Knowledge that Transforms

Marketers have been challenged by proponents of individual (one-to-one) marketing to shift from focusing on market segments to making individually customized offers. Building on current knowledge regarding the construction of customers’ preferences, the author examines the basic assumptions underlying individual marketing and presents a process model of customers’ responses to customized offers. The model addresses (1) preference development, (2) evaluation of customized offers, (3) likelihood of purchasing the customized offers, and (4) maintenance of relationships with one-to-one marketers. The analysis leads to specific propositions regarding determinants of customers’ responses to customized offers. The author discusses future research directions and managerial implications.

When firms’ customers are located in geographically dispersed areas, it can be difficult to manage service quality because its relative importance is likely to vary spatially. This article shows how addressing such spatial aspects of satisfaction data can improve management's ability to implement programs aimed at enhancing service quality. Specifically, managers can identify areas of high service responsiveness, that is, areas in which overall satisfaction is low but customers are highly responsive to improvements in service quality. The authors estimate the spatial patterns using geographically weighted regression, a technique that accounts for spatial dependence in the variables. They apply this methodology to a large national sample of automobile customers served by a network of dealerships across the United States. The authors also investigate the extent to which factors related to the physical and psychological landscape explain the importance that people in different regions place on dealership service and vehicle quality.

Consumers sometimes encounter a combination of comparative and noncomparative prices in the marketplace. For example, a grocer may employ signage that provides favorable price comparisons with those of a competitor for a portion of its products, a practice that the authors refer to as “partially comparative pricing.” The authors examine the effects of partially comparative pricing on consumer response and find that it has both desirable and undesirable effects. On the one hand, such pricing enhances consumers’ beliefs about the relative prices of comparatively priced products and about the retailer's relative prices in general. On the other hand, such pricing also reduces consumers’ relative price beliefs about noncomparatively priced products and their intentions to purchase such products. The authors further show that the adverse influence of partially comparative pricing stems from consumers’ suspicions about why price comparisons exist for some, but not all, products. They also document how these effects depend on store patronage. They discuss implications of their research and provide suggestions for future empirical efforts.

Prior research has demonstrated a clear negativity effect (greater weighting of candidate weaknesses compared with strengths) in the evaluation of U.S. presidential candidates in each of the past six elections analyzed. The authors adopt a motivational view and question the robustness of this finding. They reanalyze past National Election Studies data along with new data and conclude that the negativity effect is not universal across voters; it is a robust effect only for voters who dislike the candidate. They argue that previous findings are due to aggregation of data across voters who vary in their motivations.

Consider that a firm announces a deadline for a new product introduction. Conditional on such a preannouncement, how must an external observer evaluate whether the product will be delayed beyond that deadline? Using data collected from managers in the computer hardware, software, and telecommunications industries, the authors present an analysis that demonstrates that delays in new product introductions beyond preannounced deadlines can be jointly explained by factors related to (1) the firm's motivations to delay the product, (2) the presence of constraints that prevent delay (or the availability of opportunities to delay the product), and (3) the firm's abilities pertaining to product development.