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An Analysis for Influencing Factors in Purchasing Electric Vehicle using a Binomial Logistic Regression Model (Focused on Suwon City)

이항로지스틱 회귀모형을 이용한 전기차 구매 영향요인 분석 (수원시를 중심으로)

  • Received : 2018.08.06
  • Accepted : 2018.10.08
  • Published : 2018.12.01

Abstract

An electric vehicle is emerging as an alternative to the response of global climate change and sustainability. However, an Electric vehicle has not been popular due to the constraints such as its price or technical limitations. In order to analyze the effect of purchasing electric vehicles, this study conducted a binary logistic regression model that demonstrates the relation between purchasing and influencing variables. Variables which have high correlation were excluded from the model through the correlation analysis to prevent multicollinearity. Socio-economic variables such as the number of owned vehicles, sex, ages are not significant. On the other hand, Variables related to prices, charging and policy are found to have a significant to effect on the purchase of electric vehicles. In accordance with the model estimated result, it seems to be necessary to improve the charging incentives, or to provide electric car information and to expand opportunities for experience electric vehicles. The result is also expected to be helpful for spreading electric vehicles and formulating policies.

전 세계적으로 자동차 시장은 전기차, 수소차와 같은 친환경 차량의 도입이 추진되고 있다. 그러나 내연기관 차량 대비 고가의 차량가격, 제한적인 주행거리 등의 단점은 친환경 차량 확대에 장애요인이 되고 있다. 이에 본 연구에서는 친환경 차량인 전기차 구매에 미치는 영향요인을 분석하기 위해 이항 로지스틱 회귀 모형을 구축하였다. 모형의 종속변수는 구매의사 여부, 독립변수는 사회 경제적 변수와 전기차 구매에 영향을 미치는 특성변수로 설정하였으며, 다중공선성 문제를 해결하기 위해 독립변수 간 상관관계를 분석하여 상관계수가 높은 변수들을 제외하였다. 분석결과, 사회경제적변수인 차량보유대수, 성별, 나이는 유의한 영향을 미치지 않는 것으로 나타났다. 반면, 차량가격에 영향을 미치는 변수와 전기차 충전과 관련된 변수, 전기차 정책 및 시승정보 제공 부족 변수는 전기차 구매에 유의한 영향을 미치는 것으로 나타났다. 이를 통해 향후 전기차 보급과 관련된 정책 입안 시 전기차의 가격 결정과 찾아가는 전기차 충전 서비스 운영 등 충전 불편 해소 방안, 전기차에 대한 정보 제공 및 시승기회 확대 등의 정책을 추진하는 것이 바람직할 것으로 보인다. 본 연구 결과는 지자체 전기차 보급 활성화 및 정책 수립에 도움이 될 것으로 기대된다.

Keywords

Table 1. Review to the Variable for Applying to Model

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Table 2. Attributes of the Respondents

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Table 3. Level of Recognition and Experience for Electric Vehicle

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Table 4. Major Concerns to the Electric Vehicles

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Table 5. Result of Correlation with Electric Vehicle Purchase

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Table 6. List of the Dependent and Independent Variable

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Table 7. Model Verification

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Table 8. Model Estimation Result

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