Knowledge that Transforms

Interconnect standards increase choices. For example, in cardiac pacemakers, the IS-1 standard enables the “pulse generator” from 6 manufacturers to be combined with the “lead set” from the other 5 to create up to 30 additional mixed-brand pacemakers. However, observed assortment additions are much smaller, which is puzzling because manufacturers in extant models have welcomed such additions to reduce price competition and increase variety. Instead, conflict with the value-added resellers that create and carry these additions is commonplace. The authors extend the literature with an analytical model showing that value-added resellers limit the number and composition of additions to gain better upstream terms. This conflict is exacerbated when “keystone” components are relatively more decisive in influencing customer choices, so their exclusion from an addition represents a larger loss. The empirical study of the multibillion-dollar auto paint refinish market finds assortment additions consistent with the authors’ predictions. The article concludes with a discussion of the role of channel support programs in ameliorating these conflicts.

The question of whether customer satisfaction is mispriced by the stock market has been debated over the past decade, yet it remains unintegrated with the broader asset pricing literature. The authors critique Fornell, Morgeson, and Hult (2016) , focusing on that article's missed opportunities in addressing theoretical lacuna and empirical challenges that might establish the satisfaction mispricing anomaly. In doing so, they distinguish mispricing from value relevance, classify two broad avenues for satisfaction mispricing research, and detail the scope of future research under each avenue. They conclude by summarizing specific research opportunities and presenting implications for managers, investors, and educators that could lead marketing to become a net contributor to the marketing–finance dialogue.

A common assumption made in structural approaches to empirical strategy research in marketing is that firms and consumers satisfy the assumptions of dynamic optimality when making decisions. When faced with problems of how best to allocate resources, firms are assumed consider the future consequences of different strategic options and, in each point in time, choose the option that maximizes long-term utility. The validity of such assumptions, however, is often called into question by behavioral researchers who point to work in psychology that finds that assumptions of optimality are frequently violated in experimental settings. If this is indeed the case, it would lend support to approaches that argue that markets have inefficiencies that can be discovered and exploited by simpler, largely correlational, methods. In this article, the authors attempt to reconcile these contrasting views by proposing a framework for assessing when assumptions of dynamic optimality are likely to be good ones and when they are likely to be untenable in empirical analysis.

Category management (CM) has become a widespread trade practice in recent years. A category manager's decision problem is complex and multifaceted owing to demand dependencies across products and across time. Extant research on CM has typically focused on one or the other of these dependencies, but seldom both. The authors address this research gap by presenting a competition framework that reconciles cross-sectional breadth (large numbers of stockkeeping units in any given period) with longitudinal depth (demand effects across time). The endeavor is to offer retailers a general, realistic, and practical CM approach by comprehensively accounting for competitive effects. The authors demonstrate their approach using real-world data in the beer category for a midsize grocery chain in the northeastern United States. After determining the optimal weekly prices for the entire assortment over 23 weeks, the authors report a profit yield that is 3.30% more than in the benchmark logit model and substantially more than in the retailer's current everyday low price policy.

A key decision for the design of principal–agent agreements is how much control or authority the buyer (or principal) should be allowed to exercise in relation to the seller (or agent). Historically, agency theory has viewed exchange agreements as ranging from those in which the buyer has very high authority over the seller (formal authority) to those in which the buyer and seller are relatively independent so there is little or no authority relation (market exchange). However, some principal–agent agreements reverse the authority relationship usually assumed in agency theory by allowing the seller to exercise authority over the buyer. The authors study this unexplored type of agency agreement and refer to it as “authority relinquishment.” Using data collected from interviews with clients and guides on commercial high-altitude mountain expeditions, the authors identify conditions that make authority relinquishment likely. They also identify the benefits and drawbacks of authority relinquishment and compare them with the benefits and drawbacks of two frequently studied approaches to managing agency relationships—formal authority and authority decentralization.

Sorescu and Sorescu (2016) and Bharadwaj and Mitra (2016) have made a number of insightful observations and suggestions for future research regarding stock returns on customer satisfaction. They have also provided a series of assessments of a study by Fornell, Morgeson, and Hult (2016) that focus on abnormal returns on customer satisfaction. Building on the original study, as well as the two commentaries and previous research, the study's authors argue that the published empirical evidence is quite consistent in favor of abnormal returns on customer satisfaction. These findings are also supported by the new analysis of Sorescu and Sorescu, who make several important contributions, not only regarding the persistence of abnormal returns over and beyond the technology sector but also with respect to the critical importance of industry classification in the context of customer satisfaction—something that definitely calls for more research attention. In fact, there are many avenues for future research on the economic and financial impact of customer satisfaction, as laid out in the commentaries, the authors’ original article, and this response.

Trade shows are a popular venue for firms to demonstrate their portfolio of market-ready new products as well as product concepts under different stages of development. Utilizing auto shows as a context, the authors investigate the effects of concept and product demonstrations on the demonstrating firm's value. Event study results show that abnormal returns follow an inverted U-shaped effect of product development stages: that is, previously demonstrated concepts approaching potential launch have the strongest positive effect, followed by early-stage concepts demonstrated for the first time to the world (i.e., debuts), and then market-ready new products. Trade show locations mediate these effects. The effects of early-stage debut demonstrations appear only when concepts are presented in trade shows located in the home country of the demonstrating firm. However, the effects of displaying previously demonstrated concepts, which have survived product development hurdles, are present in venues within as well as outside the firm's home country.

Steady customer losses create pressure for firms to acquire new accounts, a task that is both costly and risky. Lacking knowledge about their prospects, firms often use a large array of predictors obtained from list vendors, which in turn rapidly creates massive high-dimensional data problems. Selecting the appropriate variables and their functional relationships with acquisition probabilities is therefore a substantial challenge. This study proposes a Bayesian variable selection approach to optimally select targets for new customer acquisition. Data from an insurance company reveal that this approach outperforms nonselection methods and selection methods based on expert judgment as well as benchmarks based on principal component analysis and bootstrap aggregation of classification trees. Notably, the optimal results show that the Bayesian approach selects panel-based metrics as predictors, detects several nonlinear relationships, selects very large numbers of addresses, and generates profits. In a series of post hoc analyses, the authors consider prospects’ response behaviors and cross-selling potential and systematically vary the number of predictors and the estimated profit per response. The results reveal that more predictors and higher response rates do not necessarily lead to higher profits.

In the preceding article, Fornell, Morgeson, and Hult (2016b) find that customer satisfaction produces abnormal returns and that customer satisfaction does have a direct and tangible financial benefit for firms. Given the unconventional nature of their findings, the authors’ research will be of great interest to marketing academics. In addition, this research will be of direct relevance to marketing practitioners in demonstrating the financial impact of customer satisfaction and reemphasizing the importance of managing customers effectively.