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admin - Oct 27, 2017 03:53:52 pm 1 Views Research

Transportation Online: Perception on Transportation on Line in Urban Area

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The emergence of online taxi in Indonesia has changed the landscape of public transportation. GoJek, Uber, and Grab are among the biggest providers that joined the public transportation in Indonesian major cities. Currently, the modes on their service include car and motorcycle, in addition to other services including food delivery, shopping service, and logistics. At the same time, the existing modes such as bus, railway-based modes, and paratransit (angkot) are still struggling to deliver the high performance as means of transportation. There are several conflicts inflicted not only by the competition among online taxi and other public transportation, but also by the agenda of municipalities to build comprehensive transit system, such as light rapid transit (LRT) and mass rapid transit (MRT).

Online taxi has several competitiveness regarding to other transportation. Before the rate is fixed, the online taxi providers offered reasonable price, which is relatively lower than that of existing taxi. Regarding to public transportation such as paratransit and BRT, online taxi covers the trip from origin point to the destination, without a need to go to transportation hub. Also, there is simplicity in paying the fare since several online taxis also provide e-payment. In addition, some even provide more services including food delivery and shopping, all of which is supported by the discounts and promos.

It is strongly suggested that the high performance of online taxi has huge influence over how urban dwellers choose the mode of transportation. However, the preference of users regarding to the online transportation needs to be analyzed further. This study aims to model the user’s perception to choose online taxi. Taking place in Bandung City, this study will measure the variables related to preference which include travel time, travel cost, and safety. The results would be analyzed by regression analysis to model the users’ choice of mode.

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