Designing a Smart Governance Model for an Integrated Urban Transportation System Using Artificial Intelligence and Private Sector Participation
Subject Areas : Urban Management Studies
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Keywords: Smart Governance, Integrated Urban Transportation, Artificial Intelligence, Smart City, Private Sector Participation,
Abstract :
emphasizing the role of artificial intelligence and private sector participation. The research, conducted using a descriptive-analytical approach, employs library, documentary, and comparative methods and analyzes the experiences of four leading countries (the Netherlands, Singapore, Japan, and Germany) based on 25 reputable sources.
The findings indicate that an optimal smart governance model for urban transportation should be grounded in three fundamental pillars: data-driven and networked governance, the application of artificial intelligence in integrated management, and strategic private sector participation. Data analysis confirms that the key components of such a model include data orientation, multi-stakeholder collaboration, transparency, institutional integration, and financial innovation.
The study further shows that successful implementation of this model requires institutional, technical, and legal prerequisites, including reforming managerial structures, developing data infrastructures, establishing clear regulatory frameworks, and ensuring data security. Meeting these conditions can significantly improve transportation system efficiency, reduce traffic congestion, decrease pollution, and enhance citizen satisfaction.
The novelty of this research lies in developing a localized smart governance model for urban transportation that simultaneously integrates the three core pillars of data-driven governance, artificial intelligence-enabled integrated management, and strategic private sector participation within a unified conceptual framework. This model can support strategic decision-making for urban managers and contribute to the development of sustainable and resilient cities.
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