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An analysis of the logistics performance index of EU countries with an integrated MCDM model

Author

Listed:
  • Ulutaş Alptekin

    (Sivas Cumhuriyet University, Faculty of Economics and Administrative Sciences, Department of International Trade and Logistics, Sivas 58140, Turkey)

  • Karaköy Çağatay

    (Sivas Cumhuriyet University, Faculty of Economics and Administrative Sciences, Department of International Trade and Logistics, Sivas58140, Turkey)

Abstract

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.

Suggested Citation

  • Ulutaş Alptekin & Karaköy Çağatay, 2019. "An analysis of the logistics performance index of EU countries with an integrated MCDM model," Economics and Business Review, Sciendo, vol. 5(4), pages 49-69, December.
    • Handle: RePEc:vrs:ecobur:v:5:y:2019:i:4:p:49-69:n:3
    DOI: 10.18559/ebr.2019.4.3
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    References listed on IDEAS

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    1. Luisa Mart𓐊Author-X-Name-First: Luisa & Leandro Garc𨀍, 2014. "The importance of the Logistics Performance Index in international trade," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2982-2992, August.
    2. Edmundas Kazimieras Zavadskas & Valentinas Podvezko, 2016. "Integrated Determination of Objective Criteria Weights in MCDM," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 267-283, March.
    3. Luisa Martí & Juan Carlos Martín & Rosa Puertas, 2017. "A DEA-logistics performance index," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 169-192, May.
    4. Rajesh Kr. Singh & Angappa Gunasekaran & Pravin Kumar, 2018. "Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach," Annals of Operations Research, Springer, vol. 267(1), pages 531-553, August.
    5. Rezaei, Jafar & van Roekel, Wilco S. & Tavasszy, Lori, 2018. "Measuring the relative importance of the logistics performance index indicators using Best Worst Method," Transport Policy, Elsevier, vol. 68(C), pages 158-169.
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    More about this item

    Keywords

    CRITIC; SWARA; PIV; MCDM; LPI; logistics; performance;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M19 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Other
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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