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Comparative Analysis of the Cost Models Used for Estimating Renovation Costs of Universities in Texas

Facility managers use various cost models and techniques to estimate the cost of renovating a building and to secure the required funds needed for building renovation. A literature search indicates that these techniques offer both advantages and disadvantages that need to be studied and analyzed. Descriptive statistical methods and qualitative analysis are employed to identify and compare techniques used by facility managers to calculate the expected renovation costs of a building. The cost models presently used to predict the cost and accumulate the budget required for renovation of a building were determined through interviews with ten Texas-based university facilities managers. The data and information gathered were analyzed and compared.
Analysis of results suggests that traditional methods like Floor Area Method (FAM) is the most accurate, less time consuming, easy to use as well as convenient for data collection. Case-Based Reasoning (CBR), though not as widely used as FAM, is known to facilities managers. This is due to the fact that, if a new type of project needs to be renovated, and the data for a similar project is not available with the facilities manager, a completely new database needs to be created. This issue can be resolved by creating a common forum where data for all types of project could be made available for the facilities managers. Methods such as regression analysis and neural networks are known to give more accurate results. However, of the ten interviewees, only one was aware of these new models but did not use them as they would be helpful for very large projects and they would need expertise. Thus such models should be simplified to not only give accurate results in less time but also be easy to use. These results may allow us to discuss changes needed within the various cost models.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-08-8466
Date2010 August 1900
CreatorsFaquih, Yaquta Fakhruddin
ContributorsRybkowski, Zofia K., Nichols, John M.
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Thesis, text
Formatapplication/pdf

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