Korean Journal of Construction Engineering and Management (한국건설관리학회논문집)

Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Forecasting of Car Distribution Considering the Population Aging

인구 고령화를 고려한 승용차 보급예측 연구

  • Kim, Hyunwoo (Korea Institute for Industrial Economics & Trade) ;
  • Lee, Du-Heon (Korea Institute for Industrial Economics & Trade) ;
  • Yang, Junseok (School of Economics, Sungkyunkwan University)
  • Received : 2014.04.11
  • Accepted : 2014.07.08
  • Published : 2014.09.30
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Abstract

It has been a long time since cars had become important means of transportation in human life. Since 1970s, cars have been increasing steadily because of rising individual income and changing lifestyle toward leisure and convenience. The number of cars is just 1.8 per thousand populations in 1970s, however, in 2012, it has increased to 291.15. Forecasting the demand for cars would be useful to plan, construction or management in the field of motor industry, road building and establishing facilities. Our study predicts the demand of cars through estimating the growth curve model. Especially, we include ageing variables to forecasting identifying the effect of ageing on the demand of cars. The main findings are as follows. In 2045, the number of cars is expected to reach 486.8 per thousand populations with passing a primary saturation point at early 2020s. Also, due to effect of ageing, the predicted demand of cars is about 10% lower than in case of which if ageing effect not exist.

현대사회에서 자동차는 통근 통학뿐만 아니라 여가 및 편의생활을 위한 매우 중요한 이동수단으로 자리매김한지 오래다. 특히 대표적인 개인 이동수단인 승용차는 개인소득 증대와 개인의 여가시간과 편의 중시하는 라이프 스타일 변화로 인해 1970년대 이후 꾸준히 증가하였다. 1970년 우리나라 인구 천명당 1.9대에 불과했던 승용차는 2012년 기준 291.5대로 42년만에 153배가 증가한 매우 가파른 증가속도로 보유대수를 늘려왔다. 이러한 승용차 보유대수의 예측은 향후 자동차 관련 산업이나 도로건설 및 시설물 설치 등을 위한 계획, 시공, 관리 등에서도 중요한 기초자료가 될 수 있다. 따라서 본 연구에서는 성장곡선모형을 이용한 승용차 보유대수 예측을 실시하였으며, 특히 인구 고령화 변수를 포함시켜 보유율에 어떤 영향을 미치는지 분석하였다. 분석결과, 2020년대 초에 1차 포화점을 지나 2045년에는 인구 천명당 486.8대를 보유할 것이며, 또한 인구 고령화의 영향으로 고령화 문제가 없을 때에 비해 2045년의 보유대수는 10%가까이 낮은 수치를 가질 것으로 예측되었다.

Keywords

References

  1. Bass, F. M. (1969). "A New Product Growth for Model Consumer Durables", Management Science, 15(5), pp. 215-227. https://doi.org/10.1287/mnsc.15.5.215
  2. Button, K., Ngoe, N., and Hine, J. (1992). "Modelling Vehicle Ownership and use in Low Income Countries", Journal of Transport Economics and Policy, 27(1), pp. 51-67.
  3. Byun, W., Lee, K., Lee, S., and Kee, H. (2012). "Demand Forecasts Analysis of Electric Vehicles for Apartment in 2020", KITS Review, 11(3), pp. 81-91. https://doi.org/10.12815/kits.2012.11.3.081
  4. Ji, W., and Oh, E. (2003). A Study on the Driving Characteristics of Senior Drivers, Research Report 2003-11, Gyeonggi Research Institute(GRI), pp. 67-158.
  5. Kang, H., and Chil, J. (2001). "A Study on the Demand Forecasting using Diffusion Models and Growth Curve Models", The Korean Journal of Applied Statistics, 14(2), pp. 233-243.
  6. Kang, S. (2005). "Analysis of older driver characteristics", General insurance magazine, 530(Jan 2013), General Insurance Association of Korea, pp. 38-53.
  7. Kim, H., Chin, K. and Lee, K. (2012). "A Study on Relationship between House Rental Price and Macroeconomic Variables", Korean journal of Construction Engineering and Management, KICEM, 13(2), pp. 128-136. https://doi.org/10.6106/KJCEM.2012.13.2.128
  8. Kim, J., Lee, S., and Preston, J. (2006). "The Demand Forecast for Diesel Passenger Cars and the Change of Air Quality in Seoul" Journal of the KRSA, 22(3), pp. 29-56.
  9. Korea Automobile Manufacturers Association(KAMA) (2003). Long-term demand forecasting model for automobile in South Korea(IV), KAMA Research Report, pp. 1-27.
  10. Kwak, S., Kim, K., Ahn, S., Jang, W., and Hong, J. (2002). "Development of a System Dynamics Model for Forecasting the Automobile Market", Korean System Dynamics Review, 3(1), pp. 79-104.
  11. Lee, D. (1998). "Eine mikrooekonometrische Untersuchung ueber das veraenderte Nachfrageverhalten fuer Koreanische Personenkraftwagen", The Sogang Journal of Commerce, 17(1), pp. 145-163.
  12. Mahajan, V., Muller, E., and Bass, F. M. (1990). "New Product Diffusion Models in Marketing: A Review and Directions for Research", Journal of Marketing, 54(1), pp. 1-126.
  13. Ministry of Land, Infrastructure and Transport(MOLIT) (2011). Traffic Safety Measure Establishment on Cause for Elderly People Traffic Accident, MOLIT Research Report, pp. 9-104.
  14. National Assembly Budget Office(NABO) (2012). 2012-2060 Long-term financial prospects and analysis, NABO Research Report, pp. 57-75.
  15. Ogut, K. S. (2004). "S-Curve Models to Determine the Car Ownership in Turkey", ARI(The Bulletin of the Istanbul Technical University), 54(2), pp. 65-69.
  16. Park, S. (2012). Effective demand forecasting methods and practices, SERI ISSUE Paper 2012-3, Samsung Economics Research Institute(SERI), pp. 2-53.
  17. Romilly, P., Song, H., and Liu, X. (1997). Modelling and Forecasting Car Ownership in Britain, Journal of Transport Economics and Policy, 32(2), pp. 165-185.
  18. Tanner, J. C. (1962). "Forecasts of Future Numbers of Vehicles in Greate Britain", Road and Road Construction, 40, pp. 263-274.
  19. Tanner, J. C. (1978). "Long-term forecasting of vehicle ownership and road traffic", The Journal of the Royal Statistical Society, 141(1), pp. 14-63. https://doi.org/10.2307/2344775
  20. Yang, S., and Park, K. (2005). "The Correlation Factors on the Analysis of Demand Factors for Apartments.", Korean journal of Construction Engineering and Management, KICEM, 6(1), pp. 80-88.