Just‐in‐Time Retail Distribution: A Systems Perspective on Cross‐Docking

Cross‐docking is a just‐in‐time strategy for distribution logistics. It is aimed at reducing inventory levels and distribution lead times by creating a seamless flow of products from suppliers to customers. Prior supply chain literature has argued that creating such a seamless product flows requires a holistic view on cross‐docking management, aimed at synchronizing cross‐docking operations at the distribution center with its inbound and outbound network logistics. This paper provides an in‐depth case study illustrating how cross‐docking operations can be managed more holistically in a retail distribution context. A discrete event simulation model has been developed to understand and improve the cross‐docking operations of a large grocery retailer in the Netherlands. The model is used to quantitatively evaluate two proposed changes that exploit opportunities in the design and control of the retailer's distribution network. An extensive real‐world data set is used as input to the model. Overall, the case and simulation results show that a holistic cross‐docking management approach can indeed improve system‐wide performance, which further stresses the importance of making cross‐dock operational decisions making and network decisions together.     

Using the Pack‐and‐a‐Half Rule to Eliminate Backroom Inventories in Retail Operations

In the retail industry, backroom inventories are typically associated with higher labor costs and greater operational complexity. Thus, retailers look for ways to eliminate backroom inventories. A heuristic used for this purpose is the pack‐and‐a‐half rule which suggests that the shelf space allocated for a product should be at least 50% larger than the case pack quantity in which the product is delivered. Despite its popularity among retailers, the pack‐and‐a‐half rule has been ignored in the academic literature. We introduce the pack‐and‐a‐half rule, assess its impact on a retailer's profits, identify cost, demand, and product characteristics driving this impact, and propose a modification. Based on an analysis of data obtained from a retailer on 1,986 SKUs in 20 categories, we find that the pack‐and‐a‐half rule decreases a retailer's profits, on average, by 10% when applied uniformly across all SKUs. Further, this decrease is significantly affected by product depth, product width, demand elasticity, case pack quantity, and inventory carrying cost. Finally, we develop a set of modifications based on these variables where the pack‐and‐a‐half rule is applied selectively and in a stepwise fashion. These modifications limit the decrease in a retailer's profits to a range between 6% and 7%.     

The Informational Role of Manufacturer Returns Policies: How They Can Help in Learning the Demand

Returns policies are usually thought of as being a way to insure retailers against excess inventory. The work of Pellegrini (1986), Chu (1993), Lin (1993) and Padmanabhan and Png (1997) highlights the fact that there is considerably more to returns policies than just a mechanism for insurance. Our work identifies a heretofore undocumented rationale for returns policy: its role in learning the demand for a new product. The model of manufacturer–retailer interaction assumes that the demand is uncertain but correlated across time periods. Thus, its true nature is revealed over time via the realization of sales. The speed of such learning depends on the size of the inventory at the retail level which in turn can be strategically influenced by the manufacturer through a returns policy. In such environments, we show that a returns policy may be a way for the manufacturer to learn the demand of a new product.     

Consistency and Recovery in Retail Supply Chains

Practitioners and researchers describe inventory service level with metrics that communicate the likelihood of demand fulfillment without considering the ongoing capabilities of the supplier, for example, in‐stock and fill rate. We develop a method for measuring inventory service level that incorporates such supplier capabilities, namely consistency (the ability of a supplier to fulfill orders repeatedly) and recovery (the ability of a supplier to fulfill orders after a lapse in service). Using data from two retail supply chains, we illustrate our approach. To demonstrate the impact of consistency and recovery on supply chain performance, we model a retailer purchasing from competing suppliers with different levels of consistency and recovery. The model incorporates the retailer's uncertainty about demand and the retailer's uncertainty about its suppliers' service levels. We characterize how the retailer's orders and profitability change with a supplier's delivery performance through numerical experiments calibrated with field data. We find notable differences in market share across suppliers with similar traditional inventory service level metrics but differences in consistency and recovery. Further, we observe that a retailer can increase its profitability by determining orders via consistency and recovery in lieu of common metrics like in‐stock. Given the influence of consistency and recovery on supply chain outcomes, we discuss implications for practice and future research.     

