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Already for a long time retailers have taken back products. In this paper we explore the factors contributing to the decision of combining vs separating inbound and outbound flows during the return handling process. We do so through a comparative analysis of the operations in nine retailer warehouses, which can be divided into three groups: food retailers, non‐food store chains and mail order companies. We identify both aggravating factors and facilitating actions for return handling. Furthermore, we bring about recommendations for practice. At the end we put forward propositions that are useful in feeding studies on return handling efficiency. In particular, we conjecture over the impact that return volume and product diversity have on the decision for combining vs separating the reverse and forward flows.

The purpose of this paper is to investigate how warehouse management, understood as a cluster of planning and control decisions and procedures, is organized and driven by task complexity (TC) and market dynamics (MD).

A multi‐variable conceptual model is developed based on the literature and tested among 215 warehouses using a survey.

The results suggest that TC and MD are the main drivers of warehouse management, measured by planning extensiveness (PE), decision rules complexity, and control sophistication. Differences between production and distribution warehouses are found with respect to the relationship between assortment changes and PE. Furthermore, TC appears to be a main driver of the specificity of the warehouse management (information) system (WMS).

This paper is based on 215 warehouses in The Netherlands and Flanders (Belgium); future research may test the model on a different sample. More research should be conducted to further validate the measures of the core dimensions of warehouse management.

Different levels of TC and MD characterize warehouses. Such a characterization is a first step in determining generic warehouse functionalities and helping managers to decide on the best software for their warehouse operations.

The paper defines the core dimensions of warehouse management, makes them measurable, tests them and assesses how these drivers impact specificity of WMS. The paper shows that PE in production warehouses is driven by different variables than in distribution centers.

In this paper, the relation between the constructs operational complexity, Web‐based orientation of the company and the company’s distribution structure used for the fulfilment of Internet customer orders is investigated in the food home shopping branch. A model is proposed with relations between these constructs, which is researched through a survey among food e‐tailers. A positive association between operational complexity and the distribution structure used could be established, meaning that more complex operations (with a full‐line assortment and a large number of orders) tend to have special (Internet orders only) distribution centres for the fulfilment of Internet customer orders. Companies with a store infrastructure tend to keep using this existing infrastructure (unless the number of orders becomes large) and new Internet‐only companies tend to use special Internet‐orders only warehouses, unless the number of orders is small, in which case co‐operation with existing stores is preferred.

The purpose of this paper is to compare efficiency scores from the benchmarking exercise with those of previous studies and to discuss the reasons behind diverging results.

This paper uses data envelopment analysis (DEA) on primary data of large container terminals.

The results differ strongly from those available in the literature. Causes for these differences are: public (secondary) data are not always accurate; different terminal types are compared; terminals of different scale are compared; and terminals are mixed with ports.

DEA may be appropriate for container terminal benchmarking, but only if better quality and additional input and output data can be obtained. In its application, the analysis should be controlled for terminal types.

Summary of the state of play in the use of DEA methodologies for comparing the efficiency of container terminals at ports.

Due to the importance of efficiency and responsiveness measures rather than just efficiency measures, this research recognizes both measures when considering overall performance of warehouse operations. Thus, the purpose of this paper is to prioritize overall performance measures associated with warehouse operations in manufacturing, third-party logistics service provider and retail industry supply chains.

The study uses an integrated approach that involves the Q-sort method to group measures into four categories. Fuzzy analytical hierarchy process was then used to prioritize individual performance measures within each category and integer liner programming model was used to validate prioritized categories, using the judgment of multiple decision makers across three industries.

The result shows that the financial category is a dominating performance category in managing warehouse operations across all three industries selected. Within the financial category, cost of insurance accounted for 25 percent of total weight of the category, and is considered to be a powerful measure. The financial category is verified by multiple decision makers across three industries, as the most important performance category.

As part of adopting the proposed methodology in practice, it needs to be guided by overall methodology appropriate for industry-specific contexts.

Key novel aspects of this study are to categorize warehouse operations measures and analyze their perspectives in different industries, understand dominant categories of warehouse operations measures in the contemporary supply chain and finally to explore to what extent current practices lead to achieving efficiency and responsiveness in the selected industries.

The purpose of this paper is to increase the understanding of how warehouse operations and design are affected by the move toward integrated omni-channels.

A structured literature review is conducted to identify and categorize themes in multi- and omni-channel logistics, and to discuss how aspects related to these themes impact and pose contingencies for warehouse operations and design.

