Optimal responses to stockouts: Lateral transshipment versus emergency order policies

In the retail industry, stockouts have a significant effect on a firm׳s profitability. When a stockout takes place, retailers often apply one of two strategies to resolve the issue – placing an emergency order with their supplier or arranging a lateral transshipment with a nearby partner store. Choosing the optimal response to a stockout is complicated by customers׳ spontaneous reactions. Customers who find that a product is out of stock may choose to give up on the purchase, to wait for delivery (through emergency order or lateral transshipment), or go to a partner store to search for the product on their own. In this study, under a single-period setting with two retail stores, we investigate the optimal inventory decisions under each strategy, and conduct a comparison between lateral transshipment and emergency order options. We also analyze the effects of the customer requesting rate and switching rate on the optimal inventory decision. Through numerical analysis, the two strategies are compared in terms of inventory levels and profitability. The results suggest that in addition to the cost associated with each of these strategies, the customers׳ behavior in response to a stockout has a significant effect on the optimal decision. The emergency order strategy is a better option when more customers request deliveries or when more customers switch to another store. Extending this analysis, we also examine the combined strategy when an emergency order is placed after a transshipment fails to fulfill unmet demands, and explore the circumstances under which this strategy provides the highest additional profit for the stores. Finally, we also find that a higher requesting rate does not necessarily increase profits, particularly when there is a high customer switching rate, because requesting emergency order or transshipment reduces switching demand.     

Advance selling with freebies and limited production capacity

We consider a two-period pricing model in which a seller offers freebies along with the product when making advance sales, and production is constrained by capacity. The seller can offer freebies to increase both market base and customer׳s valuation toward the product in advance. The customers strategically determine whether to purchase the product in advance and gain freebies when their valuation on the product is uncertain, or delay their purchase decision until the regular selling period. We characterize the optimal pricing, quality level of the freebie and production quantity decisions that maximize the expected profits of the seller over the two periods.     

An Empirical Investigation of Web Site Use Using a Commitment‐Based Model

Companies throughout industry are interested in retaining existing customers, because customers' continuous consumption of products and services is critical to the long‐term value propositions of most organizations. Thus, decision‐making strategies that promote continuous use and customer retention are of research interest, both theoretically and practically. In the present research, we investigate one important area of continuous usage, that of Web site use. In particular, we use several theories of commitment to understand how an individual's decision to continue to use a Web site is influenced by his or her commitment toward that Web site and the vendor that supports it. Results derived from data collected from 335 users of a variety of Web sites indicated that affective commitment, calculative commitment, quality of alternatives, and trust were significantly associated with an individual's behavioral intention to continue to use a Web site. Implications for customer retention and decision‐making strategies are discussed.     

Enhancing corporate social responsibility: Contract design under information asymmetry

We consider a two-stage supply chain in which a contract manufacturer (CM) sells products through a brand name retailer. The contract manufacturer can invest in corporate social responsibility (CSR) activities to improve customer perception about the firm and increase demand, while the retailer can influence the demand by exerting marketing efforts. We design optimal contracts for such a supply chain, which faces information asymmetry. The wholesale price contract was developed as the base model to derive insight into the value of information sharing. We examine the impact of CSR cost on CSR commitment and profits. We find that CM׳s CSR cost impacts the CM׳s and the retailer׳s profits differently. Under certain conditions, the CM׳s profit will increase with cost, while that of the retailer is uncertain. We also propose two-part tariff contracts for both the symmetric and asymmetric cases with the aim of maximizing the retailer׳s profit and improving CM׳s commitment to CSR. Finally, numerical experiments are conducted to illustrate and validate the proposed models and provide managerial insights.     

The allocation of promotion budget to maximize customer equity

Since the early 1980s, the concept of relationship marketing has gained increased acceptance in the field of general marketing, and particularly that of direct and interactive marketing. One of the major benefits of relationship marketing is the ability to make decisions based on their impact on customer equity. In this paper, we offer a general approach to the organization of promotion budget allocation, where the objective function is to maximize customer equity. A cornerstone in our study is the use of decision calculus in which managers’ judgments and/or estimates serve as some of the inputs to formal modeling. A series of applications of our approach to promotion budget allocation are offered under different market conditions. These applications focus on promotional expenditure allocation decisions between acquisition and retention, as well as among different promotional options for each category of expenditure. The paper also treats potential cases of synergy, or interaction, between promotional vehicles when applied to the same market segment.     

