Identifying usage intention factors of branded running tracker applications in Indonesia using utaut2 model

Abstract

Abstract. Increased public awareness of health and fitness topics, as well as the development of cellular technology, have introduced mHealth technology (mobile health) to the health sector, which is expected to continue to grow over the next few years. mHealth is widely available in the community in the form of mobile applications that can be easily accessed via smartphones. Initially designed to meet health and medical needs, several people have developed the use of the mHealth app into a lifestyle. One of them is the use of a running tracker application that is popular among sports activists who need this application to support them by providing information and statistics regarding their running performance. This trend has begun to attract the attention of companies to also publish their own branded running tracker applications, which shows the identity of the brand through the application name or brand logo, as part of their marketing communication strategy. When the applications cannot maintain their current users and acquiring the new one, the applications will also fail to

survive in the market and missed the opportunity to attract potential consumers to get into the brand. On the other hand, Indonesia with their number of population and increasing running trend is a promising prospect for application publishers and marketers to expand their market to Indonesia. In order to be able to acquire more of their application users, it is very important to identify the factors that encourage consumers to start adopting a running tracker application for Indonesian market. This study attempts to identify the behavioral intention factors from the perspective of consumer technology adoption by adapting the UTAUT2 acceptance model and investigate the relationship between the behavioral intention to the actual use of running tracker applications.

Online surveys have been distributed to running tracker application users in Bandung and Jakarta, Indonesia, to collect the primary data needed to predict accurate results for this study. The results of the PLS-SEM analysis showed that effort expectancy factors, hedonic motivation, and habits, had an impact on the behavioral intention to use the running tracker application. This analysis is expected to expand the discussion regarding the  acceptance of mHealth applications, especially in the subcategory of fitness and sports. Also as a recommendation for application developers and marketers to consider features that can encourage more users to adopt a running tracker application.

Keywords: Behavioral Intention, mHealth Apps, Mobile Apps, Running Tracker Apps, Technology Acceptance, UTAUT2