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Assessment of the taxi service in Doha

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  • Shaaban, Khaled
  • Kim, Inhi

Abstract

This research focuses on passengers’ satisfaction of the taxi service in Doha, Qatar. Qatar is a rich developing country where taxis are widely considered as a public transportation service due to the limited use of the existing bus service and the profoundly dominant use of private car by expats and Qatari locals. The main objective of this research is to identify the quality attributes of the current taxi service. A descriptive analysis relating the demographic, accessibility, and trip purposes to taxi users in general in Doha with overall service satisfaction was conducted. A Structural Equation Model was used to assess the taxi service attributes that influence the users’ perceived satisfaction. Two models were developed: one was a relationship between the demographic and satisfaction of the users while the other was between the trip time and the satisfaction of the users. The first model supports the premise that income is the greatest attribute in the demographic followed by marital status, age, and occupation. On the other hand, the latter model demonstrated that waiting time is the most contributing variable among the times spent by taxi users followed by walking from work to a station, journey time, and walking from home to a station.

Suggested Citation

  • Shaaban, Khaled & Kim, Inhi, 2016. "Assessment of the taxi service in Doha," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 223-235.
    • Handle: RePEc:eee:transa:v:88:y:2016:i:c:p:223-235
    DOI: 10.1016/j.tra.2016.04.011
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    References listed on IDEAS

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    Cited by:

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    3. Diep Ngoc Su & Duy Quy Nguyen-Phuoc & Lester W. Johnson, 2021. "Effects of perceived safety, involvement and perceived service quality on loyalty intention among ride-sourcing passengers," Transportation, Springer, vol. 48(1), pages 369-393, February.
    4. Helai Huang & Jialing Wu & Fang Liu & Yiwei Wang, 2020. "Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    5. Aleksander Król & Małgorzata Król, 2019. "A Stochastic Simulation Model for the Optimization of the Taxi Management System," Sustainability, MDPI, vol. 11(14), pages 1-22, July.
    6. Wong, R.C.P. & Szeto, W.Y., 2018. "An alternative methodology for evaluating the service quality of urban taxis," Transport Policy, Elsevier, vol. 69(C), pages 132-140.
    7. Alonso, Borja & Barreda, Rosa & dell’Olio, Luigi & Ibeas, Angel, 2018. "Modelling user perception of taxi service quality," Transport Policy, Elsevier, vol. 63(C), pages 157-164.
    8. Aguilera-García, Álvaro & Gomez, Juan & Velázquez, Guillermo & Vassallo, Jose Manuel, 2022. "Ridesourcing vs. traditional taxi services: Understanding users’ choices and preferences in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 161-178.
    9. Das, Sanhita & Boruah, Alice & Banerjee, Arunabha & Raoniar, Rahul & Nama, Suresh & Maurya, Akhilesh Kumar, 2021. "Impact of COVID-19: A radical modal shift from public to private transport mode," Transport Policy, Elsevier, vol. 109(C), pages 1-11.

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