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◆ Technology Analysis and Strategic Management2026-06-30· Expectancy theory

User perceptions and system capabilities for advancing generative artificial intelligence adoption and innovation in Industry 5.0

Sisheng Wan, Jawad Abbas, Yuchen Pan, Masooma Batool

原始摘要(英文原文)· Original abstract
In Industry 5.0, integrating advanced technologies like generative artificial intelligence (Gen-AI) is driven by user and system factors. While previous research has predominantly focused on user factors in AI adoption, limited attention has been given to system attributes. This study empirically examines the impact of both user and system factors on employees’ attitudes, behavioural intentions and actual use of Gen-AI. Using the meta-UTAUT and Task Technology Fit (TTF) frameworks, our structural analysis of 247 respondents from multinational corporations operating in Turkey reveals that user and system factors positively influence attitudes and behavioural intentions towards Gen-AI adoption, whereas performance expectancy directly strengthens Gen-AI usage. Additionally, system factors significantly enhance user-related factors, highlighting the reciprocal relationship between the two. However, performance expectancy insignificantly relates to employees’ attitudes towards Gen-AI. Our findings underscore the importance of how employees perceive and engage with Gen-AI, influencing their willingness to adopt and utilise it, which in turn fosters creativity. This research provides a comprehensive understanding of the interplay between user and system factors in Gen-AI adoption, offering insights into how their integration can enhance creative outcomes, drive employee innovation and promote widespread engagement with Gen-AI in Industry 5.0.
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User perceptions and system capabilities for advancing generative artificial intelligence adoption and innovation in Industry 5.0 — 科研速览 Science Skim