The joint effects of customer participation in various new product development stages

The notion that customers provide distinct inputs that help tackle unique tasks in each new product development (NPD) phase leads firms to engage customers concurrently in various NPD stages rather than involving them only in one NPD stage. Involving customers in diverse NPD stages is based on the belief that the constructive effects of customer participation in each NPD phase could be supplementary. However, little is known about the joint effects of embracing customers in multiple NPD stages such as whether customer participation in a certain NPD stage enlarges or undermines the returns of customer participation in another NPD stage, and whether customer participation throughout the entire NPD process is really beneficial. Drawing upon the knowledge management perspective, this research investigates in which combination of NPD stages (ideation, development, and launch) engaging customers creates a synergistic or destructive impact on new product market performance. The results reveal that involving customers in both ideation and development stages and in both development and launch stages yields synergistic returns, whereas customer participation in both ideation and launch stages does not create any additional gains. Furthermore, customer participation across all three NPD stages does not improve new product market performance beyond the sole and joint effects of customer participation in two NPD stages. These noteworthy findings imply that the joint effects of customer participation do not always lead to synergistic impacts and depend on the value of customer knowledge and the difficulty of knowledge management of transferring and integrating customer knowledge gathered in various NPD stages. In a certain combination of NPD stages, where the difficulty of knowledge management becomes higher, customer participation cannot generate supplementary returns, and thus, firms can achieve a similar level of new product market performance with customer participation in limited NPD stages.     

客户空间行为的空间交互和离散选择模型研究

客户空间行为模型可以帮助解释空间竞争态势、提供管理建议、预测销售以及选址决策.在以往相关研究的基础上,深入研究空间结构对客户空间行为的影响,指出相对空间位置的重要作用,提出相对空间位置变量及度量方法.在离散选择模型的框架下,结合相对空间位置变量的客户空间行为模型更好地解释了空间结构对空间行为的影响,提高了参数空间无关性.在一个真实的城市空间中调查客户超市选择行为数据,并基于这些数据验证了模型有效性.     

The value of VMI beyond information sharing in a single supplier multiple retailers supply chain under a non-stationary (Rn,Sn) policy

This study aims to determine the value of vendor-managed inventory (VMI) over independent decision making with information sharing (IS) under non-stationary stochastic demand with service-level constraints. For this purpose, we utilize mixed-integer linear programming formulations to quantify the benefits that can be accrued by a supplier, multiple retailers and the system as a whole by switching from IS to VMI. More specifically, we investigate the incremental value that VMI provides beyond IS in terms of expected cost savings, inventory reductions, and decrease in shipment sizes from the supplier to the retailers by conducting a large number of computational experiments. Results reveal that the decision transfer component of VMI improves these performance measures significantly when the supplier׳s setup cost is low and order issuing efficiency is high. The benefits offered by VMI are negligible under the problem settings where the supplier׳s order issuing efficiency is low and the production setup serves solely a single replenishment under IS.     

Allocating Capacity with Demand Competition: Fixed Factor Allocation*

We consider a supply chain consisting of a supplier and two retailers. The supplier sells a single product to the retailers, who, in turn, retail the product to customers. The supplier has limited production capacity, and the retailers compete for the supplier's capacity and are duopolists engaged in Cournot competition for their customers. When the sum of the retailers' orders exceeds the supplier's capacity, the supplier allocates his capacity according to a preannounced allocation rule. We propose a new capacity allocation rule, fixed factor allocation, which incorporates the ideas of proportional and lexicographic allocations: it prioritizes retailers as in lexicographic allocation, but guarantees only a fixed proportion of the total available capacity to the prioritized retailer. We show that (1) the fixed factor allocation rule incorporates lexicographic and proportional allocations from the perspectives of the supplier and the supply chain; (2) under fixed factor allocation, the supply chain profit is not affected by the allocation factor when it is greater than a threshold; (3) the retailers share the supply chain profit with the supplier depending on the value of the allocation factor; and (4) the fixed factor allocation coordinates the supply chain when the market size is sufficiently large. We also compare fixed factor with proportional and lexicographic allocations, respectively. Furthermore, we demonstrate how the supplier can optimize his capacity level and wholesale price under fixed factor allocation.     

无约束条件下多客户流失挽救最优化决策

对无约束条件下多客户流失挽救的最优方案进行了研究.借助于广义客户终身价值,通过数学建模和分析发现,只有当挽救行动判定值大于1时,对流失客户的挽救才有必要,且存在最优挽救费用,各类客户中的合理挽救次序也存在.     

