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The purpose of this paper is to extend existing and motivate future sustainable supply chain management (SCM) and logistics research by examining a structure-conduct-performance framework linking resource commitment to sustainable SCM, reverse logistics, and operational performance. A sustainable reverse logistics capability is investigated as mediating the performance benefits associated with resource commitments to sustainable SCM.

Survey methods and structural equation modeling were used to collect and analyze data from 180 supply chain professionals.

The results of a mediated model suggest that resource commitments may be used to develop a sustainable reverse logistics capability, reducing the environmental impact of reverse logistics activities. A strong sustainable reverse logistics capability results from resources committed specifically to sustainable reverse logistics and a commitment to the sustainability of the supply chain.

This study applied a purposefully general sampling procedure. Specific industries may have additional constraints (e.g. risk, transparency, governance factors) that directly impact reverse logistics. These constraints are limitations of the study as well as opportunities for future research. Resource commitment is critical to the success of an overall firm strategy to build a sustainable supply chain, especially when considering reverse logistics.

As managers examine the benefits of sustainable SCM, they must consider the resources required. For firms engaging in sustainable SCM, developing a sustainable reverse logistics capability is a key success factor for improved performance.

Given the growing acceptance and importance of sustainable SCM, this research provides insights to managers and academics regarding the key mediating role of a sustainable reverse logistics capability when integrated into existing and future supply chain research frameworks and processes.

Journals in business logistics, operations management, supply chain management, and business strategy have initiated ongoing calls for Big Data research and its impact on research and practice. Currently, no extant research has defined the concept fully. The purpose of this paper is to develop an industry grounded definition of Big Data by canvassing supply chain managers across six nations. The supply chain setting defines Big Data as inclusive of four dimensions: volume, velocity, variety, and veracity. The study further extracts multiple concepts that are important to the future of supply chain relationship strategy and performance. These outcomes provide a starting point and extend a call for theoretically grounded and paradigm-breaking research on managing business-to-business relationships in the age of Big Data.

A native categories qualitative method commonly employed in sociology allows each executive respondent to provide rich, specific data. This approach reduces interviewer bias while examining 27 companies across six industrialized and industrializing nations. This is the first study in supply chain management and logistics (SCMLs) to use the native category approach.

This study defines Big Data by developing four supporting dimensions that inform and ground future SCMLs research; details ten key success factors/issues; and discusses extensive opportunities for future research.

This study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research.

Supply chain managers are provided with a peer-specific definition and unified dimensions of Big Data. The authors detail key success factors for strategic consideration. Finally, this study notes differences in relational priorities concerning these success factors across different markets, and points to future complexity in managing supply chain and logistics relationships.

There is currently no central grounding of the term, dimensions, and issues related to Big Data in supply chain research. For the first time, the authors address subjects related to how supply chain partners employ Big Data across the supply chain, uncover Big Data’s potential to influence supply chain performance, and detail the obstacles to developing Big Data’s potential. In addition, the study introduces the native category qualitative interview approach to SCMLs researchers.

Researchers have examined the influence of the factors on reducing return rates in retailing over the years. However, the returns experience is often an overlooked way to drive customer engagement and repeat sales in the now ubiquitous omnichannel setting. The focus on returns prevention in existing research overshadows management’s need to understand better the comprehensive mechanics linking the customer in-store return experience with their repurchase actions. Recognizing the need to bridge different stages of the returns management process, this research aims to explore the facilitators and barriers of in-store return activities.

Analysis of customer corporate data from 5,339 returns at the retail level provides insights from the customer return experience. Expanding our theoretical understanding, a deductive research approach then examines how those factors impact customer repurchase intentions both online and at brick-and-mortar stores. Stage two of the study employs a scenario-based role-playing experiment with consumer respondents to test hypotheses derived from signaling theory and justice theory.

Results find that returns policy and loyalty program capabilities are essential in creating a positive customer in-store experience. Moreover, a return experience enhanced by frontline employee service can retain existing shoppers and drive additional store traffic, further stimulating retailer sales.

These findings refine our understanding of returns management in evolving omnichannel retailing and offer practical insights for retailers to manage customer relationships through in-store returns.

The influence of security practices is increasingly common in the supply chain management and logistics literature. However, an under-researched area exists within the logistics service provider (LSP) selection process. The purpose of this paper is to introduce a security capability into the LSP selection process. Specifically, this research seeks to understand partner willingness to compensate and collaborate with service providers that possess a security capability.

Adaptive choice modeling is adopted to assess the influence of a security capability in the LSP selection process. This study represents the first use of this method in supply chain management and logistics research. Cluster analysis is also performed to uncover specific buyer segments along with traditional regression-based significance testing and counting analysis.

