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Investigating switching intention of e-commerce live streaming users

As a new way of shopping, e-commerce live streaming (ELS) has gained unprecedented growth and popularity in the past years, especially in China. Because of the considerable rivalry in the ELS market, users frequently switch between ELS platforms. However, the switching intention of ELS users is yet...

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Detalles Bibliográficos
Autores principales: Ye, Dingyu, Liu, Fufan, Cho, Dongmin, Jia, Zhengzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589182/
https://www.ncbi.nlm.nih.gov/pubmed/36299521
http://dx.doi.org/10.1016/j.heliyon.2022.e11145
Descripción
Sumario:As a new way of shopping, e-commerce live streaming (ELS) has gained unprecedented growth and popularity in the past years, especially in China. Because of the considerable rivalry in the ELS market, users frequently switch between ELS platforms. However, the switching intention of ELS users is yet to be explored for gaining new knowledge and practical insights. This study aims to improve the understanding of ELS users' switching intentions by developing an extended Push-Pull-Mooring (PPM) model. Using structural equation modeling, the study model was examined based on 443 valid responses from an online survey questionnaire. SmartPLS 3.3.2 was used to validate the causal model, and most of the study hypotheses were supported. According to the results, push effects (dissatisfaction, privacy concern, and negativity perceived value), pull effects (attractiveness of alternatives, perceived usefulness, perceived ease of use, and knowledge-based trust), and mooring effects (switching cost, social influence, and inertia) significantly influence ELS users' switching intentions. Furthermore, we found that mooring effects had a moderating role on the link between push effects and ELS user switching intention. However, the link between pull effects and ELS user switching intention was not found. The findings should aid ELS providers in deciphering ELS users' intentions in switching to other platforms and developing relevant theories, services, and regulations. The present study expands on previous research by introducing the PPM as a general model and demonstrating its effectiveness in explaining user switching intentions.