Analysis of Acceptance and Use of Online Transportation on Grab and Go-Jek Application for The Public Using The UTAUT2 Model (Case Study: Bandung)

Abstract

The development of online transportation using grab and go-jek applications is now very rapidly developing and more influencing in changing people’s live. This research was focus in Bandung, West Java, Indonesia. In Indonesia, Grab services have been present since 2012 as a taxi chest application and have provided a variety of transportation choices as cats and motorcycles in the form online mobile. While go-jek began in 2010 as a motorcycle taxi call center in Indonesia, Indonesia-made application in 2015 new unch services namely goride and gocar. In the 2021 now, the grab and go-jek applications are not only developing in Indonesia, but have spread throughout Southeast Asia such as Singapore, Malaysia and Thailand. However use of the online transportation can make competition between other public transportation. This research will help online transportations to evaluate their performance on the acceptance and use of grab and go-jek applications. With this research grab and go-jek applications can know which part they need to improve and suggestion for grab and go-jek applications to increase their service and quality of orders. With this research grab and go-jek applications can know which are make customer satisfaction and which area make customer dissatisfaction. This research takes eleven major factors UTAUT 2 models that have impact with how customer can accept and use online transportation for grab and go-jek applications. Those factors are performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit, and then add two external variables are service quality and customer satisfaction. This research will use survey and distribution of questionnaires method to gain some information from customer. After collect some data and information. This research will use SPSS and AMOS to process the data to know which hypotheses is accepted and rejected. Method using by this research in AMOS is SEM. SEM will give a significant point for every question to know the result can accept or reject.