Managerial decisions of remanufacturing technology portfolio under a discrete choice model

Remanufacturing is a viable and indispensable method to restore used electronics to near-new condition, combating the alarming rise of end-of-life (EOL) products, particularly in the field of electronic waste. It aligns with Environmental, Social, and Governance (ESG) principles, emphasizing sustainability and responsible resource management. In this paper, we consider a remanufacturer’s problem in choosing various technologies to form a Remanufacturing Technology Portfolio (RTP), a strategic decision affecting remanufacturers’ efficiency, productivity, and contributions to societal and environmental welfare. To address the unique challenges posed by the variability of EOL product quality, substitutability among candidate technologies, and other considerations in the RTP problem, we employ a discrete choice modeling framework, specifically the multinomial logit model, to characterize the technology assignment process of unprocessed EOL cores. This application is novel in the remanufacturing industry. We reveal that the optimal RTP balances remanufacturing capability and profitability, consisting of a set of the most profitable technologies. Moreover, we identify conditions under which technologies are included or excluded from the optimal RTP and explore the impact of various factors such as selling price, salvage values, and production and material costs on the composition of the optimal RTP and the remanufacturing yield. This study provides valuable guidance for remanufacturers in strategically selecting technologies to enhance their performance and competitiveness in the volatile remanufacturing market, while advancing their ESG objectives. In a broader supply chain context, the findings suggest strategies to encourage other supply chain stakeholders to engage in ESG practices and offer insights on how government incentives promoting remanufacturing can be more effectively structured based on technological considerations.