Estimating Crowding Costs in Public Transport

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in April 2013Abstract Preferences for transport activities are often considered only in terms of time and money. Whilst congestion in automobile traffic increases costs by raising trip durations, the same is less obvious in public transport (PT), especially rail-based. This has lead many economic analyses to conclude that there exists a free lunch by reducing the attractiveness of automobile transport at no (or little) cost for PT users. This article argues that congestion in PT -crowding -is also costly. Using survey data from the Paris metro we estimate the degree to which users value comfort in terms of less crowding. Using a contingent valuation method (CVM) we describe marginal willingness to pay over different parts of the distribution of in-vehicle crowding and consider moderating factors. We conclude that the total welfare cost for a trip rises from e 2.42 for a seated passenger to e 3.69 under the most congested conditions. We apply our results to the cost-benefit analysis of a recent investment in PT in Paris and consider broader implications for transport policy. In particular, we highlight that PT congestion is a first-order urban externality.

The distribution of crowding costs in public transport: New evidence from Paris

“…Appendix A.3 considers an alternative decomposition of descriptive statistics by sequences of responses to bids. 19 Exploratory estimates conducted by Haywood and Koning (2013) with an ordered logit confirm that reference points are significantly influenced by objective levels of density (surveyed data and reported data). In line with this information, the expected density appears to be higher for line 1 users and for individuals interviewed during evening peaks.…”

Partial Node Failure in Shortest Path Network Problems

“…However, those metrics are often less predictable. For example, the durations of waiting and transferring times at stops are significantly influenced by crowding conditions such as those related to peak versus non-peak hours [34]. Thus, we define travel distance as C ij .…”

Calculation Method for On-Board Crowding Degree of a Bus Route/Network

“…They extended the formulation to calculate the headways by incorporating crowding discomfort costs in the objective function. Haywood et al (2013) considered that crowding in public transport was also costly and proposed the contingent valuation method to describe the marginal willingness to pay for on-board crowding. The results showed that the total cost for a trip rose from €2.42 for a seated passenger to €3.69 under the most congested conditions.…”