A governance framework to assist with the adoption of sensing technologies in construction
Sensing technologies present great improvements in construction performance including the safety, productivity, and quality. However, the corresponding applications in real projects are far behind compared with the academically research. This research aims to discover dominate influence factors in t...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
MDPI
2022
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| Subjects: | |
| Online Access: | http://purl.org/au-research/grants/arc/LP180100222 http://hdl.handle.net/20.500.11937/90928 |
| _version_ | 1848765463232774144 |
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| author | Arabshahi, Mona Wang, D. Wang, Yufei Rahnamayiezekavat, P. Tang, W. Wang, Xiangyu |
| author_facet | Arabshahi, Mona Wang, D. Wang, Yufei Rahnamayiezekavat, P. Tang, W. Wang, Xiangyu |
| author_sort | Arabshahi, Mona |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Sensing technologies present great improvements in construction performance including the safety, productivity, and quality. However, the corresponding applications in real projects are far behind compared with the academically research. This research aims to discover dominate influence factors in the sensing technologies adoption and ultimately develop a governance framework facilitating adoption processes. The framework is dedicated on general sensing technologies rather than single sensor in previous framework studies. To begin with, the influence factors of sensing technologies and other similar emerging technologies are summarised through a review. Then, a mixed methods design was employed to collect quantitative data through an online survey, and qualitative data through semi‐structured interviews. Findings of the quantitative method reveal that the most widely implemented sensing technologies are GPS and visual sensing technology, but they’re still not adopted by all construction companies. Partial Least Squares Structural Equation Modelling reveals that supplier characteristics have the highest effect in all influence factors. Qualitative method was adopted to investigate perceptions of construction stakeholders on the major decision‐making considerations in the adoption process. Ultimately, a triangulation analysis of findings from the literature review, online survey and interviews resulted in the governance framework development. The overarching contribution of this research focus on the general adoption of sensing technologies rather than the adoption of a specific sensor. Therefore, the governance framework can assist with the decision‐making process of any sensing technology adoption in construction. |
| first_indexed | 2025-11-14T11:35:39Z |
| format | Journal Article |
| id | curtin-20.500.11937-90928 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:35:39Z |
| publishDate | 2022 |
| publisher | MDPI |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-909282023-05-09T07:04:37Z A governance framework to assist with the adoption of sensing technologies in construction Arabshahi, Mona Wang, D. Wang, Yufei Rahnamayiezekavat, P. Tang, W. Wang, Xiangyu Science & Technology Physical Sciences Technology Chemistry, Analytical Engineering, Electrical & Electronic Instruments & Instrumentation Chemistry Engineering sensing technologies governance framework online survey semi-structured interviews Partial Least Squares Structural Equation Modelling triangulation analysis ENGINEERED CEMENTITIOUS COMPOSITES TIME LOCATING SYSTEMS WEARABLE TECHNOLOGY SAFETY SITES PERFORMANCE PROJECTS QUALITY Partial Least Squares Structural Equation Modelling governance framework online survey semi-structured interviews sensing technologies triangulation analysis Research Design Surveys and Questionnaires Technology Research Design Technology Surveys and Questionnaires Sensing technologies present great improvements in construction performance including the safety, productivity, and quality. However, the corresponding applications in real projects are far behind compared with the academically research. This research aims to discover dominate influence factors in the sensing technologies adoption and ultimately develop a governance framework facilitating adoption processes. The framework is dedicated on general sensing technologies rather than single sensor in previous framework studies. To begin with, the influence factors of sensing technologies and other similar emerging technologies are summarised through a review. Then, a mixed methods design was employed to collect quantitative data through an online survey, and qualitative data through semi‐structured interviews. Findings of the quantitative method reveal that the most widely implemented sensing technologies are GPS and visual sensing technology, but they’re still not adopted by all construction companies. Partial Least Squares Structural Equation Modelling reveals that supplier characteristics have the highest effect in all influence factors. Qualitative method was adopted to investigate perceptions of construction stakeholders on the major decision‐making considerations in the adoption process. Ultimately, a triangulation analysis of findings from the literature review, online survey and interviews resulted in the governance framework development. The overarching contribution of this research focus on the general adoption of sensing technologies rather than the adoption of a specific sensor. Therefore, the governance framework can assist with the decision‐making process of any sensing technology adoption in construction. 2022 Journal Article http://hdl.handle.net/20.500.11937/90928 10.3390/s22010260 English http://purl.org/au-research/grants/arc/LP180100222 http://creativecommons.org/licenses/by/4.0/ MDPI fulltext |
| spellingShingle | Science & Technology Physical Sciences Technology Chemistry, Analytical Engineering, Electrical & Electronic Instruments & Instrumentation Chemistry Engineering sensing technologies governance framework online survey semi-structured interviews Partial Least Squares Structural Equation Modelling triangulation analysis ENGINEERED CEMENTITIOUS COMPOSITES TIME LOCATING SYSTEMS WEARABLE TECHNOLOGY SAFETY SITES PERFORMANCE PROJECTS QUALITY Partial Least Squares Structural Equation Modelling governance framework online survey semi-structured interviews sensing technologies triangulation analysis Research Design Surveys and Questionnaires Technology Research Design Technology Surveys and Questionnaires Arabshahi, Mona Wang, D. Wang, Yufei Rahnamayiezekavat, P. Tang, W. Wang, Xiangyu A governance framework to assist with the adoption of sensing technologies in construction |
| title | A governance framework to assist with the adoption of sensing technologies in construction |
| title_full | A governance framework to assist with the adoption of sensing technologies in construction |
| title_fullStr | A governance framework to assist with the adoption of sensing technologies in construction |
| title_full_unstemmed | A governance framework to assist with the adoption of sensing technologies in construction |
| title_short | A governance framework to assist with the adoption of sensing technologies in construction |
| title_sort | governance framework to assist with the adoption of sensing technologies in construction |
| topic | Science & Technology Physical Sciences Technology Chemistry, Analytical Engineering, Electrical & Electronic Instruments & Instrumentation Chemistry Engineering sensing technologies governance framework online survey semi-structured interviews Partial Least Squares Structural Equation Modelling triangulation analysis ENGINEERED CEMENTITIOUS COMPOSITES TIME LOCATING SYSTEMS WEARABLE TECHNOLOGY SAFETY SITES PERFORMANCE PROJECTS QUALITY Partial Least Squares Structural Equation Modelling governance framework online survey semi-structured interviews sensing technologies triangulation analysis Research Design Surveys and Questionnaires Technology Research Design Technology Surveys and Questionnaires |
| url | http://purl.org/au-research/grants/arc/LP180100222 http://hdl.handle.net/20.500.11937/90928 |