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Optimization of On-Street Parking Charges Based on Price Elasticity of the Expected Perceived Parking Cost

Author

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  • Jun Li

    (School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510000, China)

  • Sifan Wu

    (School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510000, China)

  • Xiaoman Feng

    (School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510000, China)

Abstract

Price discrimination is widely employed to regulate on-street parking behaviors to provide better service to users, and the prices are usually set according to the occupancy of parking spaces without direct consideration of user perception. A binary logit-style choice model is built to describe the parking choice between on-street parking and off-street parking. A new index, named the price elasticity of expected perceived parking cost, is proposed to evaluate users’ response to parking charge. Based on the theory of second-degree price discrimination, three user types are defined according to the parking duration, namely, the preferred users, the neutral users, and the non-preferred users. The optimized parking prices are calculated by the proposed index. A case study of Guangzhou’s on-street parking is presented. It is found that the current pricing scheme for Type-I Zones (High Demand Zones) is reasonable, while the pricing scheme for the Type-II Zones (Low Demand Zones) does not achieve the objectives of usage optimization of on-street parking spaces. An optimized price scheme for the Type-II Zones is proposed to achieve the usage optimization of on-street parking spaces for short-term parking.

Suggested Citation

  • Jun Li & Sifan Wu & Xiaoman Feng, 2021. "Optimization of On-Street Parking Charges Based on Price Elasticity of the Expected Perceived Parking Cost," Sustainability, MDPI, vol. 13(10), pages 1-13, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5735-:d:558557
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    References listed on IDEAS

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