4.5 Article

Assessing free-fare public transport in Chilean cities through optimization models

Journal

RESEARCH IN TRANSPORTATION ECONOMICS
Volume 98, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.retrec.2023.101277

Keywords

Public transport; Free-fare; Optimization models; Small cities; Linear regression

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Many cities in Europe have made progress in providing free-fare public transport, which can help reduce car use and minimize negative externalities. Using cost minimization models and linear regression, optimal fares for bus services were estimated for 33 small and medium-sized cities in Chile. Recommendations are provided for selecting the best cities for a test of free-fare public transport in Chile, considering factors such as population, income level, student proportion, and natural boundaries.
Many public transport services receive operating subsidies from national, regional, or local Governments, part of which are directed to reducing fares. In recent years, different cities, most of them located in Europe, have advanced in the provision of free-fare public transport, which could help reduce car use and thus limit negative externalities related to its use. Using cost minimization models with variable mode share, in a circular structure with radial lines, optimal fares for bus services were estimated for 33 small and medium-sized cities in Chile. Through a linear regression model, we determined that the optimal fares decrease for cities with higher population, lower average income, a higher proportion of students, and with a CBD surrounded by natural boundaries such as seacoast. Based on the model's results, together with feasibility criteria that included competition of buses with other transportation modes, the regulation of existing systems and the quality of available data, recommendations are provided to select the best cities for a test of free-fare public transport in Chile. The methodology is applicable to cities in other countries, and future research may incorporate the effect of the valuation of crowding by users, as well as the generation of additional trips due to a drop in bus fares.

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