Knowledge that Transforms

The consequences of illness have two crucial types of stakes: for the self and for the family. Therefore, this research examines the effectiveness of health messages that present consequences for the self or for the family, focusing specifically on the dual role of emotions in serving these stakes as a provider of resources and information. The authors theorize that (1) the valence dimension of discrete emotions influences resources, thus fostering or hindering the processing of aversive health information, whereas (2) the self-/other-relatedness dimension of discrete emotions provides information that interacts with the focal referent in the message (self or family) to determine compatibility. In Experiments 1–3, the authors demonstrate that when people are primed with a positive emotion (e.g., happiness, peacefulness), the compatibility between the referent and the discrete emotion fosters the processing of health information. When the primed emotion is negative (e.g., sadness, agitation), howe...

When retailers make product assortment changes by eliminating certain stockkeeping units (SKUs), how does this affect sales of individual brands? This is the main question the authors address in this article. Using data from an online retailer that implemented a permanent systemwide SKU reduction (SR) program, the authors investigate how the program affected various components of purchase behavior for individual brands. They find substantial variations in the SR effects across brands, categories, and consumers. They explore possible drivers for these differences and find that higher-market-share, higher-priced, and more frequently promoted brands tend to gain share and that reduction in the number of sizes, reduction in the number of SKUs, and change in SKU share in the category are important in affecting change in a brand's purchase share after the SR. They also find that SRs lead to an increase in category purchase incidence and quantity for highly state-dependent consumers and frequent buyers but a decrease in category purchase and quantity for mildly state-dependent consumers and infrequent buyers. In addition, SRs tend to cause more changes in brand choice probabilities among consumers of lower state dependence and higher price and promotion sensitivity. These findings are of importance both to retailers wanting to make product assortment changes and to manufacturers affected by them.

There are ample reasons that geographic variation in brand share persists. This comment highlights intentional strategies and feedback loops. Trade promotion, advertising, coupons, and special events are likely to be differentially allocated on the basis of market position and may have different effectiveness. Distribution is highly correlated with share, and distribution can be easier to get and maintain in strong markets. The interaction between retailers and manufacturers at the category level can be strong and persistent and can be observed in market-level data as a market effect.

The other journals responded by moving into each other’s turf. Under Steve Shugan, Marketing Science has proudly expanded its focus from high symbol density to high impact, regardless of the area. Under John Deighton, Journal of Consumer Research has moved away from consumer psychology and toward consumer research that is generally relevant to understanding consumers and marketing managers. Finally, under Roland Rust, Journal of Marketing has moved away from applications-based articles for managers and theorists and toward more analytic and modelingoriented articles. What created this drive toward the center, this erosion of partitions that previously rationalized the premier journals? Part of the erosion arose from the reasonable desire on the part of each editor to get the articles with the most impact in the field and an unwillingness to reject preemptively articles that did not fit a predetermined mold. In addition, each new editor would feature his or her personal areas of expertise without excluding those of the predecessor. This mission creep was supported by the broad skills of large review boards and teams of AEs who could make up for the limitations of any one editor. Simply put, editors poached each other’s territory because they could; even if editors did not understand an issue, there were review board members or AEs who understood it well. Who are the winners and losers in this increasingly competitive academic marketplace? What are the implications for editors, readers, and the field in general? I believe that the editors now have a more difficult job because they must process more articles across a broader range of topics. Moreover, if they do not do their jobs well, they could visibly lose out to the competition. From the perspective of a reader, it could be argued that information gathering is less efficient because each journal can no longer be counted on to carry its traditional assortment of articles. However, in today’s system of Web-based access to journal articles, this loss of efficiency is arguably less binding than it was even five years ago. I believe that the field and the authors are the big winners as journal editors jockey for dominance. The authors are winners because editors actively compete for their work. This increased author power leads to several changes. Reviews have become noticeably more civil and constructive, if not less painful. Turnaround time has dropped by at least a factor of two as the editors compete on the number of days to respond to authors. It is theoretically possible for a person to have the same article reviewed by all four journals within a year. The gain to the field is that February, the first annual issue of Journal of Marketing Research (JMR), is the traditional time for new JMR editors to answer questions about their policies. What kind of work will be favored? How will the new editor try to shape the field? The purpose of this first editorial is to answer such questions. The simple answer can be given in one sentence. Through the associate editor (AE) system, I will broaden the range of articles that JMR publishes and focus on highimpact articles that reflect the cutting edge of research while striving to make them increasingly accessible to a wider range of scholars and practitioners.

