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A DEA-logistics performance index

Author

Listed:
  • Luisa Martí

    (Universidad Politécnica de Valencia)

  • Juan Carlos Martín

    (Universidad de Las Palmas de Gran Canaria)

  • Rosa Puertas

    (Universidad Politécnica de Valencia)

Abstract

Logistics and transport increasingly play a pivotal role in international trade relations. The Logistics Performance Index (LPI) measures the on-the-ground efficiency of trade supply chains or logistics performance. The aim of this paper is to propose a data envelopment analysis (DEA) approach to compute a synthetic index of overall logistics performance (DEA-LPI) and benchmark the logistics performance of the countries with LPI. Dealing with the six dimensions of LPI, the proposed approach uses DEA as a tool for multiple criteria decision making (MCDM). Furthermore, the paper also analyses the potential differences observed when using different variables, namely income and geographical area. Our findings suggest that the logistics performance depends largely on income and geographical area. High income countries are in the group of best performers, which is highly dominated by the EU.

Suggested Citation

  • 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.
    • Handle: RePEc:cem:jaecon:v:20:y:2017:n:1:p:169-192
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    Citations

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    Cited by:

    1. Naduni Kalansuriya & Shara Silva & Nishen Perera & Banuli Wanigarathna & Ruwan Jayathilaka & Parami Paranavitana & Saliya C. Arachchige, 2024. "Analysing the Influence of Logistics, Corruption, FDI and GDP on Global Competitiveness: a Cross-Sectional Study," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 13532-13551, September.
    2. Mingxuan Lu & Ruhe Xie & Peirong Chen & Yifeng Zou & Jie Tang, 2019. "Green Transportation and Logistics Performance: An Improved Composite Index," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
    3. 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.
    4. Rosa Puertas & Luisa Marti, 2019. "Sustainability in Universities: DEA-GreenMetric," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    5. Uyar, Ali & Fernandes, Valérie & Kuzey, Cemil, 2021. "The mediating role of corporate governance between public governance and logistics performance: International evidence," Transport Policy, Elsevier, vol. 109(C), pages 37-47.
    6. Bahadir Fatih Yildirim & Burcu Adiguzel Mercangoz, 2020. "Evaluating the logistics performance of OECD countries by using fuzzy AHP and ARAS-G," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(1), pages 27-45, March.
    7. Chia-Nan Wang & Jen-Der Day & Nguyen Thi Kim Lien & Luu Quoc Chien, 2018. "Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    8. Leonidas Sotirios Kyrgiakos & George Vlontzos & Panos M. Pardalos, 2021. "Ranking EU Agricultural Sectors under the Prism of Alternative Widths on Window DEA," Energies, MDPI, vol. 14(4), pages 1-26, February.
    9. Stojanović, Đurđica & Ivetić, Jelena, 2020. "Possibilities of using Incoterms clauses in a country logistics performance assessment and benchmarking," Transport Policy, Elsevier, vol. 98(C), pages 217-228.
    10. Gürler, Hasan Emin & Özçalıcı, Mehmet & Pamucar, Dragan, 2024. "Determining criteria weights with genetic algorithms for multi-criteria decision making methods: The case of logistics performance index rankings of European Union countries," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    11. Kalyana C. Chejarla & Omkarprasad S. Vaidya, 2024. "A hybrid multi-criteria decision-making approach for longitudinal data," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1013-1060, September.
    12. Göçer, Aysu & Özpeynirci, Özgür & Semiz, Meltem, 2022. "Logistics performance index-driven policy development: An application to Turkey," Transport Policy, Elsevier, vol. 124(C), pages 20-32.
    13. Mustafa Polat & Karahan Kara & Avni Zafer Acar, 2023. "Competitiveness based logistics performance index: An empirical analysis in Organisation for Economic Co-operation and Development countries," Competition and Regulation in Network Industries, , vol. 24(2-3), pages 97-119, June.
    14. Samira El Gibari & Trinidad Gómez & Francisco Ruiz, 2019. "Building composite indicators using multicriteria methods: a review," Journal of Business Economics, Springer, vol. 89(1), pages 1-24, February.

    More about this item

    Keywords

    logistics performance; freight transport; data envelopment analysis; logistics performance index :;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F1 - International Economics - - Trade
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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