The authors examine behavioral outcomes following a customer-initiated contact (CIC) with a manufacturer and develop a framework to explain the impact of vendor performance during a CIC on a customer's share of category requirements with a focal brand and word-of-mouth incidence following contact. The authors propose customer characteristics and context-specific factors that may relate to differences in the key characteristics of the underlying source model of share of category requirements and word of mouth. The authors then assess the overall importance of the explanatory variables in the source model and simultaneously test for systematic differences related to CIC-specific factors using survey data from more than 1700 CICs that involve more than 60 brands. A key assumption in much prior research that has examined customer–firm interactions is that CIC-specific factors, if they are included at all, create an automatic regularity that must be controlled for. The authors propose and find an additional effect. The responsiveness to factors under a firm's control varies across CICs, and therefore firms that adapt their processing have an advantage. Rather than provide a uniform response to all CICs, the authors' results offer managers several guidelines on how to customize their responses to the various CIC types and how to improve the efficiency and effectiveness of their firms' CIC management efforts.

In particular, the authors appreciate the support of John Larson. They also thank participants in the Marketing Science Institute-INSEAD Conference on customer relationship management and the anonymous JMR reviewers for comments on a previous version of this article. The second author acknowledges the financial support provided by the Division of Research at the Harvard Business School.

Order of entry has been demonstrated to have a significant effect on market share. A number of explanations for this effect have been suggested in the marketing and strategy literatures. To date, the market share advantage gained by pioneers has typically been treated as a main effect—an automatic regularity. Treating order-of-entry as a main effect implies that there is no penalty on the effectiveness of a brand's marketing instruments for late entry and that a late entrant can compensate for being late by dedicating sufficient marketing resources to their product. In this study, we investigate the influence of order-of-entry into a market on the effectiveness of a firm's marketing mix decisions by asking the question, “Can followers compensate for not being first by their marketing mix decisions?” Also, even if they can compensate for being late, does this effort become increasingly more difficult with later entry? That is, are there asymmetries in the effectiveness of a brand's marketing mix variables that relate to its order of entry into the market, or as has been typically assumed to date, is order of entry strictly a main effect? An asymmetry exists, for example, if the market response to advertising is different for the first entrant versus the second or third entrant. An asymmetry also exists if the effects of, say, a price change by the first entrant on the second entrant are different than the effects on the third entrant. We develop a market share attraction model where the parameters vary as a function of order-of-entry. Our main contribution is in modeling the sources of order-of-entry advantage as asymmetries in the effectiveness of a brand's marketing instruments. Hence, distinct from previous research we explain why there are inherent order-of-entry effects. This paper is potentially of interest to researchers developing market share models and studying the effectiveness of marketing-mix variables. The substantive implication of our results concern directly academics interested in marketing strategy as well as the practicing marketing strategists. We model asymmetries in the market response of early entrants versus late entrants using data from two durables and three nondurables categories. With one exception, all data sets are established from the inception of the category and hence do not suffer from the possible bias of excluding pioneers who have failed. Results show that asymmetries in the effectiveness of a brand's marketing mix variables are an essential source of order-of-entry effects; we find that the main effects of order of entry are minimal. Order-of-entry effects do not necessarily lead to lower shares, but overcoming these effects is not without substantial cost to the late entrant. Our results support previous research that has demonstrated advantages to early entry. In addition, we provide guidelines for how late entrants should compete. Later entry tends to reduce a competitor's price sensitivity, suggesting that they not instigate in a price war with earlier entrants in order t...

This research studies a neglected dimension of competitive defensive strategy—the speed of a competitor's reaction to the introduction of a new product. Building on the literature in organizational and strategic management, the authors investigate how the strategic pressures facing a firm and its organizational characteristics influence the speed with which it is willing and able to respond. A model that considers the ordered nature of the dependent measure is specified and estimated using PIMS data on industrial and consumer product manufacturers. Market growth, the market share of the reacting firm, the typical new product development time and the frequency of product changes in the industry, and the market share of the threatening firm appear to be significant determinants of reaction time.

The authors examine how brand preferences and response to marketing activity evolve for consumers new to a market. They develop a theoretical framework that begins with a consumer's first-ever purchase in a product category and describes subsequent purchases as components of sequential purchasing stages. The theory is based on the notion that choices made by consumers new to a market are driven by two competing forces: consumers' desire to collect information about alternatives and their aversion to trying risky ones. These forces give rise to three stages of purchasing: an information collection stage that focuses initially on low-risk, big brand names; a stage in which information collection continues but is extended to lesser-known brands; and a stage of information consolidation leading to preference for the brands that provide the greatest utility. The authors use a logit-mixture model with time-varying parameters to capture the choice dynamics of different consumer segments. The results show the importance of accounting for product experience and learning when studying the dynamic choice processes of consumers new to a market. Insights from this study can help marketers tailor their marketing activities as consumers gain purchasing experience.