Investigating the Impact of Key Factors on Electric/Electric-Vehicle Charging Station Adoption in Indonesia

Fajar Nurrohman Haryadi, Arionmaro Asi Simaremare, Shochrul Rohmatul Ajija, Dzikri Firmansyah Hakam, Kevin Gausultan Hadith Mangunkusumo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The transportation sector is a major contributor to carbon dioxide emissions, and the adoption of electric vehicles (EVs) is seen as a solution to reduce this impact. However, the utilization of electric charging stations (ECS) and EV charging stations (EVCS) in Indonesia is not optimal, as evidenced by low usage levels. This study aimed to understand the characteristics of ECS and EVCS users in Indonesia in order to identify determinant factors for ECS and EVCS utilization. Using descriptive quantitative analysis, exploratory factor analysis, and binary logistic regression, the study found that potential EVCS users are adults from upper-middle-class backgrounds, with four family members, who own a motorcycle and live in suburban areas. Furthermore, a wide social network, knowledge of technology, and ease of access, convenience, and price were identified as key factors for choosing ECS/EVCS. However, an attitude of caring for the environment had a negative effect on ECS/EVCS usage, and respondents who charge their electronic devices at home overnight were less likely to use ECS/EVCS. The study also found that the number of sockets in a respondent’s home, previous family members’ experience, and duration of work experience and self-identity were also reasons for choosing to use ECS/EVCS. Overall, this study provides a deeper understanding of the factors that influence the utilization of ECS and EVCS in Indonesia.

Original languageEnglish
Pages (from-to)434-442
Number of pages9
JournalInternational Journal of Energy Economics and Policy
Volume13
Issue number3
DOIs
Publication statusPublished - 17 May 2023

Keywords

  • Binary Logit Regression
  • Consumer Behavior
  • Electric Charging Stations
  • Electric Vehicle Charging Stations
  • Exploratory Factor Analysis

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