Product and service innovation with customer recognition

Product and service innovation is important for brands to succeed in a competitive marketplace. As information technology advances, customer recognition becomes a growing industry trend; that is, brands track customers' purchase history, recognize and price discriminate between repeat and new customers.The trend of customer recognition has changed the nature and intensity of competition between brands. In this article, we examine how customer recognition and the associated changes in competition affect brands' incentives to invest in product and service innovation. We find that when brands have similar equity, customer recognition increases brands' incentives to invest in product and service innovation. However, when brands have sufficiently different equity, customer recognition leads the stronger brand to invest more and the weaker brand to invest less in product and service innovation. In addition, extant literature suggests that customer recognition reduces brand profits. In contrast, we find that customer recognition can increase the weaker brand's profit but decreases it more for the stronger brand. Thus, collecting customers' purchase history data for customer recognition can be beneficial for weaker brands but detrimental for stronger brands.     

Customer satisfaction: Cost driver or value driver? Empirical evidence from the financial services industry

We investigate the relation between customer satisfaction, customer servicing costs, and customer value in a financial services firm. We find that customer satisfaction is positively associated with future customer servicing costs, as well as with customer value. The relation between customer satisfaction and customer value appears non-linear; higher customer satisfaction appears to have a higher return for the most profitable customer segments. Our findings indicate that customer satisfaction is a value driver; however, customer satisfaction is not cost-free and managers have to consider the costs, as well as the benefits, of increasing customer satisfaction.     

基于客户价值的客户序位评价研究

客户关系管理是目前管理研究的热点,企业对客户价值的序位评价是其基础问题之一,其有效性是实施客户关系管理的基础.基于价值的客户序位评价是根据客户的价值大小来定位客户.本文首先在现有的客户价值评价体系的基础上结合客户生命周期理论设计了一种新的客户价值评价指标体系,从客户的生命周期阶段和客户发展潜力两个方面来评价客户价值.然后根据该指标体系的指标特性,选择神经网络作为评价方法.最后根据客户价值评价结果进行客户序位,并对每个类别的客户特征及其相应的营销策略进行了分析.     

顾客关系价值量化模型研究述评

客户关系管理最基本的问题是量化顾客关系价值,为此从顾客盈利性分析开始,回顾了顾客终身价值量化的3种模型:顾客保持模型、顾客转移模型和最优化模型,分析了各自运用的条件和环境,总结了顾客关系价值量化的3个核心环节:交易流的量化、利润流(或现金流)的量化和顾客资产的最优化,并提出了未来研究的方向和路径。     

Strategic Capacity Management When Customers Have Boundedly Rational Expectations

In retailing industries, such as apparel, sporting goods, customer electronics, and appliances, many firms deploy sophisticated modeling and optimization software to conduct dynamic pricing in response to uncertain and fluctuating market conditions. However, the possibility of markdown pricing creates an incentive for customers to strategize over the timing of their purchases. How should a retailing firm optimally account for customer behavior when making its pricing and stocking/capacity decisions? For example, is it optimal for a firm to create rationing risk by deliberately under stocking products? In this study, we develop a stylized modeling framework to answer these questions. In our model, customers strategize over the timing of their purchases. However, customers have boundedly rational expectations in the sense of anecdotal reasoning about the firm's fill rate, i.e., they have to rely on anecdotes, past experiences, or word‐of‐mouth to infer the firm's fill rate. In our modeling framework, we distinguish two settings: (i) capacity commitment, where the firm commits to its capacity level in the long run, or (ii) the firm dynamically changes it in each season. For both settings, within the simplest form of anecdotal reasoning, we prove that strategic capacity rationing is not optimal independent of customer risk preferences. Then, using a general form of anecdotal reasoning, we provide sufficient conditions for capacity rationing to be optimal for both settings, respectively. We show that the result of strategic capacity rationing being suboptimal is fairly robust to different valuation distributions and utility functions, heterogeneous sample size, and price optimization.     

