Estimating hurricane evacuation destination and accommodation type selection with perceived certainty variables

Emmanuel Adjei1, Pamela Murray-Tuite1, Yue Ge2, Satish Ukkusuri3, Seungyoon Lee4
1Glenn Department of Civil Engineering, Clemson University, 109 Lowry Hall, Clemson, SC, 29634, USA
2School of Public Administration, University of Central Florida, 528 W. Livingston St., DPAC 448J, Orlando, FL 32816, USA
3Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, USA
4Brian Lamb School of Communication, Purdue University, 100 North University Street, West Lafayette, IN 47909, USA

Tài liệu tham khảo

Andersen, L., Fricker, R.D., 2015. Raking: An important and often overlooked survey analysis tool. Phalanx (September, 2015). <http://faculty.nps.edu/rdfricke/docs/RakingArticleV2.2.pdf> (Accessed: December 3, 2019). Arkes, 2013, The Consequences of the Hindsight Bias in Medical Decision Making, Curr. Dir. Psychol. Sci., 22, 356, 10.1177/0963721413489988 Baker, 1991, Hurricane evacuation behavior, Int. J. Mass Emerg. Disasters, 9, 287, 10.1177/028072709100900210 Baker, 2000, Hurricane evacuation in the United States, 306 Barrett, 2000, Developing a dynamic traffic management modeling framework for hurricane evacuation, Transp. Res. Rec., 1733, 115, 10.3141/1733-15 Benjamini, 1995, Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing, J. R. Stat. Soc. Ser. B, 57, 289 Bian, 2019, Modeling household-level hurricane evacuation mode and destination type choice using data from multiple post-storm behavioral surveys, Transp. Res. Part C Emerg. Technol., 99, 130, 10.1016/j.trc.2019.01.009 Brezina, 2008, What went wrong in New Orleans? An examination of the welfare dependency explanation, Soc. Probl., 55, 23, 10.1525/sp.2008.55.1.23 Burnside, 2007, The impact of information and risk perception on the Hurricane evacuation decision-making of greater New Orleans residents, Sociol. Spectr., 27, 727, 10.1080/02732170701534226 Cahyanto, 2016, Predicting information seeking regarding hurricane evacuation in the destination, Tour. Manag., 52, 264, 10.1016/j.tourman.2015.06.014 Chen, B., 2005. Modeling destination choice in hurricane evacuation with an intervening opportunity model. Master’s Thesis, Louisiana State University and Agricultural and Mechanical College. < https://digitalcommons.lsu.edu/gradschool_theses/2595/> (Accessed: February 24, 2020). Cheng, G., Wilmot, C.G., Baker, E.J., 2008. A destination choice model for hurricane evacuation. 87th Annual Meeting of the Transportation Research Board, Washington, DC. Cohen, M. P., 2008. Raking. In: Lavrakas, P. J. (Ed.), Encyclopedia of Survey Research Methods, SAGE Publications Ltd., pp. 672-673. Cohen, 1999, The problem of units and the circumstance for POMP, Multivariate Behav. Res., 34, 315, 10.1207/S15327906MBR3403_2 Collins, 2018, The effects of social connections on evacuation decision making during Hurricane Irma, Weather Clim. Soc., 10, 459, 10.1175/WCAS-D-17-0119.1 Curtin, 2000, The effects of response rate changes on the index of consumer sentiment, Public Opin. Q., 64, 413, 10.1086/318638 Czajkowski, 2011, Is It Time to Go Yet? Understanding Household Hurricane Evacuation Decisions from a Dynamic Perspective, Nat. Hazards Rev., 12, 72, 10.1061/(ASCE)NH.1527-6996.0000037 Damera, 2019, Estimating the sequencing of evacuation destination and accommodation type in hurricanes, J. Homel. Secur. Emerg. Manag., 17, 1 Dash, 2007, Evacuation decision making and behavioral responses: Individual