Marketing

Companies are collecting increasing amounts of information about their customers. This effort is based on the assumption that more information is better and that this information can be leveraged to predict customers' behavior in a variety of situations and product categories. For example, information about a customer's purchase behavior in one category can be helpful in predicting his potential behavior in a related category, which in turn could help a firm in its cross-selling efforts.

The authors propose that the revenue premium a brand generates compared with that of a private label product is a simple, objective, and managerially useful product-market measure of brand equity. The authors provide the conceptual basis for the measure, compute it for brands in several packaged goods categories, and test its validity. The empirical analysis shows that the measure is reliable and reflects real changes in brand health over time.

Customized communications have the potential to reduce information overload and aid customer decisions, and the highly relevant products that result from customization can form the cornerstone of enduring customer relationships. In spite of such potential benefits, few models exist in the marketing literature to exploit the Internet's unique ability to design communications or marketing programs at the individual level. We develop a statistical and optimization approach for customization of information on the Internet.

In this research, we tested the effects of chronic and temporary sources of accessibility on impression formation. Although some research suggests that chronicity amplifies temporary effects because of greater susceptibility to external primes, other research suggests that chronicity masks temporary effects because of redundance. We demonstrate in a thought listing study that in the domain of gender stereotypes, trait stereotypes may be routinely applied by those with a medium or high tendency to stereotype women, making external primes redundant.

Customer Experience Management introduces the five-step CEM process that managers can use to connect with their customers at every touch-point. It provides cases of successful CEM implementations in a wide variety of consumer and B2B industries.

In recent years, there has been a wealth of research examining the relevance of culture to consumer behavior. This chapter reviews a particular line of work within this larger body of research: work investigating the unique relevance of language. Our review finds that both structural features of language (properties of grammar) and lexical-semantic and phonological features of language (related to writing systems) are important.

This research focuses on the diffusion patterns of the adjacent generations of technology and its relation to the time that elapses between them (intergeneration time). The authors analyze 45 new technologies in 15 industries and find that the adoption curves systematically vary across generations from 2 years for dynamic random-access memory (DRAM) chips to more than 30 years for steelmaking. The longer the intergeneration time, the slower the adoption of the subsequent technology.

We propose and test new adaptive question design and estimation algorithms for partial-profile conjoint analysis. Polyhedral question design focuses questions to reduce a feasible set of parameters as rapidly as possible. Analytic center estimation uses a centrality criterion based on consistency with respondents' answers. Both algorithms run with no noticeable delay between questions. We evaluate the proposed methods relative to established benchmarks for question design (random selection, D-efficient designs, adaptive conjoint analysis) and estimation (hierarchical Bayes).