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2019 | 5 (19) | nr 4 | 49--69
Tytuł artykułu

An Analysis of the Logistics Performance Index of EU Countries with an Integrated MCDM Model

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Countries can check the performance of their logistics' activities to determine their competitiveness in trade logistics. One way to check these performances is to analyze the country's LPI value in detail which is released by the WB every two years. When calculating the LPI, six indicators (criteria) are taken into account. The weights (importance level) of these criteria are important for countries which would like to focus more on the most important criteria and move their ranking up in the LPI list. However the WB takes into account indicators (criteria) weights equally when calculating LPI values. In order to overcome this problem some studies have used subjective weighting methods and others have used objective weighting methods. Both methods have advantages and disadvantages. The aim of this study is to integrate two weighting methods (subjective (SWARA) and objective (CRITIC)) in determining the weights of criteria in order to balance the two weighting methods. Unlike other studies in the literature this study combines two weighting methods. Additionally the PIV method, which is seldom used to address any MCDM problem, is used in this study and a new integrated MCDM model is introduced to literature. In this respect this study contributes to the literature. (original abstract)
Rocznik
Tom
Numer
Strony
49--69
Opis fizyczny
Twórcy
  • Sivas Cumhuriyet Unıversity
  • Sivas Cumhuriyet University
Bibliografia
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  • D'Aleo, V. (2015). The mediator role of Logistic Performance Index: A comparative study. Journal of International Trade, Logistics and Law, 1(1), 1-7.
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  • Heidary Dahooie, J., Beheshti Jazan Abadi, E., Vanaki, A. S., & Firoozfar, H. R. (2018). Competency-based IT personnel selection using a hybrid SWARA and ARAS-G methodology. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(1), 5-16. Retrieved from https://doi.org/10.1002/hfm.20713.
  • Jahan, A., Mustapha, F., Sapuan, S. M., Ismail, M. Y., & Bahraminasab, M. (2012). A framework for weighting of criteria in ranking stage of material selection process. International Journal of Advanced Manufacturing Technology, 58(1-4), 411-420. Retrieved from https://doi.org/10.1007/s00170-011-3366-7.
  • Karbassi Yazdi, A., Hanne, T., Osorio Gomez, J. C., & Garcia Alcaraz, J. L. (2018). Finding the best third-party logistics in the automobile industry: A hybrid approach. Mathematical Problems in Engineering, 2018. Retrieved from https://doi. org/10.1155/2018/5251261.
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  • Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. Retrieved from https://doi.org/10.3846/jbem.2010.12.
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  • Khan, N. Z., Ansari, T. S. A., Siddiquee, A. N., & Khan, Z. A. (2019). Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method. Journal of Computers in Education, 6(2), 241-256. Retrieved from https://doi. org/10.1007/s40692-019-00135-7.
  • Madić, M., & Radovanović, M. (2015). Ranking of some most commonly used nontraditional machining processes using ROV and CRITIC methods. U.P.B. Sci. Bull., Series D, 77(2), 193-204.
  • Marti, L., Martin, J. C., & Puertas, R. (2017). A DEA-logistics performance index. Journal of Applied Economics, 20(1), 169-192. Retrieved from https://doi.org/10.1016/S1514- 0326(17)30008-9.
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171576428

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