Making Recommendations More Effective through Social Features: The Impact on Social E-commerce Users' Purchasing Intentions

Authors

Xu Li, Renmin University of ChinaFollow
Kanliang Wang, Renmin University of ChinaFollow
Qiqi Jiang, Copenhagen Business SchoolFollow

Paper Type

FP

Paper Number

346

Abstract

The interplay between social media and e-commerce is an emerging business model. Social recommendation, as an important part of social e-commerce, plays a key role in affecting consumer judgement and decision process. Despite increasing number of technical researches, the research in the role of design affordance of social display features in the context of social media driven e-commerce is still missing. Anchoring on signaling theory, we develop and validate our hypotheses using a series of online experiments. Our findings indicate the presentation of friends-based feedback can induce higher purchase intentions than presenting the crowd-based feedback. We further propose that this relationship is moderated by the temporal distance. Specifically, when the temporal distance is short, recommendations from friends are more persuasive than those from the crowd, whereas the opposite occurs for users at the longer temporal distance. Our findings have important implications for research and practice in designing effective recommendation systems.

Recommended Citation

Li, Xu; Wang, Kanliang; and Jiang, Qiqi, "Making Recommendations More Effective through Social Features: The Impact on Social E-commerce Users' Purchasing Intentions" (2021). PACIS 2021 Proceedings. 118.
https://aisel.aisnet.org/pacis2021/118