Competitive Spatial Pricing for Urban Parking Systems: Network Structures and Asymmetric Information

Inspired by new technologies to monitor parking occupancy and process market signals, we aim expand the application of demand-responsive pricing in industry. Based on a graphical Hotelling model wherein each garage has information for its incoming demand, consider general competitive spatial systems under an asymmetric structure. We focus impact urban network structure incentive sharing. Our analyses suggest that garages are always better off circular-networked city, while they could be worse suburbs star-networked city. Nevertheless, overall revenue is improved aggregate congestion reduced results also sharing helps further exploit customers who turn become worse-off. Therefore, policy-makers should carefully evaluate their transportation data policy since impacts service-providers typically conflicting. Using SFpark data, empirically confirmed value In particular, with higher price-demand elasticity lower demand variance tend enjoy larger benefits via These insights support joint design rates systems.