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Buys, F and Nkado, R (2006) A survey of maintenance management systems in South African tertiary educational institutions. Construction Management and Economics, 24(10), 997-1005.
Carmichael, S and Murray, M (2006) Record keeping for contemporaneous delay analysis: a model for effective event management. Construction Management and Economics, 24(10), 1007-18.
Carrillo, P M, Robinson, H S, Anumba, C J and Bouchlaghem, N M (2006) A Knowledge Transfer Framework: the PFI context. Construction Management and Economics, 24(10), 1045-56.
Eeing, B T and Kruse, J B (2006) Valuing self-protection: income and certification effects for safe rooms. Construction Management and Economics, 24(10), 1057-68.
Fortune, C (2006) Process standardisation and the impact of professional judgement on the formulation of building project budget price advice. Construction Management and Economics, 24(10), 1091-8.
Fu, W-K, Lo, H-P and Drew, D S (2006) Collective learning, collective knowledge and learning networks in construction. Construction Management and Economics, 24(10), 1019-28.
Huang, R-Y (2006) A performance-based bridge LCCA model using visual inspection inventory data. Construction Management and Economics, 24(10), 1069-81.
Ok, S C and Sinha, S K (2006) Construction equipment productivity estimation using artificial neural network model. Construction Management and Economics, 24(10), 1029-44.
Stoy, C and Kytzia, S (2006) Benchmarking electricity consumption. Construction Management and Economics, 24(10), 1083-9.
- Type: Journal Article
- Keywords: Benchmarking; energy; electricity consumption; office
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/01446190600799414
- Abstract:
The building stock is one of the largest energy consumers and simultaneously represents a relevant cost driver for most companies. Thus, buildings should be optimally planned, constructed and used from both an environmental and from an economic perspective. Benchmarking electricity consumption in the usage phase is a tool for achieving this objective. This requires a uniform collection of key usage indicators on the one hand, and on the other hand it is necessary to be cognisant of the factors that drive these key indicators and how they do so. This alone makes it possible to satisfy the benchmarking principle of comparing like or similar objects. Uniformly collected key indicators for electricity consumption (kWh/m2 usable floor area and year) are presented on the basis of 109 Swiss office buildings. This is broken down into further groupings on the basis of the relevant drivers. The analysis of the drivers relies on regression analysis. This demonstrates above all the great relevance of technical installation (e.g. the share of mechanically vented and ventilated as well as air-conditioned areas), given that the coverage area of such systems has a significant effect on the electricity consumption of office buildings. Accordingly, special attention should be paid to the planning, construction and use of technical installations, in order to be able to provide optimally energy-efficient buildings.