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Consumer service level-oriented resilience optimisation for e-commerce supply chain considering hybrid strategies with blockchain adoption

Author

Listed:
  • Wei Pu
  • Shuang Ma
  • Xiangbin Yan

Abstract

The booming development of customised e-commerce makes e-commerce supply chains experience a severe test of consumer service level (CSL). An efficient e-commerce supply chain resilience optimisation method addressing economic performance and service performance is proposed to improve customised services under disruption risks. The proposed method includes a hybrid strategy considering both a resistance strategy with blockchain (BCT) adoption and time-dependent recovery strategies simultaneously. A two-stage multi-period multi-product stochastic programming with BCT adoption is then proposed, which (1) implements BCT as the resistance strategy in the pre-disruption stage; (2) collaborates four recovery strategies in the post-disruption stage; (3) supports the e-tailer in making decisions and optimises his profit and order fulfillment time while taking product priorities into account. Using the actual data of Chinese e-commerce during the public health emergency in 2020, it is demonstrated that (1) the applicability of the model with BCT adoption in both supply chain resilience and CSL improvement; (2) the performance of the hybrid strategy in long-term disruption management; (3) the efficiency and robustness of the proposed solution approach for multi-objective high-dimensional stochastic programming problems. E-tailers can optimise decision-making under long-term disruptions by the proposed methodology in practices.

Suggested Citation

  • Wei Pu & Shuang Ma & Xiangbin Yan, 2024. "Consumer service level-oriented resilience optimisation for e-commerce supply chain considering hybrid strategies with blockchain adoption," International Journal of Production Research, Taylor & Francis Journals, vol. 62(19), pages 7226-7260, October.
  • Handle: RePEc:taf:tprsxx:v:62:y:2024:i:19:p:7226-7260
    DOI: 10.1080/00207543.2024.2354843
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