@article{Utami_Yuniaristanto_Sutopo_2020, place={Padang, ID}, title={Adoption Intention Model of Electric Vehicle in Indonesia}, volume={19}, url={https://josi.ft.unand.ac.id/index.php/josi/article/view/434}, DOI={10.25077/josi.v19.n1.p70-81.2020}, abstractNote={Indonesia’s government was targeting the adoption of 2.1 million units of two-wheeled electric vehicles and 2,200 units of four-wheeled electric vehicles in 2025 through the Republic of Indonesia’s Presidential Regulation No. 22 in 2017 about the National Energy General Plan. In 2019, the Government of Indonesia issued Presidential Regulation No. 55 in 2019 concerning the Acceleration of the Battery Electric Vehicle Program for Road Transportation. In 2018, the adoption of two-wheeled electric vehicles only reached 0.14% of the government’s target for 2025. Therefore, the adoption of Electric Motorcycle (EM) technology must also consider many factors to be successful. This research develops a non-behavioral electric vehicle adoption intention model. The factors include sociodemographic, financial, technological, and macro-level. The online survey involved 1,223 respondents. Logistic regression is used to obtain the function and probability value of intention to adopt EM in Indonesia. Frequency of sharing on social media, level of environmental awareness, purchase prices, maintenance costs, maximum speed, battery charging time, availability of charging station infrastructure at work, availability of home power based- charging infrastructure, purchase incentive policies, and charging cost discount incentive policies are significantly influencing the intention to adopt electric vehicles. It also shows that the opportunity for Indonesians to adopt electric motorcycles reaches 82.90%. The realization of the adoption of electric motorcycles in Indonesia requires infrastructure readiness and costs that can be accepted by consumers. Lastly, the results of this research provide some suggestions for the government and businesses to accelerate electric motorcycle adoption in Indonesia.}, number={1}, journal={Jurnal Optimasi Sistem Industri}, author={Utami, Martha Widhi Dela and Yuniaristanto, Yuniaristanto and Sutopo, Wahyudi}, year={2020}, month={Jun.}, pages={70–81} }