THE IMPACT OF POINT‐OF‐SALE DATA INACCURACY AND INVENTORY RECORD DATA ERRORS

The presence or absence of error in point‐of‐sale (POS) data and inventory system records directly affects retailer performance. This study identifies various error sources in retail supply chains and studies the influence of inventory and POS (demand) errors in a simulated retail outlet according to fill rate and average inventory. Other things being equal, we find that inventory record error reduces fill rate more than demand error. This study adds further evidence to other studies that suggest the costs caused by errors in POS systems may be overstated.     

The Role of Social Mechanisms in Demand and Supply Integration: An Individual Network Perspective

In many industries, including retail, increased complexity of marketing strategies needs to be met with increased efficiency in product delivery, requiring integration across demand and supply facing functions of the firm. For frontline logistics employees (FLEs) of manufacturing firms who are delivering and marketing products in retail stores daily, the ability to understand both the marketing and supply implications of their actions is essential. Despite the importance of cross‐functional integration at the retail frontline, little logistics research has explored how logistics frontline employees interact with managers and each other to integrate knowledge and information. The purpose of this research is to examine the antecedents to cross‐functional integration across demand and supply functions in multiple social networks of the FLE. Mixed methods, including social network analysis, structural equation modeling, and analysis of variance, are applied to test social capital theory hypotheses regarding the impact of relational embeddedness and social mechanisms, socialization and shared interpretation, on individual demand and supply integration across friendship, key enabler, and ideation networks of the frontline employee.     

LOGISTICS AND ASSORTMENT DEPTH IN THE RETAIL SUPPLY CHAIN: EVIDENCE FROM GROCERY CATEGORIES

Managing the logistical issues resulting from changes in assortment depth in the retail supply chain is challenging, involving various complex tradeoffs. While increasing assortment depth can increase sales, it also increases inventory‐holding costs and reduces the amount of space for other items. As space is taken from existing items to increase assortment depth, it reduces the inventory‐holding capacity of existing items on the shelf, increasing expected annual cost of lost sales. The paper presents a conceptual model of the relationships between assortment depth, category gross margins, and the logistical concerns resulting from inventory costs and out‐of‐stocks. Evidence for the significance of depth and resulting costs are provided in an examination of 100 product categories from a case study of a retail grocery chain.     

Cross-channel effects of omnichannel retail marketing strategies: A review of extant data-driven research

The authors review 50 empirical retailing research papers that have appeared over the last 20 years to take stock of what we know, need to know better, and do not know yet about within-retailer cross-channel effects of omnichannel retail marketing strategies on (a) consumer responses over their purchase journeys, i.e., online and/or offline search, purchase intention, frequency, amount, returns, loyalty, and (b) the retail firm's aggregate outcomes (e.g., sales, costs, profits, product returns) by channel and overall. Specifically, the authors focus on five strategies: (1) the addition of online channel by an offline retailer; (2) the addition (or subtraction) of offline channels by an online retailer; (3) addition of mobile shopping channel (website and/or app) by offline and/or online retailer; (4) cross-channel integration strategies; and (5) retail marketing mix strategies. The author/s integrate findings from empirical research on these strategies into a number of ‘insights’ about ‘what we know’. Prominent among these are the following: Adding a transactional online channel to an offline channel improves the retailer's overall sales even though offline channel sales can be cannibalized to some degree. Adding an offline channel by an online retailer, however, boosts online channel sales as well as overall sales of the retailer. Similarly, adding a mobile shopping channel usually increases customer purchase frequency and amount and overall sales of the retailer in the long-term. Strategies for greater cross-channel integration generally have a positive effect on a retailer's overall performance while online advertising has positive effects on offline channel consideration and sales as well as overall sales of a multichannel retailer. Other insights or findings that need further study or open questions are also identified. The paper closes with managerial implications of the derived empirical insights, and suggestions for future research.     

