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

To stop cheating behaviors in the online game, game providers have taken various measures, especially the anti-cheating system (ACS), but cheating behaviors are still endless. From the perspective of information interaction, this paper aims to analyze how to effectively persuade gamers to give up ch...

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Veröffentlicht in:Computers in human behavior 2019-07, Vol.96, p.149-162
Hauptverfasser: Wang, Li, Fan, Liu, Bae, SungMin
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description To stop cheating behaviors in the online game, game providers have taken various measures, especially the anti-cheating system (ACS), but cheating behaviors are still endless. From the perspective of information interaction, this paper aims to analyze how to effectively persuade gamers to give up cheating. In academic literature, ELM and signaling theory are mainly used for information interaction. Signaling theory provides a relatively concrete framework for information transmission, and ELM explains information processing in the receiver's perception. For maximizing their benefits, we propose a united persuasion model that signals (technical advantage, attitude of game providers, perceived risk, source credibility, and critical mass) and personal factors (self-efficacy, personal engagement, and positive cheating attitude) are regarded to affect gamer's intention to stop cheating. Based on data collected from 248 gamers who have held the intention to cheat once in China, the result reveals technical advantage cannot give significant influence on intention to stop cheating, which answers why current ACS cannot work as expected. Interestingly, intention to stop cheating is negatively influenced by the attitude of game provider, indicating coercive measures may cause a gamer's psychological reactance. Result also suggests personal factors significantly affect the intention to stop cheating. Our study helps game providers effectively persuade gamers to give up cheating, and also provides directions for future information interaction-related studies. •Anti-cheating technical advantage may not decrease cheating intention.•Attitude of game provider negatively affects intention to stop cheating.•Gamers prefer using simple information to decide whether to stop cheating or not.•Personal factors significantly influence the intention to stop cheating behavior.
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For maximizing their benefits, we propose a united persuasion model that signals (technical advantage, attitude of game providers, perceived risk, source credibility, and critical mass) and personal factors (self-efficacy, personal engagement, and positive cheating attitude) are regarded to affect gamer's intention to stop cheating. Based on data collected from 248 gamers who have held the intention to cheat once in China, the result reveals technical advantage cannot give significant influence on intention to stop cheating, which answers why current ACS cannot work as expected. Interestingly, intention to stop cheating is negatively influenced by the attitude of game provider, indicating coercive measures may cause a gamer's psychological reactance. Result also suggests personal factors significantly affect the intention to stop cheating. Our study helps game providers effectively persuade gamers to give up cheating, and also provides directions for future information interaction-related studies. •Anti-cheating technical advantage may not decrease cheating intention.•Attitude of game provider negatively affects intention to stop cheating.•Gamers prefer using simple information to decide whether to stop cheating or not.•Personal factors significantly influence the intention to stop cheating behavior.</description><identifier>ISSN: 0747-5632</identifier><identifier>EISSN: 1873-7692</identifier><identifier>DOI: 10.1016/j.chb.2019.02.024</identifier><language>eng</language><publisher>Elmsford: Elsevier Ltd</publisher><subject>Anti-cheating system ; Attitudes ; Cheating ; Coercivity ; Computer &amp; video games ; Critical mass ; Data processing ; Elaboration likelihood model ; Information interaction ; Online game cheating behavior ; Persuasion model ; Reactance ; Risk perception ; Signaling ; Signaling theory</subject><ispartof>Computers in human behavior, 2019-07, Vol.96, p.149-162</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. 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subjects Anti-cheating system
Attitudes
Cheating
Coercivity
Computer & video games
Critical mass
Data processing
Elaboration likelihood model
Information interaction
Online game cheating behavior
Persuasion model
Reactance
Risk perception
Signaling
Signaling theory
title How to persuade an online gamer to give up cheating? Uniting elaboration likelihood model and signaling theory
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