Paper Type

ERF

Abstract

Artificial Intelligence (AI) is increasingly positioned to improve sustainable public transportation, yet research in this domain remains fragmented across technical and managerial streams. This Emergent Research Forum paper presents a systematic literature review of 66 peer-reviewed studies on AI in sustainable public transportation. Investigating research themes dominate this literature, this study combines a structured review protocol with a human-in-the-loop thematic synthesis supported by GPT-4 under continuous author validation. The findings identify four dominant, non-exclusive themes: AI for Transit Operations & Services, AI for Network & Traffic Operations, AI for Smart Mobility Planning, and Governance & Societal Implications. Together, these themes suggest that existing scholarships are increasingly diverse, but still weigh more heavily toward planning, coordination, and operational optimization than toward broader sociotechnical and public-value concerns. The paper contributes an initial thematic map for Information Systems research and provides a foundation for future analyses of AI methods and implementation barriers.

Paper Number

1445

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Aug 15th, 12:00 AM

Managing Artificial Intelligence for Sustainable Public Transportation: A Systematic Literature Review

Artificial Intelligence (AI) is increasingly positioned to improve sustainable public transportation, yet research in this domain remains fragmented across technical and managerial streams. This Emergent Research Forum paper presents a systematic literature review of 66 peer-reviewed studies on AI in sustainable public transportation. Investigating research themes dominate this literature, this study combines a structured review protocol with a human-in-the-loop thematic synthesis supported by GPT-4 under continuous author validation. The findings identify four dominant, non-exclusive themes: AI for Transit Operations & Services, AI for Network & Traffic Operations, AI for Smart Mobility Planning, and Governance & Societal Implications. Together, these themes suggest that existing scholarships are increasingly diverse, but still weigh more heavily toward planning, coordination, and operational optimization than toward broader sociotechnical and public-value concerns. The paper contributes an initial thematic map for Information Systems research and provides a foundation for future analyses of AI methods and implementation barriers.

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