Abstract: Water footprint (WF) is an appropriate tool to help any water-intensive industrial system to adapt to climate change. WF is a metric where the direct and indirect freshwater consumption of a country, firm, activity, or product are quantified. Most of existing WF literature emphasizes the assessment of products, not the optimal decision making in the supply chain. To address this research gap, a bi-objective optimization model is developed for supplier selection in a supply chain that minimizes costs and WF. Apart from determining the sources of raw materials to use in producing the products, the model also determines the actions to be taken by the firm in case of supply shortages. The model is demonstrated using three illustrative case studies which show that WF embedded in the raw materials can influence the actions to be taken when addressing issues on raw material availability. The WF becomes significant in the decisions in this bi-objective optimization problem when it is given a weight of at least 20% (or the weight of the cost is at most 80%) for case study 1 and at least 50% for case study 2. When the assigned weight in cost reaches the point where WF becomes significant, the increase in the assigned weight in WF has an inverse impact on the total cost. Case study 3 demonstrates the stochastic variant of the model.
Supplementary information: The online version contains supplementary material available at 10.1007/s10098-023-02549-5.
Keywords: Goal programming; Material selection; Material substitution: Mathematical programming; Supply chain; Water footprint.
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.