Work

Predicting the commuter's willingness to use lrt, utilising the theory of planned behaviour and structural equation

Year: 2020

Type: article

Abstract: Many researchers highlighted that the rail-based public transport system is not the people's favourite means of transportation in the Urban Rail Development Plan (2013) plus the Kuala Lumpur Structure Plan (2020). The policy-makers focused on this issue while planning the urban transportation system in Klang Valley, Malaysia. This region has undergone rapid growth in the past few years with regards to their geographical significance and population size. However, this increased traffic congestion in the city. In this study, the researcher has aimed to investigate and increase the accessibility of the commuters to and from their homes by the train systems in the Klang Valley. For understanding the willingness of the people to use the train system in Klang Valley, the researcher studied 4 predictors, i.e., trust, situational factors, novelty-seeking and external influence, with respect to the Theory of Planned Behaviour (TPB) model. The researcher obtained the data from the people working in Klang Valley, Malaysia. The sample size used was 400 participants. The results indicated that the Perceived Behavioural Control (Pbc), attitude and subjective norm displayed positive effects on their behavioural intention to use the train system. Additionally, external influence and novelty-seeking positively affected the attitude. The 3 antecedents of trust, i.e., subjective norm, attitude and Pbc, indirectly and positively affected the intention of the commuters to use the train system. The situational factors showed an indirect, but bad influence on the intention of commuters to use trains, via the Pbc.

Source: Istrazivanja i projektovanja za privredu

DOI: 10.5937/jaes18-27013

Author: Dhafir Hussain

Institution: Mustansiriyah University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $377