Dynamic sustainability requirements of stakeholders and the supply portfolio

Elsevier BV
Publication Type:
Journal Article
Journal of Cleaner Production, 2020, 255, pp. 120148-120148
Issue Date:
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1-s2.0-S0959652620301955-main.pdfPublished version1.54 MB
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© 2020 Elsevier Ltd Extant literature on sustainability in procurement and supplier selection suffers from a number of deficiencies. First, studies pertaining to the dynamic nature of stakeholders’ expectations of sustainability and its impact on determining a supply portfolio have not been studied before. Second, there is a genuine lack of study linking the stakeholders’ sustainability requirements, firm procurement strategies, and eventual supplier selection. Third, most of the existing studies address sustainability issues in procurement and supplier selection but fall short of determining an optimal portfolio of suppliers and corresponding optimal order quantities. This study addresses the above research gaps by developing a sustainability-focused multi-criteria decision model for supplier evaluation and determining optimal order allocation among the suppliers linking the stakeholders’ sustainability requirements and firm procurement strategies. Based on dynamic capability theory, we develop a decision support framework integrating multi-phased quality function deployment and dynamic optimization. We apply the decision support framework to a European apparel company which sources apparel from Bangladesh: a country that is a low cost sourcing destination. First, this study identifies the stakeholders’ sustainability requirements. It then explicates the company's procurement strategies in terms of stakeholders’ requirements followed by translating the procurement strategies to relevant supplier assessment criteria. Finally, a linear optimization model is developed to maximize the suppliers’ sustainability performance in order to determine the optimal supply portfolio. The results identify two distinct groups of suppliers satisfying the overall sustainability performance. However the optimal order quantities among the suppliers vary randomly depending on the variations in demand and priority weights of the suppliers. The paper concludes with a detailed discussion of the results and implications.
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