PRODUCT FULFILLMENT IN SUPPLY CHAINS SUPPORTING INTERNET‐RETAILING OPERATIONS

Customer service, based on economical logistics operations across the supply chain, is key to the realization of sustainable levels of profitability in Internet retailing. Concentrating on inventory and product‐release operations, an empirical simulation model suggests that inventory centralization and market demand growth positively affect the level of cost‐effective service received by online shoppers. The results also show that under increasing demand levels, Internet retailers can provide optimal service to consumers by fulfilling orders through inventories located at their own facilities and avoid relying on inventories held elsewhere in the supply chain.     

The Retailer's Perspective on the Link Between Logistical Resources and Perceived Customer Loyalty to Manufacturer Brands

The objective of this study was to investigate the relationships between logistics and brand‐related resources, and assess their impact on the retailer's perceptions of customer loyalty to manufacturer brands. On the basis of theoretical underpinnings of the resource‐based view, this study explores the relationships among four main variables: (1) variety of collaborative logistics technologies shared between retailers and manufacturers, (2) manufacturer's logistics operations quality provided to retailers, (3) retailer's brand differentiation orientation, and (4) retailer's perceptions of customers loyalty to manufacturer brands. An online survey was conducted on 313 senior marketing and supply chain managers from retailer firms. The results of the structural equation analysis support a mediated relationship between logistical resources and perceived loyalty to manufacturer brands. The retailers believe that shared logistics technologies enable manufacturers and retailers to offer higher levels of availability and visibility of preferred brands to their end‐user customers. In turn, the end‐users become more confident with their decisions to repurchase the same brand offerings.     

Retailers’ Price Positioning and the Motivational Profiling of Store‐Brand Shoppers: The Case of Spain

In recent years, retailers have worked to advance store‐brand strategies, leading to greater success and higher congruence with the retailer's positioning. In this new competitive context, this research aims to characterize store‐brand shoppers in terms of motivation and benefits sought, as well as analyze, on the basis of congruence theory, the moderating role of a retailer's price positioning on store‐brand shopper characterizations. The empirical study combines survey and household panel information related to leading retailers in Spain; the findings reveal that store‐brand shoppers are motivated by their price sensitivity, whereas they are less sensitive to service quality and name brands. However, the retailer's price positioning exerts a moderating effect on shopper profiles: In less price‐oriented retail chains, store‐brand purchases seem motivated less by price and more by quality, brand awareness, and brand reputation.     

DOCTORAL RESEARCH IN SUPPLY CHAIN MANAGEMENT AND/OR LOGISTICS‐RELATED AREAS: 1999–2004

A total of 410 entries from Dissertation Abstracts have been identified and annotated in this fourth compendium of supply chain management (SCM) and logistics‐related dissertations. Findings relating to this latest study period (1999–2004) are presented and comparisons made to previous compendiums covering 1970–1986, 1987–1991, and 1992–1998. A larger number of colleges and universities are granting degrees in SCM and logistics‐related areas and some “new players” have entered the marketplace, resulting in an upward growth trend in the absolute number of dissertations being published since the early‐1990's. Some traditionally strong institutions have maintained their position in terms of the number of SCM and logistics‐related dissertations published, while others have reduced their outputs. Areas of SCM, decision support systems, inventory management and miscellaneous transportation (models, networks, policy issues, routing & scheduling) topics are the most popular dissertation areas, while traditional transportation, warehousing and storage, DRP, JIT, Kanban, and MRP topics are being researched to a much lesser degree. Engineering logistics, human resources, location analysis, order processing and information systems, packaging, and TQM remain areas with low research interest at the doctoral level.     

