Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa
The construction industry has been producing massive data that can be transformed for improved decision-making and better construction project delivery. However, the industry has been adjudged as a slow adopter of digital technologies such as big data analytics (BDA) to improve its service delivery...
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doaj-973dd94de9b84d2b83e8303e7723ca812021-09-10T04:58:50ZengUTS ePRESSConstruction Economics and Building2204-90292021-08-0121310.5130/AJCEB.v21i3.7634Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa Douglas Omoregie Aghimien0Matthew Ikuabe1Clinton Aigbavboa2Ayodeji Oke3Wealthy Shirinda4cidb Centre of Excellence, University of Johannesburg, Johannesburg, South AfricaSARChl in Sustainable Construction Management and Leadership in the Built Environment, University of Johannesburg, Johannesburg, South Africacidb Centre of Excellence, University of Johannesburg, Johannesburg, South AfricaSARChl in Sustainable Construction Management and Leadership in the Built Environment, University of Johannesburg, Johannesburg, South AfricaSARChl in Sustainable Construction Management and Leadership in the Built Environment, University of Johannesburg, Johannesburg, South Africa The construction industry has been producing massive data that can be transformed for improved decision-making and better construction project delivery. However, the industry has been adjudged as a slow adopter of digital technologies such as big data analytics (BDA) to improve its service delivery. The implication of this slow adoption is the lack of innovativeness and unsustainable project delivery that has characterised the industry in most countries, particularly in developing ones like South Africa. Therefore, this study assessed the intention to adopt BDA by construction organisations using the unified theory of technology adoption and use of technology (UTAUT) model. A post-positivism philosophical stance was employed, which informed the use of quantitative research with a questionnaire designed to solicit information from construction organisations in South Africa. Data analysis was done using Cronbach alpha to test for reliability and Fuzzy Synthetic Evaluation to evaluate the impact of the different constructs of the UTAUT on the adoption of BDA by construction organisations in South Africa. The study found that variables relating to facilitating conditions, performance expectancy, and social influence will significantly impact an organisation’s intention to adopt BDA. However, issues surrounding effort expectancy, resistance to use, and perceived risk cannot be overlooked as they also have high impact levels. The study provides an excellent theoretical and practical contribution to the existing discourse on construction digitalisation. https://epress.lib.uts.edu.au/journals/index.php/AJCEB/article/view/7634Big Data AnalyticsConstruction organisationDigitalisationDigital technology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Douglas Omoregie Aghimien Matthew Ikuabe Clinton Aigbavboa Ayodeji Oke Wealthy Shirinda |
spellingShingle |
Douglas Omoregie Aghimien Matthew Ikuabe Clinton Aigbavboa Ayodeji Oke Wealthy Shirinda Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa Construction Economics and Building Big Data Analytics Construction organisation Digitalisation Digital technology |
author_facet |
Douglas Omoregie Aghimien Matthew Ikuabe Clinton Aigbavboa Ayodeji Oke Wealthy Shirinda |
author_sort |
Douglas Omoregie Aghimien |
title |
Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa |
title_short |
Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa |
title_full |
Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa |
title_fullStr |
Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa |
title_full_unstemmed |
Unravelling the Factors Influencing Construction Organisations’ Intention to Adopt Big Data Analytics in South Africa |
title_sort |
unravelling the factors influencing construction organisations’ intention to adopt big data analytics in south africa |
publisher |
UTS ePRESS |
series |
Construction Economics and Building |
issn |
2204-9029 |
publishDate |
2021-08-01 |
description |
The construction industry has been producing massive data that can be transformed for improved decision-making and better construction project delivery. However, the industry has been adjudged as a slow adopter of digital technologies such as big data analytics (BDA) to improve its service delivery. The implication of this slow adoption is the lack of innovativeness and unsustainable project delivery that has characterised the industry in most countries, particularly in developing ones like South Africa. Therefore, this study assessed the intention to adopt BDA by construction organisations using the unified theory of technology adoption and use of technology (UTAUT) model. A post-positivism philosophical stance was employed, which informed the use of quantitative research with a questionnaire designed to solicit information from construction organisations in South Africa. Data analysis was done using Cronbach alpha to test for reliability and Fuzzy Synthetic Evaluation to evaluate the impact of the different constructs of the UTAUT on the adoption of BDA by construction organisations in South Africa. The study found that variables relating to facilitating conditions, performance expectancy, and social influence will significantly impact an organisation’s intention to adopt BDA. However, issues surrounding effort expectancy, resistance to use, and perceived risk cannot be overlooked as they also have high impact levels. The study provides an excellent theoretical and practical contribution to the existing discourse on construction digitalisation.
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topic |
Big Data Analytics Construction organisation Digitalisation Digital technology |
url |
https://epress.lib.uts.edu.au/journals/index.php/AJCEB/article/view/7634 |
work_keys_str_mv |
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