analytic Hierarchy Process. Engineering Management, IEEE Transactions, 43(3), 323-333.
19. Lai, K. H., Bao, Y. & Li, X. (2008). Channel Relationship and Business Uncertainty: Evidence from the Hong Kong Market. Industrial Marketing Management, 37(6), 713-724.
20. Lin, P. C. & Cheng, T. C. E. (2018) The Diffusion and the International Context of Logistics Performance. International Journal of Logistics Research and Applications, DOI:10.1080/13675567.2018.1510907.
21. Liu, C. L. & Lyons, A. C. (2011). An Analysis of Third-Party Logistics Performance and Service Provision. Transportation Research Part E: Logistics and Transportation Review, 47(4), 547-570.
22. Özceylan, E., Çetinkaya, C., Erbas, M. ve Kabak, M. (2016). Logistic Performance Evaluation of Provinces in Turkey: A GIS-Based Multi-Criteria Decision Analysis. Transportation Research Part A, 94, 323–337.
23. Piriyakul, M. (2011). A Partial Least Squares Model for SCM Strategy, Willingness for External Collaboration, Competitive Performance and Relative Performance: Effects of Marketing and Logistics Performance in the Palm Oil Industry. African Journal of Business Management, 5(4), 1431-1440.
24. Puertas, R., Martı´, L. ve Garcia, L. (2014). Logistics Performance and Export Competitiveness: European Experience. Empirica, 41, 467–480.
25. Ramanaa, D.V., Raob, K.N. ve Kumara, J. S. (2013). Evaluation of Performance Metrics of Leagile Supply Chain Through Fuzzy MCDM. Decision Science Letters, 2,211–222.
26. Ramanathan, R. (2010). The Moderating Roles of Risk and Efficiency on the Relationship between Logistics Performance and Customer Loyalty in e-commerce. Transportation Research Part E: Logistics and Transportation Review, 46(6), 950-962.
27. T.C. Gümrük ve Ticaret Bakanlığı. (2017). Lojistik Performans İndeksi 2016 Ekonomik Analiz ve Değerlendirme Dairesi, Ankara.
28. Van-Laarhoven, P. J. M. ve Pedrycz, W. (1983). A Fuzzy Extension of Saaty’s Priority Theory. Fuzzy Sets and Systems, 11, 229-241.
29. Wang, M., Jie, F. ve Abareshi, A. (2015). Business Logistics Performance Measurement in Third-Party Logistics: An Empirical Analysis of Australian Courier Firms. International Journal of Business and Information, 10(3), 323-336.
30. Wu, H. H. (2002). A Comparative Study of Using Grey Relational Analysis in Multiple Attribute Decision Making Problems. Quality Engineering, 15(2), 209-217.