<![CDATA[Transportation uses a significant amount of energy and burns most of the world's petroleum. As a result, it gives effect to the environment, such as air pollution in the forms of carbon dioxide, nitrous oxide, and particulates. Those compounds create a phenomenon called global warming. Within the transportation sector, road transport is the largest contributor to global warming. To cope with global warming, environmental regulations in developed countries are trying to reduce the individual vehicle's emissions. However, this has been counterbalanced by an increase in the number of vehicles and increased use of each vehicle. Therefore, micro-mobility may alleviate several challenges facing big cities today and offer more sustainable urban transportation. In the next ten years, e-scooter sharing is predicted to become an international business as its potential to become a multi-billion dollar industry (Purnomo Yusgiantoro, 2019). E-scooter sharing has seen a massive leap in popularity within the last few years because, on the surface, it appears to be a business model that is here to stay and, most importantly, has become a solution in creating a greener environment and economy. This research utilizes the framework of the UTAUT2 to identify and build a quantitative approach to identify factors related to the purchase intention factors of e-scooter sharing. The 200 respondents' field data were collected in Jakarta Metropolitan Area (Jabodetabek) as a rapid increase in pollution level and a considerable number of essentials of the central business district and many high-rises stores and universities. The linear regression study revealed that the consumers' purchase intention of e-scooter sharing is shaped by seven main factors: performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value, and habit. Those factors can explain 83 percent of the field data. Moreover, a brief recommendation for related stakeholders based on the Research results are proposed to increase the adoption of e-scooter sharing. The practical implications resulting from this analysis are suggested policy measures, e-scooter sharing, environmentally impact potency and strengthening green economy achievement in the communities. Keywords : E-Scooter Sharing, Green Economy, Linear Regression, Purchase Intention]]>