Flexible Capacity Investments and Product Mix: Optimal Decisions and Value of Postponement Options

In this article, we study a firm's interdependent decisions in investing in flexible capacity, capacity allocation to individual products, and eventual production quantities and pricing in meeting uncertain demand. We propose a three‐stage sequential decision model to analyze the firm's decisions, with the firm being a value maximizer owned by risk‐averse investors. At the beginning of the time horizon, the firm sets the flexible capacity level using an aggregate demand forecast on the envelope of products its flexible resources can accommodate. The aggregate demand forecast evolves as a Geometric Brownian Motion process. The potential market share of each product is determined by the Multinomial Logit model. At a later time and before the end of the time horizon, the firm makes a capacity commitment decision on the allocation of the flexible capacity to each product. Finally, at the end of the time horizon, the firm observes the demand and makes the production quantity and pricing decisions for end products. We obtain the optimal solutions at each decision stage and investigate their optimal properties. Our numerical study investigates the value of the postponed capacity commitment option in supplying uncertain operation environments.     

Customer‐Base Concentration and Inventory Efficiencies: Evidence from the Manufacturing Sector

What is the link between customer‐base concentration and inventory efficiencies in the manufacturing sector? Using hand‐collected data from 10‐K Filings, we find that manufacturers with more concentrated customer bases hold fewer inventories for less time and are less likely to end up with excess inventories, as indicated by the lower likelihood and magnitude of inventory write‐downs and reversals. Using disaggregated inventory disclosures, we find that inventory efficiencies primarily flow through the finished goods inventory account, while raw material efficiencies are offset by higher work‐in‐process holdings and longer work‐in‐process cycles. In additional analysis, we document a valuation premium for more concentrated manufacturers after controlling for other firm characteristics, including default risk and cost of capital estimates. We conclude that investors trade off the costs and benefits of relationships with a limited number of major customers and, on balance, consider customer‐base concentration as a net positive for firm valuation. Overall, our study adds to interdisciplinary research in accounting and operations management by shedding new light on the relevance of major customer disclosures for fundamental analysis and valuation in the manufacturing sector.     

基于服务能力均衡的网购供应链资源整合决策

为客户提供满意的个性化服务是网购企业提升客户体验价值和竞争力的关键,满意的个性化服务需要对网购企业后台运行的供应链资源进行有效整合。在网购供应链资源整合特征分析基础上,从网购供需服务能力动态协调与均衡的角度出发,基于网购个性化服务模式分析并挖掘出资源整合的主导因素,建立了整合决策的优化数学模型,搭建了改进的蚁群寻优算法来实现整合决策优化的求解。最后通过算例验证了方法的有效性与可行性。     

Does a Supplier's Operational Competence Translate into Financial Performance? An Empirical Analysis of Supplier–Customer Relationships

We conduct an empirical investigation of how a supplier's operational competence, as reflected by outcomes in the areas of quality, cost, delivery, flexibility, and new product development, translates into financial gains from a key customer. In contrast to previous research directed at the firm level, this study focuses on the supplier–customer relationship level. Using survey data from 158 suppliers in the manufacturing industry, we perform structural equation modeling to map out the paths from operational competence to financial performance—via dependencies and cooperative behaviors between suppliers and their customers. This study is the first scholarly attempt to examine the link between suppliers’ operational competencies and financial performance in interorganizational relationships. It is also an early investigation into operational competence as a source of bi‐lateral dependence. Our findings show that the supplier's operational competences increase its customer's dependence by enhancing the value of its products/services. However, the resulting increase in the supplier's power is not leveraged to shape relationship behaviors or capture value from its customer. In contrast, the customer's existing power as a major buyer plays an important role in shaping cooperative behaviors and affecting the supplier's financial performance from the customer relationship.     

The Economic Payout Model for Service Guarantees

Service guarantees consist of a promise to a customer (marketing), the delivery of a service to the customer (operations), and actions to appease the customer when service failures happen (recovery). A part of recovery involves offering the customer an economic and/or noneconomic payout when things go wrong. When the economic payout is too high or low, the impact on the organization and the customer is usually negative. Therefore, determining the size of the economic payout is of critical strategic and tactical importance in businesses. Yet, no systematic quantitative methods are found in the literature to help managers determine the economic payout for service failures. The current ways an economic payout is determined are management judgment, the consensus of customer focus groups, competitive benchmarking, and the use of simple expected value methods. In this article, we define the Economic Payout Model for Service Guarantees (EPMSG) that provides an optimal service guarantee economic payout under certain conditions. The EPMSG and its objective function considers customer revenue over the short‐ and long‐term, the cost of creating and providing the service, the cost of recovery, the probability of a service failure, and the probability of customer retention as a function of economic payout. A numerical example is provided of how EPMSG works. Customer retention probability distributions are examined assuming normal and gamma distributions. We end the article by describing the theoretical contributions, model limitations, managerial implications, and opportunities for future research.