Towards the Uptake of Digital Technologies for Construction Information Management: A Partial Least Squares Structural Equation Modelling Approach
Abstract
:1. Introduction
- Identification of the possible outcomes of construction information management;
- Identification of the digital tools that can be employed for construction information management;
- Modelling the quantified correlation among the identified outcomes to digital technologies by using the structural equation modelling (SEM) technique.
2. Theoretical Background
3. Materials and Methods
Hypothesized Model
4. Data Analysis
4.1. Demographic Background
4.2. Outcome of CIM—Final Structural Equation Model
5. Discussion
5.1. Communication (C)
5.2. Operational Efficiency (OE)
5.3. Market Insight (MI)
5.4. Point of Contact (PC)
5.5. Cost and Schedule (CS)
6. Contribution to Knowledge
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Gender | Frequency | Percentage (%) |
---|---|---|
Male | 169 | 65.9 |
Female | 88 | 34.1 |
Total | 257 | 100 |
Profession | ||
Architects | 34 | 13.2 |
Civil Engineers | 32 | 12.5 |
Mechanical and Electrical Engineers | 62 | 24.1 |
Quantity Surveyors | 67 | 26.1 |
Construction Project Managers | 7 | 2.7 |
Construction Managers | 21 | 8.2 |
Project Managers | 34 | 13.2 |
Total | 257 | 100 |
Firm Type | ||
Contracting | 115 | 44.6 |
Consulting | 77 | 30.1 |
Government | 65 | 25.3 |
Total | 257 | 100 |
Years of Experience | ||
1–5 years | 29 | 11.4 |
6–10 years | 106 | 41.4 |
11–15 years | 69 | 26.8 |
16–20 years | 25 | 9.6 |
21–25 years | 21 | 8.2 |
Above 25 years | 7 | 2.6 |
Total | 257 | 100 |
Number of Projects Executed | ||
1–3 projects | 22 | 8.5 |
4–6 projects | 26 | 10.2 |
7–9 projects | 52 | 20.3 |
10–12 projects | 84 | 32.7 |
13–15 projects | 32 | 12.3 |
Above 15 projects | 41 | 16.0 |
Total | 257 | 100 |
Constructs | Measurement Item | Measurement Item Code | Factor Loading | Cronbach’s Alpha | rho_A | Composite Reliability | AVE |
---|---|---|---|---|---|---|---|
C | Provide clarity | C1 | 0.763 | 0.865 | 0.894 | 0.917 | 0.652 |
Build relationships | C2 | 0.699 | ✓ | ✓ | ✓ | ✓ | |
Create commitment | C3 | 0.758 | ✓ | ✓ | ✓ | ✓ | |
Define expectations | C4 | 0.860 | ✓ | ✓ | ✓ | ✓ | |
Easy transmission of information | C5 | 0.847 | ✓ | ✓ | ✓ | ✓ | |
PC | Efficient service delivery | PC1 | 0.802 | 0.871 | 0.901 | 0.906 | 0.665 |
Accountability | PC2 | 0.657 | ✓ | ✓ | ✓ | ✓ | |
Effective utilization time | PC3 | 0.711 | ✓ | ✓ | ✓ | ✓ | |
Increased trust and dependability | PC4 | 0.783 | ✓ | ✓ | ✓ | ✓ | |
Improves company’s image | PC5 | 0.610 | ✓ | ✓ | ✓ | ✓ | |
OE | Competitive advantage | OE1 | 0.737 | 0.851 | 0.874 | 0.898 | 0.601 |
Consistency in operational system | OE2 | 0.608 | ✓ | ✓ | ✓ | ✓ | |
Increased productivity | OE3 | 0.616 | ✓ | ✓ | ✓ | ✓ | |