Bronnenberg, Dhar, and Dube (2007) show that there is a large geographic variation in market shares and perceived quality levels of a large sample of “national” and “regional” brands across many consumer packaged good categories, and they demonstrate that their geographic findings are new to academics. In this comment, the author shows that practice has been ahead of academics in this basic understanding. He then shows how a point of real leverage is to allocate marketing resources geographically on the basis of market response. There seems to be as much or more variation in market response to resources such as advertising and promotion as there is in market shares. This comment concludes with a plea for more interaction between academics and practitioners.

The authors model how to measure consumer willingness to pay (WTP) using an English, or ascending first-price, auction based on two general bidding premises: No bidder bids more than his or her WTP, and no bidder allows a rival bidder to win at a price that he or she is willing to beat. In other words, the authors propose a “no-regret” rule in bidding. They impose no other restrictive assumptions on “maximands” or the bidders' behaviors in a competitive auction context. The authors model WTP as having two components: a pure product feature component and one based on the auction market environment. The latter includes bidder experience, seller reputation, and measures for competition among bidders and items. The proposed model is general enough to include a “buy-it-now” (equivalent to a posted price) auction mechanism. The authors use data on notebook auctions from one of the largest Internet auction sites in Korea. They find that most product characteristics matter in the expected ways. There are two additional primary findings: First, WTP declines as more similar items are concurrently listed with the focal item; there is an additional effect if these similar items also belong to the same brand. Therefore, market thickness matters for consumer WTP. Second, more extensive site surfing and bidding histories lead to lower WTP, implying that search costs and experience matter in bidding. As specific substantive benefits, the authors demonstrate how sellers can calculate changes in WTP and, thus, the expected revenue as the number of concurrently available similar items varies.

This study addresses a problem commonly encountered by marketers who attempt to assess the impact of their sales promotions—namely, the lack of data on competitive marketing activity. In most industries, competing firms may have competitive sales data from syndicated services or trade organizations, but they seldom have access to data on competitive promotions at the customer level. Promotion response models in the literature either have ignored competitive promotions, focusing instead on the focal firm's promotions and sales response, or have considered the ideal situation in which the analyst has access to full information about each firm's sales and promotion activity. The authors propose a random coefficients hidden Markov promotion response model, which takes the competitor's unobserved promotion level as a latent variable driven by a Markov process to be estimated simultaneously with the promotion response model. This enables the authors to estimate cross-promotion effects by imputing the level of competitive promotions. The authors test the proposed model on synthetic data through a Monte Carlo experiment. Then, they apply and test the model to actual prescription and sampling data from two main competing pharmaceutical firms in the same therapeutic category. The two tests show that compared with several benchmark models, the proposed random coefficients hidden Markov model successfully imputes unobserved competitive promotions and, accordingly, reduces biases in the own- and cross-promotion parameters. Furthermore, the proposed model provides better predictive validity than the benchmark models.

When do internal reference prices differ from articulated price expectations? The authors propose that the internal reference price depends not only on the magnitude of the expected price but also on the confidence associated with this expectation. Four experiments delineate the effects of price expectation and confidence on the internal reference price. In Experiments 1 and 2, the authors manipulate repetition and examine the effects of repetition-induced confidence on price judgments. In Experiments 3 and 4, they manipulate confidence directly to investigate its effects on judgments. The results from all four experiments suggest that consumers with less confidence have higher internal reference prices than more confident consumers, even when they do not differ in their articulated price expectations. The authors discuss the implications of these results for pricing theory.