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Abstract
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
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