Markdown or Everyday Low Price? The Role of Behavioral Motives

We study a seller’s optimal pricing and inventory strategies when behavioral (nonpecuniary) motives affect consumers’ purchase decisions. In particular, the seller chooses between two pricing strategies, markdown or everyday low price, and determines the optimal prices and inventory level. Two salient behavioral motives that impact consumers’ purchase decisions and the seller’s optimal strategies are anticipated regret and misperception of product availability. Regret arises when a consumer initially chooses to wait but encounters stockout later, or when the consumer buys the product at the high price but realizes that the product is still available at the markdown price. In addition, consumers often perceive the product’s future availability to be different than its actual availability. We determine and quantify that both regret and availability misperception have significant operational and profit implications for the seller. For example, ignoring these behavioral factors can result in up to 10% profit losses. We contrast the roles of consumers’ strategic (pecuniary) motives with their behavioral (nonpecuniary) motives in affecting purchase, pricing, and inventory decisions. The presence of the behavioral motives reinstates the profitability of markdown over everyday low price, in sharp contrast to prior studies of only strategic motives that suggest the contrary. We characterize how and why strategic versus behavioral motives affect decisions in distinctive manners. In doing so, this paper also introduces and determines the behavioral benefits of pricing in leveraging consumers’ behavioral regularities. We advocate that tactics that may intensify consumers’ misperception of availability, such as disclosing low inventory levels, can have a far-reaching impact on improving the seller’s profit

Dynamic pricing decisions and seller-buyer interactions under capacity constraints

Focusing on sellers’ pricing decisions and the ensuing seller-buyer interactions, we report an experiment on dynamic pricing with scarcity in the form of capacity constraints. Rational expectations equilibrium solutions are constructed and then tested experimentally with subjects assigned the roles of sellers and buyers. We investigate behavior in two between-subject conditions with high and moderate levels of capacity. Our laboratory market exhibits strategic sophistication: the price offers of sellers and the buyers’ aggregate responses largely approximate equilibrium predictions. We also observe systematic deviations from equilibrium benchmarks on both sides of the market. Specifically, in our experiment the sellers are boundedly strategic: their prices often exhibit strategic adjustments to profit from buyers with limited strategic sophistication, but they are also often biased towards equilibrium pricing even when that would not be ex-post optimal

Modeling customer bounded rationality in operations management: A review and research opportunities

Many studies in operations management started to explicitly model customer behavior. However, it is typically assumed that customers are fully rational decision-makers and maximize their utility perfectly. Recently, modeling customer bounded rationality has been gaining increasing attention and interest. This paper summarizes various approaches of modeling customer bounded rationality, surveys how they are applied to relevant operations management settings, and presents the new insights obtained. We also suggest future research opportunities in this important area

Advances in Technologies and Methods for Behavior, Emotion, and Health Monitoring in Pets

This research offers a detailed descriptions of existing technologies and approaches for monitoring pets in the areas of behavior, emotion, and health. The first section discusses behavior and emotion monitoring. It includes wearable devices like smart collars that are fitted with sensors for monitoring heart rate, activity levels, and temperature. These devices communicate with AI-based anomaly detection systems that send real-time alerts through various channels such as SMS, email, and mobile app notifications. Additionally, smart cameras and sound capturing devices are employed to analyze behavior and emotional states. The second section discusses health monitoring and assistance. Users can input data such as pet breed, age, and observed behaviors into dashboards. Subsequent AI algorithms analyze the data, providing health forecasts and preventive measures. Moreover, imaging technologies employ image acquisition, preprocessing, and feature extraction to detect abnormalities, the results of which are stored in databases and can trigger alerts to medical staff. The review identifies distinct modules for each sector, including data capture, processing, and alerting mechanisms. While each module specializes in specific tasks, common functionalities such as real-time alerting and data storage are pervasive across both sectors. The study asserts that current technological advancements have significantly enhanced the ability to monitor pets in real-time, providing actionable insights for pet owners and veterinary professionals

