The effect of risk levels on technology adoption decision: the case of online games

Abstract

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.

Neuromanagement decision-making and cognitive algorithmic processes in the technological adoption of mobile commerce apps

“…Thus customer use of in-store smart technology is shaped, the adoption of digital products and services is influenced (Kliestik et al, 2021), user intentions and consumer behavior are driven (Ginevicius et al, 2020), and consumers' system adoption and satisfaction in accessing mobile shopping apps/websites are determined. Consequently, users' online buying intention is impacted Dahabiyeh et al, 2020;Ho & Rezaei, 2018;Loh et al, 2021;Sharma et al, 2018;Vahdat et al, 2020), mobile shopping adoption intention is affected (Brusch & Rappel, 2020;Jung et al, 2020;Madan & Yadav, 2018;Patel et al, 2020;Singh et al, 2020;Verkijika, 2020), and behavioral intention and usage of mobile payment services and apps are configured Dewi et al, 2020;Kalinić et al, 2020;Mamun et al, 2020;Patil et al, 2020;Siyal et al, 2021;Zafar et al, 2021) (Research Question 3).…”

“…Mobile shopping applications and payment services determine groundbreaking technological developments associated with consumer behavioral intention and adoption intention, shaping satisfaction to purchase products and services by use of smart retail systems (Cheong et al, 2019;Dahabiyeh et al, 2020;Liébana-Cabanillas et al, 2020;Tueanrat et al, 2021). The dissemination of digital technologies associated with customers' intentions to accept and adopt shopping app-based mobile commerce configure users' expectations of groundbreaking devices, reducing perceived risk and trust (Brusch & Rappel, 2020;Groß, 2018;Li, 2019;Pandey & Chawla, 2019;Sabir, 2020;Sarkar et al, 2020;Sohn & Groß, 2020).…”

“…User co-creation behavior, reaction, and experiential values (Chi et al, 2021;Dahabiyeh et al, 2020;Graf-Vlachy et al, 2018;Gray-Hawkins & Lăzăroiu, 2020;Nel & Boshoff, 2019;Seeger et al, 2019;Talwar et al, 2020b;Tueanrat et al, 2021) constitute pivotal characteristics of customer journey contentment. The main conclusions of these studies indicate that mobile shopping apps users' eagerness and social network pressure consti-tute significant consumer behavior determinants that continue notwithstanding the level of risk related to technology adoption.…”

“…The mobile Internet as a purchasing channel has surpassed the desktop device-based Internet, shaping shopping apps users' behavior. (Chi et al, 2021;Dahabiyeh et al, 2020;Graf-Vlachy et al, 2018;Gray-Hawkins & Lăzăroiu, 2020;Nel & Boshoff, 2019;Seeger et al, 2019;Tueanrat et al, 2021) Positive attitudes in relation to mobile shopping apps lead to extensive purchasing frequency and loyalty towards the brand. Information quality and source credibility influence perceived convenience and ease of use that are both determinants of mobile shopping apps users' confidence, attitudes, and behavioral intentions.…”

The Application of Contextual Physics Teaching Materials Assisted by Android-Based Virtual Labs to Improve Students’ Science Process Skills During the Learning Activities in Covid-19 Pandemic

“…Teachers have to face challenges to create engaging learning situations so students can still concentrate on learning even though they are in a hard time. This challenge also comes from the finding that young people of school age access entertainment such as games or online video streaming services more than access learning materials [13].…”