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The effectiveness of product replenishment and responsiveness of customer service delivery impact largely on satisfaction and retention of customers in retail chain logistics distribution. The fast moving goods in the complex delivery network and limited vehicle resource often lead to long customer waiting time in stock replenishment. With lack of literature systematically reviewing factors affecting retail distribution in inter-store stock transfer services and improving the operations, the purpose of this paper is to analyse and enhance this service for the retail to reduce customer dissatisfaction by developing an integrated quality service improvement methodology and an optimisation tool to improve the product delivery services.

This paper reviews inter-store stock transfer operations and the process capability of an international retail chain, and proposes improvements by integrating Six Sigma, factor analysis, and optimisation modelling. User experience and expectations are evaluated through an empirical survey. A novel principle component factored inter-store stock transfer model is developed to improve replenishment operations. A total of 11 factors affecting inter-store stock transfer delivery time are analysed. An extended model with principal component factors incorporated is developed for the simulation.

The C_pk value of 0.51 shows significant difference between the experienced and expected waiting time. With the inter-store stock transfer optimisation model developed, the model assists traffic personnel on the vehicle route planning with multiple pick-up and drop-off locations. The system also ensures the best routing with a minimal travelling time planned, facilitating a reduction of the inter-store stock transfer time, thus improving the customer waiting time. Four significant factors affecting the delivery time are also identified from exploratory and confirmatory factor analysis. The results are analysed with an extended principal component factored inter-store stock transfer model.

The developed inter-store stock transfer models minimise stock transfer time, increase customer satisfaction, and reduce loss of sales. An integrated service quality improvement methodology has been developed and applied in reviewing significant factors affecting inter-store stock transfer operations.

This paper presents an analysis on inter-store stock transfer operations of an international retail and proposes enhancements on the operations by integrating Six Sigma, factor analysis, and optimisation modelling. A novel principal component factored inter-store stock transfer model is developed to improve the stock replenishment operations.

In order to achieve competitive advantage over the physical marketplace, the e-retailers are insisted on endowing with lenient return policies. The piece-wise returns-and-reordering process incurs excessive buffering and unwanted logistics costs which raises overall fulfillment charges. The objective of this study is to re-design e-retail distribution policy by providing temporal storage at logistics service provides' (LSP) location. The impact of recurrent returns on pricing and profit margins are also investigated over time continuum.

A framework is developed to reduce the non-value added (NVA) storage and distribution efforts by providing collaborative buffering between LSP and e-retailer. The knapsack based buffering approach is tested and compared with traditional e-retail distribution practices. The revenue sharing concept is mathematically modelled and implemented in GAMS, which finally validated through multiple return scenarios.

The proposed model outperforms the existing one under all scenarios with different configuration settings of re-ordering, profit margins, and buffer time windows. The distribution cost is found, linearly related to the necessary product buffering space. The findings help to re-design sustainable return policies for individual products so that maximum customer value can be yield with minimum costs.

This study helps to determine the NVA efforts incurred while storing and delivering multi-time returned products to ensure desired service levels. The revenue sharing model provides pricing strategies for e-retail practitioners deciding which product should store in what quantity for how much time at the shipping agency location so that it fulfils the re-ordering at least waiting and sufficient buffering.

The proposed model extends the role of LPSs as temporary buffer providers to reduce returns-and-reordering fulfilment efforts in the e-retail network. This Collaborative framework offers an opportunity to amend the distribution contracts and policies time by time that enhances e-retailer's performance and customer satisfaction.

Current online business development redistributes last-mile logistics (LML) from consumer to retailer and producer. This paper identifies how empirical LML research has used and defined logistic performance measures for key grocery industry actors. Using a multi-actor perspective on logistic performance, the authors discuss coordination issues important for optimising LML at system level.

A semi-systematic literature review of 85 publications was conducted to analyse performance measurements used for effectiveness and efficiency, and for which actors.

Few empirical LML studies exist examining coordination between key actors or on system level. Most studies focus on logistic performance measurements for retailers and/or consumers, not producers. Key goals and resource utilisations lack research, including all key actors and system-level coordination.

Current LML performance research implies a risk for sub-optimisation. Through expanding on efficiency and effectiveness interplay at system level and introducing new research perspectives, the review highlights the need to revaluate single-actor, single-measurement studies.

No established scientific guidelines exist for solving LML optimisation in the grocery industry. For managers, it is important to thoroughly consider efficiency and effectiveness in LML execution, coordination and collaboration among key actors, avoiding sub-optimisations for business and sustainability.

