Using psychometric data from the stated preference (SP) experiments to search explanatory power for appropriateness of congestion charging policy - Sofyan M. Saleh; Sugiarto Sugiarto; Cut Mutiawati; Renni Angraini; Muhammad Isya (Aceh International Journal of Science and Technology, 2016)
Comprehensive stated preference (SP) experiment was conducted in Jakarta (a capital of Indonesia), where proposal for congestion charge (CC) has been considered as a way to reduce acute traffic congestion. With the government planning a CC scheme, public support is regarded as a prerequisite for its implementation. Therefore, a framework of structural equation model (SEM) is used to search explanatory power for the appropriateness of CC considering unobserved variable (latent variable) from psychometric data obtained from SP questionare.  Causal paths among psychological determinants and their strength are measured and analyzed along with proposal acceptability from a psychological perspective. The findings from analysis with a SEM approach shows that a number of psychological determinants provide an explanation for the acceptability of the proposed scheme. The findings from analysis with a SEM approach shows that a number of psychological determinants provide an explanation for the appropriateness of the proposed scheme. Latent variables representing the validity of the CC scheme, such as ACE, APC and REC appear to have a significant explanation. These emerge as psychological determinants contributing a positive correlation with enhancement of appropriateness CC policy. Empirical result further shows that males have positive scores for the latent variables of car dependency (CDC) and inhibition freedom of movement (IFM). Furthermore, the variable of annual income, it has a positive correlation with recognition of the effects of CC in mitigating congestion and environmental problems (REC), car dependency (CDC) and awareness of the problems of cars in society (APC). This means that respondents with higher incomes are more concerned with the problems manifested by motorization while, on the contrary, the path coefficient between annual income (AI) and car dependency (CDC) has a value of 0.270. This discloses an automobile dependency. These findings should provide insight that designing a more acceptable policy in respecting to the acceptance of public in large.