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Integration of the supply chain offers many opportunities to improve customer service and eliminate unnecessary costs. However, many firms lack the capability to determine the cost of moving product to market and where potential savings may exist. Supply chain costing provides an approach for measuring the cost of activities spanning the entire channel. Using cost information to evaluate channel performance has strategic implications regarding the composition and structure, evaluation of performance, and the allocation of benefits within the supply chain. Possessing the capability to improve customer value while targeting opportunities for cost reduction opens new frontiers for supply chain management.

Recycling has experienced rapid growth as a technique to reduce the solid waste stream volume. Despite the public appeal and acceptance of recycling, the reverse logistics channels used in recycling have received minimal attention. However, the reverse channels′ membership and capabilities have a significant impact on the efficiency of processing recyclable material for remanufacture into recycled products. Differing product characteristics, extensive handling, and low density shipments pose considerable obstacles to establishing an efficient reverse channel for recyclable commodities. A framework, based on interviews and current literature, describes the reverse logistics channel structure, membership and functions, and provides a foundation for identifying the issues affecting efficiency and marketability, and possible future directions for improving efficiency within the reverse channel structure.

Imagine the reaction of your company's sales force when you tell them they are losing money selling to Wal‐Mart. To counter their objections, you explain the final delivered product cost exceeds the revenue generated by Wal‐Mart sales. The scenario may seem unrealistic based on the sales volume of mass merchant discounters such as Wal‐Mart, Kmart, and Target; however, manufacturers frequently do not know the cost to serve these merchants or the cost of the functions being shifted backwards in the supply chain. Additional services increase the cost of serving the big retail accounts and jeopardize supplier profitability. While it is understandable that retailers want to lower their costs by eliminating tasks they perform, retailers also need their suppliers to obtain a reasonable margin to ensure the availability of product from a high quality supplier. It is necessary to ensure that selling to these large retail accounts is profitable by determining the costs of serving them.

Most discussions and articles about supply chain metrics are, in actuality, about internal logistics performance measures. The lack of a widely accepted definition for supply chain management and the complexity associated with overlapping supply chains make the development of supply chain metrics difficult. Despite these problems, managers continue to pursue supply chain metrics as a means to increase their “line of sight” over areas they do not directly control, but have a direct impact on their company's performance. We provide a framework for developing supply chain metrics that translates performance into shareholder value. The framework focuses on managing the interfacing customer relationship management and supplier relationship management processes at each link in the supply chain. The translation of process improvements into supplier and customer profitability provides a method for developing metrics that identify opportunities for improved profitability and align objectives across all of the firms in the supply chain.

The purpose of this paper is to analyze previous grounded theory articles and, based on this analysis, to provide a framework to assist reviewers in evaluating grounded theory research and increasing the rigor and credibility of this methodology in logistics and supply chain journals.

An analysis of existing articles appearing in the leading logistics and supply chain journals combined with an extensive review of the grounded theory method literature were used to develop a comprehensive framework for evaluating grounded theory research.

The paper finds that no standard criteria for publication of grounded theory research exists in logistics and supply chain journals. Grounded theory is routinely confused with other qualitative methodologies. Overall, this situation leads to publications that do not adequately address or report on the process for developing a grounded theory.

Reviewers can use this paper to establish the quality of grounded theory research. Reviewers who are unfamiliar with or skeptical of the grounded theory method can use the framework to evaluate the rigor and credibility of a grounded theory study rather than rejecting such research. The checklist can be used to provide thorough and constructive reviews to authors.

The paper presents a framework that provides a ready reference for reviewers to assess whether the authors have taken appropriate action in selecting a grounded theory methodology, collecting and analyzing data, developing a theory grounded in the data, and for evaluating their research. Existing research is compared with the framework to identify potential shortcomings in the review process. The application of the framework to the review of future articles provides an opportunity to increase the credibility and rigor of grounded theory research in logistics and supply chain management journals.

Supplier managed inventory (SMI) and vendor managed inventory (VMI) have emerged as potential first steps towards successfully integrating activities and information across multiple firms. Despite the potential benefits, managers interested in these programs often cannot generate the “buy‐in” among fellow management and executives or among those in the collaborative firm. The barriers stem from a misunderstanding of the concepts and an inability to demonstrate their potential effect on shareholder value across both firms. This paper draws a distinction between SMI and VMI and identifies where the approaches should be applied. A simultaneous economic value added (EVA) analysis from the customer and supplier perspectives is proposed as a means to demonstrate the effect on shareholder value, measure performance, and overcome the obstacles confronting implementation.

The majority of studies on supply chain management (SCM) emphasize the importance of cooperative relationships for improving the integration of business processes into a supply chain. It seems accepted that SCM will be a source of competitive advantage if, and only if, firms that participate in it formalize a strategic partnership between each other beforehand. This article questions whether this really is the case, given that the corporate cultures currently in place are largely founded on a tradition of adversarial relationships, the creation of large groups and the development of vertical concentrations. SCM could, in contrast, in such a case be the catalyst for powerful future strategic partnerships that could gently break arm’s‐length competition.

The purpose of this paper is to build on recent efforts occurring within business-to-business (B2B) marketing research to advance methodological developments. As phenomena within B2B relationships have become increasingly complex, marketing scholars have begun to point out the limitations associated with correlation-based methodological approaches and highlight the need for new developments in this area. One such development is the fuzzy set qualitative comparative analysis (fsQCA).

This study uses a literature review to examine the use of fsQCA in B2B marketing research.

First, the current manuscript presents the benefits that the application of fsQCA can offer to market researchers investigating B2B phenomena. Second, the paper presents the current state of fsQCA use within B2B marketing. Third, it suggests possible marketing B2B research topics that can be explored using fsQCA.

The study highlights the benefits of fsQCA, presents the current state of fsQCA use within B2B marketing and offers a rich future research agenda for B2B marketing scholars. This agenda can also help spur additional method developments in the discipline.

Retail sales usually exhibit strong trend and seasonal patterns. Practitioners have typically used seasonal autoregressive integrated moving average (ARIMA) models to predict retail sales exhibiting these patterns. Due to economic instability, recent retail sales time-series data show a higher degree of variability and nonlinearity, which makes the ARIMA model less accurate. This chapter demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) in forecasting aggregate retail sales. The hybrid forecasting method of integrating EMD and neural network (EMD-NN) models was applied to two real data sets from two different time periods. The one-period ahead forecasts for both time periods show that EMD-NN outperforms the classical NN model and seasonal ARIMA. In addition, the findings also indicate that EMD-NN can significantly improve forecasting performance during the periods in which macroeconomic conditions are more volatile.