Understanding Live-Streaming Viewers’ Post-Adoption Based on A Relationship Development Perspective

Abstract

Motivating viewers’ relationship development with live-streaming streamers faces challenge. This study fills this gap by proposing a model based on an integrated framework between flow and relationship management. We seek to analyze how post-adoption is facilitated by relationship development with streamers, which in turn is influenced by live-streaming socio-technical features and flow (optimal experience). Specifically, we conceptualize response to optimal experience as two-stage post-adoption, including relationship development and outcomes (emotional connectedness and donation). Empirical results support most hypotheses, showing that group norms and interactivity exert significant influence on flow, which in turn affects outcomes through relationship development. We provide implications for research and practice.

Keywords:

• Flow
• post-adoption
• live-streaming
• relationship development
• socio-technical environment

Acknowledgements

This study analyzes how live-streaming post-adoption outcomes are affected by viewer-streamer relationship, viewers’ flow, and socio-technical features of live-streaming. Our results show that post-adoption outcomes, in terms of donation, connectedness, are influenced by two components of relationship development–loyalty and switching cost. These components are in turn influenced by flow and socio-technical features, which are conceptualized as group norms, social identity, interactivity, and presence. The hypotheses put forth were confirmed through data collection via surveys on the Twitch platform and analyzed using partial least square data analysis methods.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research received partial funding from the National Science and Technology Council of Taiwan. (No. 110-2410-H-992 -023 -MY2).

Notes on contributors

Shih-Wei Chou

Shih-Wei Chou is a distinguished professor in the Department of Information Management at National Kaohsiung University of Science and Technology, Taiwan, specializing in knowledge management and electronic commerce. With a doctorate in computer science from Illinois Institute of Technology, his research is extensively published and presented internationally.

Meng-Jun Hsu

Meng-Jun Hsu is an assistant professor in the Department of Hotel Management at National Kaohsiung University of Hospitality and Tourism, Taiwan. Specializing in AI in hospitality, electronic commerce, and knowledge management, he is a Microsoft Certified Trainer and AWS Academy Certified Educator. His research is widely published and internationally recognized.

Hsin-Cheng Lin

Hsin-Cheng Lin is a PhD candidate in the Department of Information Management at National Kaohsiung University of Science and Technology and a lecturer at Jen-Teh Junior College of Medicine, Nursing, and Management, Taiwan. He teaches E-commerce, Information Management, and Life Education.