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Contextual and organizational factors in sustainable supply chain decision making: grey relational analysis and interpretative structural modeling

Environment, Development and Sustainability, ISSN: 1573-2975, Vol: 23, Issue: 8, Page: 12056-12076
2021
  • 11
    Citations
  • 483
    Usage
  • 58
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

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Most Recent News

Researchers at Northwestern Polytechnic University Report New Data on Sustainable Economy (Contextual and Organizational Factors In Sustainable Supply Chain Decision Making: Grey Relational Analysis and Interpretative Structural Modeling)

2022 NOV 01 (NewsRx) -- By a News Reporter-Staff News Editor at Economics Daily Report -- Current study results on Sustainability Research - Sustainable Economy

Article Description

Sustainable supply chain emerges as a major business trend essential to long-term competitive advantage. Relevant corporate decisions concern a broad range of factors and require novel analytical models for critical control. This study conducts mathematical analyses to identify the factors that are vital yet receiving insufficient attention from researchers and practitioners. Valid survey observations were collected from 113 enterprises in China, the biggest emerging economy that faces the dilemma between development and sustainability. Grey relational analysis (GRA) and interpretative structural modeling (ISM) assess the importance levels of contextual and organizational factors and explore their joint effects. Validated with conventional expert interviews, the results prioritize the factors that play crucial roles in sustainable supply chains. In particular, enterprises should pay close attention to three factors: corporate collaboration, clean production and supplier selection, which provide useful clues on the best practices of formulating low-carbon decisions. With a better understanding of critical factors, enterprises may make supply chains more sustainable with limited resources. To enhance the generalizability of findings, future studies may collect more observations from multiple countries and validate the results in the settings of global supply chains.

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