Underlying Indicators For Measuring Smartness Of Buildings In The Construction Industry

Ghansah, F.A. and Owusu-Manu, D. and Ayarkwa, J. and Darko, A. and Edwards, D.J. (2020) Underlying Indicators For Measuring Smartness Of Buildings In The Construction Industry. Smart and Sustainable Built Environment. ISSN 2046-6099

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Purpose: The introduction of the Smart Buildings Technology (SBT) concept (which incorporates elements of the Zero Energy Buildings (NZEB) concept) could be a measure in ensuring efficient energy consumption and high performance in buildings. Smart buildings provide solutions to improve building efficiency, and reduce energy consumption, carbon emissions and concomitant energy costs. In order to adopt SBT in the construction industry, it is important to identify the indicators of smartness of buildings, even though such may differ from region to region or even country to country. However, there have been inefficient studies identifying the indicators of smartness of buildings, especially in developing countries such as Ghana. This study investigates the underlying indicators for measuring the smartness of buildings in the construction industry.
Methodology: An overarching post-positivist and empirical epistemological design was adopted for this research to analyse primary quantitative data. Data was collected via a structured questionnaire survey with 227 respondents including project managers and construction design teams in Ghana. The mean ranking analysis and one sample t-test were employed to analyse the data.
Findings: Research findings revealed that the level of knowledge of smart building indicators is averagely high in the Ghanaian construction industry. With regards to the indicators of smart building, ‘sensors implementation to manage light level, air quality, temperature, fire alarm and smoke detector’ is regards as the most significant measure of smart buildings in the Ghanaian construction industry. Also, ‘remote implementation monitors building conditions and occupancy’, ‘implementation of any software that can talk to legacy equipment from many different manufactures’ and ‘data analytic’ are statistically insignificant in measuring smartness of buildings.
Practical Implication: Practically, policy makers and practitioners can use the study’s results as blueprint guidance to appreciate and utilise the idea of smartness of buildings because it can improve building performance therefore, promoting the adoption of SBTs. To the body of knowledge, this study has identified the significant indicators for measuring the smartness of buildings, which can further influence SBTs adoption.
Originality: Using the results, a model consisting of significant indicators for measuring building smartness was developed to help improve building performance.
Recommendation: The study recommends future research to evaluate the awareness level of Smart Building Technologies (SBTs) by construction professionals and identify barriers to its adoption.

Item Type: Article
Identification Number: https://doi.org/10.1108/SASBE-05-2020-0061
3 August 2020Accepted
27 August 2020Published Online
Uncontrolled Keywords: Building performance, construction industry, developing countries, energy efficiency, indicators, smart building technology
Subjects: CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-04 - planning (urban, rural and regional)
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Engineering and the Built Environment
Depositing User: David Edwards
Date Deposited: 04 Aug 2020 13:05
Last Modified: 12 Jan 2022 13:28
URI: https://www.open-access.bcu.ac.uk/id/eprint/9613

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