The review revealed a lack of focus on warehouse operations and design in multi- and omni-channels. Instead, most articles published in scientific journals discuss changes in consumer demand and implications for the network level, concerning aspects such as the organization and management of material and information flows, inventory management, resources, actors and relationships. Ten themes in omni-channel logistics were identified and grouped into two categories: the value proposition and channel management; and the physical distribution network design. The themes and related aspects have implications for warehousing, and by combining these with general warehousing knowledge, the authors derive a comprehensive and structured agenda is derived to guide future research on omni-channel warehousing.

This paper outlines a research agenda, including detailed research questions, for advancing the theory on warehouse operations and design in omni-channels.

The agenda can inspire practitioners in their work to understand the upcoming challenges and address relevant issues in omni-channel warehousing, taking into consideration its interdependence with value proposition, channel management and network decisions.

This is the first comprehensive review focusing on and synthesizing available literature on omni-channel warehousing. This topic has until now received limited coverage but is of increasing importance to scholars in the field.

To provide insight into the role and design of delivery services to address CO₂, NO _x , and PM₁₀ emissions from passenger travel.

A simulated North American data sample is served with three transportation structures: last-mile personal vehicles, local-depot-based truck delivery, and regional-warehouse-based truck delivery. CO₂, NO _x , and PM₁₀ emissions are modeled using values from the US EPA’s MOVES model and are added to an ArcGIS optimization scheme.

Local-depot-based truck delivery requires the lowest amount of vehicle miles traveled (VMT), and last-mile passenger travel generates the lowest levels of CO₂, NO _x , and PM₁₀. While last-mile passenger travel requires the highest amount of VMT, the efficiency gains of the delivery services are not large enough to offset the higher pollution rate of the delivery vehicle as compared to personal vehicles.

This research illustrates the clear role delivery structure and logistics have in impacting the CO₂, NO _x , and PM₁₀ emissions of goods transportation in North America.

This research illustrates tension between goals to reduce congestion (via VMT reduction) and CO₂, NO _x , and PM₁₀ emissions.

This chapter provides additional insight into the role of warehouse location in achieving sustainability targets and provides a novel comparison between delivery and personal travel for criteria pollutants.

Warehousing is becoming more and more a critical activity in the supply chain to outperform competitors on customer service, lead times, and costs. However, if warehousing is to be a source of competitive advantage, then the implementation of a warehouse management information system (WMS) is a necessary condition to achieve efficiently the high performance of warehousing operations required in today’s marketplace. A major practical question is then whether a given warehouse should implement a standard or a tailor‐made WMS. A standard WMS offers many advantages; it is a proven solution, it is less costly, the implementation lead time is shorter, and the after‐sales service is better. On the other hand, a standard WMS remains largely making compromises between the way a warehouse wants to work and the way the system allows the warehouse to work. In certain environments, such compromises might seriously degrade warehouse performance, in which case it then seems better to implement a tailor‐made WMS. To answer the above question, we conducted an exploratory field study of warehouses with recently implemented WMSs to first understand the empirical reality and then build up a theory linking the constructs warehouse complexity and warehouse planning and control structure. Warehouse complexity refers to the number and variety of items to be handled, the degree of their interaction, and the number, nature, i.e. technologies used, and variety of processes, determined among others by the warehouse’s position in the logistic chain and the nature of its market. Warehouse planning and control structure refers to the management functions that plan, direct, coordinate and control the flow of goods through the warehouse, from the time of receiving to the time of shipping. It is strongly related to the WMS in use. We found that the number of orderlines to be processed per day and the number of stock‐keeping units are the two main observable aspects of warehouse complexity; that the more complex the warehouse is, the more tailor‐made the planning and control structure should be; that for simple warehouses a standardized planning and control structure suffices; and that the design of a new‐to‐build warehouse should be carried out in close concert with the design of the warehouse planning and control structure.

This paper aims to report a survey carried out among European distribution centres (EDCs) in The Netherlands. EDCs are forerunners in implementing advanced logistics systems, since they are responsible for the distribution of a manufacturer's products to customers in a larger part of Europe, Middle East and Africa, often with strict service level agreements.

Warehouses with different outsourcing relations (own‐account, dedicated outsourced and public outsourced) are compared on operational aspects, performance, and future developments. Moreover, within the group of own‐account warehouses, especially Asian and American operations are tested for differences.

Outsourced warehouse operations appear to have a higher percentage of error‐free deliveries and to be more flexible than own‐account operations. Based on the literature it was expected that a difference in productivity and quality between American and Asian EDCs would be found. Some differences in operations are found. For example, Asian EDCs put more effort in quality methods and involve more native managers. However, significant differences in productivity and quality levels were not found. Apparently, the differences in operations do not have a substantial effect on the warehouse performance.

This paper is a first attempt to compare advanced warehouse operations from different origins, either operated by service providers or not.