How inventory management systems mistreat retail project quantity items and other bimodally distributed products

To insure appropriate inventory levels in retail outlets, replenishment managers concern themselves with both timing of shipments and quantity of product available within the store. While organizations regularly use inventory management or enterprise resource planning systems to procure inventories, we find that these systems can incorrectly manage a sizable group of products found within retail organizations. To illustrate, we explore a collection of goods called retail project quantity items, subsequently explaining how customers purchase and use these items in a fashion that leads to a bimodal distribution of demand. We then employ simulations to demonstrate how the use of a bimodal lead-time demand distribution, rather than a normal or Poisson distribution, improves respective product service levels. Based on these results, we offer a modified reorder point heuristic and discuss how inventory managers should alter existing replenishment processes to insure sufficient stocks of retail project quantity items. Lastly, we discuss broader implications for inventory management systems and bimodally distributed products.     

Integrated planning for product selection,shelf-space allocation,and replenishment decision with elasticity and positioning effects

As the retail industry is growing larger and more diversified, retailers' decisions about product selection, shelf-space-allocation, and replenishment become more important and challenging. This paper is to present a model for shelf-space allocation with product selection and replenishment decisions to maximize the retailer's profit. The model is based on a two-dimensional display space in which all shelves and products have widths and heights and includes factors that influence demand for each product, such as space and cross-space elasticities and positioning effects. The integrated model presented is mixed-integer non-linear programming (MINLP) because the demand function is non-convex. This research proposes two heuristic algorithms (tabu search and genetic) to solve the MINLP problem. The results show the effectiveness and efficiency of these algorithms by comparing the outputs to the MINLP optimal solution for small data sets and comparing the algorithm performances for large data sets. The solution methodologies expect to support a simultaneous decision-making process for retailers to maximize their revenue.     

Trade Logistics in Developing Countries: The Case of the Middle East and North Africa

This paper presents an analysis of obstacles facing exporting firms in developing countries by diagnosing the efficiency of trade logistics in the Middle East and North Africa region (MNA). Using logistics chain analysis for six export commodities, it presents evidence that transport and non‐transport logistics costs for export commodities from the MNA region are quite substantial, ranging from 7–25 per cent of landed product prices. Underlying these costs are key bottlenecks identified as: inefficient trucking and transport services, low export volume leading to long shipping times and the need for costly inventory accumulation, aggressive, obstructive customs authorities and procedures, low and inconsistent product quality, an underdeveloped transport intermediary sector, inefficient cross‐border transit procedures and others. Recommended actions to address developing a national transport policy, overhauling the regulatory regime for the trucking sector, export promotion measures, increasing competition in port and air freight services, reorienting customs authorities towards trade facilitation and developing cross‐border transit procedures similar to the TIR Carnets model.     

SWARM INTELLIGENCE: APPLICATION OF THE ANT COLONY OPTIMIZATION ALGORITHM TO LOGISTICS‐ORIENTED VEHICLE ROUTING PROBLEMS

This research evaluates a set of logistics‐oriented vehicle routing problems (VRP) taken from the logistics and supply chain literature under the widely used Clark‐Wright Savings algorithm and the newer metaheuristic method employing a type of swarm intelligence called Ant Colony Optimization (ACO). ACO simulates the decision‐making processes of colonies of ants as they forage for food and is related to other artificial intelligence techniques such as Tabu Search, Simulated Annealing and Genetic Algorithms. Experimentation shows that ACO is successful in finding solutions near the best‐known solutions for problems with up to 20 demand locations. In addition, testing for the affect of spatial patterns suggested by the logistics literature for facility locations appears to make a difference in the quality of the solutions for the two algorithms. Finally, ACO is shown to be superior to the savings algorithm found in software packages and as a result should be tested on even larger, more complex logistics‐oriented vehicle routing problems, representative of those encountered in larger industrial and retail settings.     

