Exploring Job Happiness Across Asian Countries: Factors, Challenges, and Strategies for Enhancing Employee Well-Being and Organizational Performance

Shifeng Chen ()
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Shifeng Chen: The University of Hong Kong

A chapter in Proceedings of the 2026 3rd International Conference on Applied Economics, Management Science and Social Development (AEMSS 2026), 2026, pp 254-262 from Springer

Abstract: Abstract With the generalized usage of artificial intelligence (AI) in the workplace, the influence on the efficiency, Human–AI trust, and task suitability of knowledge workers has become increasingly profound. Through literature analysis and theoretical exploration, this study develops an integrated model of AI tools and knowledge worker performance, examining how AI enhances the performance of knowledge workers. The findings indicate that AI tools can enhance efficiency in tasks of low complexity and AI tools in high complexity tasks tend to function as assistive tools. The establishment of Human–AI trust depends on the interpretability, transparency and feedback mechanisms of AI systems, which promote greater willingness of using AI tools. Excessive reliance on AI may weaken the capacity of knowledge workers for independent thinking and innovation. By dynamically allocating decision authority and establishing Human–AI trust, organizations can promote collaborative development between humans and AI and improve the performance of the employees.

Keywords: Artificial intelligence; Machine learning; Natural language processing (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6239-672-2_24

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DOI: 10.2991/978-94-6239-672-2_24

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