Sequence Matters: Shelf‐Space Allocation under Dynamic Customer‐Driven Substitution

Customers who face a stockout situation often decide to purchase a different product in the same category. We analyze the resulting dynamic substitution problem in a retail environment, where customers serve themselves from the store shelves, such that the sequence of customer arrivals affects how scarce products are allocated to customers. We consider a setting with constrained shelf space, and we study how a retailer should optimally allocate such space between substitute products. We characterize environments where the sequence of customer arrivals can have a substantial impact on profitability.     

Lateral transshipment with partial request and random switching

A large body of inventory management research has been devoted to lateral transshipment. Most of the existent models assume that the unmet local demand will automatically request transshipment, and that the unmet local demand does not seek inventory at other locations within the same echelon. In contrast, we investigate a two-store retailer’s inventory replenishment and transshipment decisions when those two assumptions do not hold. Specifically, we use a fixed request rate to model partial demand for transshipment at the shortage store and a random switch rate to model the arrival of the unmet demand at the surplus store. We characterize the optimal transshipment and inventory replenishment policies. We find that it is not always in the best interest of the retailer to satisfy as much as possible the transshipment demand. In light of the switched demand flowing to the surplus store, the retailer may benefit from saving the leftover inventory at the surplus store for the switched demand. The optimal transshipment policy follows a double-threshold structure when the prospect of the switched demand is not large enough; and a transshipment quantity of zero becomes optimal otherwise. Through an extensive numerical analysis, we examine the impact of the request rate and the switch rate, together with other parameters. We also evaluate a few simple-to-use transshipment heuristics, including one that we devise based on the structure of the optimal transshipment policy. The consistent, near-optimal performance of the devised heuristic is a confirmation of the importance of our theoretical work on the optimal policy.     

基于“搭便车”行为的双渠道供应链库存竞争和促销策略

本文建立了由一个制造商和一个零售商组成的双渠道供应链模型，研究了随机需求下"搭便车"行为和渠道间缺货替代行为对供应链库存竞争与促销决策的影响。结果表明：分散式决策下，网络渠道替代率越高，零售商的最优订购量越大，同样的零售渠道替代率越高，制造商会为网络渠道提供更多的库存；而"搭便车"行为对零售商与制造商订购量的影响则取决于渠道替代率的变化，但"搭便车"行为会降低零售商促销努力水平。数值分析发现：分散式决策下，零售商最优订购量随"搭便车"行为的增加而减少。然而制造商的最优库存量并非随着"搭便车"行为程度的增加而增加，不同的是制造商网络渠道最优库存量取决于市场需求对传统零售渠道促销努力水平的弹性系数，即制造商网络渠道最优库存量随"搭便车"行为的增加先增加后减少。通过比较发现在不同的"搭便车"行为程度、传统零售渠道替代率、网络渠道替代率下，集中式决策下供应链期望收益大于分散式决策下供应链期望总收益。     

Maximizing customer equity subject to capacity constraints

This paper considers a firm that wants to optimally allocate limited capacity to heterogeneous customer segments in order to maximize its customer equity. The decision whether to accept or to reject a customer׳s request in a current period influences his repurchase behavior in later periods. The allocation process becomes complex, when demand exceeds capacity, because the isolated determination and optimization of a single customer׳s lifetime value is no longer feasible. Using a Markov decision process formulation, we study how to trade off short-term attainable revenues and long-term customer relationships. Furthermore, we analyze when and how intertemporal customer behavior influences capacity allocation. Finally, we investigate the impact of limited capacity on the customer lifetime value by introducing an opportunity cost-based approach that understands customer profitability as a customer׳s contribution to customer equity.     

The Effect of Product Variety and Inventory Levels on Retail Store Sales: A Longitudinal Study

We examine the effects of product variety and inventory levels on store sales. Using 4 years of data from stores of a large retailer, we show that increases in product variety and inventory levels are both associated with higher sales. We also show that increasing product variety and inventory levels has an indirect negative effect on store sales through their impact on phantom products—products that are physically present at the store, but only in storage areas where customers cannot find or purchase them. Our study highlights a consequence of increased product variety and inventory levels that has previously been overlooked in studies of retail product variety and inventory management. It also quantifies the impact of phantom products on store sales. In addition, our study provides empirical evidence to support earlier claims that higher product variety and inventory levels lead to an increase in defect rate. We discuss the implications of our findings for retail inventory and assortment planning and for the design of retail stores.     

