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Addressing the BENEFIT Project objectives and expected impacts, the BENEFIT project followed a multi-analysis approach throughout its course. Starting from a purely descriptive statistics analysis, the workflow continued with parallel qualitative and quantitative analyses of the BENEFIT project case database based on the BENEFIT Matching Framework indicators.


More specifically, qualitative analysis was conducted per mode:


  • On an Ad-hoc basis, to identify through case analysis the factors influencing project performance,
  • Using the BENEFIT conceptual framework as an analysis framework
  • Using the BENEFIT Matching Framework indicators as measures for the assessment of project performance.

    The analysis of the BENEFIT Matching Framework indicators was conducted by applying the following methodologies to the entire sample and appropriate sub-samples:


  • Fuzzy Set Qualitative Comparative Analysis (fsQCA)
  • Importance (or Sensitivity) Analysis (IA)
  • Econometric Modelling.

    In addition, ad hoc analyses were conducted to validate the construction of the BENEFIT Matching Framework indicators. These analyses also led to interesting findings and conclusions.

    Furthermore, the limitations of the BENEFIT Matching Framework as well as the interrelations of its elements and constituent indicators were investigated through a cause and effect mapping study. This effort was based on specific project cases and aimed to enhance the understanding and the interpretations that originated from previous analysis streams.

    Table 1 presents the analyses that have been undertaken within the BENEFIT project. In all cases, the financing scheme (PPP vs public financing) was investigated and the focus was to identify factors influencing project outcomes and measuring the impact of the recent financial crisis. Some findings, produced through the various analyses, were cross-cutting. Some findings were generated through the combination and complementarity of all analyses.

    Findings were discussed in two Policy Dialogue events, which took place in Milano, Italy and Frankfurt, Germany. Policy Dialogue events also produced their own findings.

    In each analysis, the focus was placed on factors and conditions supporting key project outcomes. As mentioned earlier, of the large range of possible project outcomes, only four were assessed when considering the funding and financing of transport infrastructure project delivery and operation:


  • Cost to (construction) Completion
  • Time to (construction) Completion
  • Actual versus Forecast Traffic
  • Actual versus Forecast Revenues.

  • Table 1 Analyses Conducted within the BENEFIT Project



    While the above outcomes do not capture the entire scope of a project, they are directly related to the structuring of its funding and financing.

    BENEFIT recognises the importance and potential positive impacts a project may have on the wider economy, society, and environment. As these wider positive impacts may counterbalance less-than-expected performance on any of the above-mentioned outcomes, BENEFIT knowledgeably does not attempt to provide an overall assessment of a project. The scope of findings and lessons learnt presented concerned the potential to solely achieve the above stated outcomes, independently of the alignment or disparity of perspectives and objectives that relevant actors may have. In this context, BENEFIT is stakeholder–neutral. It remains to the individual stakeholder to weight and assess the relative importance of achieving specific or a combination of outcomes, keeping in mind that these may be related with other outcomes which are not considered in the present study.

    The research effort has been conducted on four levels:

    1.  Identifying key factors that influence transport infrastructure project performance, especially with respect to the implemented funding and financing scheme.

    2.  Expressing transport infrastructure project performance through a system of indicators (BENEFIT Matching Framework), which capture the key factors and their interrelations as these affect the expected outcomes.

    3.  Identifying factors influencing the performance of each mode.

    4.  Assessing and improving the explanatory power of the BENEFIT Matching Framework.



    Read More

    Synthesis of Analysis Findings

    Qualitative Analysis

    Fuzzy-Set Qualitative Comparative Analysis

    Importance Analysis

    Econometric Models


    Contact us

    Dr. Athena Roumboutsos

    University of the Aegean 
    Department of Shipping, Trade and Transport

    Email: benefit@aegean.gr

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