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The success of closed loop supply chains is contingent upon consumer acceptance of remanufactured products, yet little is known about how consumers value such products. The purpose of this paper is to provide theoretical grounding for understanding consumers’ value perceptions as related to remanufactured products.

Diffusion of innovation theory and customer perceived value literature help form the theoretical model, which is tested empirically using survey data of consumers. Structural equation modeling was employed to test the hypotheses.

Perceived value of remanufactured products is measured as a function of perceived benefits (environmental benefits; price advantage) and perceived sacrifices (perceived quality; perceived risk), all of which are shown to impact perceived value. Additionally, perceived risk is found to partially mediate the relationship between perceived quality and perceived value.

This research makes two significant contributions. First, mid-range theory that is contextualized to the closed loop supply chain is developed to aid researchers and practitioners in better understanding the consumer’s role in the closed loop supply chain, as related to the acceptance of remanufactured products. Second, consumer acceptance of remanufactured products represents a form of supply chain demand risk that has previously been unrecognized. The results provide a foundation for incorporating this type of demand risk in to future research efforts.

Discussion regarding the implications of and antecedents to the decision to outsource manufacturing functions has dominated both the academic literature and popular press for over 30 years. However, economic and competitive landscapes across the globe have changed such that the tenability of outsourcing is being re-evaluated by many organizations. Using the rich body of literature regarding the decision to outsource as a starting point, the purpose of this paper is to investigate the reasons why firms insource and the associated implications thereof.

This case study research captures data from 12 firms in the manufacturing industry that have insourced a previously outsourced function. Data were collected via interviews with executives, researcher observations, and archival records over a nine-month period.

The findings suggest that the primary drivers for insourcing were predominantly the same as those cited for outsourcing. However, insourcing decisions are often made in response to a specific, external trigger event and not necessarily in concert with long-term, strategic goals. This is in contrast to firms’ desires to make more strategic location decisions. The findings also show that insourcing/outsourcing location decisions require continuous evaluation in order to optimize competitiveness and align with long-term firm goals.

This research contributes by not only assimilating and gaining an understanding of key factors affecting insourcing decisions, but also by establishing a baseline for future investigation into this burgeoning area via the presentation of testable propositions.

This paper provides insights for supply chain, logistics, and operations management professionals who seek to better understand the critical factors that should be considered when deciding whether or not to insource.

The benefits of insourcing are being considered to a greater extent across industry, yet there is a dearth of academic or practitioner literature that business leaders and academicians can use as the basis for examining this decision. This research provides both the basis and motivation for developing knowledge in this area of increasing importance.

The global business environment combined with increasing societal expectations of sustainable business practices challenges firms with a host of emerging risk factors. As such, firms seek to increase supply chain transparency, enabling them to monitor operational activities and manage supply chain risks. Drawing on organizational information processing theory, the purpose of this paper is to examine how supply chain analytics (SCA) capabilities support operational supply chain transparency.

Using data from 477 survey participants, hypotheses are tested using seemingly unrelated regression.

The results reveal that: analytics capability in support of planning functions indirectly affects organizational supply chain transparency (OSCT) via SCA capabilities in source, make, and deliver functions; SCA capabilities in source, make, and deliver positively influence OSCT; and supply uncertainty moderates the relationship between SCA capabilities in make and OSCT.

This research suffers from limitations inherent in all survey-based research. Nonetheless, the authors found convincing evidence that suggests firms can employ SCA capabilities to meet transparency requirements.

The findings inform design of SCA systems, noting the importance of linking planning tools with tools that support source, make, and deliver functions. The research also shows how transparency can be increased via employing SCA capabilities.

This is one of first studies to empirically demonstrate that SCA capabilities can be used to increase supply chain transparency. The research also advances organizational information processing theory by illustrating an analytics capability paradox, where increased levels of certain analytics capabilities can become counterproductive in the face of supplier uncertainty.

Big data and predictive analytics (BDPA) has received great attention in terms of its role in making business decisions. However, current knowledge on BDPA regarding how it might link organizational capabilities and organizational performance (OP) remains unclear. Drawing from the resource-based view, the purpose of this paper is to propose a model to examine how information technology (IT) deployment (i.e. strategic IT flexibility, business–BDPA partnership and business–BDPA alignment) and HR capabilities affect OP through BDPA.

To test the proposed hypotheses, structural equation modeling is applied on survey data collected from 159 Indian firms.

The results show that BDPA diffusion mediates the influence of IT deployment and HR capabilities on OP. In addition, there is a direct effect of IT deployment and HR capabilities on BDPA diffusion, which also has a direct relationship with OP.

Through this study, authors demonstrate that IT deployment and HR capabilities have an indirect impact on OP through BDPA diffusion.

The purpose of this paper is to understand how big data and predictive analytics (BDPA), as an organizational capability, can improve both visibility and coordination in humanitarian supply chains.

The authors conceptualize a research model grounded in contingent resource-based view where the authors propose that BDPA capabilities affect visibility and coordination under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the hypotheses using survey data collected from informants at 205 international non-government organizations.

The results indicate that BDPA has a significant influence on visibility and coordination. Further, the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the actors in humanitarian supply chains.

The major limitation of the study is that the authors have used cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that can address common method bias or endogeneity-related problems.

Managers can use this framework to understand: first, how organizational resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to improve visibility and coordination in the humanitarian supply chain.

This is the first research that has empirically tested the anecdotal and conceptual evidence. The findings make notable contributions to existing humanitarian supply chain literature and may be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.

Circular economy (CE) initiatives are taking hold across both developed and developing nations. Central to these initiatives is the reconfiguration of core supply chain management (SCM) processes that underlie current production and consumption patterns. This conceptual article provides a detailed discussion of how supply chain processes can support the successful implementation of CE. The article highlights areas of convergence in hopes of sparking collaboration among scholars and practitioners in SCM, CE, and related fields.

This article adopts a theory extension approach to conceptual development that uses CE as a “method” for exploring core processes within the domain of SCM. The article offers a discussion of the ways in which the five principles of CE (closing, slowing, intensifying, narrowing, dematerialising loops) intersect with eight core SCM processes (customer relationship management, supplier relationship management, customer service management, demand management, order fulfilment, manufacturing flow management, product development and commercialization, returns management).

This article identifies specific ways in which core SCM processes can support the transition from traditional linear approaches to production and consumption to a more circular approach. This paper results in a conceptual framework and research agenda for researchers and practitioners working to adapt current supply chain processes to support the implementation of CE.

This article highlights key areas of convergence among scholars and practitioners through a systematic extension of CE principles into the domain of SCM. In so doing, the paper lays out a potential agenda for collaboration among these groups.