Pengaruh persepsi teknologi, persepsi risiko, dan institution based trust terhadap online trust dan perilaku penggunaan jasa ojek

The problem of congestion has become a phenomenon attached to daily life, especially for the citizens of big cities in Indonesia. One of the transportation that can be a solution to cope with traffic jams is online bike. Online bike is currently known as a business opportunity for young businessmen which is also useful to be one of the popular transportation. Based on a survey conducted by Indonesian Consumer Foundation (2017), the reason for the use of online transportation services is cheap (84.1%) and fast (81.9%). The highest rating sequence of online bike was Gojek (72.6%), Grab (66.9%) and Uber (51%). Based on the same survey, there are some forms of consumer disappointment in terms of technology such as difficult to get the driver (21.19%) and broken map application (13.11%); in terms of risk such as insufficient vehicles (6.04%) and inconsiderate drivers (4.73%); in terms of trust such as the driver does not want to be honest with the consumer (5.03%) and the driver does not want to be notified (2.89%). There are five latent variables in this research, such as perceived technology, perceived risk and institution based trust as independent variables, online trust and service usage as dependent variable. The purpose of this research is (1) to identify the service usage of online bike, (2) to analyze the influence of perceived technology, perceived risk and institution based trust towards online trust, (3) to analyze the influence of perceived technology, perceived risk and online trust towards service usage of online bike and (4) to formulate managerial implications that can be applied for companies and government in terms of management of online bike marketing activities. This research took place in Ciluar Asri Housing Area, District of North Bogor, Bogor City. This research has been completed from June to December 2017. The approach used in this research is the survey of household level. The type of data used is the primary data in the form of self-report questionnaires and interviews. The sampling technique used in this research is systematical random sampling with kish grid approach. The terms of respondents in this study is the respondents who have an online bike application, book through the application, and use the online bike service at least once a month. Data processing technique used in this research is Structural Equation Modeling (SEM) with LISREL 8.7 software and descriptive analysis using SPSS 24. Based on the results of the study, it is found that the majority of respondents are women in the age group of 15-24 years old and students with undergraduate background of education. Ownership of vehicles dominated by cars, motorcycles and bicycles. Online bike users are dominated by the 15-24 years age group and this age group has three online bike applications that tend to compare the three online bike before deciding to use the particular one. The majority of respondents use Grab (96%), followed by Gojek (89.5%) and Uber (56.5%). Rarely frequency of used is dominated by Uber (56.5%) whereas in the category of often and always are dominated by Grab. The cash payment method is dominated by Uber (96.5%) and non-cash payment method is dominated by Gojek (33.5%). The feedback rating is dominated by Grab (46.9%). The ranks of the reasons of using online bike for Gojek and Grab brands are price, promotion, convenience, security, easy to get, driver and method of payment. A slight difference on the Uber which is easy to obtain is not included in the sequence of reasons for the selection of Uber so that it can be concluded that it is difficult to get an online bike of Uber. This phenomenon is closely related to the absence of respondents who have only one Uber application alone. The use of Uber application is always together with other online bike applications. Based on the evaluation of overall model fit, this research model includes good fit so it is feasible to do hypothesis test. Based on the measurement model fit, the result does not include Y3 indicator which is payment method by cash. Based on the results of structural model fit, it is obtained the result that all hypothesis is significant except hypothesis 2 (the influence of perceived risk towards online trust) which is not significant. The result of this research is perceived technology influenced positive and significantly to online trust; perceived risk has no significant influence on online trust; institution based trust influence positive and significantly to online trust; perceived technology influence positive and significantly to service usage; perceived risk influenced negative and significantly to service usage; online trust has a positive and significant influence on the service usage. Some form of managerial implication for the companies are to maintain features that can assist consumers in tracking the driver's existence, maintain the promo rate but ensure that the promo rate information is known to the consumer, and maintain the protection of personal information for consumers. The managerial implication for the government is to set rules for online bike companies and provide protection for online bike