Journal article
EXPRESS: VotingWait Times and Political Misinformation on Social Media
Production and operations management
03/20/2026
DOI: 10.1177/10591478261437886
Abstract
The direct impacts of long wait times in elections, such as lost wages for voters and suppressed turnout, are well-documented. Drawing upon the service operations literature, we hypothesize that such operational inefficiencies may have far-reaching consequences beyond the immediate voter experience, in particular, the spread of political misinformation. Using a novel dataset that combines granular measures of voter wait times from cellphone location data, social media content, and demographic information at the county level, we find evidence that longer wait times are associated with greater sharing of political fake news on Reddit in the aftermath of the 2016 U.S. presidential election. Importantly, this relationship exhibits significant heterogeneity based on the racial composition of counties, with more diverse counties experiencing greater increases in misinformation spread due to wait times. To shed light on the mechanisms underlying this link, we leverage individual-level survey data on voters’ polling place experiences and perceptions of electoral integrity. Our analysis reveals that experiencing long wait times erodes voters’ confidence in the integrity of the election process, particularly at the local level. These findings underscore the societal importance of efficient election operations management and highlight how they can have profound implications for the health of democracy. Our work introduces a new factor—the operational efficiency of election administration—into the study of political misinformation, thus opening up avenues for operations management research to contribute to a pressing social challenge.
Details
- Title: Subtitle
- EXPRESS: VotingWait Times and Political Misinformation on Social Media
- Creators
- Feng Mai - University of IowaJingyi Sun - Stevens Institute of TechnologyMuer Yang - University of St. Thomas - Minnesota
- Resource Type
- Journal article
- Publication Details
- Production and operations management
- DOI
- 10.1177/10591478261437886
- ISSN
- 1059-1478
- eISSN
- 1937-5956
- Publisher
- Sage
- Grant note
The authors received no financial support for the research, authorship and/or publication of this article.
- Language
- English
- Electronic publication date
- 03/20/2026
- Academic Unit
- Business Analytics
- Record Identifier
- 9985149577702771
Metrics
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