The Acceptance Technology of E-Vehicles in Medan City

The purpose of this study is to investigate the acceptance of electric vehicle (EV) technology in Medan City, focusing on aspects that drive public adoption. The Unified Theory of Acceptance and Use of Technology (UTAUT) and Lazy User (LUM) models are used to understand these dynamics. A survey was conducted with 411 respondents from several sub-districts in Medan City. The questionnaire included demographic information, driving habits, electric car expectations, purchase intentions, and Likert scale items related to the UTAUT constructs. Data analysis was performed using Structural Equation Modeling (SEM) with the PLS method. Effort Expectancy and Facilitating Conditions significantly influenced Behavioral Intention and Use Behavior, while Performance Expectancy and Social Influence showed inconsistent effects. LUM was supported, indicating that Effort Expectancy influenced the preference for the behavior with the least effort.

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Publication Details

Journal
EKONOMIS Journal of Economics and Business
Published
2025-03-20
DOI
https://doi.org/10.33087/ekonomis.v9i1.1989
Primary Topic
Blockchain Technology in Education and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

The Acceptance Technology of E-Vehicles in Medan City

Teuku Muhammad Syauqi, Cut Aprilia
EKONOMIS Journal of Economics and Business
Blockchain Technology in Education and Learning
article

The Acceptance Technology of E-Vehicles in Medan City

Teuku Muhammad Syauqi, Cut Aprilia
article en

Abstract

The purpose of this study is to investigate the acceptance of electric vehicle (EV) technology in Medan City, focusing on aspects that drive public adoption. The Unified Theory of Acceptance and Use of Technology (UTAUT) and Lazy User (LUM) models are used to understand these dynamics. A survey was conducted with 411 respondents from several sub-districts in Medan City. The questionnaire included demographic information, driving habits, electric car expectations, purchase intentions, and Likert scale items related to the UTAUT constructs. Data analysis was performed using Structural Equation Modeling (SEM) with the PLS method. Effort Expectancy and Facilitating Conditions significantly influenced Behavioral Intention and Use Behavior, while Performance Expectancy and Social Influence showed inconsistent effects. LUM was supported, indicating that Effort Expectancy influenced the preference for the behavior with the least effort.

EKONOMIS Journal of Economics and BusinessVol. 9(1)
Openalex Percentile: Top 91%
Blockchain Technology in Education and Learning
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