Decarbonising product supply chains: Design and development of an integrated evidence-based decision support system-the supply chain environmental analysis tool (SCEnAT)

S. C. Lenny Koh, Andrea Genovese, Adolf A. Acquaye, Paul Barratt, Nasir Rana, Johan Kuylenstierna, David Gibbs

    Research output: Contribution to journalArticlepeer-review

    88 Scopus citations

    Abstract

    Based upon an increasing academic and business interest in greening the industrial supply chains, this paper establishes the need for a state-of-the-art decision support system (DSS) for carbon emissions accounting and management, mainly across the product supply chains by identifying methodological shortcomings in existing tools, and proposing a supply chain (SC) framework which provide businesses with a holistic understanding of their supply chains and ensuring partners within supply chain collaborative networks have a shared understanding of their emissions. It describes the design and development of a DSS now known as supply chain environmental analysis tool (SCEnAT) in detail, putting its unique and innovative features into a comparative perspective vis-à-vis existing tools and software of different types. The methodological framework used to design and develop SCEnAT integrates different individual techniques/methods of supply chain (SC) mapping, SC carbon accounting, SC interventions and SC interventions evaluation on a range of key performance indicators (KPIs). These individual methods have been used and applied innovatively to the challenge of designing SCEnAT within the desired framework. Finally, we demonstrate the application of SCEnAT, especially the advantage of using a robust carbon accounting methodology, to a SC case study. The SCEnAT framework pushes the theoretical boundary by addressing the problems of intra-organisational approach in decision making for lowering carbon along the supply chain; with an open innovation, cutting edge, hybridised framework that considers the supply chain as a whole in co-decision making for lowering carbon along the supply chain with the most robust methodology of hybrid life cycle analysis (LCA) that considers direct and indirect emissions and interventional performance evaluation for low carbon technology investment and business case building in order to adapt and mitigate climate change problems. This research has implications for future sustainability research in SC, decisions science, management theory, practice and policy.

    Original languageBritish English
    Pages (from-to)2092-2109
    Number of pages18
    JournalInternational Journal of Production Research
    Volume51
    Issue number7
    DOIs
    StatePublished - 1 Apr 2013

    Keywords

    • decision support system
    • SC carbon accounting
    • SC decarbonisation
    • SC low carbon interventions
    • SC management
    • SC mapping

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