Impact of Recommender Systems on Unplanned Purchase Behaviours in e-Commerce

The emergence of the Chinese online marketplace has stimulated the increasing popularity of recommender systems among websites as a tool that assists consumers to reduce information overload. This study proposes a framework that employs a user-cantered approach to evaluate the impact of recommender systems on unplanned purchase behaviours of Chinese consumers in e-commerce. Multi-item scales are adopted from the literature and used to measure five constructs, namely, perceived ease of use, perceived usefulness, shopping enjoyment, consumer satisfaction, and unplanned purchase behaviour. The final samples comprised 281 usable Chinese respondents in both gender groups via online survey. Structural equation modelling technique is employed to test all hypotheses. Results show that perceived usefulness plays a leading role in influencing impulse buying. Apart from having a direct and positive effect on unplanned purchase behaviours, perceived usefulness indirectly contributes to impulse buying by affecting consumer satisfaction, which is also essential to promoting unplanned purchases.