Uncover Configurational Paths of Streamers' Characteristics Predicting High vs. Low Consumers' Watching Intention to TikTok Live Streaming

The recent popularity of live streaming on social media has fascinated scholars' devotion. Though, prior studies have yet to satisfactorily elucidate how continuous watching intentions are enlightened regarding live streaming. This study aims to develop an asymmetrical framework for predicting consumers' watching intentions based on streamers' characteristics, such as beauty, humor, warmth, passion, and expertise. A total of 450 respondents who watched live streaming on TikTok participated in this study. This study attempts to examine propositions that specify models that predict high vs. low watching intentions based on the five streamers' characteristics using the fsQCA 3.0. The findings designate two configurations that signify both high vs. low watching intention. To achieve high watching intention, conditions of humor, warmth, passion, and expertise are required. Meanwhile, consumers will not continue to watch TikTok live streaming when the absence of beauty, humor, passion, and warmth is significant. This study signifies theoretical implication where a configurational model of live streaming watching intention based on streamers' characteristics was well-validated. At the same time, this study also provides marketers with practical guidelines on increasing watching intention using four configurations of streamers' characteristics.