Effectiveness of AI Assistance in Live Streaming: A Randomized Field Experiment

Presenter Information

Lingli Wang, Tsinghua UniversityFollow
Yumei He, University of HoustonFollow
Jiandong Ding, Alibaba GroupFollow
Nina Huang, University of HoustonFollow
Yili Hong, University of HoustonFollow
Xunhua Guo, Tsinghua UniversityFollow
De Liu, University of MinnesotaFollow
Guoqing Chen, Tsinghua University, BeijingFollow

Paper Number

1379

Paper Type

short

Description

Live streaming selling is a transformative e-commerce channel that features real-time interaction between a streamer and a mass audience. However, streamers’ service capacities cannot fulfill viewers’ needs for social interaction, resulting in a loss of viewer engagement and financial gains. Accordingly, we examine whether the implementation of an AI assistant that tracks, understands, and responds to viewers’ requests can facilitate social interaction and drive viewers’ purchase decision. In collaboration with Taobao.com, we conducted a randomized field experiment on its live streaming platform. In the experiment, a subject was either assigned to the treatment group with an AI assistant in each live streaming or the control group in which the AI assistant was absent. We will collect data to evaluate the effectiveness of the AI assistant. Our research contributes to the literature on the business value of AI applications and live streaming while implicates AI system designs for live streaming platforms.

Comments

10-HCI

Recommended Citation

Wang, Lingli; He, Yumei; Ding, Jiandong; Huang, Nina; Hong, Yili; Guo, Xunhua; Liu, De; and Chen, Guoqing, "Effectiveness of AI Assistance in Live Streaming: A Randomized Field Experiment" (2021). ICIS 2021 Proceedings. 3.
https://aisel.aisnet.org/icis2021/hci_robot/hci_robot/3