Selecting key quality indicators in public transport systems by a robust method

Barabino, Benedetto

Member of the Collaboration Group

;Conversano, Claudio;Cabras, Nicola Aldo;Fantola, Massimo

2019-01-01

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Abstract

Recent interests in transit services have captured attention of experts on the monitoring of public transport quality. Previous research has focused on the development of relevant models and methods for monitoring transit service quality and identified where and when different levels of service quality occur. However, little attention has been given to objectively determining a pool of key quality indicators (KQIs) for monitoring purposes. In this paper, we address this gap by proposing a robust methodology that identifies a lengthy list of potential KQIs and defines their properties, then enlists the judgement of both researchers and practitioners regarding each KQI, evaluates the initial list, and recommends the most promising KQI set. We demonstrate the effectiveness of this methodology using an international survey and Monte Carlo simulation methods. The outcomes will prove useful in helping practitioners to monitor transit service quality according to a set of recognised KQIs.