and household, Nat. Hazards Rev., 8, 69, 10.1061/(ASCE)1527-6988(2007)8:3(69) Dash, 2000, Return delays and evacuation order compliance: The case of Hurricane Georges and the Florida Keys, Environ. Hazards, 2, 119 Dillman, 2014 Dow, 2002, Emerging hurricane evacuation issues: Hurricane Floyd and South Carolina, Nat. Hazards Rev., 3, 12, 10.1061/(ASCE)1527-6988(2002)3:1(12) Elliott, 2006, Race, class, and Hurricane Katrina: Social differences in human responses to disaster, Soc. Sci. Res., 35, 295, 10.1016/j.ssresearch.2006.02.003 Florida Division of Emergency Management, 2017. Evacuation orders - Florida disaster. <https://www.floridadisaster.org/evacuation-orders/> (Accessed: August 15, 2020). Glickman, 2014, False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies, J. Clin. Epidemiol., 67, 850, 10.1016/j.jclinepi.2014.03.012 Greene, 2002 Hasan, 2013, A random-parameter hazard-based model to understand household evacuation timing behavior, Transp. Res. Part C Emerg. Technol., 27, 108, 10.1016/j.trc.2011.06.005 Hasan, 2011, Behavioral model to understand household-level hurricane evacuation decision making, J. Transp. Eng., 137, 341, 10.1061/(ASCE)TE.1943-5436.0000223 Horney, 2010, Factors associated with evacuation from Hurricane Isabel in North Carolina, Int. J. Mass Emerg. Disasters, 28, 33, 10.1177/028072701002800102 Huang, 2012, Household evacuation decision making in response to hurricane Ike, Nat. Hazards Rev., 13, 283, 10.1061/(ASCE)NH.1527-6996.0000074 Huang, 2016, Who Leaves and Who Stays? A Review and Statistical Meta-Analysis of Hurricane Evacuation Studies, Environ. Behav., 48, 991, 10.1177/0013916515578485 Kang, 2007, Hurricane evacuation expectations and actual behavior in Hurricane Lili, J. Appl. Soc. Psychol., 37, 887, 10.1111/j.1559-1816.2007.00191.x Lim, 2016, A household-level flood evacuation decision model in Quezon City, Philippines, Nat. Hazards, 80, 1539, 10.1007/s11069-015-2038-6 Lin, 2010, Risk assessment of hurricane storm surge for New York City, J. Geophys. Res. Atmos., 115, 1, 10.1029/2009JD013630 Lindell, 2005, Household decision making and evacuation in response to Hurricane Lili, Nat. Hazards Rev., 6, 171, 10.1061/(ASCE)1527-6988(2005)6:4(171) Lindell, 2011, The logistics of household hurricane evacuation, Nat. Hazards, 58, 1093, 10.1007/s11069-011-9715-x Lindell, 2019 Lindell, 2012, The protective action decision model: Theoretical modifications and additional evidence, Risk Anal., 32, 616, 10.1111/j.1539-6924.2011.01647.x Lindell, 2007, Critical behavioral assumptions in evacuation time estimate analysis for private vehicles: Examples from hurricane research and planning, J. Urban Plan. Dev., 133, 18, 10.1061/(ASCE)0733-9488(2007)133:1(18) Lindell, 2018, Communicating imminent risk, 449 Lindell, 2020, Improving Hazard Map Comprehension for Protective Action Decision Making, Front. Comput. Sci., 2, 1, 10.3389/fcomp.2020.00027 Lindell, 2016, Perceptions and expected immediate reactions to tornado warning polygons, Nat. Hazards, 80, 683, 10.1007/s11069-015-1990-5 Litt, 2008, Getting out or staying put: An African American women’s network in evacuation from Katrina, Natl. Women Stud. Assoc. J., 20, 32 Liu, 2012, Analysis of child pick-up during daily routines and for daytime no-notice evacuations, Transp. Res. Part A Policy Pract., 46, 48, 10.1016/j.tra.2011.09.003 Louie, 2007, Tackling the Monday-morning quarterback: Applications of hindsight bias in decision-making settings, Soc. Cogn., 