Modelling the utility and occupancy costs of local authority office buildings.

A review of the published literature revealed that although obsolescence in buildings has been the subject of academic interest for a number of decades, existing research into the subject is limited. There have been a number of empirical studies into property depreciation, which have resulted in statistical models for explaining variation between the value of buildings based on differences in their physical and locational characteristics. However, these models are intended for use by property owners and investors. This study therefore developed comparable models for occupiers, using data from a sample of 64 office buildings spread across five English local authorities. The primary contribution of this study is in the theoretical framework and research methods that were used to develop the models.Data were collected in respect of the physical characteristics of the sample buildings, the characteristics of the buildings' occupants and the characteristics of the occupier organisations. These characteristics were employed as explanatory variables in the analysis. Data were also collected in relation to the utility (functional performance) and operation costs (financial performance) of the buildings. These performance measures were employed as outcome variables in the analysis. One of the key contributions of this study was the development of a valid and reliable scale for evaluating utility. Derived from exhaustive focus group research with building occupants, the scale indicated that utility could be measured along 22 attributes and four distinct factors: configuration, environment, appearance and functionality.The results of the statistical analysis lend support to the premise that the physical characteristics of a building and the characteristics of its occupants can be used to explain its utility relative to a group of similar buildings. The statistically significant relationships provided an insight into which combinations of building and occupant characteristics were associated with higher or lower scores on particular factors and attributes. By and large, the relative contribution of the two groups of explanatory variables varied across the four factors, a finding that might have implications for the management and refurbishment of buildings. Nevertheless, the inclusion of other additional explanatory variables, such as cultural indicators, might improve the level of explanation provided by the regression models.The level of explanation provided by the operation cost models was found to be higher than for the utility models. Measures of cost efficiency were found to be correlated with building characteristics and occupancy characteristics. The results of the analysis were therefore an improvement over those from previous research, which had concluded that there was littlecorrelation between costs and building characteristics. This improvement might be attributed to the wider range of building characteristics analysed in this study. Moreover, by modelling utility and operation costs in tandem, it was possible to identify areas of divergence between functional and financial performance. Such information could be of use during the design and refurbishment of buildings. For instance, design characteristics or utilisation strategies that are associated with higher costs but lower utility could be changed or omitted.