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Modelling Supply Chain Measurement in Omni-Channel Supply Chain

Author

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  • Jirapan Liangrokapart

    (Mahidol University)

  • Sukanya Prakongwittaya

    (Mahidol University)

Abstract

Retail business has transformed into omni-channel retail, a modern approach utilizing multiple channels several years ago. The performance measurement used in the past which mainly focused on financial measures may not be applicable to omni-channel retail. This research aims to model a supply chain performance measurement framework for the omni-channel supply chain and to draw a relationship among performance measures and their association with the goals of resource efficiency, customer service level, and flexibility. Total Interpretive Structural Model (TISM), a qualitative modelling technique, is applied in the study for building links between measures. The experts were asked to complete the TISM questionnaires for interpretive logic-knowledge. Then, a hierarchical model with interpretive logic for the overall supply chain performance measurement framework was developed. An omni-channel supply chain was used as a case study, and the result showed that the relationships among measures including “demand forecast accuracy,” “planning accuracy,” “urgent order response speed,” “service reliability,” “cost,” and “information readiness” can lead to “efficiency,” “time for decision-making,” “market change response speed,” and “revenues.” The key contribution of this research is a structured performance measurement framework for omni-channel supply chain using TISM to identify and interpret the relationships among key performance indicators, particularly for the goals of efficiency, customer service, and responsiveness. Detailed strategies for improving supply chain performance have been provided. Lastly, theoretical and managerial implications are discussed, and recommendations for future research are presented.

Suggested Citation

  • Jirapan Liangrokapart & Sukanya Prakongwittaya, 2025. "Modelling Supply Chain Measurement in Omni-Channel Supply Chain," SN Operations Research Forum, Springer, vol. 6(3), pages 1-28, September.
    • Handle: RePEc:spr:snopef:v:6:y:2025:i:3:d:10.1007_s43069-025-00490-5
    DOI: 10.1007/s43069-025-00490-5
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    References listed on IDEAS

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    1. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    2. Pereira, Marina Meireles & Frazzon, Enzo Morosini, 2021. "A data-driven approach to adaptive synchronization of demand and supply in omni-channel retail supply chains," International Journal of Information Management, Elsevier, vol. 57(C).
    3. Raut, Rakesh D. & Mangla, Sachin Kumar & Narwane, Vaibhav S. & Dora, Manoj & Liu, Mengqi, 2021. "Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    4. Shradha A. Gawankar & Angappa Gunasekaran & Sachin Kamble, 2020. "A study on investments in the big data-driven supply chain, performance measures and organisational performance in Indian retail 4.0 context," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1574-1593, March.
    5. Chia-Ying Li & Chien-Hsiang Liao & Yu-Hui Fang, 2025. "A dedication-constraint model of omnichannel shopping journey," Electronic Markets, Springer;IIM University of St. Gallen, vol. 35(1), pages 1-26, December.
    6. Vikash Sharma & Rakesh D. Raut & Sachin Kumar Mangla & Balkrishna E. Narkhede & Sunil Luthra & Ravindra Gokhale, 2021. "A systematic literature review to integrate lean, agile, resilient, green and sustainable paradigms in the supply chain management," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 1191-1212, February.
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