Inventory Sharing with Transshipment: Impacts of Demand Distribution Shapes and Setup Costs

We study a firm's optimal transshipment problem considering the impacts of setup costs for transshipment and demand distribution shapes. We assume that the demand follows a three‐point distribution, which changes from a degenerate distribution, to a unimodal distribution, and to a bimodal distribution as the demand shape parameter increases. We find that as the demand shape parameter increases, the optimal transshipment strategy changes from no transshipment to transshipment, and finally to no transshipment. The firm would use two‐way transshipment when the shape parameter is relatively small, while it would use one‐way transshipment when the shape parameter is relatively large. When the optimal strategy is one‐way transshipment, the transshipment direction depends on the contribution margin as well as the demand shape, when the difference between the two demand uncertainties is small. Our study of a dual‐channel retail system shows that the additional benefit of two‐way transshipment is negligible when there are many retail stores.     

Self‐Service Operations at Retail Stores: The Role of Inter‐Customer Interactions

Inter‐customer interactions are important to the operation of self‐services in retail settings. More specifically, when self‐service terminals are used as part of customers’ checkout processes in retail operations without the explicit involvement of retailers as the direct service providers, inter‐customer interactions become a significant managerial issue. In this article, we examine the impact of inter‐customer interactions at retail self‐service terminals on customers’ service quality perceptions and repeat purchase intentions at retail stores. We conduct a scenario‐based experimental design (N = 674) using a 2 × 2 factorial design in which inter‐customer interactions are divided into “positive” vs. “negative” and occur during the “waiting” or during the actual “transaction” stages of self‐services at a retail store. We use attribution theory to develop the hypotheses. The results demonstrate that, through their interactions, fellow customers can exert influences on a focal customer's quality perceptions and repeat purchasing intentions toward a retail store. Furthermore, these influences were impacted by how customers attribute blame or assign responsibility toward the retail store. Service operations managers should leverage these interactions by designing into self‐service settings the capacities and interfaces that are best suited for customers’ co‐production of their self‐service experiences.     

Joint product assortment,inventory and price optimization to attract loyal and non-loyal customers

In this paper, we analyze the emerging retail practice of carrying a combined product assortment consisting of both regular “standard” products and more fashionable and short-lived “special” products. The purpose of this practice is to increase store traffic by attracting heterogeneous classes of customers, which drives up sales of standard products due to the potential cross-selling effect. Customers who are primarily attracted by special products will also buy some standard products. In this context, we analyze three decisions that are crucial for a retailer׳s commercial success: the product assortment, the inventory levels and the pricing. We propose an optimization model and an iterative heuristic to analyze the trade-offs between the combined product assortment, the inventory level and the price per product when there is limited shelf space. Using numerical experiments, we show that our heuristic can be trusted and that its accuracy improves when the number of products increases. Our findings indicate that to attract more customers for standard products, a retailer may benefit from carrying low priced special products which, if considered in isolation, would be non-profitable. As the cross-selling effect decreases, a retailer should focus more on the standard assortment by increasing its size and decreasing the prices. However, introducing special products and ignoring the cross-selling effect may decrease a retailer׳s profitability. We show that the introduction of special products involves more than just choosing the right specials for non-loyal customers but impacts the global assortment planning, the standard products and the products pricing.     

Linking Perceived Quality and Customer Satisfaction to Store Traffic and Revenue Growth*

Effects of perceived merchandise and service quality, relative to competition, on retail store performance are investigated using store traffic and revenue growth as outcome variables. A model is proposed and tested using aggregate customer data and store performance outcomes from a group of stores owned by a national retail organization. Results suggest that both service and merchandise quality exert significant influence on store performance, measured by sales growth and customer growth, and their impact is mediated by customer satisfaction. Implications of the results and future research directions are discussed.     

