Venkatesh Shankar

Customer value, satisfaction, loyalty, and switching costs: An illustration from a business-to-business service context

Although researchers and managers pay increasing attention to customer value, satisfaction, loyalty, and switching costs, not much is known about their interrelationships. Prior research has examined the relationships within subsets of these constructs, mainly in the business-to-consumer (B2C) environment. The authors extend prior research by developing a conceptual framework linking all of these constructs in a business-to-business (B2B) service setting. On the basis of the cognition-affect-behavior model, the authors hypothesize that customer satisfaction mediates the relationship between customer value and customer loyalty, and that customer satisfaction and loyalty have significant reciprocal effects on each other. Furthermore, the potential interaction effect of satisfaction and switching costs, and the quadratic effect of satisfaction, on loyalty are explored. The authors test the hypotheses on data obtained from a courier service provider in a B2B context. The results support most of the hypotheses and, in particular, confirm the mediating role of customer satisfaction.

Customer Satisfaction and Loyalty in Online and Offline Environments

Abstract We address the following questions that are becoming increasingly important to managers in service industries: Are the levels of customer satisfaction and loyalty for the same service different when customers choose the service online versus offline? If yes, what factors might explain these differences? How is the relationship between customer satisfaction and loyalty in the online environment different from that in the offline environment? We propose a conceptual framework and develop hypotheses about the effects of the online medium on customer satisfaction and loyalty and on the relationships between satisfaction and loyalty. We test the hypotheses through a simultaneous equation model using two data sets of online and offline customers of the lodging industry. The results are somewhat counterintuitive in that they show that whereas the levels of customer satisfaction for a service chosen online is the same as when it is chosen offline, loyalty to the service provider is higher when the service is chosen online than offline. We also find that loyalty and satisfaction have a reciprocal relationship such that each positively reinforces the other, and this relationship between overall satisfaction and loyalty is further strengthened online.

Are the Drivers and Role of Online Trust the Same for All Web Sites and Consumers?: A Large-Scale Exploratory Empirical Study

This research investigates the determinants and role of consumer trust in e-business. It examines consumer perceptions of trust in a Web site and addresses the following key research questions: What factors influence consumer trust in a Web site and what specific Web site trust cues are associated with these factors? How does trust affect consumer behavioral intent on a Web site? To address these questions, we develop a conceptual model that links consumer perceptions of Web site characteristics, consumer characteristics and demographics to perceptions of trust in a Web site, and trust to behavioral intent related to a Web site. We also examine whether trust mediates the relationship between Web site and consumer characteristics and behavioral intent related to the Web site. We test our hypotheses in a large-scale empirical study that estimates this model from 6831 consumers across 25 Web sites and eight industry categories. We validate the model using a holdout sample. The results show that Web site, consumer, category and demographic variables can explain 76% of the variance in trust. Web site characteristics such as privacy and security, navigation, presentation, brand, and advice account for as much as 98% of this explained variance in Web site trust. Surprisingly, over 80% of the explained variance in Web trust is due to factors other than privacy and security-mainly navigation, brand, advice, absence of errors, and presentation. We also find that trust mediates the relationships between Web site and consumer characteristics and behavioral intent related to Web sites. The results offer important implications for Web site strategies that include the manipulation of factors influencing Web site trust to favorably impact consumer behavior at the Web site

Challenges and Opportunities in Multichannel Customer Management

Multichannel customer management is the design, deployment, coordination, and evaluation of channels through which firms and customers interact, with the goal of enhancing customer value through effective customer acquisition, retention, and development. The authors identify five major challenges practitioners must address to manage the multichannel environment more effectively: (a) data integration, (b) understanding consumer behavior, (c) channel evaluation, (d) allocation of resources across channels, and (e) coordination of channel strategies. The authors also propose a framework that shows the linkages among these challenges and provides a means to conceptualize the field of multichannel customer management. A review of academic research reveals that this field has experienced significant research growth, but the growth has not been distributed evenly across the five major challenges. The authors discuss what has been learned to date and identify emerging generalizations as appropriate. They conclude with a summary of where the research-generated knowledge base stands on several issues pertaining to the five challenges.

LATE MOVER ADVANTAGE : HOW INNOVATIVE LATE ENTRANTS OUTSELL PIONEERS

Although pioneers outsell late movers in many markets, in some cases innovative late entry has produced some remarkably successful brands that outsell pioneers. The mechanisms through which innovat...

