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Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management
Failing to mitigate propagation of disease spread can result in dire economic consequences for agricultural networks. Pathogens like Porcine Epidemic Diarrhea virus, can quickly spread among producers. Biosecurity is designed to prevent infection transmission. When considering biosecurity investment...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077803/ https://www.ncbi.nlm.nih.gov/pubmed/32182247 http://dx.doi.org/10.1371/journal.pone.0228983 |
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author | Clark, Eric M. Merrill, Scott C. Trinity, Luke Bucini, Gabriela Cheney, Nicholas Langle-Chimal, Ollin Shrum, Trisha Koliba, Christopher Zia, Asim Smith, Julia M. |
author_facet | Clark, Eric M. Merrill, Scott C. Trinity, Luke Bucini, Gabriela Cheney, Nicholas Langle-Chimal, Ollin Shrum, Trisha Koliba, Christopher Zia, Asim Smith, Julia M. |
author_sort | Clark, Eric M. |
collection | PubMed |
description | Failing to mitigate propagation of disease spread can result in dire economic consequences for agricultural networks. Pathogens like Porcine Epidemic Diarrhea virus, can quickly spread among producers. Biosecurity is designed to prevent infection transmission. When considering biosecurity investments, management must balance the cost of protection versus the consequences of contracting an infection. Thus, an examination of the decision making processes associated with investment in biosecurity is important for enhancing system wide biosecurity. Data gathered from experimental gaming simulations can provide insights into behavioral strategies and inform the development of decision support systems. We created an online digital experiment to simulate outbreak scenarios among swine production supply chains, where participants were tasked with making biosecurity investment decisions. In Experiment One, we quantified the risk associated with each participant’s decisions and delineated three dominant categories of risk attitudes: risk averse, risk tolerant, and opportunistic. Each risk class exhibited unique approaches in reaction to risk and disease information. We also tested how information uncertainty affects risk aversion, by varying the amount of visibility of the infection as well as the amount of biosecurity implemented across the system. We found evidence that more visibility in the number of infected sites increases risk averse behaviors, while more visibility in the amount of neighboring biosecurity increased risk taking behaviors. In Experiment Two, we were surprised to find no evidence for differences in behavior of livestock specialists compared to Amazon Mechanical Turk participants. Our findings provide support for using experimental gaming simulations to study how risk communication affects behavior, which can provide insights towards more effective messaging strategies. |
format | Online Article Text |
id | pubmed-7077803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70778032020-03-23 Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management Clark, Eric M. Merrill, Scott C. Trinity, Luke Bucini, Gabriela Cheney, Nicholas Langle-Chimal, Ollin Shrum, Trisha Koliba, Christopher Zia, Asim Smith, Julia M. PLoS One Research Article Failing to mitigate propagation of disease spread can result in dire economic consequences for agricultural networks. Pathogens like Porcine Epidemic Diarrhea virus, can quickly spread among producers. Biosecurity is designed to prevent infection transmission. When considering biosecurity investments, management must balance the cost of protection versus the consequences of contracting an infection. Thus, an examination of the decision making processes associated with investment in biosecurity is important for enhancing system wide biosecurity. Data gathered from experimental gaming simulations can provide insights into behavioral strategies and inform the development of decision support systems. We created an online digital experiment to simulate outbreak scenarios among swine production supply chains, where participants were tasked with making biosecurity investment decisions. In Experiment One, we quantified the risk associated with each participant’s decisions and delineated three dominant categories of risk attitudes: risk averse, risk tolerant, and opportunistic. Each risk class exhibited unique approaches in reaction to risk and disease information. We also tested how information uncertainty affects risk aversion, by varying the amount of visibility of the infection as well as the amount of biosecurity implemented across the system. We found evidence that more visibility in the number of infected sites increases risk averse behaviors, while more visibility in the amount of neighboring biosecurity increased risk taking behaviors. In Experiment Two, we were surprised to find no evidence for differences in behavior of livestock specialists compared to Amazon Mechanical Turk participants. Our findings provide support for using experimental gaming simulations to study how risk communication affects behavior, which can provide insights towards more effective messaging strategies. Public Library of Science 2020-03-17 /pmc/articles/PMC7077803/ /pubmed/32182247 http://dx.doi.org/10.1371/journal.pone.0228983 Text en © 2020 Clark et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Clark, Eric M. Merrill, Scott C. Trinity, Luke Bucini, Gabriela Cheney, Nicholas Langle-Chimal, Ollin Shrum, Trisha Koliba, Christopher Zia, Asim Smith, Julia M. Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
title | Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
title_full | Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
title_fullStr | Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
title_full_unstemmed | Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
title_short | Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
title_sort | using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077803/ https://www.ncbi.nlm.nih.gov/pubmed/32182247 http://dx.doi.org/10.1371/journal.pone.0228983 |
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