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Digital Government Research and Practice (DGOV)
Article . 2024 . Peer-reviewed
License: CC BY
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Article . 2024
License: CC BY
https://dx.doi.org/10.48550/ar...
Article . 2023
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Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting

Authors: Joshua Chu-Yue Yang; Carina I. Hausladen; Dominik Peters; Evangelos Pournaras; Regula Hänggli Fricker; Dirk Helbing;

Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting

Abstract

Participatory Budgeting (PB) has evolved into a key democratic instrument for resource allocation in cities. Enabled by digital platforms, cities now have the opportunity to let citizens directly propose and vote on urban projects, using different voting input and aggregation rules. However, the choices cities make in terms of the rules of their PB have often not been informed by academic studies on voter behaviour and preferences. Therefore, this work presents the results of behavioural experiments where participants were asked to vote in a fictional PB setting. We identified approaches to designing PB voting that minimise cognitive load and enhance the perceived fairness and legitimacy of the digital process from the citizens’ perspective. In our study, participants preferred voting input formats that are more expressive (like rankings and distributing points) over simpler formats (like approval voting). Participants also indicated a desire for the budget to be fairly distributed across city districts and project categories. Participants found the Method of Equal Shares voting rule to be fairer than the conventional Greedy voting rule. These findings offer actionable insights for digital governance, contributing to the development of fairer and more transparent digital systems and collective decision-making processes for citizens.

Countries
France, Switzerland
Keywords

FOS: Computer and information sciences, General Economics (econ.GN), 330, J.4, Computer Science - Human-Computer Interaction, legitimacy, K.4.3, Trust, 91B14, explainable AI, Human-Computer Interaction (cs.HC), Méthodes informatiques spéciales, FOS: Economics and business, Digital democracy, Computer Science - Computers and Society, H.5.3, Computer Science - Computer Science and Game Theory, Computers and Society (cs.CY), Computer Science - Multiagent Systems, Economics - General Economics, Collective decision-making, I.2.11, H.5.3; J.4; K.4.3; I.2.11; F.2.0, 006, trust, collective decision-making, digital democracy, Explainable AI, Participatory budgeting, Participatory budgeting; digital democracy; collective decision-making; explainable AI; trust; legitimacy, F.2.0, Computer Science and Game Theory (cs.GT), Multiagent Systems (cs.MA)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
Green
hybrid