Customer participation in the production of goods and services appears to be growing. The marketing literature has largely focused on the economic implications of this trend and has not addressed customers’ potential psychological responses to participation. The authors draw on the social psychological literature on the self-serving bias and conduct two studies to examine the effects of participation on customer satisfaction. Study 1 shows that consistent with the self-serving bias, given an identical outcome, customer satisfaction with a firm differs depending on whether a customer participates in production. Study 2 shows that providing customers a choice in whether to participate mitigates the self-serving bias when the outcome is worse than expected. The authors present theoretical and practical implications and provide directions for further research.

The authors use panel data constructed from the responses of repeatedly surveyed top managers at 261 companies regarding their firm's market orientation, along with objective performance measures, to investigate the influence of market orientation on performance for a nine-year period from 1997 to 2005. The authors measure market orientation in 1997, 2001, and 2005 and estimate it in the interval between these measurement periods. The analyses indicate that market orientation has a positive effect on business performance in both the short and the long run. However, the sustained advantage in business performance from having a market orientation is greater for the firms that are early to develop a market orientation. These firms also gain more in sales and profit than firms that are late in developing a market orientation. Firms that adopt a market orientation may also realize additional benefit in the form of a lift in sales and profit due to a carryover effect. Market orientation should have a more pronounced effect on a firm's profit than sales because a market orientation focuses efforts on customer retention rather than on acquisition. Environmental turbulence and competitive intensity moderate the main effect of market orientation on business performance, but the moderating effects are greater in the 1990s than in the 2000s.

Customers form relationships with the employees who serve them as well as with the vendor firms these employees represent. In many cases, a customer's relationship with an employee who is closest to them, a key contact employee, may be stronger than the customer's relationship with the vendor firm. If the key contact employee is no longer available to serve that customer, the vendor firm's relationship with the customer may become vulnerable. In this article, the authors present the results of two studies that examine what business-to-business customers value in their relationships with key contact employees, what customers' concerns are when a favored key contact employee is no longer available to serve them, and what vendor firms can do to alleviate these concerns and to retain employee knowledge even if they cannot retain the employee in that position. The studies are based on a discovery-oriented approach and integrate input from business-to-business customers, key contact employees, and managers from a broad cross-section of companies to develop testable propositions. The authors discuss managerial and theoretical implications and directions for further research.

Customer equity and brand equity are two of the most important topics to academic researchers and practitioners. As part of the 2005 Thought Leaders Conference held at the University of Connecticut, the authors were asked to review what was known and not known about the relationship between brand equity and customer equity. During their discussions, it became clear that whereas two distinct research streams have emerged and there are distinct differences, the concepts are also highly related. It also became clear that whereas the focus of both brand equity and customer equity research has been on the end consumer, there is a need for research to understand the intermediary’s perspective (e.g., the value of the brand to the retailer and the value of a customer to a retailer) and the consumer’s perspective (e.g., the value of the brand versus the value of the retailer). This article represents general conclusions from the authors’ discussion and suggests a modeling approach that could be used to investigate linkages between brand equity and customer equity as well as a modeling approach to determine the value of the manufacturer to a retailer.

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This paper provides a theoretical explanation for the inconsistent findings from previous econometric analyses of aggregated data concerning the duration of advertising carryover. Using this theoretical explanation and the knowledge of a data interval bias, the paper reviews and summarizes the empirical work in the area of sales response modeling, and then after adjusting for aggregation bias, presents support for an empirical generalization that the average advertising duration interval is of brief duration—typically between six and nine months.advertising, advertising duration/carryover, regression-data aggregation

The authors develop and apply a probabilistic model designed to identify currently nonexporting manufacturers with a relatively high potential for future exports. The proposed model includes a new predictive construct (market expansion ability), which incorporates the time dimension of firm behavior, in addition to more familiar attitudinal constructs such as perceived barriers to exporting. The model is demonstrated with a sample of 345 nonexporting manufacturers. Several evaluative tests, including a test of predictive validity with a sample of 43 current exporters, provide evidence of the model's ability to identify nonexporting manufacturers with export potential.

Many firms are now using referral marketing campaigns to harness the power of word of mouth and to increase referrals to acquire new customers. Prior research has identified a method of computing the value of referrals using only a customer's actual past referral behavior to compute customer referral value (CRV). In this article, the authors develop and test a new four-step approach to compute CRV. In addition, they determine the behavioral drivers of CRV and then identify the most effective methods of targeting the most promising customers on the basis of their customer lifetime value (CLV) and CRV scores. The authors illustrate and test this approach through four separate field experiments with firms from two industries: financial services and retailing. They find that to maximize profitability, it is critical to manage customers in terms of both their CLV and CRV scores and that understanding the behavioral drivers of CRV can help managers better target the most profitable customers with their referral marketing campaigns.