To assess the overall benefits of the DIAMOND project in addressing fair inclusion for woman in transport systems and building a more inclusive transport system, an impact assessment framework is proposed. The essence of this framework is to evaluate proposed innovations (fairness interventions or measures) in delivering the main objectives of the DIAMOND project.
The impact assessment focuses on the extent to which the defined fairness measures deliver their respective objectives in terms of the following four use-cases:
- Public transport and infrastructure
- Autonomous vehicles
- Bike sharing
- Employment of women in the rail industry
More precisely, the framework will support the transport stakeholders (transport operators, as well as policy makers) to better understand the benefits generated in relation to women as users and employees in the transport sector.
The framework includes two stages:
- 3Es (Efficiency, Effectiveness and Equity) impact assessment
- Sensitivity analyses
The first stage is based on already developed Efficiency-Effectiveness-Equity or 3E approach of the impact assessment framework, which includes identification and measurement of Efficiency and Effectiveness of the selected fairness measures per each use case and an evaluation of relevant Equity-based indicators. This evaluation will be performed through observations, when possible, and through expectation surveys when observations are not possible.
Sensitivity analyses represent the sustainability assessment of the DIAMOND results and it includes AHP-based sensitivity analysis (AHP-SA) as well as the 3Es-based sensitivity analysis.
AHP-based sensitivity analysis
AHP-based sensitivity analysis (AHP-SA) represents a crucial step for the sustainability assessment of DIAMOND results. The subject of the analysis is the final hierarchy of the main attributes known also as Fairness Characteristics we obtained from the analysis for each use case and which actually represent crucial aspects that female users find important for a comfortable, safe and useful service or for an inclusive and fair employment in transport. The final hierarchy is obtained by Analytic Hierarchy Process (AHP) as one of the most popular methods of evaluation and selection among the set of alternatives subject to a number of heterogeneous criteria.
AHP-SA is divided into two parts:
- Sensitivity analysis of results over time: The final priorities of the Fairness Characteristics are dependent on the weights given to them in the AHP analysis. These weights reflect the perceptions and judgments of the users of transport services and employees in the transport sector. The fairness characteristics hierarchy will be obtained per each of the special groups (religion, education, age, disability,…) but priorities of each of these groups can change with the time and then the final fairness characteristics hierarchy and consequently the fairness measures (service provisions) generation process Therefore, the aim of this stage is to evaluate the stability of the final ranking (or the wrights) of Fairness Characteristics against the slight changes in user perceptions over time. As it is illustrated on Figure 1., the essence of the approach is to assess how the weights of the fairness characteristics on the lower level will change when the weights of each fairness characteristic on upper level increase or decrease by a 50%. The most preferred fairness characteristics (80%) will be considered for further analysis.
Figure 1. Sensitivity analysis over time
- Sensitivity analysis of results over space: This stage is conducted in order to assess the validity of the DIAMOND’s results in different parts of Europe and different cultures. This sensitivity analysis over space will be carried out for a set of Fairness Characteristics (FC) for all the considered use-cases and all the member states addressed by DIAMOND by applying the AHP with screened data per countries (intersectional analysis per Member States or cultures).
This 3Es-based sensitivity analysis will be conducted by applying inferences in the Bayesian Network (BN) analysis and will feed the simulation module of DIAMOND’s toolbox. The aim of this stage is to assess how changes in efficiency and/or effectiveness will impact on the equity resulting from implementation of a specific fairness measure (Figure 2.).
Figure 2. 3E sensitivity analysis.
About the author
Dr. Milos Milenkovic is Associate Professor at The Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia. He also holds a position of research fellow at the Zaragoza Logistics Center (MIT-Zaragoza Program).
University of Belgrade, Faculty of Transport and Traffic Engineering
The Faculty of Transport and Traffic Engineering (FTTE), as one of the faculties of the University of Belgrade is the oldest academic and research institution in the field of transportation in South East Europe (SEE). The FTTE promotes applied research, new methodologies and technologies to provide solutions in the area of transport engineering. It participates to DIAMOND project defining the methodology for efficient and impact assessment and analysis based on productive equity concept.