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Assessment of Methods for Adjusting Construction Cost Estimates by Geographical Location
Conceptual cost estimates are fundamental to the success of construction projects. These early estimates are commonly prepared through the aid of historical data and later adjusted to take into account specific project characteristics such as location. The common practice for adjusting estimates for location is to use sets of location cost factors. When a location is not represented in the chosen data set, the nearest location factor is usually selected. The validity of this interpolation method has not been substantiated. Geographical Information System (GIS) techniques are used to conduct spatial analysis of the RSMeans' City Cost Index (CCI) national reference data. Spatial auto-correlation of these CCI values is tested to determine the validity of the nearest neighbor interpolation method at both the national and state level. In addition, an alternative analysis between nearest neighbor and the state average CCI value methods has been performed. Findings reveal positive, nationwide correlation between proximity and CCI values. In addition, 19 individual states showed highly significant results of positive correlation between proximity and CCI value and no state showed significant negative correlation. The alternative analysis between nearest neighbor and state average was not conclusive. Half the time the nearest neighbor measure provided a better estimate, and half the time the state average proved a better measure.
Assessment of Methods for Adjusting Construction Cost Estimates by Geographical Location
Conceptual cost estimates are fundamental to the success of construction projects. These early estimates are commonly prepared through the aid of historical data and later adjusted to take into account specific project characteristics such as location. The common practice for adjusting estimates for location is to use sets of location cost factors. When a location is not represented in the chosen data set, the nearest location factor is usually selected. The validity of this interpolation method has not been substantiated. Geographical Information System (GIS) techniques are used to conduct spatial analysis of the RSMeans' City Cost Index (CCI) national reference data. Spatial auto-correlation of these CCI values is tested to determine the validity of the nearest neighbor interpolation method at both the national and state level. In addition, an alternative analysis between nearest neighbor and the state average CCI value methods has been performed. Findings reveal positive, nationwide correlation between proximity and CCI values. In addition, 19 individual states showed highly significant results of positive correlation between proximity and CCI value and no state showed significant negative correlation. The alternative analysis between nearest neighbor and state average was not conclusive. Half the time the nearest neighbor measure provided a better estimate, and half the time the state average proved a better measure.
Assessment of Methods for Adjusting Construction Cost Estimates by Geographical Location
Migliaccio, Giovanni C. (author) / Zandbergen, Paul (author) / Martinez, Adam A. (author)
Construction Research Congress 2009 ; 2009 ; Seattle, Washington, United States
Building a Sustainable Future ; 886-895
2009-04-01
Conference paper
Electronic Resource
English
Assessment of Methods for Adjusting Construction Cost Estimates by Geographical Location
| British Library Conference Proceedings | 2009
| British Library Online Contents | 2014