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An Integrated Approach to Select Key Quality Indicators in Transit Services

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Abstract

Recent interests in transit services have captured attention of experts on the monitoring of public transport quality. Previous research focused on relevant models and methods to monitor the quality of transit services and showed where and when different service quality levels occur. However, there was little attention to detect objectively a pool of key quality indicators (KQI) to be monitored, from a large set. This paper covers this gap by the proposal of an integrated approach, which identifies a long list of KQI, defines their properties, involves experts to elicit judgments for each KQI, evaluates the long list, and points out the most promising set. This integrated approach is demonstrated with an application based on an international survey and a Monte Carlo simulation method. Moreover, a restricted and relevant set of 9 overlapping KQI is derived by linking these results with those obtained from two different approaches.

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Notes

  1. For instance, the regularity can be measured in terms of the percentage of buses which maintain evenness headways at bus stops—transit—perspective orientation—or in terms of the percentage of passengers who wait at bus stops less than a fraction of scheduled headways—passenger-perspective orientation (e.g., Barabino et al. 2017).

  2. CEN/TC 320 (2002) issued the European Norm EN 13816:2002 for the definition, targeting and measurement of transit service quality. See the “Appendix” for details.

  3. These indicators are usually evaluated by PTCs for the purposes of standardization, benchmarking and quality certification.

  4. Eboli and Mazzulla (2015) began the analysis by choosing among 33 sub-indicators and restrict the investigation to a railway transit system.

  5. For the sake of synthesis, in what follows, service aspects, indicators and sub-indicators will all be referred to as indicators or KQI.

  6. EN 13816:2002 is a ground-breaking standard designed to enhance the promotion of a more customer-oriented quality approach within the public transportation sector. It is intended to be adopted by PTCs in the presentation and monitoring of their services, but it is recommended for use by authorities and transit agencies for the procurement of public passenger transport services in the preparation of invitations to tender.

    EN 15140:2006 is intended to help construct the measurement system and to help understand and reduce the causes of biases that any system of measurement may introduce. Moreover, a set of reference levels needed to measure the degree of fulfilment of the EN 13816:2002 indicators has been introduced, so to help in the adoption of standardized measurement methods and operational procedures for the service quality determination.

  7. Although this method may be questionable (Dyer 1990), many scholars defend it and document about the advantages deriving from its use (e.g., Saaty 1990; Harker and Vargas 1990; Forman and Gass 2001; Ramanathan 2001; Millet and Wedley 2002; Macharis et al. 2004; Oguztimur 2011). Moreover, AHP is widely adopted in many fields of engineering, which contribute to reinforce its use among bus operators (e.g., de Steiguer et al. 2003).

  8. For instance, the waiting time is not explicitly mentioned in CEN/TC 320 (2002), but it can be derived easily from measurements of regularity and/or punctuality (e.g., Barabino et al. 2017).

  9. http://cwur.org/2016.php.

  10. http://www.shanghairanking.com/.

  11. https://www.timeshighereducation.com/.

  12. http://www.uitp.org/. UITP is a no profit international organization including 1,400 members from 96 countries worldwide.

  13. https://it.linkedin.com/.

  14. www.skrapp.io.

  15. www.growthbot.org.

  16. For sake of completeness, the distribution of weights attributed to the quality and methodological components by academic and practitioners w.r.t. their geographical localization is reported in Table 10 in the “Appendix”.

  17. For sake of completeness, the distribution of weights attributed to the attributes of quality and methodological components by academic and practitioners w.r.t. their geographical localization is reported in Tables 11 and 12 in the “Appendix”.

  18. See Table 9 in the “Appendix” for details.

  19. www.scimagojr.com.

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Acknowledgements

This work was partially supported by the Italian Ministry of University and Research (MIUR), within the Smart City framework (project: PON04a2_00381 “CAGLIARI2020”) and by Regione Autonoma della Sardegna (IT) (Grant Name: Programmazione Unitaria 2007/2013—P.O. FESR 2007/2013, Interventi a sostegno della competitività e dell’innovazione 2016-2018).

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Authors and Affiliations

  1. Department of Civil Engineering, Architecture, Land, Environment and Mathematics (DICATAM), University of Brescia, via Branze 43, 25123, Brescia, Italy

    Benedetto Barabino

  2. School of Economics, Law and Social Sciences, University of Cagliari, Viale S. Ignazio 78, 09123, Cagliari, Italy

    Nicola Aldo Cabras

  3. Department of Business and Economics Sciences, University of Cagliari, Viale S. Ignazio 17, 09123, Cagliari, Italy

    Claudio Conversano

  4. Department of Civil Engineering, Environment and Architecture, University of Cagliari, Via Marengo 2, 09123, Cagliari, Italy

    Alessandro Olivo

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  1. Benedetto Barabino
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Correspondence to Claudio Conversano.

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Appendix

Appendix

See Tables 9, 10, 11 and 12.

Table 9 The long list of KQI.
Full size table
Table 10 Distribution of observed weights of methodological and relevance to quality components
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Table 11 Distribution of observed weights of methodological components
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Table 12 Distribution of adjusted weights of quality components
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Barabino, B., Cabras, N.A., Conversano, C. et al. An Integrated Approach to Select Key Quality Indicators in Transit Services. Soc Indic Res 149, 1045–1080 (2020). https://doi.org/10.1007/s11205-020-02284-0

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