Integrating the traditional and structural approaches to information load measurement, this research investigates the impact of information overload on decision strategy. Decision strategy refers to whether a consumer uses a recommendation agent and the consumer's reactance behavior to the agent advice (whether the chosen product was the same or different from the recommended product). The research further shows the effects of information overload and decision strategy on choice quality, choice confidence, and e-store interactivity. The experiment, which involved 466 consumers, had three levels for the number of alternatives (6, 18, and 30), three levels for the number of attributes (15, 25, and 35), and two different attribute distributions across alternatives (proportional vs. disproportional). The results contribute to the literature of information overload and decision support systems by underscoring that (1) the relationship between information load and perceived overload is curvilinear, (2) informat...

Trust in rich media environments is conceptualized as comprising both trust in the retailer and trust in the others represented virtually during on-line interaction. More specifically, the authors posit that media richness (manipulated by the modality of the privacy disclosure) affects the e-store social presence that drives retailer trust and behavioral intentions, and that in rich media environments, agent trust (trustworthiness of the virtually represented agent communicating the disclosure) (1) mediates the relation between social presence and retailer trust, and (2) shapes consumer judgments of retailer trustworthiness and purchase intentions. These hypotheses are supported by the results of an experiment with 423 consumers, which show that there is a hierarchical order for social influence in rich media environments that entices retailers to manage not only the media richness of their B2C messages but also the social actors communicating these messages at their e-stores.

Purpose: The internet has become mainstream in everyday communications and transactions. This research aims to provide a segmentation analysis for the online market based on the various uses of the internet.Design/methodology/approach: A review of the online consumer segmentation literature is first conducted. Survey method and cluster analysis techniques are used in the empirical study. A sample of 407 participants that belonged to a large consumer panel adequately responded to an online survey and provided their pattern of internet use, internet experience, and psychological characteristics.Findings: The analysis shows that the online consumers form three global segments: the basic communicators (consumers that use the internet mainly to communicate via e‐mail), the lurking shoppers (consumers that employ the internet to navigate and to heavily shop), and the social thrivers (consumers that exploit more the internet interactive features to socially interact by means of chatting, blogging, video streaming, and downloading). Subsequent χ² and ANOVA tests illustrate that consumers from these segments exhibit significantly divergent demographic and experience profiles.Research limitations/implications: The results indicate that online consumers differ according to their pattern of internet use. The results have external and ecological validity; however, they lack the control provided in a laboratory experiment. Future research should examine if the findings can be replicated using behavioral measures.Practical implications: Practitioners that plan to follow a resource‐based approach should consider the distinctive characteristics of the online market segments for an optimal allocation of marketing expenditure. Marketing and advertising strategies can be developed according to the customer's online segment. Further, online marketers can use the demographic and experience profiles to predict their customer's segment.Originality/value: This paper is the first to perform a segmentation analysis to the online consumer market according to internet use pattern. The results show that usage can reliably be used as a segmentation base. Managerial and theoretical implications are furnished.

Purpose – Since their inception, which took place more than two decades ago, product recommendation agents (RAs) still attract very few consumers. Notably, most of academic work in the field had an empirical quantitative structure. In addition, no research has developed a comprehensive model to explain the adoption and usage of commercial RAs. The purpose of this paper is to follow a qualitative approach to investigate the factors behind the adoption and usage of commercial RAs, explore the effect of user age, and deduce the success factors of these RAs. Design/methodology/approach – This research followed a qualitative approach. Qualitative research aims to form an in-depth understanding of human behavior. It is essential for building grounded theory and for proposing comprehensive models for future examination. As such, in four discussion groups, participants provided their input following the shopping trial for a product using a factual RA (MyProductAdvisor.com). Discussion groups were used because they outline an important aspect of qualitative research and because they are ideal for both the inception and development of products and services. Findings – Underlying the major themes, the analysis first provides insight in consumers' RA use and the products consumers regard as adequate to be offered using a commercial RA. The analysis then delineates some important factors that can be considered by developers to enhance the usability and trustworthiness of commercial RAs. Further, the analysis suggested four higher-order factors that can be considered the success factors of a commercial RA: users appear to require a commercial RA that is friendly, smart, trusted, and informational. The themes that emerged from participants in the youth and the older discussion groups were rather invariant. Originality/value – This is one of the few qualitative studies that focused on commercial RAs. The commercial RA success factors and their determinants are summarized in the form of a general framework to guide future work. This qualitative work provides a cornerstone that is of importance to theory development in the field of intelligent RAs and assistive technology. The results have important implications for RAs' developers and researchers.