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• W2793509918 startingPage "1654" @default.
• W2793509918 abstract "This paper is among the first proposing an integrated auction and market design method for the parking space sharing and allocation problem. Drivers (agents) who fail to exchange their own parking spaces can then rent them to the platform. The platform receives private parking spaces from agents and manages some public parking spaces. We first develop the urban parking management cloud platform through Internet of Things. Based on this systemic framework, parking spaces are shared among agents via a price-compatible top trading cycles and chains (PC-TTCCs) mechanism and the platform's parking spaces are reassigned via a one-sided Vickrey-Clarke-Groves (O-VCG) auction. Both the PC-TTCC mechanism with rule e (PC-TTCC [e]) and O-VCG auction are effective in terms of strategy-proofness and (allocative or Pareto) efficiency. In the PC-TTCC [e] mechanism, the platform's payment rule used in private parking space sharing is determined based on historical O-VCG auction prices. Our experimental results further show that the proposed mechanism results in system profitability of 20%-30% and ex post budget balance for the platform." @default.
• W2793509918 created "2018-03-29" @default.
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• W2793509918 date "2018-10-01" @default.
• W2793509918 modified "2023-10-17" @default.
• W2793509918 title "IoT-Enabled Parking Space Sharing and Allocation Mechanisms" @default.
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• W2793509918 doi "https://doi.org/10.1109/tase.2017.2785241" @default.
• W2793509918 hasPublicationYear "2018" @default.
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