Understanding “window” shopping and browsing experience on social shopping website

Purpose Social shopping website (SSW) introduce the social side into the shopping process, thus making “window” shopping or browsing more interesting for customers. The purpose of this paper is to investigate customer online browsing experience and its antecedents (i.e. information quality and social interaction) and consequences (i.e. urge to buy impulsively and continuous browsing intention) in the context of SSW. Design/methodology/approach A survey questionnaire was distributed to visitors of online SSW to collect data, and partial least squares technology was used to test the research model. Findings The results of this study reveal that three types of web browsing, namely, utilitarian browsing, hedonic browsing and social browsing, take place in a SSW. The unique factors of SSW, namely, the quality of user generated contents and social interaction are critical for facilitating customers’ browsing experiences. Furthermore, the findings reveal that hedonic browsing experience is found to be the most salient factor influencing customers’ urge to buy impulsively and continuance intention. Practical implications The findings suggest that practitioners, such as designers and managers of SSW should give special attention to the benefits of browsing activity to convert web browsers into impulse purchasers and increase customers’ loyalty. Moreover, they should focus on improving the quality of user generated content and pay more attention to support and encourage social interaction to enhance browsing experiences on a SSW. Originality/value Existing studies about browsing behavior mostly focus on traditional online e-commerce website. This study represents the first step toward understanding browsing activity on SSW. Moreover, prior studies mainly focused on utilitarian and hedonic browsing experience; however, there is a lack of research on social browsing experience. The current study attempts to fill this research gap.

Social motivation in online social shopping

Literature review demonstrates that social motivation has not been researched systematically and comprehensively. This study aims at filling the void by exploring the components of social motivation as well as examining the impact of these component on consumers' intention to engage in online social shopping. The results of pilot and main study indicate that social motivation involves five components, namely social browsing, social bonding, opinion showing, power seeking and social association. Moreover, all these components affect intention to engage in online social shopping. This study has therefore contribution in both academic and practical aspects.

When more is more? The impact of breadth and depth of information disclosure on attributional confidence about and interpersonal attraction to a social network site profile owner

Social network sites (SNSs) provide users with ample opportunity to share information about themselves and to engage in social browsing to learn about others. This article reports results from two experiments (with participants from the U.S.) that investigate the impacts of breadth and depth of information disclosed in a profile on viewers’ attributional confidence about and interpersonal attraction to the profile owner. In the first experiment (n = 320), participants viewed a profile containing either low or high breadth of information. Analyses indicated that, higher breadth of information shared in the profile increased interpersonal attraction and that attributional confidence mediated this relationship. The second experiment (n = 537) tested the respective influences of breadth (low vs. high) and depth of disclosure (low vs. high) in a profile on perceivers’ attributional confidence and interpersonal attraction. Analyses indicated that, while increasing the breadth of information had a positive impact on interpersonal attraction to profile owners, increasing the depth of information reduced attraction. Additionally, there was a significant interaction between breadth and depth of information in predicting attributional confidence; increasing the depth of information shared in an SNS profile enhanced attributional confidence only when the breadth of information shared was low.

The GALILEI Platform

For a few years, social software has appeared on the Internet to challenge the problem of handling the mass of information available. In this chapter, we present the GALILEI platform using social browsing to build communities of interests where relevant information and expertise are shared. The users are described in terms of profiles, with each profile corresponding to one specific area of interest. While browsing, users’ profiles are computed on the basis of both the content of the consulted documents and the relevance assessments from the profiles. These profiles are then grouped into communities, which allows documents of interest to be shared among members of a same community and experts to be identified.