research-article

Examining WeChat users' motivations, trust, attitudes, and positive word-of-mouth

Authors:

Yang CaoAuthors Info & Claims

Computers in Human Behavior, Volume 41, Issue C

Pages 104 - 111

https://doi.org/10.1016/j.chb.2014.08.013

Published: 01 December 2014 Publication History

Abstract

Entertainment, sociality, and information positively influence users' attitudes.Trust has a positive effect on WeChat users' attitudes.Increasing users' trust will increase their willingness in making positive WOM.Improving users' attitudes will enhance their willingness in making positive WOM. WeChat is a mobile instant text and voice messaging communication service and has become an important social media platform in China. The objectives of this article are to examine the effects of psychological motivations (entertainment, sociality, and information) and trust on WeChat users' attitudes and to assess the influence of users' attitudes and their trust on positive word-of-mouth. This study represents one of the few that empirically investigates WeChat users' motives, attitudes, trust, and their associated behavior. The research model was tested using data randomly collected from the database of Sojump. The numbers of valid observations were 264. Structure equation modeling was employed to verify and validate the research model. The outcomes confirm the path effects showing that entertainment, sociality, information, and trust positively influence WeChat users' attitudes and users' trust and their attitudes significantly affect positive WOM. The research results provide insight into how WeChat can motivate users and build their trust to improve their attitudes which in turn will increase WeChat users' willingness in making positive comments on products and services.

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cover image Computers in Human Behavior

Computers in Human Behavior Volume 41, Issue C

December 2014

554 pages

ISSN:0747-5632

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2014

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Cited By

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https://dl.acm.org/doi/10.1016/j.tele.2024.102174
Frey VMartinez J(2024)Interpersonal trust modelling through multi-agent Reinforcement LearningCognitive Systems Research10.1016/j.cogsys.2023.10115783:COnline publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cogsys.2023.101157
Martínez-Comeche JRuthven I(2023)Informational features of WhatsApp in everyday life in MadridJournal of Information Science10.1177/016555152199061249:1(122-132)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1177/0165551521990612
Zhao P(2023)Artificial Intelligence-Based Digital Media Design Effect Enhancement MechanismAdvances in Multimedia10.1155/2023/86005432023Online publication date: 1-Jan-2023
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