Pre‐Orders for New To‐be‐Released Products Considering Consumer Loss Aversion

Advance selling through pre‐orders is a strategy to transfer inventory risk from a retailer to consumers. A newsvendor retailer can have three strategies to choose from: no advance selling allowed (NAS), moderate advance selling with a moderate discount for pre‐orders (MAS), and deep advance selling with a deep discount for pre‐orders (DAS). This research studies how a retailer could design an advance selling strategy to maximize her own profits. We find some interesting results. For example, there exist two thresholds for the selling season profit margin and two thresholds for consumer's expected valuation. For products with higher profit margin than the high threshold on profit margin, a retailer should always use DAS. For products with medium profit margin within the two thresholds, a retailer should adopt MAS if consumer's expected valuation is lower than the high threshold and use DAS otherwise. For products with lower profit margin than the low threshold, a retailer should use NAS, DAS, or MAS, respectively, if consumer's expected valuation is lower than the low threshold, higher than the high threshold, or between the two thresholds, respectively. Through sensitivity analyses, we also show the effects of multiple consumer characteristics on a retailer's optimal advance selling strategy.     

考虑退货的定价和订货优化及信息发布美化策略

考虑顾客由感知差异引起的退货行为,以及促销期与日常销售期不同的行为特点,对日常销售期和促销期顾客购买率和退货率分别进行了解析表述.在此基础上分析了确定需求下信息发布美化策略对最大利润的影响.建立了随机需求下在线零售商的期望利润模型,对定价和订货量进行联合优化.最后通过算例分析了在感知价值和感知差异服从更为一般的分布形式且存在相关性条件下,最优策略下的预期利润随信息发布美化程度的变化规律,以及相关性对信息发布美化策略有效性的影响.研究结果表明,基于感知价值和感知差异构建的购买率和退货率模型可较好解释已有实证研究结果,以此为基础对定价和库存进行联合优化更符合实际,优化条件下的最大利润随信息发布美化程度的提高先增后降,取得最大利润的信息美化值促销期大于日常销售期,且线性相关程度越高的产品取得最大利润的信息美化值越大。     

Demand–Supply Mismatches and Stock Market Performance: A Retailing Perspective

We provide empirical evidence that the volatility of inventory productivity relative to the volatility of demand is a predictor of future stock returns in a sample of publicly listed U.S. retailers over the period 1985–2013. This key performance indicator, entitled demand–supply mismatch (DSM), captures the fact that low variation in inventory productivity relative to variation in demand is indicative of the superior synchronization of demand‐ and supply‐side operations. Applying the Fama and French (1993) three‐factor model augmented with a momentum factor (Carhart 1997), we find that zero‐cost portfolios formed by buying the two lowest and selling the two highest quintiles of DSM stocks yield abnormal stock returns of up to 1.13%. These strong market anomalies related to DSM are observed over the entire sample period and persist after controlling for alternative inventory productivity measures and firm characteristics that are known to predict future stock returns. Further, we reveal that DSM is indicative of lower future earnings and lower sales growth and provide evidence that the observed market inefficiency results from investors’ failure to incorporate all of the information that inventory contains into the pricing of stocks.     

基于不同支付方式的线上企业库存与定价策略研究

复杂的网购环境,频发的网购事故,严重影响顾客的网购意图;货到付款支付方式所隐含的保险机制能够刺激潜在需求,但可能提高退货率,增加线上企业的经营成本。如何有效权衡利弊,制定不同支付方式下的最优经营决策是线上企业必须的核心问题。利用理性预期均衡的相关知识,考虑网上预付和双模式（同时提供网上预付和货到付款）两类支付方式下顾客的购买与退货行为,研究线上企业的最优价格和库存决策。结果表明：1）零售价格在网上预付方式下比双模式下更高;2）双模式中顾客全部选择网上预付时,两类模式的相对优劣依赖企业单位营业收入以及潜在市场需求;双模式中顾客全部选择货到付款时,两类模式的相对优劣则只取决于潜在市场需求;3）双模式中全部顾客选择网上预付比选择货到付款时企业利润更高,但都小于双模式中企业的利润最大值,且该利润最大值随市场结构的变化而改变。     