CONSUMER DIRECT FULFILLMENT PERFORMANCE IN INTERNET RETAILING: EMERGENCY TRANSSHIPMENTS AND DEMAND DISPERSION

The collaborative fulfillment of consumer orders by Internet retailers and wholesalers has proven important in the realization of sustainable levels of online profitability. Concentrating on consumer direct fulfillment (or drop shipping), an empirical simulation model evaluates avenues for improving logistical performance. The empirical simulation model centers on the online music CD retailing industry. It evaluates the effects of emergency transshipments and demand dispersion on inventory and product‐release performance, as well as on transportation costs, in consumer direct fulfillment operations. Results show that emergency transshipments improve inventory and product‐release performance in these operations. Furthermore, the inventory‐performance improvements are maximized when inventory facilities fulfill demand that is uniformly balanced across markets primarily assigned to each facility. Finally, gains in inventory and release performance obtained from emergency transshipments outweigh additional transportation costs incurred from a greater reliance on emergency transshipments for consumer direct fulfillment.     

Disaster‐Relief Logistics With Limited Fuel Supply

Disaster‐relief logistics consists of providing adequate emergency supplies rapidly to the affected people so as to minimize human suffering and death. This study empirically examines the impact that the shortage of fuel, a commonly encountered problem in many disaster situations, can have on the effectiveness of disaster‐relief logistics operations. We focus on investigating the following two issues: (1) whether the shortage of fuel is more damaging in attaining logistical goals than the equivalent‐sized shortage in emergency supplies themselves, and (2) what types of vehicles should be used when the fuel supply is limited. Results suggest that the shortage of fuel may be more damaging than the shortage of emergency supplies, and that smaller trucks may be preferred to larger trucks when the shortage of fuel becomes severe.     

Influences of retail brand trust,off‐line patronage,clothing involvement and website quality on online apparel shopping intention

This study examines the influence of retail brand trust, off‐line patronage, clothing involvement, and website quality on online apparel shopping intention for young female US consumers. Data for this study were collected from 200 young female consumers who completed an online survey. Participants were asked to select one of three pre‐determined apparel retail brands that they have either had experience with or were familiar with. Respondents were then asked to keep their selected retailer in mind when completing the questionnaire and were also asked to briefly visit the retailer's website shopping for a shirt or blouse. Factor, correlation and multiple regression analyses were conducted to test our hypotheses. Retail brand trust, off‐line patronage, clothing involvement and two factors of website quality (usability and information quality, visual appeal and image) were found to significantly influence online apparel shopping intention. Off‐line patronage was the strongest predictor of online shopping intention. Implications for multi‐channel apparel retailers were discussed based on these findings.     

Assessing the demand for value‐based organic meats in Canada: a combined retail and household scanner‐data approach

We apply sets of weekly retail and household scanner data to estimate consumer demand of selected organic and conventional fresh beef products in the Canadian retail market. The main contribution of our study stems from the application of a two‐stage procedure that provides new and deeper insight into consumers' responses to changing retail environment and pricing for organic and conventional meat products. Combined knowledge of point‐of‐sale consumer behaviour for value‐based products, such as organic products, and distinct socio‐demographic profiles of buyers vs. non‐buyers of meat is especially interesting for retail managers and meat industry stakeholders. First, household meat consumption patterns are investigated based on household scanner data that track household's meat purchases in the period 2006–2007. The second step of analysis then involves the estimation of an almost ideal demand system for selected organic and conventional fresh beef products using retail scanner data for the period 2000–2007. The introduction of greater selections in organic product lines across mainstream supermarkets in Canada in response to consumer health concerns is expected to spur retail competition in an otherwise saturated Canadian retail market. The analysis of socio‐demographic profiles in beef consumption using individual household's purchase data reveals that besides regional differences in preferences, household size and resource characteristics are major determinants of point‐of‐sale beef purchase decisions. Our demand system results indicate that organic beef is highly dependent on price and expenditures, whereas demand for conventional beef is mostly driven by income, habits and ‘typical’ Canadian seasonal beef consumption patterns. Altogether, our conclusions on organic beef vs. conventional beef buyers may have further implications for institutional regulations.