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Avila, J, Rapp, R, Dunbar, S and Jackson, A T (2021) Burnout and Worklife in Disaster Restoration: Maslach Burnout Inventory and Areas of Worklife Survey. Journal of Construction Engineering and Management, 147(02).
Chen, S, Tian, Y, Jin, L and Xiang, L (2021) Estimating the Frequency of Exposure to Uncertain Hazards: Impact of Wind Conditions on Concrete Dam Construction. Journal of Construction Engineering and Management, 147(02).
Choi, C, Ryu, K R and Shahandashti, M (2021) Predicting City-Level Construction Cost Index Using Linear Forecasting Models. Journal of Construction Engineering and Management, 147(02).
- Type: Journal Article
- Keywords: Engineering news-record (ENR) construction cost index (CCI); Cost prediction; Linear forecast models; US cities;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001973
- Abstract:
Because of the importance of budget planning and contract bidding, accurate prediction of future movements of the construction cost index (CCI) has been a crucial part of construction cost management. Despite the fact that construction costs can vary widely across locations with different market conditions and environments, the national CCI, the simple average of construction costs for 20 US metropolitan areas, has often been used to forecast CCIs across the nation. This study finds considerable differences across US cities in both the level and growth rates of CCIs and shows that using the national CCI for predicting city-level CCIs can cause nonnegligible forecast errors. Comparing four popular linear forecasting models, including standard autoregressive integrated moving average (ARIMA) models and a multivariate vector error correction model (VECM) drawn on monthly CCI data from January 1995 to December 2019, this study reveals that no single model is dominant in terms of the out-of-sample performance. If any leading indicator is available at the city level, however, it is recommended to choose between the ARIMA model based on the Bayesian information criterion (BIC) rule and the multivariate VECM augmented with the leading indicators. For the leading indicator in multivariate VECM, city consumer price index (CPI) works better than national CPI. In the absence of such leading indicators, it is recommended to use a parsimonious ARIMA model based on the BIC rule. The proposed approach is expected to help decision makers in the construction industry prepare more accurate budgets and biddings for regional construction projects.
Correia, J M F, de Oliveira Neto, G C, Leite, R R and da Silva, D (2021) Plan to Overcome Barriers to Reverse Logistics in Construction and Demolition Waste: Survey of the Construction Industry. Journal of Construction Engineering and Management, 147(02).
Gao, X, Pishdad-Bozorgi, P, Shelden, D R and Tang, S (2021) Internet of Things Enabled Data Acquisition Framework for Smart Building Applications. Journal of Construction Engineering and Management, 147(02).
Gunduz, M and Elsherbeny, H A (2021) Critical Assessment of Contract Administration Using Multidimensional Fuzzy Logic Approach. Journal of Construction Engineering and Management, 147(02).
He, Q, Wang, T, Chan, A P C and Xu, J (2021) Developing a List of Key Performance Indictors for Benchmarking the Success of Construction Megaprojects. Journal of Construction Engineering and Management, 147(02).
He, X, Liu, R and Anumba, C J (2021) Data-Driven Insights on the Knowledge Gaps of Conceptual Cost Estimation Modeling. Journal of Construction Engineering and Management, 147(02).
Kaminsky, J (2021) Who Are We Talking To? Situating Construction Engineering and Management Knowledge. Journal of Construction Engineering and Management, 147(02).
Kong, F and Dou, D (2021) Resource-Constrained Project Scheduling Problem under Multiple Time Constraints. Journal of Construction Engineering and Management, 147(02).
Labib, Y N, Lotfallah, W B, Hanna, A S and Boulos, N W (2021) Development and Application of Performance Index for Comparative Assessment of Public Capital Projects. Journal of Construction Engineering and Management, 147(02).
Li, G, Chen, C, Martek, I, Ao, Y and Dai, J (2021) Bid or No-Bid Decision Model for International Construction Projects: Evidential Reasoning Approach. Journal of Construction Engineering and Management, 147(02).
O’Connor, J T and Koo, H J (2021) Proactive Design Quality Assessment Tool for Building Projects. Journal of Construction Engineering and Management, 147(02).
Panwar, A and Jha, K N (2021) Integrating Quality and Safety in Construction Scheduling Time-Cost Trade-Off Model. Journal of Construction Engineering and Management, 147(02).
Ryu, J, Diraneyya, M M, Haas, C T and Abdel-Rahman, E (2021) Analysis of the Limits of Automated Rule-Based Ergonomic Assessment in Bricklaying. Journal of Construction Engineering and Management, 147(02).
Srijaroen, C, Hoy, M, Horpibulsuk, S, Rachan, R and Arulrajah, A (2021) Soil–Cement Screw Pile: Alternative Pile for Low- and Medium-Rise Buildings in Soft Bangkok Clay. Journal of Construction Engineering and Management, 147(02).
Wang, B, Cui, Q and Zhang, S (2021) Noncompete Provision Design for Transportation PPP Projects. Journal of Construction Engineering and Management, 147(02).
Zhang, L, Fu, Y and Lu, W (2021) Contract Enforcement for Claimants’ Satisfaction with Construction Dispute Resolution: Moderating Role of Shadow of the Future, Fairness Perception, and Trust. Journal of Construction Engineering and Management, 147(02).
Zhu, F, Hu, H, Xu, F and Tang, N (2021) Predicting the Impact of Country-Related Risks on Cost Overrun for Overseas Infrastructure Projects. Journal of Construction Engineering and Management, 147(02).