Pre-distribution vs. post-distribution for cross-docking with transshipments

Cross-docking operation is a logistics service mode aims to remove the storage and picking up functions of a warehouse, and coordinate goods loading between delivery vehicles and shipping vehicles. Transshipment is another logistic technique that allows goods to be conveyed from an overstocked store to a nearby understocked store, to avoid backordering or loss of sale. This paper models and analyzes two typical cross-docking operations: pre-distribution cross-docking operations (Pre-C) and post-distribution cross-docking operations (Post-C) when transshipments among retail stores are applied. The different operational performances are investigated and compared. The analytical results show that, considering the inventory cost, transshipment cost and operations cost at the cross-dock, the suitability of Pre-C and Post-C are highly sensitive to operations environment factors such as the uncertainty of demand, the unit operations cost at the cross-dock, and the unit inventory holding and shortage cost.     

Estimating the Impact of Understaffing on Sales and Profitability in Retail Stores

In this study, we use hourly data on store traffic, sales, and labor from 41 stores of a large retail chain to identify the extent of understaffing in retail stores and quantify its impact on sales and profitability. Using an empirical model motivated from queueing theory, we calculate the benchmark staffing level for each store, and establish the presence of systematic understaffing during peak hours. We find that all 41 stores in our sample are systematically understaffed during a 3‐hour peak period. Eliminating understaffing in these stores can result in a significant increase in sales and profitability in these stores. Also, we examine the extent to which forecasting errors and scheduling constraints drive understaffing in retail stores and quantify their relative impacts on store profits for the retailer in our study.     

Strategic inventory deployment for retail and e-tail stores

In this paper, we study a supply chain comprising one manufacturer and one retailer. Customers can make purchases either from the retailer or directly from the manufacturer via an e-tail channel. From the manufacturer's perspective of managing the two channels, we study three different inventory strategies, namely centralized inventory strategy, a Stackelberg inventory strategy, and a strategy where the e-tail operation is outsourced to a third party logistics provider (3PL). For each strategy, we obtain the optimal inventory levels in retail and e-tail stores and the respective expected profits. We compare the performance of various strategies. Managerial insights are provided through analytical and numerical analyses to illustrate the applicability of different strategies.     

A Stochastic Inventory Model With Fast‐Ship Commitments

We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast‐shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast‐ship option. We find a range of markups for fast‐ship orders such that the fast‐ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win–win for both players may not exist even when offering fast‐ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast‐ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast‐ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast‐ship option because the supplier may choose not to support the fast‐ship option when fast‐ship participation increases due to the fact that the fast‐ship participation rate adversely affects the initial order size.     

考虑无缺陷退货下零售商转运的供应链回购契约研究

针对由单个供应商和同一连锁企业的两个零售商组成的供应链系统中无缺陷退货问题。在随机需求下,假设零售商努力水平与无缺陷退货率成反比,以及两个零售商之间可以相互进行库存转运,建立了期望收益决策模型。通过比较集中决策和分散决策下零售商订货量及各方期望利润,确定了零售商最优订货量和最优努力水平,并提出了改进的差异化回购契约,算例分析表明,改进的差异化回购契约能够达到供应链协调。     

Stockout Recovery under Consignment: The Role of Inventory Ownership in Supply Chains

We examine how a supply chain firm may implement an incentive contract under inventory consignment to recover stockouts and to retain customers. Inventory consignment allows an upstream firm (e.g., a manufacturer) to own and control inventory at a downstream firm (e.g., a retailer), representing a structural change in supply chain governance. Motivated by cases in pet toy and electronics component industries, we formulate principal–agent models based on the newsvendor framework to capture the strategic interactions in a supply chain. We find that consignment can be effective in reducing stockouts because the ownership and control of the product by the manufacturer allows better prevention of stockouts, which complements stockout recovery and leads to fewer stockouts. However, the lower level of stockout under consignment does not necessarily translate into profitability—when the manufacturer is highly opportunistic, that is, readily exploring outside opportunities for its product, consignment may lead to lower profitability for both the manufacturer and the supply chain. On the other hand, consignment will improve profitability for the manufacturer and the supply chain, if both the manufacturer opportunism and the retailer opportunism are moderate.      

Managing big data in the retail industry of Singapore: Examining the impact on customer satisfaction and organizational performance

Much of the research on big data analytics has been centered on technical or system development. Research has been carried out on the usage of big data analytics to understand customer relationships and experience, amongst others. Still, there is a lack of research in the retail industry considering big data management, examining the impact on customer satisfaction and organizational performance in the retail sector. Retailers explore analytics to gain a unified picture of their customers and operations across the store or online channels and make strategic decisions contributing to the growth of the retail industry. Thereof, this study has been conducted by majorly focusing on the Singapore retail industry to clarify the feasibility of big data management analytics. Quantitative research method was employed involving 500 participants from the retail industry of Singapore. The results of the study stated that amongst the different big data analytics utilized within the retail industry of Singapore, social media analytics had been majorly answered by the participants. Future researchers can study about the upcoming retail trends in Singapore and how the effects of big data analysis changed in the past few years and deal with the unexpected future recessions in the retail industry within Singapore.     

