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Joint Distribution Promotion by Interactive Factor Analysis using an Interpretive Structural Modeling Approach

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  • Fuli Zhou
  • Yandong He
  • Felix T. S. Chan
  • Panpan Ma
  • Francesco Schiavone

Abstract

With the increasing demand of individual customption and awareness of cost reduction in express delivery organizations, the Chinese express industry faced with serious challenges especially under the background of government’s strict restrictions on environment and transportation. Therefore, a new service mode called joint distruction (JD) is being tried by the logistics industry, which is expected to address the challenges on online shopping. However, the insufficient understanding of JD adoption factors and their complicated interactions blocks the effectively implementation of the joint distribution. This study aims at identifying potential factors for JD adoption and promoting an effective joint distribution by discovering the interactive relationships among addressed factors. Firstly, potential ingredients for the adoption and implementation of JD are summarized from the literature and industrial interviews. Then, 23 variables are selected and classified into as objectives, drivers, barriers and affected operations. The Interpretive Structural Modeling (ISM) approach is then employed to analyze the crucial factors and the mutual influences amongst 23 variables. Finally, a case study is performed to construct the hierarchical structure of factors toward joint distribution adoption using the proposed ISM-modeling steps. The perplex hierarchical co-relationships are also identified by categorizing the driving variables and dependent variables. Results can assist express enterprises to promote the novel joint distribution mode and acheive higher efficiency of logistics operation by better understanding on crucial factors of JD adoption and implementation.

Suggested Citation

  • Fuli Zhou & Yandong He & Felix T. S. Chan & Panpan Ma & Francesco Schiavone, 2022. "Joint Distribution Promotion by Interactive Factor Analysis using an Interpretive Structural Modeling Approach," SAGE Open, , vol. 12(1), pages 21582440221, February.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:1:p:21582440221079903
    DOI: 10.1177/21582440221079903
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    2. Fuli Zhou & Yijie Liu, 2022. "Blockchain-Enabled Cross-Border E-Commerce Supply Chain Management: A Bibliometric Systematic Review," Sustainability, MDPI, vol. 14(23), pages 1-23, November.

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