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How design features affect evaluations of participatory platforms

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  • Christensen, Henrik Serup

    (Åbo Akademi University)

Abstract

Online participatory platforms are introduced to boost citizen involvement in political decision-making. However, the design features of these platforms vary considerably, and these are likely to affect how prospective users evaluate the usefulness of these platforms. Previous studies explored how prevalent different design features are and how they affect the success of platforms in terms of impact, but the attitudes of prospective users remain unclear. Since these evaluations affect the prospects for launching successful participatory platforms, it is imperative to assess what citizens want from such digital possibilities for participation. This study uses a conjoint experiment (n=1048) conducted in Finland that explore the impact of seven design features: Discussion possibilities; Interaction with politicians and experts; Information availability, Aim of participation; Identity verification; Anonymous participation and Accessibility. Furthermore, it is examined whether the effects differ across use of ICTs measured by generation, time online and prior use of participatory platforms. The results suggest that most design features have clear effects on evaluations, and that deliberative features have the strongest effects. Furthermore, the effects are relatively stable across prior use although the less experienced put a stronger emphasis on verification.

Suggested Citation

  • Christensen, Henrik Serup, 2020. "How design features affect evaluations of participatory platforms," SocArXiv 4ubwh_v1, Center for Open Science.
  • Handle: RePEc:osf:socarx:4ubwh_v1
    DOI: 10.31219/osf.io/4ubwh_v1
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    References listed on IDEAS

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    1. Leeper, Thomas J. & Hobolt, Sara B. & Tilley, James, 2020. "Measuring Subgroup Preferences in Conjoint Experiments," Political Analysis, Cambridge University Press, vol. 28(2), pages 207-221, April.
    2. Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2014. "Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments," Political Analysis, Cambridge University Press, vol. 22(1), pages 1-30, January.
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