IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v80y2022ics003801212100166x.html
   My bibliography  Save this article

Designing pandemic-resilient voting systems

Author

Listed:
  • Schmidt, Adam
  • Albert, Laura A.

Abstract

The 2020 general election occurred while many parts of the nation were under emergency orders related to the COVID-19 pandemic. This led to new requirements and considerations for voting systems. We introduce a model of the voting process to capture pandemic-related changes. Using a discrete event simulation case study of Milwaukee, WI, we study how to design in-person voting systems whose performance are robust to pandemic conditions, such as protective measures implemented during the COVID-19 pandemic. We assess various voting system designs on the voter wait times, voter sojourn times, line lengths at polling locations, voter time spent inside, and the number of voters inside. The analysis indicates that poll worker shortages, social distancing, and personalized protective equipment usage and sanitation measures can lead to extremely long voter wait times. We consider several design choices for mitigating the impact of pandemic-related changes on voting metrics. The case study suggests that long wait times can be avoided by staffing additional check-in locations, expanding early voting, and avoiding consolidated polling locations. Additionally, the analysis suggests that implementing a priority queue discipline has the potential to reduce waiting times for vulnerable populations at increased susceptibility to health risks associated with in-person voting.

Suggested Citation

  • Schmidt, Adam & Albert, Laura A., 2022. "Designing pandemic-resilient voting systems," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:soceps:v:80:y:2022:i:c:s003801212100166x
    DOI: 10.1016/j.seps.2021.101174
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S003801212100166X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2021.101174?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Enrico Cantoni, 2020. "A Precinct Too Far: Turnout and Voting Costs," American Economic Journal: Applied Economics, American Economic Association, vol. 12(1), pages 61-85, January.
    2. Yang, Muer & Wang, Xinfang (Jocelyn) & Xu, Nuo, 2015. "A robust voting machine allocation model to reduce extreme waiting," Omega, Elsevier, vol. 57(PB), pages 230-237.
    3. Muer Yang & Theodore Allen & Michael Fry & W. Kelton, 2013. "The call for equity: simulation optimization models to minimize the range of waiting times," IISE Transactions, Taylor & Francis Journals, vol. 45(7), pages 781-795.
    4. Xinfang (Jocelyn) Wang & Muer Yang & Michael J Fry, 2015. "Efficiency and equity tradeoffs in voting machine allocation problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(8), pages 1363-1369, August.
    5. Muer Yang & Michael J. Fry & W. David Kelton & Theodore T. Allen, 2014. "Improving Voting Systems through Service-Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 23(7), pages 1083-1097, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Konrad, Renata A. & Maass, Kayse Lee & Dimas, Geri L. & Trapp, Andrew C., 2023. "Perspectives on how to conduct responsible anti-human trafficking research in operations and analytics," European Journal of Operational Research, Elsevier, vol. 309(1), pages 319-329.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kumar, Sameer & Yang, Muer & Goldschmidt, Kyle H., 2018. "Will aging voting machines cause more voters to experience long waits?," International Journal of Production Economics, Elsevier, vol. 198(C), pages 1-10.
    2. Yang, Muer & Wang, Xinfang (Jocelyn) & Xu, Nuo, 2015. "A robust voting machine allocation model to reduce extreme waiting," Omega, Elsevier, vol. 57(PB), pages 230-237.
    3. Thomas W. Lucas & W. David Kelton & Paul J. Sánchez & Susan M. Sanchez & Ben L. Anderson, 2015. "Changing the paradigm: Simulation, now a method of first resort," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(4), pages 293-303, June.
    4. Billings, Stephen B. & Braun, Noah & Jones, Daniel & Shi, Ying, 2022. "Disparate Racial Impacts of Shelby County v. Holder on Voter Turnout," IZA Discussion Papers 15829, Institute of Labor Economics (IZA).
    5. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    6. Gérard P. Cachon & Dawson Kaaua, 2022. "Serving Democracy: Evidence of Voting Resource Disparity in Florida," Management Science, INFORMS, vol. 68(9), pages 6687-6696, September.
    7. Mariella Gonzales & Gianmarco León-Ciliotta & Luis R. Martínez, 2022. "How Effective Are Monetary Incentives to Vote? Evidence from a Nationwide Policy," American Economic Journal: Applied Economics, American Economic Association, vol. 14(1), pages 293-326, January.
    8. Kelly, Andrea & Lindo, Jason M. & Packham, Analisa, 2020. "The power of the IUD: Effects of expanding access to contraception through Title X clinics," Journal of Public Economics, Elsevier, vol. 192(C).
    9. Jean-Victor Alipour & Lindlacher Valentin, 2022. "No Surprises, Please: Voting Costs and Electoral Turnout," CESifo Working Paper Series 9759, CESifo.
    10. Yang, Yongjian & Yin, Yunqiang & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Dhamotharan, Lalitha, 2023. "Distributionally robust multi-period location-allocation with multiple resources and capacity levels in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1042-1062.
    11. Marco Frank & David Stadelmann & Benno Torgler, 2020. "Electoral Turnout During States of Emergency and Effects on Incumbent Vote Share," CREMA Working Paper Series 2020-10, Center for Research in Economics, Management and the Arts (CREMA).
    12. Kyle Raze, 2022. "Voting rights and the resilience of Black turnout," Economic Inquiry, Western Economic Association International, vol. 60(3), pages 1127-1141, July.
    13. Bowles, Jeremy & Larreguy, Horacio & Woller, Anders, 2020. "Information Versus Control: The Electoral Consequences of Polling Place Creation," TSE Working Papers 20-1154, Toulouse School of Economics (TSE).
    14. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Xie, Ying, 2022. "Service fairness and value of customer information for the stochastic container relocation problem under flexible service policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    15. Enrico Cantoni & Vincent Pons, 2021. "Strict Id Laws Don’t Stop Voters: Evidence from a U.S. Nationwide Panel, 2008–2018," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(4), pages 2615-2660.
    16. Zhizheng Zhang & Wentao Wei & Tianlu Zhu & Ming Zhou & Yajun Li, 2022. "New Dimension on Quality of Life Differences among Older Adults: A Comparative Analysis of Digital Consumption in Urban and Rural Areas of China," IJERPH, MDPI, vol. 19(22), pages 1-23, November.
    17. Marco Frank & David Stadelmann & Benno Torgler, 2023. "Higher turnout increases incumbency advantages: Evidence from mayoral elections," Economics and Politics, Wiley Blackwell, vol. 35(2), pages 529-555, July.
    18. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    19. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Zeng, Qingcheng, 2020. "The stochastic container relocation problem with flexible service policies," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 116-163.
    20. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:80:y:2022:i:c:s003801212100166x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.