Abstract
The current literature links Risk Response Strategy Selection (RRSS) practices in construction projects to a limited number of criteria, focusing on probability and impact assessments. Moreover, it adopts a “flat” approach to decision-making as analysis frameworks, for example the ‘micro-meso-macro’ ontology, fail to capture the hierarchical nature of decision-making at the ‘micro’ (project) level. Construction projects are more complex than the traditional approach can accommodate, making it of limited value if not potentially detrimental to project outcomes. An innovative methodology for complex modelling is proposed to include all selection criteria critical to RRSS and use temporality and locality of their interactions to define sub-levels in decision-making within the ‘micro’ (project) level to capture its true hierarchical nature. Data collection involved surveys and interviews with 235 construction practitioners worldwide. The model was validated using real-life project data. This approach to modelling represents the departure point for better risk response planning in construction projects. The successfully tested and validated RRSS model can be extended to all complex risk response planning in construction project management research.
| Original language | English |
|---|---|
| Journal | Journal of Construction Engineering and Management |
| Publication status | Submitted - 13 Dec 2019 |
| Externally published | Yes |
Keywords
- Project Risk Management
- Risk Response Planning
- Complex Adaptive Systems
- Multiple Criteria Analysis
- Fuzzy Logic Systems (FLS)