Yayınlanmış 1 Ocak 2019 | Sürüm v1
Dergi makalesi Açık

Spillover parking

  • 1. Penn State Univ, Dept Econ, University Pk, PA 16802 USA
  • 2. Sabanci Univ, Fac Arts & Social Sci, TR-34956 Orhanli Tuzla Istanbul, Turkey
  • 3. Univ British Columbia, Solider Sch Business, 2053 Main Mall, Vancouver, BC V6T 1Z2, Canada

Açıklama

Parking space near popular destinations is often scarce or expensive. Instead, visitors may park in adjoining locales where they impede through traffic, take parking space from other users, and create environmental externalities. We develop a model to study spillover parking generated by a major retailer (e.g., a mall) that provides limited on-site parking. Some customers park at the mall, some park on the street, and others who live or work nearby visit the mall on foot. The retailer chooses its parking lot capacity, the parking fee, and the retail markup. We compare the effectiveness of four policies for dealing with spillover parking: on-street parking fees, on-street parking bans (aka residential parking permits), regulating mall parking fees, and regulating mall parking capacity (aka minimum/maximum parking requirements). Policy effectiveness depends on the severity of congestion, the amount of mall shopping by local and nonlocal shoppers, and the mall's market power. A curbside parking ban is harmful unless congestion is severe. If the mall has no market power, both on-street parking fees and mall parking fee regulation can support the social optimum, whereas mall parking lot capacity regulation is useless. In contrast, if the mall has substantial market power, capacity regulation in the form of a minimum parking requirement can be the most effective policy. The benefits of implementing pairs of policies can be larger, or smaller, than the sum of the benefits from applying them individually. (C) 2019 Elsevier Ltd. All rights reserved.

Dosyalar

bib-71b1332e-9e55-47ef-baad-abda58ddf086.txt

Dosyalar (126 Bytes)

Ad Boyut Hepisini indir
md5:dec8dbd98019462db0f06c6bf6a9564b
126 Bytes Ön İzleme İndir