Valuing Manggarai Station – Soekarno-Hatta International Airport Rail Link Using Stated Preference Approach - Wahyu Tamtomo Adi (Department of Civil and Environmental Engineering, Faculty of Engineering, UGM, 2013)
This study attempts to identify the characteristics and preference of the SHIA airport travelers, estimate the subjective value of in-vehicle time and waiting time by providing choice experiments regarding the available modes in combination with the Airport Rail Link (ARL) service as hypothetical situation, analyze how the values vary according to the socio-demographics of respondents and forecasting the mode sharing and the elasticity based on several scenarios. Five hundred respondents as potential demand for the airport access mode from both the online and on-field survey in Jakarta value reliability as the most important factors followed by comfort, journey time, fares and safety, while the most reliable journey according to the respondents is by train.After various attempts to best analyze the data, statistically significant result is obtained from MNL and Nested models. The values of IVT vary between 632 Rupiah/Minute and 871 Rupiah/Minutes, the values of waiting time vary between 901 Rupiah/Minute and 1,504 Rupiah/Minute. The results of unobserved parameters from the alternative modes are satisfactory negative for bus and positive for ARL alternative.The segmented models results vary that the value of male is higher than female, the value of high income is higher than low income, the values of taxi user is higher than car user, the value of business traveler is higher than leisure and commuter traveler, the value of self-finance journey is lower than the journey paid by the company. With the standard level of service, the probability result of mode sharing shows that the majority of respondents will use the train service (40.99%), followed by the other modes: bus (30.90%), car (16.52%), and taxi (11.59%).Keywords: Jakarta, SHIA airport, access mode, value of in-vehicle time, value of waiting time, model segmentation, mode sharing.