The purpose of this paper is to find ways to develop more efficient mass transit systems across the USA and, thus, make the best use of state/federal/municipal government funds and taxpayers’ monies. This paper conducts benchmarking studies. In doing so, this paper identifies the best-in class mass transit practices that every regional mass transit system can emulate.
The continuous underutilization of a mass transit system can increase public scrutiny concerning the increased investment in mass transit services. To defuse such scrutiny, this paper analyzes the past (in year 2011) performances of 515 mass transit agencies in the USA using data envelopment analysis (DEA). Also, to identify which factors influences those performances, the authors paired DEA scores for transit efficiency at the state level against a set of independent variables using a special form of regression analysis called Tobit regression.
The authors found that the greater population density of the service area, the greater number of riders can be served in a short amount of distance and time. Also, the authors discovered that the transportation mode of mass transit services could affect mass transit efficiency. On the other hand, the authors found no evidence indicating that the public ownership or private operation of transit systems could make any differences in the transit efficiency.
This paper is one of the few that assessed the performance of mass transit systems in comparison to their peers using a large-scale data and identify the leading causes of mass transit inefficiency. Thus, this paper helps transit authorities in handling juggling acts of protecting the conflicting interests of government policy makers against the general public and, then, make sensible future investment decisions.
The authors would like to express sincere gratitude to both the US Department of Transportation and the Incheon National University for partly funding this research.
Min, H., Ahn, Y. and Lambert, T. (2017), "Benchmarking and improving mass transit systems in the United States based on best-in class practices: Policy implications", International Journal of Logistics Management, The, Vol. 28 No. 1, pp. 172-193. https://doi.org/10.1108/IJLM-01-2015-0031Download as .RIS
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