KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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Demand Analysis of Electric Vehicle by Household Type

전기자동차의 가구유형별 수요에 대한 고찰

  • Received : 2018.09.10
  • Accepted : 2018.11.05
  • Published : 2018.12.01
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Abstract

The conversion of the internal combustion engine vehicle to the electric vehicle is suggested as a solution to the problem of global climate change and environmental pollution. Accordingly, this study was started to promote the use of electric vehicles. The purpose of this study is to identify the basic background knowledge and current status of electric vehicles in Korea and abroad, and expand from previous understanding on which factors affect ones choice on electric vehicles by considering individual characteristics and context in detail. In the analysis, a set of demand forecasting models were constructed by grouping the respondents based on the household characteristics as well as the vehicle ownership. At the time in need for better understanding of the feasibility of electric vehicles, it is expected that the research can assist the promotion of electric vehicles. In the follow-up study, I would like to continue the research on the activation of electric vehicles.

본 연구에서는 전기자동차 수요에 대해 가구의 유형 및 차량 보유별로 그룹을 분류하고 개인의 특성과 가구차량보유구조 및 구매의향이 있는 경우 등에 따른 차량 구매 선택요인을 찾고자 한다. 이를 위하여 시행한 설문조사 결과를 토대로 수요예측모형을 구축하고 탄력성을 분석 하였다. 주요 결과는 다음과 같다. 첫째, 개인특성인 연령은 증가할수록 전기자동차 구매의향이 높아졌으나 성별은 구매에 있어서 유의미함을 찾아보기 어려웠다. 주택유형 또한 아파트의 경우만 유의미한 결과가 나타났다. 둘째, 차량이 있는 가구의 경우 전기자동차 구입의 중요 요인으로는 연료비와 충전시간, 주행가능거리 등과 같은 실제 사용에 있어 편의성과 관련된 요인이 탄력성이 높은 것으로 나타났다. 셋째, 차량이 없는 가구의 경우에는 차량구매가격이 탄력성이 높은 것으로 분석되었다. 본 연구에서 도출된 연구결과는 향후 전기자동차 수요예측과 보급활성화를 위한 기초적인 자료로 활용될 수 있을 것이라 판단된다.

Keywords

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Fig. 1. Classification of Intent to Buy Vehicle According to the Ownership of Vehicle

Table 1. Respondent Household Type and Average Household Income Attributes

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Table 2. Vehicle Ownership Ratio by Houeshold Type

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Table 3. Variables

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Table 4. Variable Setting Level

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Table 5. [Model 1] Electric Vehicle Demand Forecasting Model for All Respondents (500 sample)

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Table 6. [Model 2] Electric Vehicle Demand Forecasting Model of Households Vehicles (423 sample)

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Table 7. [Model 3] For the Household with Intention to Purchase a Vehicle Purchasing Intended Household (303 sample)

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Table 8. [Model 4] Vehicle Purchasing Intended Household Among Households with Vehicle Ownership (265 sample)

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Table 9. Ioniq-EV Cross Elasticity Due to Price Change

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Table 10. Ioniq-EV (Per 100km) Cross Elasticity Due to Fuel Cost Change

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References

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