Modeling significant factors affecting commuters’ perspectives and propensity to use the new proposed metro service in Doha

Author:

Shaaban Khaled1,Hassan Hany M.2

Affiliation:

1. Department of Civil Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.

2. Department of Civil Engineering, Ain Shams University, 1 Al-Sarayat Street, Abbasia, Cairo, Egypt.

Abstract

The Qatari government introduced a major public transport project titled the Doha Metro system to address the fast growing transportation demands in Qatar’s urban areas and to be ready for the Qatar 2022 FIFA World Cup. To benefit from this new metro system in reducing traffic congestion problems in Doha, it must be attractive with a reasonable level of service to attract large numbers of car users to switch to the new metro. This goal can be achieved by a better understanding of the user’s needs and expectations in Qatar. This paper aims to identify and quantify the significant factors affecting commuters’ perspectives, preferences and tendencies to use this new metro network for their daily trips in the future. The data used for the analysis was obtained from a self-reported questionnaire survey carried out among a sample of commuters living in Doha. Different data mining techniques were employed including conditional distributions and two-way analysis. In addition, logistic regression and structural equation modeling approaches were developed. The results revealed that the location of metro stations, the metro station’s features, the metro’s features, gender, the number of daily trips, the purpose of trips, and the average duration of trips in Doha were the significant factors that affected commuters’ willingness and tendency to use the new metro system. The results of this study provide authorities and decision makers in Doha with valuable insights that should be taken into consideration prior to implementing the new metro service to ensure its success.

Publisher

Canadian Science Publishing

Subject

General Environmental Science,Civil and Structural Engineering

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