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Agent‐Based Models as an Integrating Boundary Object for Interdisciplinary Research

dc.contributor.authorReilly, Allison C.
dc.contributor.authorDillon, Robin L.
dc.contributor.authorGuikema, Seth D.
dc.date.accessioned2021-08-03T18:15:33Z
dc.date.available2022-08-03 14:15:32en
dc.date.available2021-08-03T18:15:33Z
dc.date.issued2021-07
dc.identifier.citationReilly, Allison C.; Dillon, Robin L.; Guikema, Seth D. (2021). "Agent‐Based Models as an Integrating Boundary Object for Interdisciplinary Research." Risk Analysis 41(7): 1087-1092.
dc.identifier.issn0272-4332
dc.identifier.issn1539-6924
dc.identifier.urihttps://hdl.handle.net/2027.42/168480
dc.description.abstractMany of the most complicated and pressing problems in hazards research require the integration of numerous disciplines. The lack of a common knowledge base, however, often prohibits clear communication and interaction among interdisciplinary researchers, sometimes leading to unsuccessful outcomes. Drawing on experience with several projects and collective expertise that spans multiple disciplines, the authors argue that a promising way to enhance participation and enable communication is to have a common model, or boundary object, that can integrate knowledge from different disciplines. The result is that researchers from different disciplines who use different research methods and approaches can work together toward a shared goal. This article offers four requirements for boundary objects that may enhance hazards research. Based on these requirements, agent‐based models have the necessary characteristics to be a boundary object. The article concludes by examining both the value of and the challenges from using agent‐based models as the boundary object in interdisciplinary projects.
dc.publisherUniversity of South Carolina
dc.publisherWiley Periodicals, Inc.
dc.subject.otherinterdisciplinary research
dc.subject.otherAgent‐based modeling
dc.subject.otherboundary objects
dc.subject.otherhazards
dc.titleAgent‐Based Models as an Integrating Boundary Object for Interdisciplinary Research
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBusiness (General)
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/168480/1/risa13134.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/168480/2/risa13134_am.pdf
dc.identifier.doi10.1111/risa.13134
dc.identifier.sourceRisk Analysis
dc.identifier.citedreferenceBonabeau, E. ( 2002 ). Agent‐based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99 ( suppl 3 ), 7280 – 7287.
dc.identifier.citedreferenceAn, L. ( 2012 ). Modeling human decisions in coupled human and natural systems: Review of agent‐based models. Ecological Modelling, 229, 25 – 36.
dc.identifier.citedreferenceAxelrod, R. ( 2006 ). Agent‐based modeling as a bridge between disciplines. Handbook of Computational Economics, 2, 1565 – 1584.
dc.identifier.citedreferenceTierney, K. ( 2005 ). Effective strategies for hazard assessment and loss reduction: The importance of multidisciplinary and interdisciplinary approaches. Boulder, CO: Natural Hazards Research and Applications Information Center, Institute of Behavioral Science, University of Colorado. Report online, last accessed July 25, 2017: Retrieved from https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.7480
dc.identifier.citedreferenceThiele, J. C., Kurth, W., & Grimm, V. ( 2014 ). Facilitating parameter estimation and sensitivity analysis of agent‐based models: A cookbook using NetLogo and R. Journal of Artificial Societies and Social Simulation, 17 ( 3 ), 11.
dc.identifier.citedreferenceStar, S. L., & Griesemer, J. R. ( 1989 ). Institutional ecology, “translations” and boundary objects: Amateurs and professionals in Berkeley’s Museum of Vertebrate Zoology, 1907–39. Social Studies of Science, 19 ( 3 ), 387 – 420.
dc.identifier.citedreferenceRosenkoetter, M. M., Covan, E. K., Cobb, B. K., Bunting, S., & Weinrich, M. ( 2007 ). Perceptions of older adults regarding evacuation in the event of a natural disaster. Public Health Nursing, 24 ( 2 ), 160 – 168.
dc.identifier.citedreferenceReilly, A. C., Guikema, S. D., Zhu, L., & Igusa, T. ( 2017 ). Evolution of vulnerability of communities facing repeated hazards. PLoS One, 12 ( 9 ), e0182719.
dc.identifier.citedreferenceRafols, I., Leydesdorff, L., O’Hare, A., Nightingale, P., & Stirling, A. ( 2012 ). How journal rankings can suppress interdisciplinary research: A comparison between innovation studies and business & management. Research Policy, 41 ( 7 ), 1262 – 1282.
dc.identifier.citedreferenceNateghi, R., Guikema, S. D., & Quiring, S. M. ( 2011 ). Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes. Risk Analysis, 31 ( 12 ), 1897 – 1906.
dc.identifier.citedreferenceMacal, C. M., & North, M. J. ( 2010 ). Tutorial on agent‐based modelling and simulation. Journal of Simulation, 4 ( 3 ), 151 – 162.
dc.identifier.citedreferenceLeigh Star, S. ( 2010 ). This is not a boundary object: Reflections on the origin of a concept. Science, Technology, & Human Values, 35 ( 5 ), 601 – 617.
dc.identifier.citedreferenceLachman, R., Tatsuoka, M., & Bonk, W. J. ( 1961 ). Human behavior during the tsunami of May 1960. Science, 133 ( 3462 ), 1405 – 1409.
dc.identifier.citedreferenceLach, D. ( 2014 ). Challenges of interdisciplinary research: Reconciling qualitative and quantitative methods for understanding human‐landscape systems. Environmental Management, 53 ( 1 ), 88 – 93.
dc.identifier.citedreferenceFitzpatrick, C., & Mileti, D. S. ( 1991 ). Motivating public evacuation. International Journal of Mass Emergencies and Disasters, 9 ( 2 ), 137 – 152.
dc.identifier.citedreferenceWindrum, P., Fagiolo, G., & Moneta, A. ( 2007 ). Empirical validation of agent‐based models: Alternatives and prospects. Journal of Artificial Societies and Social Simulation, 10 ( 2 ), 8.
dc.identifier.citedreferenceEpstein, J. M., & Axtell, R. ( 1996 ). Growing artificial societies: Social science from the bottom up. Washington, DC: Brookings Institution Press.
dc.identifier.citedreferenceDillon, R. L., Tinsley, C. H., & Burns, W. J. ( 2014 ). Near‐misses and future disaster preparedness. Risk Analysis, 34 ( 10 ), 1907 – 1922.
dc.identifier.citedreferenceWenger, E. ( 1998 ). Communities of practice: Learning, meaning, and identity. Cambridge, MA: Cambridge University Press.
dc.identifier.citedreferenceCutter, S. L., Mitchell, J. T., & Scott, M. S. ( 1997 ). Handbook for conducting a GIS‐based hazards assessment at the county level. Columbia, SC: University of South Carolina.
dc.identifier.citedreferenceCampbell, L. M. ( 2005 ). Overcoming obstacles to interdisciplinary research. Conservation Biology, 19 ( 2 ), 574 – 577.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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