Service Design to Balance Waiting Time and Infection Risk: An Application for Elections During the COVID-19 Pandemic

Susana Mondschein (), Marcelo Olivares (), Fernando Ordóñez (), Daniel Schwartz (), Andres Weintraub (), Ignacio Torres-Ulloa (), Cristian Aguayo () and Gianpiero Canessa ()
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Susana Mondschein: Instituto Sistemas Complejos de Ingenieria, Department of Industrial Engineering, University of Chile, Santiago, Chile
Marcelo Olivares: Instituto Sistemas Complejos de Ingenieria, Department of Industrial Engineering, University of Chile, Santiago, Chile
Fernando Ordóñez: Instituto Sistemas Complejos de Ingenieria, Department of Industrial Engineering, University of Chile, Santiago, Chile
Daniel Schwartz: Instituto Sistemas Complejos de Ingenieria, Department of Industrial Engineering, University of Chile, Santiago, Chile
Andres Weintraub: Instituto Sistemas Complejos de Ingenieria, Department of Industrial Engineering, University of Chile, Santiago, Chile
Ignacio Torres-Ulloa: Instituto Sistemas Complejos de Ingenieria, Department of Industrial Engineering, University of Chile, Santiago, Chile
Cristian Aguayo: Université Libre de Bruxelles, 1050 Bruxelles, Belgium
Gianpiero Canessa: KTH Royal Institute of Technology, 114 28 Stockholm, Sweden

Service Science, 2022, vol. 14, issue 2, 90-109

Abstract: The COVID-19 pandemic has caused great disruption to the service sector, and it has, in turn, adapted by implementing measures that reduce physical contact among employees and users; examples include home-office work and the setting of occupancy restrictions at indoor locations. The design of services in the context of a pandemic requires balancing between two objectives: (i) special measures must be implemented to maintain physical separation among people to reduce the risk of infection, and (ii) these sanitary measures also reduce process capacity, thereby increasing the waiting times of users. We study this problem in the context of election processes, in which balancing waiting time with public safety is of first order relevance to ensuring voter turnout, using as a real-world application the Chilean 2020 national referendum. Analyzing this problem requires a multidisciplinary approach that consists of integrating randomized experiments to measure how voters weigh infection risk relative to waiting time and stochastic modeling/discrete event simulation to prescribe recommendations for the service design—specifically setting capacity limits to trade off between overcrowding and process efficiency. Overall, our results shows that infection risk is an important factor affecting voter turnout during a pandemic and that capacity limits can be a useful design tool to balance these risks with other service quality measures. Some of these findings were considered in the guidelines that Servel provided to manage capacity and voter arrival patterns at voting centers.

Keywords: service design; queueing; discrete event simulation; randomized experiment; process analysis; COVID-19; voting behavior (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orserv:v:14:y:2022:i:2:p:90-109

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