Electronic commerce typically lacks human warmth and sociability, since it is more impersonal, anonymous and automated than traditional face-to-face commerce. This paper explores how human warmth and sociability can be integrated through the web interface to positively impact consumer attitudes towards online shopping. An empirical study was undertaken to investigate the impact of various level...

The Technology Acceptance Model (TAM) is a very important modelling approach in information technology research. In this study, an attempt is made to explain consumer acceptance of e-shopping by means of an extended model based on TAM. Perceived trust, perceived enjoyment, perceived information quality, perceived system quality and perceived service quality factors are added to the classical TA...

There have been few studies investigating the effects of collaboration on online shopping. In this paper, we consider an online shopping scenario where the user and a partner, who are not collocated, plan the travel collaboratively. We develop a research model based on Website Trust to explain the user’s Website Intentions. To test the model, we conducted a field experiment with 605 individuals...

With its rapid economic growth and the largest number of Internet users worldwide, China and its vast online markets are of particular interests to companies globally. This paper describes a study of Chinese users’ acceptance of an emerging Ecommerce technology: social commerce websites. Leveraging the power of social networking technologies with online shopping, social commerce sites have emer...

This study extends a stimulus–organism–response (S–O–R) model to include impulse-buying behavior, which plays a vital role in electronic shopping but has not gained much attention in e-commerce research. Grounding our research in environmental psychology, we test the effects of virtual atmospheric cues on online impulse-buying behavior and spending, via a consumer survey. The study applies elab...

This paper describes the application of a new technique, rough clustering, to the problem of market segmentation. Rough clustering produces different solutions to k-means analysis because of the possibility of multiple cluster membership of objects. Traditional clustering methods generate extensional descriptions of groups, that show which objects are members of each cluster. Clustering techniq...