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Modelling Influencing Factor Relationship for the Prediction of Construction Cost Indices
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 Title & Authors
Modelling Influencing Factor Relationship for the Prediction of Construction Cost Indices
Yi, Kyoo-Jin;
 
 Abstract
Construction projects typically require extensive periods for the completion and there are usually considerable time gap between cost estimation and project completion. It is essential to accurately predict construction costs in order to effectively estimate costs for construction projects. In the construction industry, construction cost indices (CCI) are useful in explaining the trend of construction cost variation. CCI are recorded and announced periodically and are influence by many other related factors such as price indices and business indices. Understanding the influencing relationship will help predicting future values of CCI and incorporating such understanding and prediction into estimating will help practitioners manage construction costs. This paper adopted system dynamics modeling methods and proposes CCI prediction model by incorporating influencing factors as model variables. Comparing the simulated results by the proposed model and the real values of CCIs verifies that the proposed model provides the future CCI values with sufficient statistical significance.
 Keywords
Costruction Cost Index (CCI);System Dynamics;Modelling;
 Language
Korean
 Cited by
 References
1.
고성석, 실적공사비 분석을 통한 유통시설물의 적정공사비 추정에 관한 연구, 한국건설관리학회 논문집, 9(3), 2008, 108-117

2.
김기찬 외, Vensim을 활용한 System Dynamics, 서울경제경영, 2007

3.
박종원, 공사비 지수 적용을 통한 군 시설공사의 예산산정 모델, 대한건축학회논문집 구조계 21(2), 2005, 111-121

4.
유용환, 공동주택 실적공사비 산정시 공종별 변동요인에 관한 연구, 한국건축시공학회 논문집 4(4), 2004, 117-126 crossref(new window)

5.
임대희, 공공아파트 실적데이터 기반의 지역지수 산정모델 개발, 한국건축시공학회 논문집, 10(2), 2010, 75-80

6.
전석한, 실적공사비 산정시스템에 관한 연구, 한국건축시공학회 논문집, 5(1), 2005, 111-121 crossref(new window)

7.
Ashuri, B., Time series analysis of ENR construction cost index, Journal of. Construction. Engineering and Management, 136(11), 2010, 1227-1237 crossref(new window)

8.
Diekmann, J. E., Probabilistic estimating: Mathematics and applications, Journal of Construction Engineering Management, 109(3), 1983, 297-308 crossref(new window)

9.
Koppula, S. D., Forecasting engineering costs: Two case studies, Journal of Construction. Division,., 107(4), 1981, 733-743

10.
Shahandashti, S. M., Forecasting Engineering News-Record Construction Cost Index Using Multivariate Time Series Models, Journal of Construction Engineering and Management, 139(9), 2013, 1237-1243 crossref(new window)

11.
Hwang, S., Dynamic Regression Models for Prediction of Construction Costs, Journal of Construction Engineering and Management, 135(5), 2009, 360-367 crossref(new window)

12.
Hwang, S., Time Series Models for Forecasting Construction Costs Using Time Series Indexes, Journal of Construction Engineering and Management, 137(9), 2011, 656-662 crossref(new window)

13.
Ventana Systems, Inc., Vensim User's guide version 5, 2007

14.
Williams, T. P., Predicting changes in construction cost indexes using neural networks, Journal of Construction Engineering and Management, 120(2), 1994, 306-320. crossref(new window)

15.
Wilmot, C. G., Estimating future highway construction costs, Journal of Construction Engineering and Management, 129(3), 2003, 272-279 crossref(new window)

16.
한국건설기술연구원 (2014.02.11)

17.
통계청 (2014.02.11)

18.
한국은행 (2014.02.11)