Operational and Economical Perspectives on Consumer Returns

Customer return policies are one of common after sale services offered by a retailer in order to boost sales, improve customer satisfaction and diminish customer fit uncertainty. With such a service, the retailer accepts the return of a product after the sale has occurred, if it does not satisfy the customers expectations. This study investigates consumer returns from three different perspectives. First, we start with a single period inventory planning problem of multi-variants in which customers have a right to return products in case of dissatisfaction. We assume that returns can be as-good-as-new condition after a minor restocking process and they are resalable in the same selling period. At the time of purchasing, a customer may choose to substitute her choice with another variant of the item, if the former is sold out. This, so called substitution, and resalable returns are important parameters in assortment planning that might affect the total profit dramatically. Under this setting, we aim to illustrate the effect of return and substitution on the optimal order quantities of variants and the total expected profit. We show that the total profit decreases as the probability of returns or the probability of resalable returns increases. In addition, the probability of substitution, return, or resalable return has a negative effect on inventory level of variants. Second, we analyze a retailers return policy problem when the market consists of loss-averse customers who are more sensitive to losses than gains instead of being risk-neutral customers. We examine the situation in which a seller makes price and quantity decisions for a single item and also designs an appropriate returns policy in order to maximize his profit. We analyze the case where the seller offers either a full-refund or a partial-refund policy if he decides to accept returns or chooses not to accept any returns. With the full-refund policy, the seller reimburses the consumer the full price of the product if it does not fit the customers preferences. With a partial-refund policy, the seller offers a refund which is strictly less than the purchase price. We assume that customers are strategic customers aiming to maximize their utilities of the product. With this model, we aim to analyze the impact of loss aversion on the sellers price and order quantity decisions. We show that the seller keeps fewer inventories as customers get more loss-averse and loss-aversion has a negative effect on the expected unit profit. Thus, the total profit decreases as loss-aversion. Finally, we present a model that investigates the effects of return policies on each of the two sellers pricing decisions when these sellers engage in market size competition. Our model simultaneously addresses a consumers purchase decision and the competing sellers price decisions, along with their respective return policies. We assume that two competing sellers which do not have a capacity problem only decide their prices and return policies. The sellers may independently offer no-refund, full-refund of the price of the product, or a partial-refund. The market share of each party depends on his and the rivals price and return policy; customer valuations of the product and the degree of competition between the sellers. Before purchasing, a consumer cannot evaluate the products utility which is a decreasing function of the price set by the seller from which she chooses to purchase it and the disutility of purchase and/or return which is related to the physical distance between the consumer and the sellers location. The return policy of a seller may also affect a consumers decision via her expected utility. Thus, pricing and return policy decisions play an important role in the division of the total market. We show that the full-refund policy yields a higher purchasing price compare to the no-refund or partial-refund policy. However, it only performs better in terms of profit when the product has a small salvage value and a partial-refund policy is not an option for the retailer. When the retailer offers the partial-refund policy, it always dominates the other refund policies. In addition, we show that the full-refund policy provides the highest consumer surplus since customers do not face any risk of misfit. On the other hand, the full-refund policy is socially efficient only when the salvage value is high. For low salvage values, the partial-refund policy yields a higher level of social welfare.Ph.D., Decision Sciences -- Drexel University, 201

Decision-making experiments on dual sales channel coordination

In this thesis, we conduct an experimental study with human decision makers, on dual sales channel coordination. We aim to determine dual channel strategies for a manufacturer who sells its product thorough both an independent retailer channel and its totally owned direct online channel. The two channels compete on service, where the service level of the retailer channel is measured with its product availability level, and the service level of the direct channel is measured with its delivery lead time. This multi-stage game-theoretical model was previously solved for the wholesale price contract (Chen et al. 2008) and buyback contract (Gökduman and Kaya 2009) cases. We compare these models' theoretical predictions with the outcome of our experiments with human decision makers. In particular, we analyze the theoretical and observed coordination performance of the wholesale price and buyback contracts between the two firms. We identify deviations from theoretical predictions that can be attributed to behavioral factors, such as risk aversion

Garments without guilt? : an exploration of corporate social responsibility within the context of the fashion supply chain : case study of Sri Lanka

Currently unavailable