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Interpretive Structural Modeling Technique to Analyze the Interactions Between the Factors Influencing the Performance of the Reverse Logistics Chain

Author

Listed:
  • Jalel Euchi

    (Sfax University)

  • Dalel Bouzidi

    (Sfax University)

  • Zahira Bouzid

    (Sfax University)

Abstract

The aim of this study is to analyze the interactions among the different factors influencing the performance of the reverse logistics chain. We attempted to explore the factors touching performance of reverse logistics relatively to customer satisfaction. We have proposed a structural analysis based on MICMAC (Impact Matrix Cross-Reference Multiplication Applied to a Classification) method to classify factors rendering their direct/indirect influences and dependencies. The upshot of this research is to identify the relationship between the 31 variables used in the experimentation. It observed that this exploration might cooperate in reverse logistics policy development arrangement, motivated by customer necessity.

Suggested Citation

  • Jalel Euchi & Dalel Bouzidi & Zahira Bouzid, 2019. "Interpretive Structural Modeling Technique to Analyze the Interactions Between the Factors Influencing the Performance of the Reverse Logistics Chain," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 43-55, March.
    • Handle: RePEc:spr:gjofsm:v:20:y:2019:i:1:d:10.1007_s40171-018-0200-1
    DOI: 10.1007/s40171-018-0200-1
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    References listed on IDEAS

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    1. Krumwiede, Dennis W. & Sheu, Chwen, 2002. "A model for reverse logistics entry by third-party providers," Omega, Elsevier, vol. 30(5), pages 325-333, October.
    2. Kim, In Joon & Kim, So Jung & Yoon, Sun-Joong, 2014. "A dark side of international capital market integration: Domestic investors' view," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 238-256.
    3. Maher Agi & Rohit Nishant, 2017. "Understanding influential factors on implementing green supply chain management practices: An interpretive structural modelling analysis," Post-Print hal-02005891, HAL.
    4. Sushil, 2018. "How to check correctness of total interpretive structural models?," Annals of Operations Research, Springer, vol. 270(1), pages 473-487, November.
    5. Angappa Gunasekaran & Rameshwar Dubey & Surya Prakash Singh, 2016. "Flexible Sustainable Supply Chain Network Design: Current Trends, Opportunities and Future," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 17(2), pages 109-112, June.
    6. Sushil, 2017. "Modified ISM/TISM Process with Simultaneous Transitivity Checks for Reducing Direct Pair Comparisons," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(4), pages 331-351, December.
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    Cited by:

    1. Sourour Aouadni & Jalel Euchi, 2022. "Using Integrated MMD-TOPSIS to Solve the Supplier Selection and Fair Order Allocation Problem: A Tunisian Case Study," Logistics, MDPI, vol. 6(1), pages 1-18, January.
    2. H. Trollman & J. A. Colwill, 2020. "A Transformational Change Framework for Developing Ecologically Embedded Manufacturing," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(4), pages 341-368, December.
    3. Papadopoulos Panagiotis & Ezziane Zoheir, 2020. "Managing Expats and Their Effectiveness: A Comparative Study," Journal of Intercultural Management, Sciendo, vol. 12(1), pages 138-157, March.

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