Sep 2026· Asia-Pacific Journal of Business Administration· 0 citations· 64 references
TL;DR
This study identifies individual competencies that enhance employees' IWB in GAI-enabled work environments by identifying individual competencies that enhance employees' IWB in GAI-enabled work environments.
Abstract
Drawing on innovation diffusion theory, this study examines how AI literacy (AIL) promotes innovative work behavior (IWB) in generative AI–enabled work environments and investigates the moderating roles of occupational expertise and metacognition.
This study examines the individual competencies that shape IWB in generative GAI–enabled work environments. Data were collected through an online survey using a stratified sampling method targeting employees with experience using GAI at work. A total of 600 valid responses were analyzed using hierarchical and moderated regression analyses.
The results of the analysis demonstrate that AIL has a positive effect on IWB. Moreover, this effect was moderated by both occupational expertise and metacognition. Specifically, the positive impact of AIL on IWB was stronger among individuals with higher occupational expertise. Similarly, the effect of AIL on IWB was amplified among those with higher metacognition levels. These findings have theoretical and practical implications for research and practice in organizational behavior, human resource management and human resource development.
This study makes a significant contribution to the relevant research field by identifying individual competencies that enhance employees' IWB in GAI-enabled work environments. Specifically, by highlighting the roles of AIL, occupational expertise and metacognition, this study provides a theoretical foundation for understanding how individual competencies influence IWB. Beyond its theoretical contributions, this study also offers practical guidance for managers and policymakers by suggesting strategies for talent development, selection and placement to promote sustainable growth and maintain a competitive advantage.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
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A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
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The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
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This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
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