AN EMOTIONAL EXPECTANCY CONSTRUCTION IN A UNIFIED THEORY OF ACCEPTANCE AND USE OF ARTIFICIAL INTELLIGENCE TECHNOLOGY IN NIGERIA
The Unified Theory of Acceptance and Use of Technology (UTAUT) model theorizes that four constructs play a significant role as direct determinants of user acceptance and usage behavior: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC). Even though several researchers discuss the relevance of EE in user acceptance of new technologies, the UTAUT model does not use EE as a direct determinant. This study argues that EE is a direct determinant of behavioral intention. The aim of this research is to construct an emotional expectancy model in a unified theory of acceptance for the use of AI technology, provided by the Nigerian context. The study conducted a quantitative study by using a questionnaire distributed via emails and WhatsApp to examine the impact of EE on the behavior intention to adopt AI technology among Nigerians. Seven hypotheses were tested, and results indicated that PE significantly influenced BI (β = .357, p < .05), suggesting that respondents had positive attitudes toward AI services. SI also had a positive influence on BI (β = .161, p > .05), highlighting the role of social acceptance in AI adoption. FC was found to significantly influence BI (β = .116, p < .05), indicating that users are more likely to adopt AI if they have the necessary resources and support. EE, however, did not significantly impact BI (β = .010, p > .05), contradicting previous studies that emphasized its importance. internet trust and PE were the strongest predictors of AI adoption. Given EE’s limited influence, the study proposes extending the UTAUT model by incorporating Emotional Expectancy as a new construct to better understand AI adoption in Nigeria. The research provides valuable insights for policymakers and technology planners to enhance AI acceptance by addressing key determinants.
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