Knowledge that Transforms

Marketing Science greatly benefited from the admirable and fastidious efforts of more than 200 different individuals who provided manuscript reviews last year. Beyond those individuals already recognized on the editorial board, the editor-in-chief and guest editors of Marketing Science are indebted to the many guest editors, guest associate editors, and ad hoc reviewers who provided expert counsel and guidance on a voluntary basis. The following list acknowledges the contribution of guest editors, guest associate editors, and ad hoc reviewers who served from January 1, 2017 to December 31, 2017. Finally, our sincere appreciation to the authors, whose outstanding submissions and careful revisions make the journal the go-to resource for leading edge knowledge in quantitative marketing. K. Sudhir Yale University

This report describes entrants in the 2016 ISMS Gary Lilien Marketing Science Practice Prize Competition, representing the best examples of rigor plus relevance that our profession produces. The winner, describing a collaboration between the World Bank and a team based at the London Business School, involved a randomized control experiment to calibrate the relative effectiveness of business training on business performance of microentrepreneurs in South Africa. The other four finalists include a method to estimate the value of key word searches that allowed for cannibalization of organic search at eBay; a methodology to model and manage customer satisfaction at the National Dutch Railways; a stock-carrying algorithm to assist a fashion department store manage inventory on a store-by-store basis, implemented by Celect, an inventory-management consultant based in Boston; and an integrated marketing communications-optimization tool used by Mercedes-Benz to increase advertising effectiveness.

This paper investigates a manufacturer’s ability to influence compliance rates among its authorized online retailers by exploiting changes in the minimum advertised price (MAP) policy and in dealer agreements. MAP is a pricing policy widely used by manufacturers to influence prices set by their downstream partners. A MAP policy imposes a lower bound on advertised prices, subjecting violating retailers to punishments such as termination of distribution agreements. Despite this threat, violations are common. I uncover two key elements to improve compliance: customization to the online environment and credible monitoring and punishments. I analyze the pricing, enforcement, and channel management policies of a manufacturer over several years. During this period, new channel policies take effect, providing a quasi-experiment. The new policies lead to substantially fewer violations. With improved compliance, channel prices increase by 2% without loss in volume. The reduction in violations is particularly stark among authorized retailers with lower sales volume, those that previously operated unapproved websites, and those that have received violation notifications for the specific product before. Moreover, low service providers improve their service. At the same time, there is an increase in opportunistic behavior among top retailers, or retailers that received notifications for other products, and for less popular products via deep discounting. Data and the online appendix are available at https://doi.org/10.1287/mksc.2018.1092 .

Quota-based and partial-refund return policies abound in practice between manufacturers and their resellers. While the literature has provided insights into the design of the partial-refund policy, little attention has been directed at the design of the quota-based return policy. Accordingly, this paper explores the relative preference of a quota-based policy vis-à-vis a partial-refund policy. We do this, first, in the context of risk-neutral channel partners to identify the strategic decisions of each party and the effect of demand uncertainty on the variation of their respective profits. Our results reveal that the manufacturer faces higher profit variation (between the different demand realizations) under the quota policy. The variance in profits for the reseller is, however, higher under the partial-refund policy. We explain the source of profit variations by comparing it across different channel structures (centralized and decentralized). Next, we formally extend the model to include a disutility associated with profit variation and show that when the manufacturer has a variation-induced disutility, the partial-refund contract should be used, as it is the dominating contract. Similarly, when the retailer has a variation-induced disutility, the quota contract should be used. This is consistent with the pattern of profit variations in the risk-neutral case where the manufacturer has lower variation with the partial-refund contract while the reseller has lower variation with the quota contract. Finally, our analysis also shows how the manufacturer may employ a combination policy to better manage its own profit variation while providing adequate overstocking protection for the reseller. The online appendix is available at https://doi.org/10.1287/mksc.2018.1094 .

Consumer preferences change through time and firms must adjust their product positioning for their products to continue to be appealing to consumers. These changes in product positioning require fixed investments such that firms reposition only occasionally. I construct a model that can include predictable and unpredictable consumer preference changes, and where a firm optimally repositions its product given the current market conditions, and expected future repositionings. When unpredictable consumer preferences evolve away from a current firm’s positioning, the decision to reposition is like exercising an option to be closer to current consumer preferences, or waiting to reposition later or for those preferences to return so as to be closer to the firm’s current position. We characterize this optimal repositioning strategy, how it depends on the discount factor, variance of preferences, and repositioning costs. I compare the optimal policy of the firm with what could be optimal from a social welfare point of view, and find that the firm repositions more frequently than is efficient when there is full market coverage. With predictable changes in consumer preferences, the optimal repositioning strategy involves overshooting and asymmetric repositioning thresholds. The online appendix is available at https://doi.org/10.1287/mksc.2017.1075 .

In various cultural and behavioral respects, emerging market consumers differ significantly from their counterparts of developed markets. They may thus derive consumption utility from different aspects of product meaning and functionality. Based on this premise, we investigate whether the economic rise of emerging markets may have begun to impact the typical one-size-fits-all design of many international product categories. Focusing on Hollywood films, and exploiting a recent relaxation of China’s foreign film importation policy, we provide evidence suggesting that these impacts may exist and be nonnegligible. In particular, we show that the Chinese society’s aesthetic preference for lighter skin can be linked to the more frequent casting of pale-skinned stars in films targeting the Chinese market. Implications for the design of international products are drawn. Data and the online appendix are available at https://doi.org/10.1287/mksc.2018.1089 .

Online search intermediaries, such as Amazon or Expedia, use rankings (ordered lists) to present third-party sellers’ products to consumers. These rankings decrease consumer search costs and increase the probability of a match with a seller, ultimately increasing consumer welfare. Constructing relevant rankings requires understanding their causal effect on consumer choices. However, this is challenging because rankings are endogenous: consumers pay more attention to highly ranked products, and intermediaries rank the most relevant products at the top. In this paper, I use the first data set with experimental variation in the ranking from a field experiment at Expedia to make three contributions. First, I identify the causal effect of rankings and show that they affect what consumers search, but conditional on search, do not affect purchases. Second, I quantify the effect of rankings using a sequential search model and find an average position effect of $1.92, which is lower than literature estimates obtained without experimental variation. I also use model predictions, data patterns, and a feature of the data set (opaque offers) to show rankings lower search costs, instead of affecting consumer expectations or utility. Finally, I show a utility-based ranking built on this model’s estimates benefits consumers and the search intermediary. Data and the online appendix are available at https://doi.org/10.1287/mksc.2017.1072 .