Rethinking Performance Based Parking Pricing: A Case Study of SFpark

Transportation Research Part A: Policy and Practice, Forthcoming

22 Pages Posted: 2 Oct 2017 Last revised: 16 Mar 2018

See all articles by Tayo Fabusuyi

Tayo Fabusuyi

University of Michigan at Ann Arbor - Transportation Research Institute; Numeritics

Robert Hampshire

University of Michigan at Ann Arbor - Transportation Research Institute

Date Written: September 28, 2017

Abstract

In an effort to reduce circling and cruising in cities’ central business districts (CBDs), a number of cities have begun implementing pricing programs that modify parking rates based on observed occupancy levels. We improve on this pricing mechanism by developing a forward-looking policy instrument. The instrument employs a two-stage panel data regression and optimization model that influences demand for parking spaces by changing parking rates via computed price elasticities of parking demand measures. Coefficient estimates that include the elasticity measures from the panel data regression are used to fit a linear prediction model that is the primary input to the optimization model.

An application of the approach is presented using SFpark, a federal government-funded demonstration program in San Francisco as a case study. We evaluate the effectiveness of the modified pricing mechanism by comparing actual occupancy and parking rate tuples with the optimized result to ascertain the potential improvement in SFpark’s performance. Policy scenarios are subsequently explored by carrying out sensitivity analysis primarily through SFpark pricing rules. Relative to SFpark’s figures, our model yielded approximately 16% improvement in systems performance when measured by the number of blocks that deviate from the 60 to 80% occupancy target. Our findings highlight the importance of moving towards a predictive regime that allows for proactively managing the parking program compared to a reactive approach based on observed parking occupancy.

Keywords: curb parking, price elasticity, panel data, random effect, policy scenarios

JEL Classification: C01, R41

Suggested Citation

Fabusuyi, Tayo and Hampshire, Robert, Rethinking Performance Based Parking Pricing: A Case Study of SFpark (September 28, 2017). Transportation Research Part A: Policy and Practice, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3044818 or http://dx.doi.org/10.2139/ssrn.3044818

Tayo Fabusuyi (Contact Author)

University of Michigan at Ann Arbor - Transportation Research Institute ( email )

2901 Baxter Road
Ann Arbor, MI 48109
United States

Numeritics ( email )

5907 Penn Avenue
Suite 313
Pittsburgh, PA 15206

Robert Hampshire

University of Michigan at Ann Arbor - Transportation Research Institute ( email )

2901 Baxter Road
Ann Arbor, MI 48109
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
56
Abstract Views
412
rank
393,223
PlumX Metrics