In remanufacturing, variability in quality levels of available cores (end-of-life products) has an impact on both the process cost and the process time. While previous research suggests that quality grading adds value, there are also concerns raised regarding how reliably the grades can be identified. We argue that uncertainty is inherent to the grading process and investigate the value of grading by taking into account the underlying uncertainty. We develop a robust optimisation model for remanufacturing planning, where both the per-unit cost and resource requirement to remanufacture a core are uncertain parameters that are assumed to reside in two different uncertainty sets; box and ellipsoidal. We analyse both uncapacitated and capacitated cases, and based on extensive numerical analysis, conclude that while on average, there is still value in grading, it becomes significantly smaller when the inherent uncertainty is accounted for. For the capacitated case, we also consider a cost for grading and find that it may cause a significant deterioration in the value of grading, if not rendering the grading totally useless. We show the validity of our approach through extensive numerical analyses.

The apparel and textile industry (AT) is considered one of the most polluting industries in the world due to the complexity of the supply chain and the high volume of natural resources and toxic chemicals used during manufacturing. Closed loop supply chains (CLSC) for apparel and textile are unique and therefore the circular economy solutions that exist for other industries, especially the electronics industry where these solutions are used extensively, may not be successful. This study aims to evaluate the practices of fashion brands that currently employ a CLSC to better understand the existing strategies and prevalent issues in comparison to the electronics industry. We developed a framework based on factors that identify the delineating aspects of a CLSC and performed a content analysis of the publicly available sustainability reports of companies. The results show the need for different solutions between the industries and indicate a need for research that is informed by the AT specific contextual factors since one‐fits‐all solutions will not work well across industries.

The empirical literature considers firm-specific aspects affecting corporate sustainability decisions but generally omits the influence of the competition. We advocate that sustainability actions of a company impact its marketplace and vice versa. Therefore, the sustainability return of the single firm is a function of the other firms’ sustainability decisions. We approach sustainability decisions as strategic decisions and evaluate the effect of competition and spillovers in a static market entry game. We estimate the parameters of the discrete choice model using the social performance ratings from MSCI KLD 400 Social Index as proxy for sustainability decisions and financial information from Wharton Research Data Services’ COMPUSTAT dataset. When strategic interaction is not accounted for, we find that an increase in the number of competitors increases the likelihood of sustainability investments, seemingly shows the spillover effect dominates the competition. When we apply the multi-stage approach, which incorporates competitive interaction, we provide empirical evidence that the effect of competition on the likelihood of entry into the sustainability market dominates the effect of spillover. We find that strategic motives, typically ignored in the empirical literature, appear to be an important factor in understanding sustainability-related decisions.

Sustainability has become a significant concern worldwide in recent decades. There seems to be implicit competition among firms for better sustainability performance. Like any other firm activity, sustainability undertakings require resources and their efficient use to achieve the desired performance. Firms may hesitate to undertake sustainability initiatives due to the underlying costs, leading to the question of how efficient they are in their sustainability practices. Relying on data from CSRHub and COMPUSTAT, we employed data envelopment analysis to evaluate the sustainability efficiency of 1141 large U.S. manufacturing firms from 2009 to 2018. We measured the sustainability efficiency of each firm relative to those on the efficient frontier for all the firms in our sample and also separately for each industry. The analysis results indicate that firms’ sustainability efficiency varies across years and industries. Furthermore, we show a quadratic relationship between sustainability performance and sustainability efficiency. This finding implies a process that begins with firms struggling to streamline their sustainability efforts and decreasing their efficiency as sustainability performance increases. Sustainability efficiency starts increasing only after a certain threshold is reached in sustainability performance. Our findings offer valuable insights for firms and stakeholders in their efforts to achieve desired levels of sustainability efficiency.