Nexus between running costs and building characteristics of commercial buildings: hedonic regression modelling

Abstract

Purpose

Traditionally, early-stage investment decisions on buildings purely based initial capital costs and simply ignored running costs and total lifecycle cost. This was basically due to the absence of estimating models that yield running costs at the early design stage. Often, when the design of a building, which is responsible for 10–15% of its total cost, is completed, 80% of the total cost is committed. This study aims to develop a building characteristic-based model, which is an early-stage determinant of running costs of buildings, to predict the running costs of commercial buildings.

Design/methodology/approach

A desk study was carried out to collect running costs data and building characteristics of 35 commercial buildings in Sri Lanka. A Pareto analysis, bivariate correlation analysis and hedonic regression modelling were performed on collected data.

Findings

According to Pareto analysis, utilities, services, admin work and cleaning are four main cost constituents, responsible for 80% of running costs, which can be represented by highly correlated building characteristics of building height, number of floors and size. Approximately 94% of the variance in annual running costs/sq. m is expressed by variables of number of floors, net floor area and working hours/day together with a mean prediction accuracy of 2.89%.

Research limitations/implications

The study has utilised a sample of 35 commercial buildings due to non-availability and difficulty in accessing running cost data.

Originality/value

Early-stage supportive running costs estimation model proposed by the study would enable construction professionals to benchmark the running costs and thereby optimise the building design. The developed hedonic model illustrated the variance of running costs concerning the changes in characteristics of a building.

Citation

Geekiyanage, D. and Ramachandra, T. (2020), "Nexus between running costs and building characteristics of commercial buildings: hedonic regression modelling", Built Environment Project and Asset Management, Vol. 10 No. 3, pp. 389-406. https://doi.org/10.1108/BEPAM-12-2018-0156