Managerial Innovations for Urban Public Transportation Transformation

Modern urban governance is transitioning from traditional approaches towards data-driven, transparent, and participatory models. This article integrates two distinct yet deeply interconnected domains - "Big Data Sources" and "Local Governance Innovation" - to present a unified framework for understanding the transformation of public transportation systems. We first conduct a systematic review of the most significant modern data sources, including Automated Fare Collection (AFC) systems, mobile phone Call Detail Records (CDR), Global Positioning System (GPS) data, social media, and Automated Passenger Counting (APC) data. We examine the advantages, limitations, and technical applications of each in estimating Origin-Destination (OD) matrices, predicting demand, and optimizing services. Second, we demonstrate how this data constitutes not merely technical tools but the foundation for a transformation in local governance. This transformation manifests in performance-based budgeting, precise policy impact evaluation, participatory service design, and enhanced transparency and accountability. The article concludes by discussing the challenges facing this transformation, including privacy concerns, the digital divide, and the need for capacity building in local institutions. It argues that the intelligent integration of these data sources into governance processes is key to achieving efficient, equitable, and intelligent public transportation systems.

کلیدواژه ها:

Data-Driven Governance ، Big Data Sources ، Public Transportation ، Urban Innovation ، Local Governance