One of the pressing issues in marketing is whether loyalty programs really enhance behavioral loyalty. Loyalty program members may have a much higher share-of-wallet at the firm with the loyalty program than non-members have, but this does not necessarily imply that loyalty programs are effective. Loyal customers may select themselves to become members in order to benefit from the program. Since this implies that program membership is endogenous, we estimate models for both the membership decision (using instrumental variables) and for the effect of membership on share-of-wallet, our measure of behavioral loyalty. We use panel data enhance share-of-wallet, and we provide guidelines how to achieve this.

The importance of pricing decisions for firms has fueled an extensive stream of research on price elasticities. In an influential meta-analytical study, Tellis (1988) summarized price elasticity research findings until 1986. However, empirical generalizations on price elasticity require modifications because of (1) changes in market characteristics (i.e., characteristics of brands, product categories, and economic conditions) and (2) changes in the research methodology used to assess price elasticities. Therefore, the authors present a meta-analysis of price elasticity with new empirical generalizations on its determinants. Across a set of 1851 price elasticities based on 81 studies, the average price elasticity is −2.62. A salient finding is that over the past four decades, sales elasticities have significantly increased in magnitude, whereas share and choice elasticities have remained fairly constant. The authors find that accommodating price endogeneity has a strong (magnitude-increasing) impact on price elasticities. A striking null result is that accounting for heterogeneity does not affect elasticities significantly. The authors also present an analysis that explains the difference between their findings and Tellis's findings, and they indicate which new price elasticity studies are most desirable.

Product-harm crises are among a firm's worst nightmares. A firm may experience (i) a loss in baseline sales, (ii) a reduced own effectiveness for its marketing instruments, (iii) an increased cross sensitivity to rival firms' marketing-mix activities, and (iv) a decreased cross impact of its marketing-mix instruments on the sales of competing, unaffected brands. We find that this quadruple jeopardy materialized in a case study of an Australian product-harm crisis faced by Kraft peanut butter. We arrive at this conclusion by using a time-varying error-correction model that quantifies the consequences of this crisis on base sales, and on own- and cross-brand short- and long-term effectiveness. The proposed modeling approach allows managers to make more informed decisions on how to regain the brands' pre-crisis performance levels.brand management, product recalls, brand equity, marketing and public policy, error-correction models, time-varying parameters, time-series models, missing-data problems, Gibbs sampling methods

The growing sales of private labels (PLs) pose significant challenges for national brands (NBs) around the world. A major question is whether consumers continue to be willing to pay a price premium for NBs over PLs. Using consumer survey data from 22,623 respondents from 23 countries in Asia, Europe, and the Americas across, on average, 63 consumer packaged goods categories per country, this article studies how marketing and manufacturing factors affect the price premium a consumer is willing to pay for an NB over a PL. These effects are mediated by consumer perceptions of the quality of NBs in relation to PLs. Although the results do not bode well for NBs in the sense that willingness to pay decreases as PLs mature, the authors offer several managerial recommendations to counter this trend. In countries in which PLs are more mature, the route to success is to go back to manufacturing basics. In PL development countries, there is a stronger role for marketing to enhance the willingness to pay for NBs.

Social media sites have created a reverberating “echoverse” for brand communication, forming complex feedback loops (“echoes”) between the “universe” of corporate communications, news media, and user-generated social media. To understand these feedback loops, the authors process longitudinal, unstructured data using computational linguistics techniques and analyze them using econometric methods. By assembling one of the most comprehensive data sets in the brand communications literature with corporate communications, news stories, social media, and business outcomes, the authors document the echoverse (i.e., feedback loops between all of these sources). Furthermore, the echoverse has changed as online word of mouth has become prevalent. Over time, online word of mouth has fallen into a negativity spiral, with negative messages leading to greater volume, and firms are adjusting their communications strategies in response. The nature of brand communications has been transformed by online technology as corporate communications move increasingly from one to many (e.g., advertising) to one to one (e.g., Twitter) while consumer word of mouth moves from one to one (e.g., conversations) to one to many (e.g., social media). The results indicate that companies benefit from using social media (e.g., Twitter) for personalized customer responses, although there is still a role for traditional brand communications (e.g., press releases, advertising). The evolving echoverse requires managers to rethink brand communication strategies, with online communications becoming increasingly central.