Paper Info
Title
A Governance Framework to Assist with the Adoption of Sensing Technologies in Construction
Abstract
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.
Year
DOI
Venue
2022
10.3390/s22010260
SENSORS
Keywords
DocType
Volume
sensing technologies, governance framework, online survey, semi-structured interviews, Partial Least Squares Structural Equation Modelling, triangulation analysis
Journal
22
Issue
ISSN
Citations 
1
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Mona Arabshahi100.68
Di Wang221.08
Yufei Wang300.68
Payam Rahnamayiezekavat400.68
Weichen Tang500.68
Xiangyu Wang600.68