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. Empirical generalizations on price elasticity, however, require modifications because of: a) changes in market characteristics, i.e. characteristics of brands, product categories, and economic conditions, and b) changes in the research methodology to assess price elasticities. Therefore, we present a meta-analysis of price elasticity with new empirical generalizations on its determinants. Across a set 1851 price elasticities based on 81 studies, the average price elasticity is −2.62. One of the most salient findings is that over the past four decades, sales elasticities have significantly increased in magnitude, whereas share and choice elasticities have remained fairly constant. Across all determinants studied, we find that accommodating price endogeneity has the strongest (magnitude-increasing) impact on price elasticities. A striking null result is that accounting for heterogeneity does not affect elasticities significantly. We also present an analysis that explains the difference between our findings and Tellis (1988), and indicate which new price elasticity studies are most desirable

Rentrak, and Michael A. Marcell at Nielsen EDI who all kindly provided data for this study. This

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The authors are listed in reverse alphabetical order. They gratefully acknowledge the support of IRI/Europanel, who provided the data on which this study is based. They thank the participants at the MSI Conference on Competitive Reaction for constructive comments on an earlier draft of this work. Financial support by the Flemish Science Foundation (F.W.O) under grant G.0145.97 and the Research Council of the Catholic University of Leuven under grant OT.96.4 is greatly How do competitors react to each other’s price-promotion and advertising actions? How do these reactions influence the net sales impact we observe? We answer these questions by performing a large-scale empirical study of the short-run and long-run reactions to promotion and advertising shocks in over 400 consumer product categories, over a four-year time span. Competitive reaction can be passive, accommodating or retaliatory. We first develop a series of expectations on the type and intensity of reaction behavior, and on the moderators of this behavior. These expectations are assessed in two ways. First, vector-autoregressive models quantify the short-run and long-run effect of a promotion or advertising action on competitive sales and on competitive reactions. By cataloging the numerical results, we are able to formulate

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Services for providing the data. They thank Els Gijsbrechts and Marnik Dekimpe for useful comments on a previous version. Do Loyalty Programs Enhance Behavioral Loyalty? An Empirical Analysis Accounting for Program Design and Competitive Effects This paper studies the effects of loyalty programs on share-of-wallet using marketwide household panel data on supermarket purchases. We find that loyalty programs relate positively to share-of-wallet, but the programs differ in effectiveness and some are ineffective. Both a saving component and a multi-vendor structure enhance the effectiveness of a loyalty program, but high discounts do not lead to higher share-ofwallets. Further, if households have multiple loyalty cards, the effectiveness of a specific loyalty program is much smaller. The positive loyalty program effects on share-of-wallet entail substantial additional customer revenues. However, given the high number of loyalty programs already available in the market, our model predicts that a new loyalty program introduction will only lead to small effects on share-ofwallet. JEL-code: M31 Key-words: Marketing, retailing, loyalty programs, tobit-model, attraction model

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Wosinska, and the anonymous MSI and Journal of Marketing reviewers for their valuable comments and suggestions. ROI Implications for Pharmaceutical Promotional Expenditures: The Role of Marketing Mix Interactions The authors empirically explore the revenue impact of marketing mix variables and their interactions. The findings include: pharmaceutical direct to consumer advertising (DTC) and detailing (sales force) affect demand synergistically; detailing raises price elasticity; and, detailing has a higher ROI than DTC. Recent years have seen an explosive growth in direct to consumer advertising (DTC) by pharmaceutical manufacturers. Pharmaceutical DTC expenditures varied from a little less than a billion in 1996 to 2.5 billion in 2000. Contrast that to expenditures on detailing (where sales reps detail the physicians in their offices), which have increased from 8 billion dollars in 1995 to only about 9 billion in