25, 32, 10.1521/soco.2007.25.1.32 Maghelal, 2017, Evacuating together or separately: Factors influencing split evacuations prior to Hurricane Rita, Nat. Hazards Rev., 18, 04016008, 10.1061/(ASCE)NH.1527-6996.0000226 McFadden, D., 1977. Quantitative methods for analyzing travel behavior of individuals: Some recent developments. Cowles Foundation Discussion Paper No. 474. <https://cowles.yale.edu/sites/default/files/files/pub/d04/d0474.pdf> (Accessed: March 24, 2020). Mercer, A., Lau, A., Kennedy, C., 2018. For weighting online opt-in samples: What matters most? Pew Research Center. <https://www.pewresearch.org/methods/2018/01/26/for-weighting-online-opt-in-samples-what-matters-most/> (Accessed: December 15, 2019). Mesa-Arango, R., Hasan, S., Ukkusuri, S.V., Murray-Tuite, P., 2013. Household-level model for hurricane evacuation destination type choice using Hurricane Ivan Data. Nat. Hazards Rev. 14(1), 11–20. Meyer, 2014, The dynamics of hurricane risk perception: Real-time evidence from the 2012 Atlantic hurricane season, Bull. Am. Meteorol. Soc., 95, 1389, 10.1175/BAMS-D-12-00218.1 Mileti, 1992, Toward an explanation of mass care shelter use in evacuations, Int. J. Mass Emerg. Disasters, 10, 25, 10.1177/028072709201000102 Mileti, D., Sorensen, J., Bogard, W., 1985. Evacuation decision-making: Process and uncertainty. <https://inis.iaea.org/collection/NCLCollectionStore/_Public/17/025/17025870.pdf> (Accessed: January 14, 2020). Morrow, B., Gladwin, H., 2005. Hurricane Ivan behavioral study final report. <https://www.researchgate.net/publication/280154979_Hurricane_Ivan_Behavioral_Study_Final_Report> (Accessed: November 15, 2019). Murray-Tuite, 2012, Changes in evacuation decisions between Hurricanes Ivan and Katrina, Transp. Res. Rec., 15, 98, 10.3141/2312-10 National Oceanic and Atmospheric Administration (NOAA), 2017. Tropical cyclone report on Hurricane Matthew. <https://www.nhc.noaa.gov/data/tcr/AL142016_Matthew.pdf> (Accessed: February 24, 2020). National Oceanic and Atmospheric Administration (NOAA), 2019. Weather disasters and cost. <https://coast.noaa.gov/states/fast-facts/weather-disasters.html> (Accessed: December, 14, 2019). National Oceanic and Atmospheric Administration (NOAA), 2020. Billion-dollar weather and climate disasters. <https://www.ncdc.noaa.gov/billions/events/US/1980-2019> (Accessed: January 4, 2020). National Weather Service, 2017. Probabilistic tropical storm surge 2.6. <http://slosh.nws.noaa.gov/psurge2.0/index.php?S=Matthew2016&Adv=29&Ty=e10&Z=m1&D=agl&Ti=cum&Msg=17&Help=about> (Accessed: August 15, 2020). Perry, 2007 Perry, 1981 Prater, C. S., Wenger, D., Grady, K., 2000. Hurricane Bret post storm assessment: A review of the utilization of hurricane evacuation studies and information dissemination <https://hrrc.arch.tamu.edu/_common/documents/00-05R%20Prater,%20Wenger%20%20 arch.tamu.edu/_common/documents. Quarantelli, E.L., 1980. Evacuation behavior and problems: Findings and implications from the research literature. <http://udspace.udel.edu/handle/19716/1283> (Accessed: March 18, 2020). Sadri, 2017, The role of social networks and information sources on hurricane evacuation decision making, Nat. Hazards Rev., 18, 10.1061/(ASCE)NH.1527-6996.0000244 Sherman-Morris, 2015, Measuring the effectiveness of the graphical communication of hurricane storm surge threat, Weather Clim. Soc., 7, 69, 10.1175/WCAS-D-13-00073.1 Sime, 1993, Crowd psychology and engineering: Designing for people or ball bearings?, 119 