Transparency enhancement of supply chain capabilities through social media: a proposed hierarchical model

Sharfuddin Ahmed Khan (), Muhammad Shujaat Mubarik (), Syed Imran Zaman (), Alessio Ishizaka () and Kanwal Saleem ()
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Sharfuddin Ahmed Khan: University of Regina
Muhammad Shujaat Mubarik: Institute of Business Management (IoBM)
Syed Imran Zaman: Sichuan Tourism University
Alessio Ishizaka: NEOMA Business School
Kanwal Saleem: Jinnah University for Women

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 2, No 67, 4363-4401

Abstract: Abstract Despite an abundance of research on sustainable supply chains, the question of what factors contribute to transparency and how its hierarchical structure is formed is seldom addressed succinctly. In addition, the literature demonstrates that social media may aid in the improvement of Sustainable supply chain capabilities (SSCCs) characteristics associated with supply chain transparency. Therefore, the aim of this research is to develop a hierarchal model to determine how various SSCCs lead to increased transparency and how different social media tools can contribute to the enhancement of SSCCs. This study explores the relationship among a set of SSCCs, supported and developed a hierarchal model by the Interpretive Structural Modeling and Fuzzy Matrix Impact Cross Multiplication Applied to Classification approach. The result showed that information gathering is relatively more important to execute transparency; achieving transparency can help the firm get maximum customer satisfaction, greater employee engagement, and better partnership development. The broad goal of the study is to contribute to the operational usage of social media tools to effectively gather and monitor vital information to successfully implement SSCCs.

Keywords: Supply chain transparency; Sustainable supply chain capabilities; Sustainability; Fuzzy-matrix impact cross multiplication applied to classification; Interpretive structural modelling (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-023-04080-5

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