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A hierarchical analytical model for performance management of integrated logistics

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  • Mahamaya Mohanty
  • Ravi Shankar

Abstract

In this paper, a holistic hierarchical analytical model is proposed to assess the performance of enablers in an integrated logistics system. Due to the ambiguous and complex environment, various refinements are needed to assess enablers and prioritize for the criteria such as economic, operational, and environment. The proposed hierarchical model is developed by a systematic approach that includes fuzzy analytical hierarchy process (FAHP), triangular fuzzy numbers (TFN), an evidential reasoning algorithm (ERA), and expected utility theory (EUT). The FAHP is used to analyze and obtain the weights of the criteria by considering the expert’s opinions. ERA is used to synthesize the enablers based on the selected criteria. These enablers are represented using subjective assessment along with a set of evaluation grades for a qualitative attribute. EUT helps in obtaining crisp values of enablers for their performance estimation. With these set of methodologies, a hierarchical model is proposed that prevent low flexibility and inadequate appropriateness of the proposed model. Further, the model helps in scenario generation for the logistics professionals who are facing various problems in integrating logistics and incorporating sustainability due to lack of appropriate methodologies and evaluation techniques. Finally, sensitivity analysis is used for overall model validation.

Suggested Citation

  • Mahamaya Mohanty & Ravi Shankar, 2019. "A hierarchical analytical model for performance management of integrated logistics," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(2), pages 173-208, April.
    • Handle: RePEc:taf:tjmaxx:v:6:y:2019:i:2:p:173-208
    DOI: 10.1080/23270012.2019.1608326
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    Cited by:

    1. Yongping Xie & Yixuan Yin & Wei Xue & Hui Shi & Dazhi Chong, 2020. "Intelligent supply chain performance measurement in Industry 4.0," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 711-718, July.
    2. Maria Gabriela Mendonça Peixoto & Maria Cristina Angélico Mendonça & Cleber Carvalho de Castro & Luiz Gonzaga de Castro Júnior & Gustavo Alves de Melo & Mário Otávio Batalha, 2022. "Evaluation of the operational efficiency of southeast intermodal terminals in the grain logistics chain using data envelopment analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 3044-3058, October.
    3. Zhou, Honggeng & Li, Ling, 2020. "The impact of supply chain practices and quality management on firm performance: Evidence from China's small and medium manufacturing enterprises," International Journal of Production Economics, Elsevier, vol. 230(C).
    4. Ravi Shankar & Laxmi Gupta, 2024. "Modelling risks in transition from Industry 4.0 to Industry 5.0," Annals of Operations Research, Springer, vol. 342(2), pages 1275-1320, November.

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