Governance pressures and performance outcomes of sustainable supply chain management – An empirical analysis of UK manufacturing industry

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Abstract

Although sustainable supply chain management (SSCM) has recently received increasing attention among UK manufacturing firms, there is a concern as to whether SSCM practices are being implemented because they are profitable or only because of governance coercive pressure. Thus, the aims of this paper are twofold: first, determining the role of governance in the adoption of SSCM practices; second, investigating whether SSCM practices can be both environmentally beneficial and commercially viable. In light of these issues, this paper develops and empirically assesses an integrated model of governance pressures-SSCM practices-performance. Data was collected from 146 UK manufacturing managers, and analysed using the structural equation modelling method. Exogenous driving forces of governance were found to be precursors to the successful implementation of SSCM practices. The empirical results further suggest that while the implementation of sustainable supply chain management has a positive effect on environmental performance, it does not necessarily lead to improved economic performance, as only sustainable procurement was found to have a positive effect on economic performance. This paper contributes to the literature by highlighting the role of governance in SSCM adoption and performance gains in environmental protection while economic performance is partially compromised. The results also provide useful insights for both managers seeking to adopt sustainable practices and policy-makers seeking to further promote sustainable supply chain.

Details

Original languageEnglish
Pages (from-to)66-78
JournalJournal of Cleaner Production
Volume155
Early online date21 Jul 2016
Publication statusPublished - 1 Jul 2017

Keywords

  • Sustainable supply chain management (SSCM), Coercive pressure, Manufacturing firms, Environmental performance, Economic performance, Structural equation modelling (SEM), UK