Network Effects and Competition: An Empirical Analysis of the Home Video Game Industry

Building on the resource‐based view of the firm, we advance the idea that a firms customer network can be a strategic asset. We suggest that network effects are a function of network size (i.e., installed customer base) and network strength (i.e., the marginal impact of a unit increase in network size on demand). We empirically study these network effects in the 16‐bit home video game industry in which the dominant competitors were Nintendo and Sega. In the spirit of the new empirical IO framework, we estimate a structural econometric model assuming the data are equilibrium outcomes of the best fitting noncooperative game in price and advertising. After controlling for other effects, we find strong evidence that network effects are asymmetric between the competitors in the home video game industry. Specifically, we find that the firm with a smaller customer network (Nintendo) has higher network strength than the firm with the larger customer base (Sega). Thus, our results provide a possible explanation for this situation in which the firm with a smaller customer network (Nintendo) was able to overtake the sales of a firm with a larger network size (Sega). Copyright

Can Price Dispersion in Online Markets Be Explained by Differences in E-Tailer Service Quality?

It has been hypothesized that the online medium and the Internet lower search costs and that electronic markets are more competitive than conventional markets. This suggests that price dispersion of an item with the same measured characteristics across sellers at a given point in time for identical products sold by e-tailers online should be smaller than it is offline, but some recent empirical evidence reveals the opposite. Based on an empirical analysis of 105 e-tailers comprising 6.739 price observations for 581 items in eight product categories, the authors show that online price dispersion is persistent, even after controlling for e-tailer heterogeneity. The general conclusion is that the proportion of the price dispersion explained by e-tailer characteristics is small. Also, after controlling for differences in e-tailer service quality, prices at pure-play e-tailers are equal to or lower than those at bricks-and-clicks e-tailers for all categories except books and computer software.

Price Levels and Price Dispersion Within and Across Multiple Retailer Types: Further Evidence and Extension

In this article, the authors develop hypotheses on how prices and price dispersion compare among pure-play Internet, bricks-and-mortar (traditional), and bricks-and-clicks (multichannel) retailers and test them through an empirical analysis of data on the book and compact disc categories in Italy during 2002. Their results, based on an analysis of 13,720 prkce quotes, show that when posted prices are considered, traditional retailers have the highest prices, followed by multichannel retailers, and pure-play e-tailers, in that order. However, when shipping costs are included, multichannel retailers have the highest prices, followed by pure-play e-tailers and traditional retailers, in that order. With regard to price dispersion, pure-play e-tailers have the highest range of prices, but the lowest standard deviation. Multichannel retailers have the highest standard deviation in prices with or without shipping costs. These findings suggest that online markets offer opportunities for retailers to differentiate within and across the retailer types.

New Product Preannouncements and Shareholder Value: Don't Make Promises You Can't Keep

New product preannouncements are strategic signals that firms direct at their customers, competitors, channel members, and investors. They have been touted as effective means of deterring competitor entry, informing potential customers, and even tipping the balance of technological standard battles in favor of the preannouncing firms. However, preannouncements also carry the risks of unwanted competitive reaction and the negative consequences of undelivered promises. From a shareholder value standpoint, do the benefits outweigh the risks of preannouncing? To address this question, the authors build on agency and signaling theories to develop hypotheses about the effects of preannouncements on shareholder value, and they empirically test these hypotheses on a sample of software and hardware new product preannouncements. The findings indicate that the financial returns from preannouncements are significantly positive in the long run. The authors show that preannouncements generate positive short-term abnormal returns only for firms that offer specific information about the preannounced product. They also show that firms earn positive long-term abnormal returns after a preannouncement if they continue to update the market on the progress of the new product. Both the short-term and the long-term returns are further magnified if the reliability of the preannouncement (i.e., the credibility of the preannouncing firm) is high. The findings offer executives of preannouncing firms clear guidelines on how to manage communications in the market to extract financial value from new product preannouncements.

The Roles of Channel-Category Associations and Geodemographics in Channel Patronage

Consumers purchase goods from various channels or retail formats, such as grocery stores, drugstores, mass merchandisers, club stores, and convenience stores. To identify the most appropriate channels and to allocate the distribution of products among channels efficiently, managers need a better understanding of consumer behavior with respect to these channels. The authors examine the moderating role of channel-category associations in consumer channel patronage by extending the literature on brand associations to the context of channels, and they estimate a model that links channel-category associations with consumer geodemographics and channel share of volume. The authors first identify the product categories associated with particular channels through a correspondence analysis of a field-intercept survey. They then use the channel-category associations and geodemographic factors to estimate their direct and interactive effects on channel share of volume. The channel-category associations have significant main effects and interaction effects with channel type and geodemographic factors on channel share of volume, and they account for the majority of the explained variance (72%) in channel share of volume. Overall, the findings provide several conceptual and managerial insights into consumer channel perceptions and patronage behavior.