Flexibility of employees | OE4 | 0.703 | ✓ | ✓ | ✓ | ✓ | |
Time maximization | OE5 | 0.880 | ✓ | ✓ | ✓ | ✓ | |
CS | Rapid decision-making | CS1 | 0.763 | 0.724 | 0.861 | 0.828 | 0.684 |
Collection of quality data | CS2 | 0.679 | ✓ | ✓ | ✓ | ✓ | |
Matching standard requirements | CS3 | 0.770 | ✓ | ✓ | ✓ | ✓ | |
Product performance and variety | CS4 | 0.800 | ✓ | ✓ | ✓ | ✓ | |
MI | Client’s satisfaction | MI1 | 0.845 | 0.761 | 0.880 | 0.787 | 0691 |
Alertness to opportunities | MI2 | 0.642 | ✓ | ✓ | ✓ | ✓ | |
Revenue generation | MI3 | 0.839 | ✓ | ✓ | ✓ | ✓ | |
Improved/better decision-making | MI4 | 0.657 | ✓ | ✓ | ✓ | ✓ | |
DT | Smart sensor devices | DT1 | 0.728 | 0.897 | 0.925 | 0.920 | 0.674 |
Smart wearable | DT2 | 0.755 | ✓ | ✓ | ✓ | ✓ | |
Cloud storage | DT3 | 0.731 | ✓ | ✓ | ✓ | ✓ | |
Artificial intelligence | DT4 | 0.794 | ✓ | ✓ | ✓ | ✓ | |
Robotics | DT5 | 0.836 | ✓ | ✓ | ✓ | ✓ | |
Augmented reality technology | DT6 | 0.882 | ✓ | ✓ | ✓ | ✓ | |
Autonomous vehicle | DT7 | 0.808 | ✓ | ✓ | ✓ | ✓ | |
Quantum computing | DT8 | 0.779 | ✓ | ✓ | ✓ | ✓ | |
Big data | DT9 | 0.929 | ✓ | ✓ | ✓ | ✓ |
C | PC | OE | CS | MI | DT | |
---|---|---|---|---|---|---|
C | 0.807 | |||||
PC | 0.737 | 0.831 | ||||
OE | 0.801 | 0.777 | 0.827 | |||
CS | 0.661 | 0.603 | 0.621 | 0.815 | ||
MI | 0.603 | 0.687 | 0.602 | 0.470 | 0.775 | |
DT | 0.645 | 0.536 | 0.584 | 0.442 | 0.352 | 0.821 |
Hypothetical Path | Path Coefficient | Sample MEAN | Standard Deviation | t-Value | p-Value | Interpretation |
---|---|---|---|---|---|---|
C –> DT | 0.650 | 0.359 | 0.144 | 4.724 | 0.022 | Significant |
PC –> DT | 0.427 | 0.214 | 0.119 | 1.951 | 0.058 | Partially Significant |
OE –> DT | 0.754 | 0.723 | 0.156 | 3.842 | 0.013 | Significant |
CS –> DT | 0.065 | -0.071 | 0.101 | 0.831 | 0.453 | Not Significant |
MI –> DT | 0.890 | 0.756 | 0.168 | 5.846 | 0.000 | Significant |
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Adekunle, P.; Aigbavboa, C.; Akinradewo, O.; Ikuabe, M.; Otasowie, K. Towards the Uptake of Digital Technologies for Construction Information Management: A Partial Least Squares Structural Equation Modelling Approach. Buildings 2024, 14, 827. https://doi.org/10.3390/buildings14030827
Adekunle P, Aigbavboa C, Akinradewo O, Ikuabe M, Otasowie K. Towards the Uptake of Digital Technologies for Construction Information Management: A Partial Least Squares Structural Equation Modelling Approach. Buildings. 2024; 14(3):827. https://doi.org/10.3390/buildings14030827
Chicago/Turabian StyleAdekunle, Peter, Clinton Aigbavboa, Opeoluwa Akinradewo, Matthew Ikuabe, and Kenneth Otasowie. 2024. "Towards the Uptake of Digital Technologies for Construction Information Management: A Partial Least Squares Structural Equation Modelling Approach" Buildings 14, no. 3: 827. https://doi.org/10.3390/buildings14030827