What Signals Are You Sending? How Signal Consistency Influences Consumer Purchase Behavior in Live Streaming Commerce

Driven by digital technology, live streaming business is becoming increasingly common worldwide. Unlike traditional online shopping, live streaming commerce integrates real-time interaction, social communication, and e-commerce. It also eliminates the limitations of one-way information transmission and promotes purchasing behavior by conveying signals such as products, brands, and the personal charm of live streamers to consumers through real-time communication. The core issues explored in this study are whether the cues between the signal transmitters and receivers are consistent and how they affect consumers’ purchasing behavior. In this study, the consistency of the signal is measured by five dimensions, namely self–product fit, live streamer–product fit, live content–product fit, danmaku content–product fit, and self–live streamer fit. In order to study this problem, we constructed a structural equation modeling (SEM) model. In the causal relationship between signal consistency and purchase intention, performance responses have also been discussed as mediating variables. Accordingly, signal consistency enables consumers to perceive performance expectancy, whereby consumers believe that products that perform well positively influence satisfaction. To verify these hypotheses, 443 randomly collected valid questionnaires were used in empirical analyses. The results showed that most of our hypotheses were validated, aside from the relationship between self–live streamer fit and perceived performance expectancy. The findings suggest that signal consistency cues such as live streamer–product fit, live content–product fit, danmaku content–product fit, and self–product fit positively influence consumers’ perceived performance expectancy and satisfaction, which in turn promote purchase intention. These findings not only enrich the application of signaling theory in the field of live streaming commerce but also expand consumer behavior theory. Moreover, they also inspire practitioners in live streaming commerce by helping them to improve live streaming sales and bolster their market competitiveness through signal display optimization, content planning, and precision marketing.

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Publication Details

Journal
Journal of theoretical and applied electronic commerce research
Published
2025-05-20
DOI
https://doi.org/10.3390/jtaer20020109
Citations
3
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
12.60
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article

What Signals Are You Sending? How Signal Consistency Influences Consumer Purchase Behavior in Live Streaming Commerce

Kyungtag Lee, Yu Peng Zhu, Huimin Wang
3 citations
Journal of theoretical and applied electronic commerce research
Digital Marketing and Social Media
12.60
article

What Signals Are You Sending? How Signal Consistency Influences Consumer Purchase Behavior in Live Streaming Commerce

Kyungtag Lee, Yu Peng Zhu, Huimin Wang
article en
3 citations

Abstract

Driven by digital technology, live streaming business is becoming increasingly common worldwide. Unlike traditional online shopping, live streaming commerce integrates real-time interaction, social communication, and e-commerce. It also eliminates the limitations of one-way information transmission and promotes purchasing behavior by conveying signals such as products, brands, and the personal charm of live streamers to consumers through real-time communication. The core issues explored in this study are whether the cues between the signal transmitters and receivers are consistent and how they affect consumers’ purchasing behavior. In this study, the consistency of the signal is measured by five dimensions, namely self–product fit, live streamer–product fit, live content–product fit, danmaku content–product fit, and self–live streamer fit. In order to study this problem, we constructed a structural equation modeling (SEM) model. In the causal relationship between signal consistency and purchase intention, performance responses have also been discussed as mediating variables. Accordingly, signal consistency enables consumers to perceive performance expectancy, whereby consumers believe that products that perform well positively influence satisfaction. To verify these hypotheses, 443 randomly collected valid questionnaires were used in empirical analyses. The results showed that most of our hypotheses were validated, aside from the relationship between self–live streamer fit and perceived performance expectancy. The findings suggest that signal consistency cues such as live streamer–product fit, live content–product fit, danmaku content–product fit, and self–product fit positively influence consumers’ perceived performance expectancy and satisfaction, which in turn promote purchase intention. These findings not only enrich the application of signaling theory in the field of live streaming commerce but also expand consumer behavior theory. Moreover, they also inspire practitioners in live streaming commerce by helping them to improve live streaming sales and bolster their market competitiveness through signal display optimization, content planning, and precision marketing.

Journal of theoretical and applied electronic commerce researchVol. 20(2)
Ningbo University (CN), Chongqing University (CN), Yeungnam University (KR)
Openalex Percentile: Top 2%
Digital Marketing and Social Media
12.60
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