应对突发事件的库存共享策略

以包含两个销售商的库存系统为例,构建了一个描述库存共享应对突发事件的非合作博弈模型,证明了其纳什均衡解是唯一存在的。研究结果显示库存共享策略总有可能使得销售商的期望利润得以改进。另外,比较静态分析反映了转载价格和转载成本显著影响库存共享销售商的最优订货量和最优期望利润。最后,提出了一个简单的求解模型纳什均衡解的启发式算法。     

Customer Learning Processes,Strategy Selection,and Performance in Business‐to‐Business Service Firms*

Learning about customers takes place through relevant dialogues with those customers, also known as customer relationship management (CRM). As relationships develop, information about the customer is gathered in the firm's customer information systems (CIS): the content, processes, and assets associated with gathering and moving customer information throughout the firm. This research develops a measure of CIS management capabilities based on learning organization theory and measured by the ability to get, store, move, and use information throughout the business unit. This measure is then used to analyze customer learning processes and associated performance in the context of marketing strategic decision making. This study of 209 business services firms finds that generic marketing strategy positioning (low‐cost and differentiation) and the marketing tactics of personalization and customization are related to CIS development. Customer information systems development in turn is associated with higher levels of customer‐based performance, which in turn is associated with increased business growth. Since the strongest association with customer‐based performance is strategy selection, the long‐term benefits of the knowledge gained from the CIS may be in the ability to assist in measuring customer‐based performance, rather than in the ability to immediately contribute to performance. Finally, for these firms, customization and personalization are not directly associated with performance and thus may not be necessary to support every firm's marketing strategy.     

Optimal Uniform Pricing Strategy of a Service Firm When Facing Two Classes of Customers

When facing heterogeneous customers, how should a service firm make its pricing decision to maximize revenue? If discrimination is allowed, then priority schemes and differentiated pricing are often used to achieve that. In many applications, however, the firm cannot or is not allowed to set discriminatory prices, for example, list price in retail stores, online shopping, and gas stations; thus a uniform price must be applied to all customers. This study addresses the optimal uniform pricing problem of a service firm using a queueing system with two classes of customers. Our result shows that the potential pool of customers plays a central role in the firm's optimal decision. Depending on the range of system parameters, which are determined explicitly by the primitive data, the firm's optimal strategy may choose to serve only one class of customers, a subset of a class of customers, or a combination of different classes of customers. In addition, the optimal price is in general not monotonic with respect to the potential market sizes because their changes may lead to a major shift in the firm's decision on which customer class to serve. However, unless such a shift occurs, the optimal price is weakly decreasing in the potential market sizes.     

Contracting in a Supply Chain with Stochastic Demand and Substitute Products

Retailers often stock competing products from multiple manufacturers. When the retailer stocks out of a particular item, customers who prefer the item are likely, with some probability, to switch to a substitute product from another manufacturer at the same store. In such an event, a “lost sale” for the manufacturer is not a “lost sale” for the retailer. This exacerbates differences in manufacturer's and retailer's stockout costs for the item. Such differences in stockout cost influence the optimal contract between the manufacturer and the retailer and also impose agency costs on the channel. Such contracts, in turn, determine equilibrium inventory levels and fill rates. We study these issues in a single‐period supply chain, consisting of a manufacturer and a retailer, under three different scenarios (when the two firms are integrated into a single entity, when the retailer makes stocking decisions, and when the manufacturer makes stocking decisions). We compare, and present a methodology for comparing, stocking quantities, manufacturer efforts, and supply chain profits across different scenarios. We find that VMI performs better when manufacturer effort is a substantial driver of consumer demand and when consumers are unlikely to substitute to another brand in case of a stockout. On the other hand, if non‐contractible manufacturer effort is unimportant, or when substitution is significant, VMI can exacerbate, rather than mitigate, channel inefficiencies, and can perform worse than traditional Retailer Managed Inventory.