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Chatbots and team-based working dynamics: management decision implications

Antonio Cimino Orcid Logo, Paul Jones Orcid Logo, Francesco Longo, Vittorio Solina Orcid Logo, Ciro Troise Orcid Logo

Management Decision (forthcoming), Pages: 1 - 29

Swansea University Author: Paul Jones Orcid Logo

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Abstract

PurposeThis study investigates the relationship between artificial intelligence (AI)-related system characteristics and two interpersonal states commonly associated with effective teamwork, namely employee well-being and mutual trust. While generative AI has shown potential to improve organizational...

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Published in: Management Decision (forthcoming)
ISSN: 0025-1747 1758-6070
Published: Emerald
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa71424
Abstract: PurposeThis study investigates the relationship between artificial intelligence (AI)-related system characteristics and two interpersonal states commonly associated with effective teamwork, namely employee well-being and mutual trust. While generative AI has shown potential to improve organizational performance, its specific effects on internal team-based working relationships remain underexplored.Design/methodology/approachA theoretical model is developed to explore the influence of three antecedent variables, quality of information, system quality and generative AI use, on collaboration within teams. Collaboration is operationalized using two key constructs: employee well-being and mutual trust. The model is empirically tested using data from a large-scale survey of 208 professionals working in team-based environments. Data analysis is conducted using partial least squares structural equation modeling (PLS-SEM).FindingsThe results confirm that all three antecedent variables positively influence team-based collaboration dynamics. Specifically, the use of generative AI chatbots, such as ChatGPT, is shown to enhance employee well-being and foster mutual trust within teams, both of which act as interpersonal enablers of team collaboration. These outcomes suggest that the integration of high-quality AI tools can meaningfully support collaborative processes in professional settings.Originality/valueThis study contributes to the emerging field of generative AI research by shifting the focus from performance outcomes to collaboration mechanisms within teams. It offers practical implications for managers seeking to optimize teamwork in AI-enabled environments, including investing in system quality, redesigning workflows to integrate AI effectively and promoting a culture of trust and transparency around AI adoption.
College: School of Management
Start Page: 1
End Page: 29