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Measuring willingness to pay for shared parking

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  • Ardeshiri, Ali
  • Safarighouzhdi, Farshid
  • Hossein Rashidi, Taha

Abstract

This study explores how individuals evaluate different shared parking features, as an emerging concept. In this paper, we develop a latent class behavioural model for a sample of 1,008 residents in New South Wales, Australia to explore different segments of taste and preference for shared parking. The outcome of this study extends our understanding about the emerging concept of shared parking by quantifying monetary value, in terms of willingness-to-pay, of different features of this new emerging phenomenon. This study contributes to the literature by providing firsthand insights about how demand for shared parking is formed and how different policy implication can be made accordingly. The results indicate that pricing persists to be the sole most effective parking policy, however non-price-related attributes can help decision makers to make more informative decision when it comes to different pricing schemes. The study also highlights that shared parking can perform a significant role in accommodating the surplus arising from the excessive parking demand and inadequate supply up to almost 40% of demand. The outcome of this study is anticipated to inform and equip city authorities with advanced knowledge about such an emerging phenomenon which can help developing regulations before the concept is out of control. Information from this study can also guide the private sector and the wider community to identify and develop opportunities related to shared parking.

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  • Ardeshiri, Ali & Safarighouzhdi, Farshid & Hossein Rashidi, Taha, 2021. "Measuring willingness to pay for shared parking," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 186-202.
    • Handle: RePEc:eee:transa:v:152:y:2021:i:c:p:186-202
    DOI: 10.1016/j.tra.2021.08.014
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    3. Macea, Luis F. & Serrano, Iván & Carcache-Guas, Camila, 2023. "A reservation-based parking behavioral model for parking demand management in urban areas," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

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