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Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach

  • Multiple Objective Optimization
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Abstract

Managing value chain of perishable food items or pharmaceutical drugs is known as cold chain management. In India, approximately 30% fruits and vegetables get wasted due to lack of effective cold chain management. Logistic providers play a crucial role in making cold chains more effective. Based on literature review, ten criteria are selected for the third party logistics (3PL) selection process. Some of these criteria are transportation and warehousing cost, logistic infrastructure and warehousing facilities, customer service and reliability, network management, etc. This study illustrates a hybrid approach for selection of 3 PL for cold chain management under fuzzy environment. A hybrid model of Fuzzy AHP and Fuzzy TOPSIS is proposed in this paper for the selection of an appropriate 3PL in order to outsource logistics activities of perishable products. Fuzzy AHP is used to rank different criteria for 3PL selection, then Fuzzy TOPSIS is used to select the best 3 PL based on performance. The results imply that logistic providers should focus on practices such as automation of processes and innovation in cold chain processes to become more competitive.

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Acknowledgements

Authors would like to express their sincere thanks to the Chief Editor of the journal and unanimous reviewers for valuable comments and suggestions to enhance quality and content of the paper. Authors also acknowledge the support of Mr. Ankit Bansal and Mr. Sidhant Issar, UG students in doing this research work.

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  1. Management Development Institute, Gurgaon, India

    Rajesh Kr. Singh

  2. School of Business and Public Administration, California State University, Bakersfield, USA

    Angappa Gunasekaran

  3. Delhi Technological University, Delhi, India

    Pravin Kumar

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Singh, R.K., Gunasekaran, A. & Kumar, P. Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach. Ann Oper Res 267, 531–553 (2018). https://doi.org/10.1007/s10479-017-2591-3

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