Analyzing citizens’ views on new spatial-infrastructure projects

From the average view towards various clusters within the Participatory Value Evaluation Method

Master Thesis (2020)
Author(s)

Lisa Volberda (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

Maarten Kroesen – Mentor (TU Delft - Technology, Policy and Management)

Niek Mouter – Graduation committee member (TU Delft - Technology, Policy and Management)

Niels van Oort – Graduation committee member (Transport and Planning)

José Ignacio Hernández – Coach (TU Delft - Technology, Policy and Management)

N. Dogterom – Coach (Goudappel Coffeng)

Faculty
Civil Engineering & Geosciences
More Info
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Publication Year
2020
Language
English
Graduation Date
11-03-2020
Awarding Institution
Delft University of Technology
Programme
Transport, Infrastructure and Logistics
Faculty
Civil Engineering & Geosciences
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Abstract

This study identified the distribution of citizens for the allocation of the public budget towards spatial-infrastructure projects using the Participatory Value Evaluation (PVE) tool. The dataset of a PVE experiment in the Region of Amsterdam (Vervoersregio Amsterdam) is used. A Latent Class Cluster Analysis model was estimated to identify citizens selecting a similar combination of spatial-infrastructure projects. The results of this study found that individuals are more likely to select projects in their living area. Furthermore, individuals prefer rather a higher number of projects having low costs than one expensive project, and individuals assign high values to safety compliance projects. The results indicate individuals do neither necessarily base their choice on quantitative attribute values, such as minutes of travel time reduction realized by a new project, nor do individuals select a combination of projects based on travel mode improvements realized by these projects. By doing experts’ interviews, this study also provides a rich reflection of the implications of the clusters identified. The desirability of the location-effect depends on the aim of the experiment. The main implication of the results is that researchers have to be aware of the strong location-effect and that future research should control for this effect.

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