A sourcing–inventory model with flexible production for sustainable supply chains: machine learning and relational view theory

Abstract

Supply chain members manage inventory levels through vendor-managed inventory and sourcing strategies to achieve customer satisfaction while reducing costs. The juxtaposition of environmental responsibility and cost-effectiveness presents a unique challenge in supply chain management. This paper addresses the research question: How can a vendor-managed inventory policy improve environmental and cost performance simultaneously when considering supplier selection? Through the theoretical lens of the relational view, we presented a conceptual model to test hypothesized relationships. Moreover, this paper develops a sourcing-based vendor-managed inventory model for a single-product supply chain consisting of a retailer, a manufacturer, and multiple suppliers. This study uses data from a pharmaceutical company as a case study to explore its operations and performance. A machine-learning algorithm, the recurrent neural network, is used to predict demand in the proposed model. The findings suggest that the proposed model can significantly improve environmental and cost performance. The main contribution of this paper is analytical and theoretical support to explain how production flexibility and carbon tax can impact firms’ performance. Show more