The findings indicate that security can have an important influence on the LSP selection process. In particular, the findings note a willingness to pay for a security capability in LSP selection. Applying segmentation techniques to the findings, three LSP buying segments are determined, each placing different importance and value on LSP capabilities.

This research notes an ongoing provider deficiency in security offerings. Partner firms sometimes maintain a cost focus, but others show a willingness to pay higher prices for access to partners with a security capability. Key practitioner findings include the need to include security with other traditional selection variables. The study walks the researcher and manager through the development of segments based on LSP capabilities.

This manuscript investigates logistic service provider selection. The authors detail an advanced form of conjoint analysis, adaptive conjoint modeling, for first time consideration. Additionally, this is the first study to integrate security into the LSP selection process. This is also the first study to identify a willingness to pay for a security capability.

This paper discusses how the features of blockchain technology impact supply chain transparency through the lens of the information security triad (confidentiality, integrity and availability). Ultimately, propositions are developed to encourage future research in supply chain applications of blockchain technology.

Propositions are developed based on a synthesis of the information security and supply chain transparency literature. Findings from text mining of Twitter data and a discussion of three major blockchain use cases support the development of the propositions.

The authors note that confidentiality limits supply chain transparency, which causes tension between transparency and security. Integrity and availability promote supply chain transparency. Blockchain features can preserve security and increase transparency at the same time, despite the tension between confidentiality and transparency.

The research was conducted at a time when most blockchain applications were still in pilot stages. The propositions developed should therefore be revisited as blockchain applications become more widely adopted and mature.

This study is among the first to examine the way blockchain technology eases the tension between supply chain transparency and security. Unlike other studies that have suggested only positive impacts of blockchain technology on transparency, this study demonstrates that blockchain features can influence transparency both positively and negatively.

The purpose of this paper is to create an instrument for conducting future supply chain transparency research by developing and validating a measure of supplier transparency. Specifically, the research develops a two-dimensional measure of supplier transparency that builds on previous studies that independently examine visibility and traceability in supply chain management (SCM)/logistics.

The scale development process is carried out over three stages (item generation, scale purification, scale validation). Survey methods are used with two separate data collection phases involving a total of 358 managers from multiple and diverse industries.

The new supplier transparency measure is a concise, two-dimensional scale that has the potential for significant usage in the development and testing of SCM theory.

This study implemented a purposefully general sampling procedure. However, different industries may have additional, specific constraints regarding what it means to be a transparent supplier. Additional opportunities for future research include applying the new supplier transparency measure to examine supply chain frameworks, regulatory compliance, supply chain relationships and the implementation of information technology.

Firms are under increasing pressure to be transparent about partner sourcing, resource utilization and other transactional issues related to the products and processes in their supply chains. The new measure may be utilized to address these issues as well as the interaction between supply chain operations and stakeholders by facilitating a quantitative assessment of supplier transparency.

Drawing on the established constructs of supply chain visibility and traceability, a measure of supplier transparency is developed, supported by a review of the literature, input from subject matter experts and interviews with supply chain managers. Suggestions are made for future validation of supplier transparency within established supply chain frameworks.

The purpose of this paper is to explore the influence of collaboration and information technology (IT) on the reverse logistics competency of firms. Through collaboration firms can improve their ability to handle returns, but this research introduces IT as providing a moderating influence over the impact of collaboration in the advancement of a reverse logistics competency.

A survey was administered to employees involved with supply chain relationships. Empirical evidence from 267 respondents is analyzed with structural equation modeling.

Support is found for the positive moderating influence of an IT competency on the relationship between collaboration and a reverse logistics competency. Additional benefits for logistics performance are also realized.

This research provides theoretical implications for the development of a reverse logistics competency through an application of resource-based theory/resource-based view of the firm. The study is limited to the selected research questions and sample of predominantly US firms.

This research assists managers as they attempt to develop a reverse logistics competency to address the growing problem of returns through collaboration with supply chain members and the development of an IT competency.

The framework developed in this research provides insights regarding the handling of product returns. Specifically, the moderating influence of an IT competency is addressed as it enhances the impact of collaboration on the development of a reverse logistics competency.

This manuscript develops a reverse logistics monitoring system for controlling reverse flows of materials through marketing channels in emerging economies. Institutional theory is incorporated to show that both positive and negative impacts on environmental sustainability can be predicted. A partner control framework and scales are then developed for use by managers and researchers in furthering their understanding of the effective management of global reverse logistic networks