How to persuade an online gamer to give up cheating? Uniting elaboration likelihood model and signaling theory

The Impact of Government Social Media Information Quality on Public Panic During the Infodemic

The COVID-19 pandemic triggered the first global “Infodemic” in the era of social media. Understanding how governments deal with the negative impacts of the infodemic (e.g., public panic) has become a priority. This paper uses the theoretical framework of the Elaboration Likelihood Model (ELM) to explore mechanisms for alleviating panic associated with the infodemic. It considers, in particular, the quality of information circulated on Government Social Media (GSM) as the central route and local government trust as the peripheral route. An empirical study was conducted using data from a focus group interview and a questionnaire survey collected within the first three weeks following the citywide lockdown of Wuhan, China. The results show that as: (1) Quality of GSM information does not significantly reduce public panic, but local government trust significantly increases people’s pandemic prevention knowledge; (2) Pandemic prevention knowledge is a critical mediator between information quality of GSM and public panic, as well as local government trust and public panic; and (3) Information quality of GSM significantly increases people’s trust in local governments. This paper contributes to the literature on infodemic and government social media and provides implications for practice.

Understanding online health community users' information adoption intention: an elaboration likelihood model perspective

Purpose

The purpose of this research is to draw on the elaboration likelihood model (ELM) to examine users' information adoption intention in online health communities (OHC).

Design/methodology/approach

The authors collected 350 valid responses using a survey and conducted the moderated regression analysis to examine the research model.

Findings

The results indicated that users' information adoption intention is influenced by both central cues (argument quality) and peripheral cues (source credibility and emotional support). In addition, self-efficacy moderates the effect of both central cues and peripheral cues on information adoption intention.

Originality/value

Previous research has focused on the effect of individual motivations such as reciprocity and benefits on user behavior, and has seldom disclosed the influencing process of external factors on OHC users' behavioral decision. This research tries to fill the gap by adopting ELM to uncover the mechanism underlying OHC users' information adoption.

Effect of data environment and cognitive ability on participants’ attitude towards data governance

Data governance has received research attention, but its effect on public attitude has not been sufficiently explored. To analyse the attitude towards public participation in data governance in the context of a tourism platform, we conduct an empirical model that aims to understand the impact of data governance environment and participants’ cognitive ability on attitude. Taking tourism sharing platforms as an example, we collected 339 questionnaires for data analysis. Results show that data quality and website design have a positive effect on users’ attitude towards data governance through data literacy self-efficacy. Data literacy self-efficacy has a suppression effect between data quality and attitude towards data governance and has the same effect between website design and attitude towards data governance. Data quality and website design have a positive effect on users’ attitude towards data governance through platform interaction. Platform interactivity plays a mediating role between data quality and attitude towards data governance and has the same effect between website design and attitude towards data governance. Data policy has a positive effect on users’ data literacy self-efficacy but no significant effect on platform interactivity. Moreover, this study provides theoretical and practical implications that can guide the government in policy implementation and platform managers in data governance.