RESEARCH ARTICLE


Study of Online Taxi Choice Model in Indonesia



Tarita Aprilani Sitinjak1, *Ludfi Djakfar1Achmad Wicaksono1
1 Department of Civil Engineering, Universitas Brawijaya, Janti Barat Street, C/7, Malang, East Java, Indonesia 65145


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Creative Commons License
© 2020 Sitinjak et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at Department of Civil Engineering, Universitas Brawijaya, Janti Barat Street, C/7, Malang, East Java, Indonesia 65145; Tel: +62-81349054393; E-mail: taritasitinjak@yahoo.co.id


Abstract

Background:

Online taxis, a travel mode with personalized comfort based on mobile Internet technology, are now rapidly expanding in Indonesia.

Objectives:

This study aims to analyze the influence of the personal characteristics and travel characteristics on the choice of an online taxi or conventional taxi and to analyze the online taxi performance in the cities of Surabaya and Malang, Indonesia.

Methods:

A Stated Preference questionnaire was designed and a Google Forms survey was conducted to obtain data; 200 responses were collected. The binary logit model was employed to analyze the influence of the personal characteristics and travel characteristics on the choice modal. Importance-Performance Analysis was proposed to understand the performance of online taxis.

Results:

By applying the binary logit model, it was found that for variables based on a personal characteristic, age and occupation are the most influential variables that affect the decision to use an online-taxi, while for travel characteristic variables, travel cost is the most influential factor in traveler’s choice-making. According to the sensitivity analysis, the midpoint for travel cost was found to be Rp 9.606,20, and 13,43 minutes for pick up time. Through Importance-Performance Analysis, it was found that no attributes need to be improved.

Conclusion:

The estimated logit model can describe the personalized travel mode choice well. The users of an online taxi are people of young age and non-working group. If the gap price and the gap pick up time more than midpoint, the majority of travelers will most likely shift to conventional taxis. The online taxi performance has already met passenger satisfaction.

Keywords: Binary logit model, Conventional taxi, Importance-performance analysis, Mode choice model, Online taxi performance, Pick-up time, Travel cost.