Abstract

To mitigate car traffic problems, the United Nations Human Settlements Programme (UN-Habitat) issued a document that provides guidelines for sustainable development and the promotion of public transport. The efficiency of the policies and strategies needs to be evaluated to improve the performance of public transportation networks. To assess the performance of a public transport network, it is first necessary to select evaluation criteria. Based on existing indicators, this research proposes a public transport criteria matrix that includes the basic public transport infrastructure level, public transport service level, economic benefit level, and sustainable development level. A public transport criteria matrix AHP model is established to assess the performance of public transport networks. The established model selects appropriate evaluation criteria based on existing performance standards. It is applied to study the Stonnington, Bayswater, and Cockburn public transport network, representing a series of land use and transport policy backgrounds. The local public transport authorities can apply the established transport criteria matrix AHP model to monitor the performance of a public transport network and provide guidance for its improvement.

Highlights

  • Worldwide, metropolitan areas of numerous countries are facing a set of urgent issues related to the growing trend of private car usage and the subsequent damage to the environment [1]

  • We investigated the performance of public transport networks at the basic public transport infrastructure level, public transport service level, economic benefit level, and sustainable development level

  • Based on the existing standards for each sub-standard, the new evaluation model gives a score for a city’s public transportation network performance, and the results show the aspects that the government should consider improving in the future

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Summary

Introduction

Metropolitan areas of numerous countries are facing a set of urgent issues related to the growing trend of private car usage and the subsequent damage to the environment [1]. In response to these issues, one major approach is to use public transport [2]. There are three major methods for measuring the efficiency of public transport networks: stochastic frontier analysis (SFA), analytic hierarchy process (AHP), and data envelopment analysis (DEA) [4,5,6] Both SFA and DEA focus only on measuring production efficiency related to economic theory [5].

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