A SCIENTOMETRIC ANALYSIS OF EMOTIONAL ARTIFICIAL INTELLIGENCE IN ENGINEERING MANAGEMENT: IMPACTS ON TEAM DYNAMICS AND LEADERSHIP EFFECTIVENESS
Abstract
ABSTRACT
This study explores the landscape of emotional artificial intelligence (EAI) in engineering management, emphasizing its impacts on team dynamics, leadership effectiveness, and project outcomes. Employing scientometric methodology, data was sourced from the Web of Science database through targeted keyword searches. CiteSpace software was utilized for analysis and visualization of the results. Findings reveal strong collaborative networks among leading researchers, particularly from China and India, highlighting a global commitment to advancing EAI. The analysis identifies key contributors, including foundational work by authors like Devlin J, which has significantly shaped current methodologies. The study underscores the importance of fostering interdisciplinary collaboration and investment in training to enhance the integration of EAI within engineering management practices. These insights provide a roadmap for future research and practical applications aimed at leveraging emotional intelligence to drive improved project outcomes and effective leadership in increasingly complex environments.
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