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Published July 2019 | Supplemental Material
Journal Article Open

Impact of Personalized Information on Vote Intention: Evidence from a Randomized Field Experiment


Voting advice applications (VAAs) are voter information tools that millions of individuals have used in recent elections throughout the world. However, little is known about how they affect political behavior. Until now, observational studies of VAA have produced inconclusive results. Here we present the results from a randomized field experiment in Switzerland that estimates the causal effects of VAA use on voters' vote intentions. Our results suggest that usage of the Swiss VAA smartvote strengthened the vote intention for the most preferred party and also increased the number of parties considered as potential vote options. These results imply that VAAs can influence voting behavior and that they can play an important role in electoral politics.

Additional Information

© 2019 by the Southern Political Science Association. Published online April 23, 2019. We would like to thank the following institutions that supported this research by giving us the time to work on the project, access to data, and financial support for participating in conferences and meetings: Swiss Graduate School of Public Administration (University of Lausanne), the Politools team, NCCR Democracy (University of Zurich), Swiss Chair on Federalism and Democracy at the Department of Political and Social Sciences of the European University Institute (EUI) in Florence (financed by the Swiss State Secretariat for Education, Research and Innovation), European Union Democracy Observatory at the Robert Schuman Center for Advanced Studies at the EUI, smartvote, University of Zurich, ETH Zurich, University of Bern, and University of Lucerne. We also thank the participants of the panel on Technology, Elections and Politics in the Western Political Science Association Annual Meeting 2013 in Hollywood, CA, as well as the seminar participants at the Ifo Institute in Munich and the University of Konstanz. Finally, we would like to thank Andreas Ladner and Diego Garzia for their comments on earlier versions. Data and supporting materials necessary to reproduce the numerical results in the article are available in the JOP Dataverse (https://dataverse.harvard.edu/dataverse/jop). An online appendix with supplementary material is available at https://dx.doi.org/10.1086/702946.

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