Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Determinants of cloud computing deployment in South African construction organisations using structural equation modelling and machine learning technique
https://orcid.org/0000-0002-6661-5679
https://orcid.org/0000-0001-8297-3006
https://orcid.org/0000-0001-5835-0554
This paper presents the findings from the assessment of the determinants of cloud computing (CC) deployment by construction organisations. Using the technology-organisation-environment (TOE) framework, the study strives to improve construction organisations' project delivery and digital transformation by adopting beneficial technologies like CC.
This study adopted a post-positivism philosophical stance using a deductive approach with a questionnaire administered to construction organisations in South Africa. The data gathered were analysed using descriptive and inferential statistics. Also, the fusion of structural equation modelling (SEM) and machine learning (ML) regression models helped to gain a robust understanding of the key determinants of using CC.
The study found that the use of CC by construction organisations in South Africa is still slow. SEM indicated that this slow usage is influenced by six technology and environmental factors, namely (1) cost-effectiveness, (2) availability, (3) compatibility, (4) client demand, (5) competitors' pressure and (6) trust in cloud service providers. ML models developed affirmed that these variables have high predictive power. However, sensitivity analysis revealed that the availability of CC and CC's ancillary technologies and the pressure from competitors are the most important predictors of CC usage in construction organisations.
The paper offers a theoretical backdrop for future works on CC in construction, particularly in developing countries where such a study has not been explored.
Determinants of cloud computing deployment in South African construction organisations using structural equation modelling and machine learning technique
https://orcid.org/0000-0002-6661-5679
https://orcid.org/0000-0001-8297-3006
https://orcid.org/0000-0001-5835-0554
This paper presents the findings from the assessment of the determinants of cloud computing (CC) deployment by construction organisations. Using the technology-organisation-environment (TOE) framework, the study strives to improve construction organisations' project delivery and digital transformation by adopting beneficial technologies like CC.
This study adopted a post-positivism philosophical stance using a deductive approach with a questionnaire administered to construction organisations in South Africa. The data gathered were analysed using descriptive and inferential statistics. Also, the fusion of structural equation modelling (SEM) and machine learning (ML) regression models helped to gain a robust understanding of the key determinants of using CC.
The study found that the use of CC by construction organisations in South Africa is still slow. SEM indicated that this slow usage is influenced by six technology and environmental factors, namely (1) cost-effectiveness, (2) availability, (3) compatibility, (4) client demand, (5) competitors' pressure and (6) trust in cloud service providers. ML models developed affirmed that these variables have high predictive power. However, sensitivity analysis revealed that the availability of CC and CC's ancillary technologies and the pressure from competitors are the most important predictors of CC usage in construction organisations.
The paper offers a theoretical backdrop for future works on CC in construction, particularly in developing countries where such a study has not been explored.
Determinants of cloud computing deployment in South African construction organisations using structural equation modelling and machine learning technique
https://orcid.org/0000-0002-6661-5679
https://orcid.org/0000-0001-8297-3006
https://orcid.org/0000-0001-5835-0554
This paper presents the findings from the assessment of the determinants of cloud computing (CC) deployment by construction organisations. Using the technology-organisation-environment (TOE) framework, the study strives to improve construction organisations' project delivery and digital transformation by adopting beneficial technologies like CC.
This study adopted a post-positivism philosophical stance using a deductive approach with a questionnaire administered to construction organisations in South Africa. The data gathered were analysed using descriptive and inferential statistics. Also, the fusion of structural equation modelling (SEM) and machine learning (ML) regression models helped to gain a robust understanding of the key determinants of using CC.
The study found that the use of CC by construction organisations in South Africa is still slow. SEM indicated that this slow usage is influenced by six technology and environmental factors, namely (1) cost-effectiveness, (2) availability, (3) compatibility, (4) client demand, (5) competitors' pressure and (6) trust in cloud service providers. ML models developed affirmed that these variables have high predictive power. However, sensitivity analysis revealed that the availability of CC and CC's ancillary technologies and the pressure from competitors are the most important predictors of CC usage in construction organisations.
The paper offers a theoretical backdrop for future works on CC in construction, particularly in developing countries where such a study has not been explored.
Determinants of cloud computing deployment in South African construction organisations using structural equation modelling and machine learning technique
Cloud computing and construction organisation
Aghimien, Douglas (Autor:in) / Aigbavboa, Clinton Ohis (Autor:in) / Chan, Daniel W.M. (Autor:in) / Aghimien, Emmanuel Imuetinyan (Autor:in)
Engineering, Construction and Architectural Management ; 31 ; 1037-1060
01.03.2024
24 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| Emerald Group Publishing | 2023
| BASE | 2020
| British Library Conference Proceedings | 2008
Non-governmental organisations and the South African state: present and future relations
| Oxford University Press | 1993