Abstract
Based on the examination of the transactions made in 58 case study projects, we have developed probabilistic causation models that include relationships hypothesised from exhaustive literature reviews. These models contain relationships that relate a number of significant project variables to transport infrastructure project performance. Here, we report on the use of the Importance Analysis approach to identify the most significant factors linked to variables measuring project performance. Such an approach is used in combination of Bayesian Networks and Sensitivity Analysis. Some variables that resulted important to achieve cost, time, and revenue expectations in transport infrastructure projects are identified. These include factors other than those related to project governance but linked to the funding and financing schemes in a project and its context of implementation. Additionally, we analysed how projects in the BENEFIT database responded to the effects of the European economic crisis in 2008. The results indicated that some actions were implemented at some instances during the crisis time. Specific factors that appeared to be sufficiently robust to face the economic crisis were found.
Original language | English |
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Pages (from-to) | 481-498 |
Number of pages | 18 |
Journal | European journal of transport and infrastructure research |
Volume | 18 |
Issue number | 4 |
Publication status | Published - 1 Jan 2018 |
Keywords
- Causal modelling
- Cost overrun
- Funding and financing schemes
- Project governance
- Uncertainty in projects