Improving the Milk Supply Chain in Developing Countries: Analysis,Insights, and Recommendations

Quality issues in milk—arising primarily from deliberate adulteration by producers—have been reported in several developing countries. In the milk supply chain, a station buys raw milk from a number of producers, mixes the milk and sells it to a firm (that then sells the processed milk to end consumers). We study a non‐cooperative game between a station and a population of producers. Apart from penalties on proven low‐quality producers, two types of incentives are analyzed: confessor rewards for low‐quality producers who confess and quality rewards for producers of high‐quality milk. Contrary to our expectations, whereas (small) confessor rewards can help increase both the quality of milk and the station's profit, quality rewards can be detrimental. We examine two structures based on the ordering of individual and mixed testing of milk: pre‐mixed individual testing (first test a fraction of producers individually and then [possibly] perform a mixed test on the remaining producers) and post‐mixed individual testing (first test the mixed milk from all producers and then test a fraction of producers individually). Whereas pre‐mixed individual testing can be socially harmful, a combination of post‐mixed individual testing and other incentives achieves a desirable outcome: all producers supply high‐quality milk with only one mixed test and no further testing by the station.     

A Sales Forecast Model for Short‐Life‐Cycle Products: New Releases at Blockbuster

We develop, in this article, a sales model for movie and game products at Blockbuster. The model assumes that there are three sales components: the first is from consumers who have already committed to purchasing (or renting) a product (e.g., based on promotion of, or exposure to, the product prior to its launch); the second comes from consumers who are potential buyers of the product; and the third comes from either a networking effect on closely tied (as in a social group) potential buyers from previous buyers (in the case of movie rental and all retail products) or re‐rents (in the case of game rental). In addition, we explicitly formulate into our model dynamic interactions between these sales components, both within and across sales periods. This important feature is motivated by realism, and it significantly contributes to the accuracy of our model. The model is thoroughly tested against sales data for rental and retail products from Blockbuster. Our empirical results show that the model offers excellent fit to actual sales activity. We also demonstrate that the model is capable of delivering reasonable sales forecasts based solely on environmental data (e.g., theatrical sales, studio, genre, MPAA ratings, etc.) and actual first‐period sales. Accurate sales forecasts can lead to significant cost savings. In particular, it can improve the retail operations at Blockbuster by determining appropriate order quantities of products, which is critical in effective inventory management (i.e., it can reduce the extent of over‐stocking and under‐stocking). While our model is developed specifically for product sales at Blockbuster, we believe that with context‐dependent modifications, our modeling approach could also provide a reasonable basis for the study of sales for other short‐Life‐Cycle products.     

Motivation and Complex Verbal Phenomena: Implications for Organizational Research and Practice

The concept of motivation has attracted the attention of scholars in the field of Organizational Behavior Management (OBM) over the last two decades. In this paper, we revisit the behavior analytic conceptualization of motivation and highlight recent developments that may contribute to further research and application in OBM. This paper includes a proposed consideration of verbal stimuli (e.g., rules, goals, and values) as potential intervening variables to motivate performance in organizational settings.     

Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment

Internet advertising has been the fastest growing advertising channel in recent years, with paid search ads comprising the bulk of this revenue. We present results from a series of large‐scale field experiments done at eBay that were designed to measure the causal effectiveness of paid search ads. Because search clicks and purchase intent are correlated, we show that returns from paid search are a fraction of non‐experimental estimates. As an extreme case, we show that brand keyword ads have no measurable short‐term benefits. For non‐brand keywords, we find that new and infrequent users are positively influenced by ads but that more frequent users whose purchasing behavior is not influenced by ads account for most of the advertising expenses, resulting in average returns that are negative.     

