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Evaluation and selection of third party logistics provider under sustainability perspectives: an interval valued fuzzy-rough approach

Author

Listed:
  • Jagannath Roy

    (National Institute of Technology Warangal)

  • Dragan Pamučar

    (University of Defence in Belgrade)

  • Samarjit Kar

    (National Institute of Technology Durgapur)

Abstract

In today’s world, industries are facing massive pressure to integrate sustainability issues for efficient and successful supply chain management (SCM). Hence, worldwide it has become critically important to make economic operational balance satisfying environment protection norms and social welfare perspectives. Consequently, the industries are investigating their SCM structures in association with a third party logistics (3PL) service provider adopting the triple bottom line framework for improving the overall supply chain performance. Therefore, selection of the right 3PL provider for the sustainable alliance is supremely important for broader perspective of greater business value. Thus, the main objective of this research work is the selection of most appropriate 3PL provider for a food manufacturing company (FMC) after systematic evaluation of six different feasible logistic providers serving over a decade in India. Selection of optimal alternative 3PL provider is very complex and challenging because of the qualitative description of service provider performances and the inherent uncertainty due to subjectivity. The concept of interval-valued fuzzy-rough number (IVFRN) offers perfect treatment of such uncertainty. In this paper, we develop a multi criteria decision making (MCDM) model combining the factor relationship (FARE) and multi-attributive border approximation area comparison (MABAC) models based on IVFRN. The proposed model is tested and validated on a case study where the optimal selection of 3PL providers is performed for an Indian FMC. Based on the results obtained in sensitivity analysis, it was shown that the proposed IVFRN based FARE-MABAC model produces stable/consistent solutions. Through the research presented in this paper, it is shown that the new hybrid MCDM method is a useful and reliable tool for rational decision-making.

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  • Jagannath Roy & Dragan Pamučar & Samarjit Kar, 2020. "Evaluation and selection of third party logistics provider under sustainability perspectives: an interval valued fuzzy-rough approach," Annals of Operations Research, Springer, vol. 293(2), pages 669-714, October.
    • Handle: RePEc:spr:annopr:v:293:y:2020:i:2:d:10.1007_s10479-019-03501-x
    DOI: 10.1007/s10479-019-03501-x
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    1. Hsiao, H.I. & Kemp, R.G.M. & van der Vorst, J.G.A.J. & (Onno) Omta, S.W.F., 2010. "A classification of logistic outsourcing levels and their impact on service performance: Evidence from the food processing industry," International Journal of Production Economics, Elsevier, vol. 124(1), pages 75-86, March.
    2. Gwo-Hshiung Tzeng & Chi-Yo Huang, 2012. "Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems," Annals of Operations Research, Springer, vol. 197(1), pages 159-190, August.
    3. Dilip Kumar Sen & Saurav Datta & Siba Sankar Mahapatra, 2017. "Decision Support Framework for Selection of 3PL Service Providers: Dominance-Based Approach in Combination with Grey Set Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 25-57, January.
    4. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 2001. "Rough sets theory for multicriteria decision analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 1-47, February.
    5. Adile Yesim Yayla & Asil Oztekin & Alev Taskin Gumus & Angappa Gunasekaran, 2015. "A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making," International Journal of Production Research, Taylor & Francis Journals, vol. 53(20), pages 6097-6113, October.
    6. Hosang Jung, 2017. "Evaluation of Third Party Logistics Providers Considering Social Sustainability," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    7. Aguezzoul, Aicha, 2014. "Third-party logistics selection problem: A literature review on criteria and methods," Omega, Elsevier, vol. 49(C), pages 69-78.
    8. Chia-Nan Wang & Hong-Xuyen Thi Ho & Shih-Hsiung Luo & Tsung-Fu Lin, 2017. "An Integrated Approach to Evaluating and Selecting Green Logistics Providers for Sustainable Development," Sustainability, MDPI, vol. 9(2), pages 1-21, February.
    9. McCarthy, Ian & Anagnostou, Angela, 2004. "The impact of outsourcing on the transaction costs and boundaries of manufacturing," International Journal of Production Economics, Elsevier, vol. 88(1), pages 61-71, March.
    10. Jabbour, Ana Beatriz Lopes de Sousa & Jabbour, Charbel Jose Chiappetta & Latan, Hengky & Teixeira, Adriano Alves & de Oliveira, Jorge Henrique Caldeira, 2014. "Quality management, environmental management maturity, green supply chain practices and green performance of Brazilian companies with ISO 14001 certification: Direct and indirect effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 39-51.
    11. Xihui Wang & Yunfei Wu & Liang Liang & Zhimin Huang, 2016. "Service outsourcing and disaster response methods in a relief supply chain," Annals of Operations Research, Springer, vol. 240(2), pages 471-487, May.
    12. Devika Kannan & Kiran Garg & P. C. Jha & Ali Diabat, 2017. "Integrating disassembly line balancing in the planning of a reverse logistics network from the perspective of a third party provider," Annals of Operations Research, Springer, vol. 253(1), pages 353-376, June.
    13. Thomas L. Saaty & Luis G. Vargas, 2012. "Models, Methods, Concepts & Applications of the Analytic Hierarchy Process," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4614-3597-6, September.
    14. Zaras, Kazimierz, 2004. "Rough approximation of a preference relation by a multi-attribute dominance for deterministic, stochastic and fuzzy decision problems," European Journal of Operational Research, Elsevier, vol. 159(1), pages 196-206, November.
    15. Animesh Debnath & Jagannath Roy & Samarjit Kar & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2017. "A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products," Sustainability, MDPI, vol. 9(8), pages 1-33, July.
    16. 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.
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    Cited by:

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    2. Simic, Vladimir & Gokasar, Ilgin & Deveci, Muhammet & Karakurt, Ahmet, 2022. "An integrated CRITIC and MABAC based type-2 neutrosophic model for public transportation pricing system selection," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    3. Zhou, Yaoming & Kundu, Tanmoy & Goh, Mark & Chakraborty, Shankar & Bai, Xiwen, 2023. "A multi-stage multi-criteria data analytics approach to rank commercial service airports," Journal of Air Transport Management, Elsevier, vol. 111(C).
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    5. Ananna Paul & Nagesh Shukla & Sanjoy Kumar Paul & Andrea Trianni, 2021. "Sustainable Supply Chain Management and Multi-Criteria Decision-Making Methods: A Systematic Review," Sustainability, MDPI, vol. 13(13), pages 1-28, June.
    6. Mladen Krstić & Giulio Paolo Agnusdei & Snežana Tadić & Pier Paolo Miglietta, 2023. "Prioritization of e-traceability drivers in the agri-food supply chains," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-26, December.
    7. Mohammed Alnahhal & Mosab I. Tabash & Diane Ahrens, 2021. "Optimal selection of third-party logistics providers using integer programming: a case study of a furniture company storage and distribution," Annals of Operations Research, Springer, vol. 302(1), pages 1-22, July.

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