Assessing the Societal Impact of Academic Research with Artificial Intelligence (AI): A Scoping Review of Best Practices in Business School Scholarship

Abstract

This paper explores how current evaluative frameworks for academic research can translate scholarly findings into practical applications to tackle global grand challenges. Using a scoping review methodology, the investigation analyzes the metadata of 4,051 journal articles, integrating quantitative and qualitative analyses of publication data with supervised AI-human collaboration. This paper underscores the transformative potential of integrating AI in academic research to achieve broader societal benefits. The research identifies ten core themes related to the societal impact of research in business and management disciplines. Key findings highlight gaps in the literature concerning the practical application of research insights, an overemphasis on scholar-to-scholar versus scholar-to-society research, and insufficient research alignment with the United Nations Sustainable Development Goals (SDGs). The discussion emphasizes the need for academic institutions to expand research appraisal criteria beyond traditional metrics and cultural norms to include real-world impacts. The study introduces Disciplined Vision Casting (DVC) as a novel approach to envisioning a sustainable future by fostering societal impact through research. Recommendations for future research, practice, and policy include developing holistic research assessment frameworks to directly incentivize researchers to address global wicked problems. This paper demonstrates how academic research can be a transformative "force for good" in business and other disciplines.

Keywords: societal impact, responsible research, scholarly engagement, research assessment, impactful research, grand challenges, wicked problems, Sustainable Development Goals, SDGs, business and management disciplines, scoping review, responsible management education, AI research methods, AI ethics, Disciplined Vision Casting (DVC), research impact

JEL Classification: A10, A20, C10, C80, D80, I20, O30, M10, M20