On‐Shelf Availability,Retail Performance,and External Audits: A Field Experiment

A potential answer to retailer's shelf out‐of‐stocks (OOS), where the item is in the store but customers cannot find it, is to employ third‐party service providers to execute audits and corrections. However, given the nontrivial cost of executing external audits, it is still necessary to assess whether external audits are capable of reducing shelf‐OOS, whether they can be performed in an economical way, and whether the benefits from the audits translate into higher sales. In an effort to address these questions, we partnered with a product manufacturer and a retail service provider and conducted a field experiment in a national retailer's store set. We used transactional data to detect abnormal operations and respond to possible shelf‐OOS by sending auditors to correct empty shelves and incorrect inventory records. At the conclusion of the experiment, we found that Stock Keeping Units in the treatment group were less likely to have shelf‐OOS and inventory record inaccuracies, and that our intervention had a positive effect on sales. Furthermore, we found that the external audit initiative is economically viable since these improvements required low auditing efforts after a transitional period, and in steady state the cost of running the program is a small fraction of the benefits it generates. We discuss the limitations of our study and the implications of our findings for researchers and practitioners.     

The Path‐Dependent Nature of R&D Search: Implications for (and from) Competition

We formalize R&D as a search process for technology improvements across different technological domains. Technology improvements from a specific domain draw upon a common knowledge base, and as such they share technological content. Moreover, different domains may rely on similar scientific principles, and therefore, knowledge about the technology improvements by one domain might be transferable to another. We analyze how such a technological relatedness shapes the direction of R&D search when knowledge generated from past search efforts disseminates to rival firms. We show that firms optimally diversify their search efforts, even toward domains that are riskier and less promising on expectation. This is amplified for higher competition intensity, i.e., higher cross‐product substitutability. Our work also suggests that different sources of learning about the domains may have opposite effects on the direction of search. Higher ability to infer the potential of an explored domain prompts the clustering of searches, whereas the ability to learn across domains prompts diversification. Finally, we discuss the technological landscape properties that prompt firms to engage in a sequential R&D search, instead of a parallel competitive search.     

First‐Price Auctions With General Information Structures: Implications for Bidding and Revenue

We explore the impact of private information in sealed‐bid first‐price auctions. For a given symmetric and arbitrarily correlated prior distribution over values, we characterize the lowest winning‐bid distribution that can arise across all information structures and equilibria. The information and equilibrium attaining this minimum leave bidders indifferent between their equilibrium bids and all higher bids. Our results provide lower bounds for bids and revenue with asymmetric distributions over values. We also report further characterizations of revenue and bidder surplus including upper bounds on revenue. Our work has implications for the identification of value distributions from data on winning bids and for the informationally robust comparison of alternative auction mechanisms.     

Improving the Impact and Implementation of Disaster Education: Programs for Children Through Theory‐Based Evaluation

A main weakness in the evaluation of disaster education programs for children is evaluators’ propensity to judge program effectiveness based on changes in children's knowledge. Few studies have articulated an explicit program theory of how children's education would achieve desired outcomes and impacts related to disaster risk reduction in households and communities. This article describes the advantages of constructing program theory models for the purpose of evaluating disaster education programs for children. Following a review of some potential frameworks for program theory development, including the logic model, the program theory matrix, and the stage step model, the article provides working examples of these frameworks. The first example is the development of a program theory matrix used in an evaluation of ShakeOut, an earthquake drill practiced in two Washington State school districts. The model illustrates a theory of action; specifically, the effectiveness of school earthquake drills in preventing injuries and deaths during disasters. The second example is the development of a stage step model used for a process evaluation of What's the Plan Stan?, a voluntary teaching resource distributed to all New Zealand primary schools for curricular integration of disaster education. The model illustrates a theory of use; specifically, expanding the reach of disaster education for children through increased promotion of the resource. The process of developing the program theory models for the purpose of evaluation planning is discussed, as well as the advantages and shortcomings of the theory‐based approaches.     

“Know What to Do If You Encounter a Flash Flood”: Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making

Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder‐area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods.