Green supply chain management and product innovation both have become sources of competitive advantage for companies from different industries. However, research on the configuration of green supply chains for new products represents a comparably new trend. In this paper, a goal programming approach is suggested to optimise the supply chain (SC) configuration for a new consumer product under consideration of economic and environmental criteria. The approach is illustrated by the case example of a fast moving consumer goods manufacturer. In this context, trade-offs between the ecologic factor of carbon emission, on the one hand, and financial value creation and customer service level on the other hand, are assessed in the deterministic analyses. The influence of long-term demand uncertainties is modelled in a scenario approach. It is observed that decentralised SC configurations enable carbon emission reduction without deteriorating the economic SC performance. Furthermore, it is detected that a focused economic optimisation strongly amplifies negative environmental impacts of demand uncertainties.

Sustainable operations and sustainable supply chain management (SSCM) have become a highly relevant topic for scientific research and management, as well as policy-making practice. Despite surging growth in extant research, the need for theoretical and conceptual substantiation persists, and large opportunities for further research remain unexploited. This paper responds to the need for a conceptual foundation and, therefore, aims at providing a structured agenda for future research areas in SSCM. Based on an abductive reasoning approach, SSCM constructs and concepts are gathered from existing literature and recombined into a comprehensive conceptual SSCM framework. Areas and directions for future SSCM research, as suggested in earlier studies, are summarized, positioned in the framework, and outlined to stimulate further SSCM research activities. To overcome the lack of holistic research in the field, sophisticated techniques and integrated systems to support decision-making are required to tackle related issues’ complexity. Therefore, this paper’s contribution lies in the synthesis of state-of-the-art literature to provide a more comprehensive view of SSCM. Researchers may find promising recommendations and a suitable foundation for future studies, while practitioners may find helpful orientation and guidance for decision- and policy-making.

The Industry 4.0 (I4.0) concept paves the way for the circular economy (CE) as advanced digital technologies enable sustainability initiatives. Hence, I4.0-driven CE-oriented supply chains (SCs) have improved sustainable performance, flexibility and interoperability. In order to smoothly embrace circular practices in digitally enabled SCs, quantitative techniques have been identified as crucial. Therefore, the intersection of I4.0, CE, supply chain management (SCM) and quantitative techniques is an emerging research arena worthy of investigation. This article presents a bibliometric analysis to identify the established and evolving research clusters in the topological analysis by identifying collaboration patterns, interrelations and the studies that significantly dominate the intersection of the analysed fields. Further, this study investigates the current research trends and presents potential directions for future research. The bibliometric analysis highlights that additive manufacturing (AM), big data analytics (BDA) and the Internet of Things (IoT) are the most researched technologies within the intersection of CE and sustainable SCM. Evaluation of intellectual, conceptual and social structures revealed that I4.0-driven sustainable operations and manufacturing are emerging research fields. This study provides research directions to guide scholars in the further investigation of these four identified fields while exploring the potential quantitative methods and techniques that can be applied in I4.0-enabled SCs in the CE context.