The Dynamics of Decision-Making in Interdisciplinary Teams

Authors

DOI:

https://doi.org/10.61838/kman.jrmde.2.3.4

Keywords:

Interdisciplinary Teams, Communication Dynamics, Decision-Making, Team Dynamics, Project Management, Qualitative Research

Abstract

This study aims to explore the perspectives of professionals involved in AI implementation across different industries, focusing on the benefits, challenges, and future implications of AI in resource management. This qualitative study was conducted through semi-structured interviews with 17 professionals, including AI developers, resource management experts, policy makers, and academic researchers. Participants were selected using purposive sampling to ensure a wide range of insights. Data collection continued until theoretical saturation was achieved, and thematic analysis was employed to identify and analyze emerging themes from the interview data. Four main themes were identified: Benefits of AI, Challenges of AI, Policy and Regulation, and Future Implications. Key benefits noted include enhanced efficiency, decision support, cost reduction, innovation, and sustainability. Major challenges encompass integration difficulties, data-related issues, ethical concerns, and technological limitations. Policy and regulation discussions highlighted the need for robust regulatory frameworks and ethical governance. Future implications touched on AI’s potential to transform long-term strategies, workforce, and public perceptions. The study concludes that while AI offers significant opportunities to enhance resource management, it also requires careful handling of various challenges, particularly in integration, ethics, and policy. Strategic approaches and robust governance are essential for leveraging AI's benefits while mitigating its risks. Future developments should focus on enhancing AI's ethical implementation and addressing global disparities in AI access.

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Published

2024-05-09

How to Cite

Etehadi, S. (2024). The Dynamics of Decision-Making in Interdisciplinary Teams. Journal of Resource Management and Decision Engineering, 2(3), 18-24. https://doi.org/10.61838/kman.jrmde.2.3.4

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