The study contributes to current knowledge by reviewing empirical research on LML performance in the grocery sector, showing how previous research disregards the importance of multiple actors and coordination of actors, efficiency and effectiveness.

Preface The functions of business divide into several areas and the general focus of this book is on one of the most important although least understood of these—DISTRIBUTION. The particular focus is on reviewing current practice in distribution costing and on attempting to push the frontiers back a little by suggesting some new approaches to overcome previously defined shortcomings.

Professor Rosenberg argues that, in the US at least, the traditional department store, faced with rising expenses, is in danger of becoming the victim of the ‘wheel of retailing’ hypothesis. In order to survive, running costs may have to be cut by 10%; one way is to re‐appraise the role of physical distribution — or retail logistics as it is described in the States.

All the evidence from retail companies who have invested in recent years in the computer field is that it is the inventory‐intensive businesses that can benefit the most. This article summarises what management's attitude should be to the potentialities of the computer, and includes three case studies of American companies. Gamma Telecommunications is a recently formed company which developed out of Gamma Associates, an established British consultancy specialising in minicomputers, and AW Consultants, an American company.

Airlines all over the world are facing financial stringencies. Capital costs for equipment replacement have skyrocketed. The operational costs have been increasing due to fuel costs, landing costs, wages and salaries etc. The growth of traffic and revenue receipts have been lagging behind forecasts. Hence, cash surplus generated by the airlines have dwindled. Some airlines even have run into working capital problems. All these developments seem to indicate that the airlines of the world have to seek new avenues of economising and cost control. One such area seems to be materials planning and provisioning.

The purposes of this paper are to propose a different profitability metric (i.e. anchor category profits) at the category level based on the concept of anchor categories and to illustrate how such a metric can be calculated in field settings to offer a balanced view of profit structure from both the accounting and marketing perspectives.

First, the concept of anchor categories is developed drawing on anchor effects theory and automatic cognitive processing theory. Based on anchor categories, this paper proposes a formula for calculating anchor category profits. Using the data collected with a survey instrument, this paper calculates accounting profits and anchor category profits for two grocery stores.

The intra-store analysis of accounting profits and anchor category profits reveals that the two profit measures project different profit contribution patterns by product categories for each store. The inter-store analysis provides quite different, yet useful information about profit structures for the two grocery stores. Although the two stores are similar in terms of accounting profits, their anchor category profits show different pictures regarding profit contribution patters by product categories between the two stores, revealing that different categories attract customers to different stores.

Comparing accounting profits and anchor category profits allows retail managers to identify traffic generator categories and cash generator categories, which helps retail managers develop more effective category management to increase storewide profits.

This paper increases understanding of the relationship between product categories and store choice behavior by offering a theoretical rationale to explain why some product categories influence consumers’ store choice. This paper also proposes anchor category profits as a more implementation-friendly category-level profitability metric that combines accounting principles with consumers’ shopping trip planning behavior.

With the increasing awareness of global warming and the important role of last mile distribution in logistics activities, the purpose of this paper is to build an environmental and effective last mile distribution model considering fuel consumption and greenhouse gas emission, vehicle capacity and two practical delivery service options: home delivery (HD) and pickup site service (PS). This paper calls the problem as the capacitated pollution-routing problem with pickup and delivery (CPRPPD). The goal is to find an optimal route to minimize operational and environmental costs, as well as a set of optimal speeds over each arc, while respecting capacity constraints of vehicles and pickup sites.

To solve this problem, this research proposes a two-phase heuristic algorithm by combining a hybrid ant colony optimization (HACO) in the first stage and a multiple population genetic algorithm in the second stage. First, the HACO is presented to find the minimal route solution and reduce distribution cost based on optimizing the speed over each arc.

To verify the proposed CPRPPD model and algorithm, a real-world instance is conducted. Comparing with the scenario including HD service only, the scenario including both HD and PS option is more economical, which indicates that the CPRPPD model is more efficient. Besides, the results of speed optimization are significantly better than before.

The developed CPRPPD model not only minimizes delivery time and reduces the total emission cost, but also helps logistics enterprises to establish a more complete distribution system and increases customer satisfaction. The model and algorithm of this paper provide optimal support for the actual distribution activities of logistics enterprises in low-carbon environment, and also provide reference for the government to formulate energy-saving and emission reduction policies.

This paper provides a great space for the improvement of carbon emissions in the last mile distribution. The results show that the distribution arrangement including HD and PS services in the last mile adopting speed optimization can significantly reduce the carbon emission. Additionally, an integrated real-world instance is applied in this paper to illustrate the validity of the model and the effectiveness of this method.