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The study aims to explore and develop a smart route planning system for the cross-docking delivery operations of a large supermarket chain using an action research (AR) approach and assessing through a design science research (DSR) lens.

This study took a problem-solving AR (PAR) approach toward the delivery operational issue of the case firm. The research process has accorded with the solution incubation and the refinement phases defined by a DSR framework. An intervention-based research framework for DSR is developed to assess the validity of this study as a DSR research and derive mid-range theories.

Dramatic operational and financial improvements were achieved for the case firm. Significant and unintended environmental and social benefits were also found. A design proposition (DP) and several mid-range theories are proposed as an extension of AR research to DSR research.

A problem-solving DSR research can be better assessed by the intervention-based DSR framework developed in this study. DSR studies should be encouraged for both practical and theoretical advancement purposes.

A challenging business problem-solving study can be tackled effectively through an industry/academic collaboration taking a PAR approach to deliver substantial values and organization transformational results.

Drivers and store associates are safer with smart delivery operations in the case firm.

There are still limited PAR design science case studies in the supply chain/logistics research literature. The research experience and findings gained from this study provide more insights toward how this type of research can be conducted and assessed.

The adoption of efficient consumer response (ECR) has been slow in many regions, despite its many potential benefits to supply chain participants through reduction of inventory level and operating costs. There has not been any well‐developed theory that can explain this slow uptake. Argues that the inherent characteristics of ECR have actually created barriers to its own adoption. As an inter‐organisational system (IOS), ECR adoption requires co‐operation and trust between trading partners, which are unlikely to happen unless costs, benefits and risks of ECR implementation can be mutually shared. Shows, using a case study conducted within one supply chain, that an unequal distribution of costs, benefits and risks among manufacturer, distributor and retailer is inherent in the implementation of cross‐docking, which typifies the overall ECR program. The findings of this study lead to a new direction in understanding the barriers to adoption of ECR and IOS in general.

The objective of this paper is to examine the impact of cross-docking on the retail out of stock (OOS).

The research is based on a three-phase Delphi study consisting of a seeding/literature review phase, a pre-testing phase and a three-round Delphi study. The Delphi study used in this paper brings together leading supply chain management experts with leading academics.

The findings of the paper show that cross-docking may impact the retailers OOS drivers positively or negatively. The study demonstrates that cross-docking has a negative impact on ordering, placement, delivery, handling, DC handling and receipt. On the other hand, cross-docking has a positive effect on supplier ordering. Finally, academics and supply chain managers disagreed on the effect of cross-docking on the promotions driver. Academics consider that cross-docking has a positive impact on promotions OOS driver, while supply chain managers believe the opposite.

The Delphi study was administrated to supply chain managers from a single major FMCG company, which is a supplier of grocery retailers. By including supply chain managers from the retailers' side, more perspectives on the impact of cross-docking on the OOS drivers can be investigated.

The study develops an original instrument to investigate the impact of cross-docking on OOS drivers. This is the first scholarly work to investigate the relationship between a distribution strategy and the OOS drivers.

The technique of cross-docking is attractive to organisations because of the lower warehousing and transportation (consolidated shipments) costs. This concept is based on the fast movement of products. Accordingly, cross-docking operations should be monitored carefully and accurately. Several factors in cross-docking operations can be impacted by uncertain sources that can lead to inaccuracy and inefficiency of this process. Although many papers have been published on different aspects of cross-docking, there is a need for a comprehensive review to investigate the sources of uncertainties in cross-docking. Therefore, the purpose of this paper is to analyse and categorise sources of uncertainty in cross-docking operations. A systematic review has been undertaken to analyse methods and techniques used in cross-docking research.

A systematic review has been undertaken to analyse methods and techniques used in cross-docking research.

The findings show that existing research has limitations on the applicability of the models developed to solve problems due to unrealistic or impractical assumption. Further research directions have been discussed to fill the gaps identified in the literature review.

There has been an increasing number of papers about cross-docking since 2010, among which three are literature reviews on cross-docking from 2013 to 2016. There is an absence of study in the current literature to critically review and identify the sources of uncertainty related to cross-docking operations. Without the proper identification and discussion of these uncertainties, the optimisation models developed to improve cross-docking operations may be inherently impractical and unrealistic.

