The effect of risk levels on technology adoption decision: the case of online games - Dahabiyeh, Laila; Najjar, Mohammad S; Agrawal, Deepti (Information technology & people (West Linn, Or.), 2020)
PurposeInformation technology is associated with psychological and physical risks such as high stress levels and antisocial behavior. The purpose of this paper is to understand why people engage in technology risk behavior, despite the negative consequences that might follow. Focusing on online games, this study identifies factors that affect individuals' intention to play online games and investigate whether the effects of these factors differ across different risk levels.Design/methodology/approachExperimental design was used as the research methodology. Subjects were randomly assigned to a single treatment with two conditions: high and low risk scenarios. A total of 597 responses were analyzed to test the research hypotheses.FindingsThe research findings reveal that subjective norms, curiosity and playfulness have a positive effect on the intention to play online games, while critical mass has no effect on the intention decisions. Further, among the three significant constructs, playfulness turned out to be the only factor that is affected by risk levels.Research limitations/implicationsThis study extends prior literature on technology adoption by examining the effect of different risk levels on adoption intention decisions. It further extends prior literature on online games by identifying the factors that drive individuals to play games while accounting for the risks associated with playing these games.Practical implicationsThe research study identifies factors that should be taken into consideration when promoting the adoption of technologies, including online games.Originality/valueThis study offers a new understanding of technology adoption decisions that takes into account the different levels of risk associated with technology use. It shows that an individual's curiosity and the pressure emanating from one's social network are powerful behavior drivers that persist regardless of the level of risk. Further, this research study is among the first to apply categorical least squares methodology combined with a procedure for a moderated structural equation model to test a structural equation model with categorical multiplicative terms in LISREL.