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Article Dans Une Revue Computational Urban Science Année : 2022

Passengers receptivity of a new public transport mode: case of a BRT project in Lebanon

Walid Al-Shaar
Nabil Nehme
  • Fonction : Auteur
Olivier Bonin
Jocelyne Adjizian-Gérard
  • Fonction : Auteur
Mohamad Al-Shaar
  • Fonction : Auteur

Résumé

Abstract This study examines how far the level of knowledge on a new public transport mode in Lebanon might affect mode choice. Indeed, passenger mode choice is a major issue associated with the effectiveness of new transport projects, as their level of effectiveness and feasibility will depend on the number of new adopters. This investigation is performed by developing mode choice models based on data collected via a questionnaire-based survey. The models were used to compare preferences among private cars, current public transport modes and a newly proposed Bus Rapid Transit system. The driving factors are divided into two categories: economic and psychological. The results reveal that explicit evaluations of several factors on the proposed transport modes yields mode choices different from direct evaluation. Besides, the structure of the utility function reveals that economic driving factors prevail over the psychological aspects, which is the opposite of what is observed with direct mode assessment. Moreover, people’s expectations of the proposed Bus Rapid Transit were significantly positive in terms of usability in addition to operational and economic reliability. This study shows that people’s level of knowledge of previous transport modes and their perceptual expectations of new travel modes must be taken into consideration in the feasibility studies of any transport implementations in the developing countries where the public transport services are discouraged.

Domaines

Géographie

Dates et versions

halshs-03832015 , version 1 (27-10-2022)

Identifiants

Citer

Walid Al-Shaar, Nabil Nehme, Olivier Bonin, Jocelyne Adjizian-Gérard, Mohamad Al-Shaar. Passengers receptivity of a new public transport mode: case of a BRT project in Lebanon. Computational Urban Science, 2022, 2 (1), pp.25. ⟨10.1007/s43762-022-00053-y⟩. ⟨halshs-03832015⟩
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