The cost of pharmaceutical supply chain due to drug waste is one of the current major issues in health care. Drug waste associated with intravenous (IV) fluid form of medication is one of the crucial issues for many pharmacies. The purpose of this paper is to apply a cross-docking model to minimize the IV delivery lead time to reduce drug waste by scheduling staff in a local hospital’s inpatient pharmacy.

A mixed integer linear programming model is applied to the IV delivery system of a hospital. The parameters are selected based on the observations made in the inpatient pharmacy.

The result implies that cross-docking approach can be effectively applied to IV delivery system. In fact, the cross-docking optimization model employed in this case study reduces the IV delivery completion time of the inpatient pharmacy by 41 percent.

The scope of this research is limited to the activities performed after IV preparation.

The application of cross-docking system in staff scheduling will be beneficial for health care organizations that aim to minimize medication waste.

The prime value of this study lies in the introduction of a cross-docking concept in an internal hospital ordering process. Cross-docking models are widely used in general supply chain systems; however, their application for specific activities inside hospitals is the novelty of this study, which can fill the research gap in terms of drug waste management within the inpatient pharmacy.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

Collaborative Logistics (CL) and merging operations are crucial strategies for reducing costs and improving service in transportation companies. This study proposes a model for optimizing efficiency in supply chain networks through inbound and outbound Collaborative Logistics implementation among the carriers in centralized, coordinated networks with cross-docking.

A mixed-integer non-linear programming model is developed to determine the optimal truck-goods assignment while gaining economies of scale through mixing multiple less-than-truckload (LTL) products with different weight-to-volume ratios. Unlike the previous studies that have considered Collaborative Logistics from the cost and profit-sharing perspective, the proposed model seeks to determine an appropriate form of Collaborative Logistics in the VRP.

This article shows that in a three-echelon supply chain consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. This approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of collaborative logistics among the carriers was discussed. In a three-echelon SC consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. Using a combination of experimental analysis and optimization process, it was recommended that managers be cautious that too much (full or complete) or no collaboration can result in SC performance deterioration.

The suggested approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of Collaborative Logistics among the carriers was discussed.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

Exel Logistics’ experience in a number of industry sectors, product profiles, operational techniques and technology suggests that the outputs of cross‐docking can appear magical, even though they result from fairly standard operational inputs. Explains the origins of cross‐docking and explores the operational aspects of switching from a traditional stockholding supply chain system to a cross‐docking system, using a case study from the motor industry. States that key benefits resulting from the adoption of cross‐docking techniques relate to improvements in service levels, inventory levels, stock returns and unit costs.

The purpose of this paper is to investigate the costs/benefits of implementing the cross-docking strategy in a retail supply chain context using a cost model. In particular, the effects of using different typologies of cross-docking compared to traditional warehousing are investigated, taking into consideration an actual case study of a fast-moving consumer goods (FMCG) company and a major French retailer.

The research is based on a case study of an FMCG company and a major French retailer. The case study is used to develop a cost model and to identify the main cost parameters impacted by implementing the cross-docking strategy. Based on the cost model, a comparison of the main cost factors characterizing four different configurations is made. The configurations studied are, the traditional warehousing strategy (AS-IS configuration, the reference configuration for comparison), where both retailers and suppliers keep inventory in their warehouses; the cross-docking pick-by-line strategy, where inventory is removed from the retailer warehouse and the allocation and sorting are performed at the retailer distribution centre (DC) level (TO-BE1 configuration); the cross-docking pick-by-store strategy, where the allocation and sorting are done at the supplier DC level (TO-BE2 configuration); and finally a combination of cross-docking pick-by-line strategy and traditional warehousing strategy (TO-BE3 configuration).

The case study provides three main observations. First, compared to traditional warehousing, cross-docking with sorting and allocation done at the supplier level increases the entire supply chain cost by 5.3 per cent. Second, cross-docking with allocation and sorting of the products done at the retailer level is more economical than traditional warehousing: a 1 per cent reduction of the cost. Third, combining cross-docking and traditional warehousing reduces the supply chain cost by 6.4 per cent.

A quantitative case study may not be highly generalisable; however, the findings form a foundation for further understanding of the reconfiguration of a retail supply chain.

This paper fills a gap by proposing a cost analysis based on a real case study and by investigating the costs and benefits of implementing different configurations in the retail supply chain context. Furthermore, the cost model may be used to help managers choose the right distribution strategy for their supply chain.