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Ben Mahmoud, B, Lehoux, N and Blanchet, P (2024) Integration mechanisms for material suppliers in the construction supply chain: a systematic literature review. Construction Management and Economics, 42(01), 70–107.

Choudhary, R and Tian, W (2014) Influence of district features on energy consumption in non-domestic buildings. Building Research & Information, 42(01), 32-46.

Denny-Smith, G, Williams, M, Loosemore, M, Sunindijo, R Y and Piggott, L (2024) What social value do Indigenous contractors create?. Construction Management and Economics, 42(01), 16–34.

Dykes, C and Baird, G (2014) Performance benchmarks for non-domestic buildings: towards user perception benchmarks. Building Research & Information, 42(01), 62-71.

Hong, S-M, Paterson, G, Mumovic, D and Steadman, P (2014) Improved benchmarking comparability for energy consumption in schools. Building Research & Information, 42(01), 47-61.

Isaacs, N and Hills, A (2014) Understanding the New Zealand non-domestic building stock. Building Research & Information, 42(01), 95-108.

Liddiard, R (2014) Room-scale profiles of space use and electricity consumption in non-domestic buildings. Building Research & Information, 42(01), 72-94.

Nguyen Chau, T, Pham, T T T, Ha, T C V and Nguyen, D (2024) Corruption, market structure, and industry competition in the Vietnamese construction sector. Construction Management and Economics, 42(01), 54–69.

Rueda-Benavides, J, Gransberg, D, Khalafalla, M and Mayorga, C (2024) Probabilistic cost-based decision-making matrix: IDIQ vs. DBB contracting. Construction Management and Economics, 42(01), 1–15.

Steadman, P, Hamilton, I and Evans, S (2014) Energy and urban built form: an empirical and statistical approach. Building Research & Information, 42(01), 17-31.

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0961-3218
  • URL: https://doi.org/10.1080/09613218.2013.808140
  • Abstract:
    The geometrical forms of buildings have important effects on their use of energy. These relationships are explored at the scale of the entire non-domestic building stock of London. A three-dimensional digital model of the city is used to make a series of geometrical measures: building volume, exposed surface area (walls plus roof) and plan depth. These are compared with figures for the consumption of gas and electricity published by the UK Department of Energy and Climate Change (DECC). The comparisons are made at different levels of spatial aggregation, from boroughs to census districts. Strong correlations are demonstrated between exposed surface area and both gas and electricity use. The analysis also provides some evidence of a sharp increase in electricity use in districts with buildings whose depth in plan exceeds 14 m (in which air-conditioning and permanent artificial lighting are typically required). A multiple regression model is used to measure the contribution of these effects to total energy use, as compared with floor area, activities and number of employees.

Taylor, S, Fan, D and Rylatt, M (2014) Enabling urban-scale energy modelling: a new spatial approach. Building Research & Information, 42(01), 4-16.

Zhang, S, Leiringer, R and Winch, G (2024) Procuring infrastructure public-private partnerships: capability development and learning from an owner perspective. Construction Management and Economics, 42(01), 35–53.