Online reputation mechanisms are emerging as a promising alternative to more traditional trust building mechanisms, such as branding and formal contracting, in settings where the latter may be ineffective or prohibitively expensive; a lot of electronic trading communities fall under these categories. Although a number of commercial websites already employ various forms of reputation mechanisms, rigorous research into their properties is still in its infancy. This fledgling field can benefit from past results in economics and game theory. Moreover, in order to translate the stylized results of game theory into concrete managerial guidance for implementing and participating in effective reputation mechanisms further advances are needed in a number of important areas: First, the design space of such mechanisms needs to be scoped and the effects of different design choices on performance need to be better understood. Second, the economic efficiency of various classes of reputation mechanisms needs to be quantified and compared to that of alternative mechanisms for building trust. Third, the robustness of those mechanisms against boundedly rational players, noisy ratings and strategic manipulation needs to be studied and improved. This paper surveys past results that have been derived in a variety of contexts, but which are relevant as a basis for building online reputation systems, presents two analytical models that illustrate the role of such systems in electronic markets and identifies opportunities for further MS/OR research in this fascinating area.

With the ever increasing popularity of electronic commerce, the evaluation of antecedents and of customer satisfaction have become very important for the cyber shopping store (CSS) and for researchers. The various models of customer satisfaction that researchers have provided so far are mostly based on the traditional business channels and thus may not be appropriate for CSSs. This research has employed case and survey methods to study the antecedents of customer satisfaction. Though case methods a research model with hypotheses is developed. And through survey methods, the relationships between antecedents and satisfaction are further examined and analyzed. We find five antecedents of customer satisfaction to be more appropriate for online

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. In addition, the relationship between overall satisfaction and loyalty is stronger online than offline and there is a positive reciprocal relationship between loyalty and satisfaction online. These results

Can what you could have had influence your valuation of what you do have? J. Jeffrey Inman is assistant professor of marketing, University of Wisconsin-Madison, Madison, WI 53706, James S. Dyer is professor of MSIS, University of Texas at Austin, Austin, TX 78712, and Jianmin Jia is assistant professor of marketing at the Chinese University of Hong Kong. The authors thank Eugene Anderson for his comments and advice regarding this paper. A GENERALIZED UTILITY MODEL OF DISAPPOINTMENT AND REGRET EFFECTS ON POST-CHOICE VALUATION Abstract In this paper we show that performance information about "forgone" alternatives (i.e., alternative that were considered but not chosen) can have a significant impact on post-choice valuation. Our approach introduces a new and parsimonious way of looking at satisfaction that combines the literature on post-choice valuation with research regarding generalized expected utility theory. While the post-valuation literature focuses on the selected brand as the ...

A recent trend in Human-Computer Interaction (HCI) research addresses human needs that go beyond the instrumental, resulting in an increasing body of knowledge about how users form overall evaluative judgments on the quality of interactive products. An aspect largely neglected so far is that of temporality, i.e. how the quality of users ’ experience develops over time. This paper presents an in-depth, fiveweek ethnographic study that followed 6 individuals during an actual purchase of the Apple iPhone™. We found prolonged use to be motivated by different qualities than the ones that provided positive initial experiences. Overall, while early experiences seemed to relate mostly to hedonic aspects of product use, prolonged experiences became increasingly more tied to aspects reflecting how the product becomes meaningful in one’s life. Based on the findings, we promote three directions for CHI practice: designing for meaningful mediation, designing for daily rituals, and designing for the self. Author Keywords User experience, experience-centered design, qualitative

MIS literature has not addressed the measurement of customer information satisfaction in electronic commerce. Current models for measuring user information satisfaction (UIS) and end-user computing satisfaction (EUCS) are perceived as inapplicable as they are targeted primarily towards either conventional data processing or the end-user computing environment. This study develops a comprehensive model and instrument for measuring customer information satisfaction (CIS) for web sites that market digital products and services. This paper first discusses the concepts and definitions of customer information satisfaction from the literature. We summarize our findings in a theoretical framework. Based on this framework, we develop a measurement instrument to measure customer information satisfaction. The procedures used in generating items, collecting data, and purifying a multiple-item scale are described. We have carefully examined evidences of reliability, content validity, criterion-related validity, convergent validity, discriminant validity, and nomological validity by analyzing data from a quota sample of 520 adult respondents. The norms of the instrument are then developed, and the potential applications for practitioners and researchers are explored. Finally, we conclude this study by discussing limitations and potential future research. We hope that our CIS instrument can be used by other researchers to develop and test Internet marketing and EC theories in the future.

Many firms are moving to make virtual interfaces their primary, or even sole, points of customer contact. In this environment, some traditional service quality dimensions that determine customer satisfaction, such as the physical appearance of facilities, employees, and equipment, and employees ’ responsiveness and empathy are unobservable. In contrast, trust may play a central role here in enhancing customer satisfaction. We model trust as an endogenously formed entity that ultimately impacts customer satisfaction, and we elucidate the linkages between trust and other factors related to the performance of the online service provider and to the service environment. The model is validated using two samples—one comprising 225 online investors of a large online broker, and the other comprising 203 members of the American Association of Individual Investors (AAII). The findings suggest that perceived trustworthiness of an online broker is a significant antecedent to investors ’ satisfaction, and that perceived environmental security and perceived operational competence impact the formation of trust. The results have important managerial implications.

This paper evaluates complete versus partial classification for the problem of identifying customers at risk. We define customers at risk as customers reporting overall satisfaction, but these customers also possess characteristics that are strongly associated with dissatisfied customers. This definition enables two viable methodological approaches for identifying such customers, i.e. complete and partial classification. Complete classification entails the induction of a classification model to discriminate between overall dissatisfied and overall satisfied instances, where customers at risk are defined as overall satisfied customers who are classified as overall dissatisfied. Partial classification entails the induction of the most prevalent characteristics of overall dissatisfied customers in order to discover overall satisfied customers who match these characteristics. In our empirical work, we evaluate complete and partial classification techniques and compare their performance on both quantitative and qualitative criteria. The intent of the paper is not on proving the superiority of partial classification, but rather to provide an alternative and valuable approach that offers new and different insights. In fact, taking predictive accuracy as the performance criterion, results for this study show the superiority of the complete classification approach. On the other hand, partial classification offers additional insights that complete classification techniques do not offer, i.e. it offers a rule-based description of criteria that lead to dissatisfaction for locally dense regions in the multidimensional instance space.

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The electronic learning (e-learning) literature has not addressed the measurement of learner satisfaction with asynchronous elearning systems. Current models for measuring user satisfaction (US) and students’ evaluation of teaching effectiveness (SETE) are perceived as inapplicable as they are targeted primarily towards either organizational information systems or classroom education environment. My study developed a comprehensive model and instrument for measuring learner satisfaction with asynchronous e-learning systems. The procedures used in conceptualizing the survey, generating items, collecting data, and validating the multiple-item scale are described. This study carefully examined evidence of reliability, content validity, criterion-related validity, convergent validity, discriminant validity, and nomological validity by analyzing data from a sample of 116 adult respondents. The norms of the instrument were then developed, and the potential applications for practitioners and researchers explored. Finally, this paper discusses limitations of the work. The empirically validated instrument should be useful to other researchers in developing and testing their e-learning theories.