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Cost models for local road transit

Umberto Petruccelli () and Salvatore Carleo
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Umberto Petruccelli: School of Engineering

Public Transport, 2017, vol. 9, issue 3, 527-548

Abstract: Abstract Knowing the standard cost of public transit services is essential both for contracting authorities to banish and competently perform public tender and for states or regions to allocate resources for public transport between local authorities according to the actual local needs. Unfortunately, contracting authorities do not have access to robust cost estimates that take into account the characteristics of the service and the context in which it is produced, and that are, at the same time, detached from the specific characteristics of the company. Instead, most authorities use the historic cost, which is heavily influenced by the conditions of the specific market in which the companies operate, or the cost derived by the available budget of the authority. Both values can obviously differ greatly from the standard cost. This work proposes a methodology for building a synthetic model to assess a reference cost for local road transit services. This methodology is based on statistical analysis that correlates the features and the costs from contracted services in conditions that presuppose a highly efficient business. The developed model distinguishes between the characteristics of the service that are related to the operating program and the business efficiency parameters, which are not typically known outside of the company and are not the same for all companies. The proposed methodology is generally applicable, easy to use, and ensures reliable results if supported by a sufficiently large database. The model developed for suburban and intercity public road transit, although it was calibrated using a restricted database, represents the reality quite closely, as evidenced by the results of the statistical tests performed.

Keywords: Cost Function; Public Transport; Transit Service; Standard Cost; Transport Company (search for similar items in EconPapers)
Date: 2017
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