Smith, K., 1999. Estimating the costs of hurricane evacuation: A study of evacuation behavior and risk interpretation using combined revealed and stated preference household data. <https://www.cs.rice.edu/~devika/evac/papers/kevinsmith.pdf> (Accessed: January 15, 2020). Smith, 2009, Fleeing the storm(s): An examination of evacuation behavior during Florida’s 2004 hurricane season, Demography, 46, 127, 10.1353/dem.0.0048 Stewart, S.R., 2017. Hurricane Matthew. National Hurricane Center Tropical Cyclone Report, < https://www.nhc.noaa.gov/data/tcr/AL142016_Matthew.pdf> (Accessed: September 26, 2020). Steyerberg, 2004, Validation and updating of predictive logistic regression models: A study on sample size and shrinkage, Stat. Med., 23, 2567, 10.1002/sim.1844 Taylor, 2009, Reading Hurricane Katrina: Information sources and decision-making in response to a natural disaster, Soc. Epistemol., 23, 361, 10.1080/02691720903374034 The Weather Channel, 2016. Hurricane Matthew evacuation orders for Florida, Georgia, Carolinas <https://weather.com/safety/hurricane/news/hurricane-matthew-evacuation-orders-by-state> (Accessed: October train6, 2020). Thompson, 2017, Evacuation from Natural Disasters: A Systematic Review of the Literature, Risk Anal., 37, 812, 10.1111/risa.12654 Tormala, 2018, Attitude certainty: Antecedents, consequences, and new directions, Consum. Psychol. Rev., 1, 72, 10.1002/arcp.1004 Train, 2009 Ukkusuri, 2017, A-RESCUE: An agent based regional evacuation simulator coupled with user enriched behavior, Netw. Spat. Econ., 17, 197, 10.1007/s11067-016-9323-0 United States Army Corps of Engineers (USACE), 2000. Southeast United States Hurricane Evacuation Traffic Study, Tallahassee, Florida. < https://www.hsdl.org/?view&did=779186> (Accessed: April 15, 2020). United States Army Corps of Engineers (USACE), 2017. Behavioral analysis for Southeast Louisiana hurricane events. < https://www.sdmi.lsu.edu/sdmi/wpcontent/uploads/2017/06/Behavioral.AnalysisForSELAHurricaneEvents.pdf> (Accessed: October 5, 2020). United States Census Bureau, 2017. 2016 urban and rural areas from American factfinder. <http://census.gov/faces/nav/jsf/pages/searchresults.rhtml?refresh=t> (Accessed: August 15, 2020). United States Census Bureau, 2018. 2016 American community demographic and housing estimates of Jacksonville City, FL. <https://www.census.gov/acs/www/data/data-Tables-and-tools/data-profiles/2016/> (Accessed: March 28, 2020). Van Willigen, 2002, Riding out the storm: The experiences of the physically disabled during Hurricanes Bonnie, Dennis, and Floyd, Nat. Hazards Rev., 3, 98, 10.1061/(ASCE)1527-6988(2002)3:3(98) Walmsley, A.L.E., Brown, M.C., 2017. What is power? Statistics Teacher. https://www.statisticsteacher.org/2017/09/15/what-is-power/. Accessed: June 11, 2021. Washington, S., Karlaftis, M.G., Mannering, F.L., 2011. Statistical and econometric methods for transportation data analysis. 2nd Ed., CRC Press, Boca Raton, FL. Weber, L., Peek, L., 2012. Displaced: Life in the Katrina Diaspora. University of Texas Press, Austin, TX. Whitehead, 2003, One million dollars per mile? The opportunity costs of hurricane evacuation, Ocean Coast. Manag., 46, 1069, 10.1016/j.ocecoaman.2003.11.001 Whitehead, 2000, Heading for higher ground: Factors affecting real and hypothetical hurricane evacuation behavior, Environ. Hazards, 2, 133, 10.1016/S1464-2867(01)00013-4 Whitehead, 2000, Hurricane evacuation behavior: A preliminary comparison of Bonnie, Dennis, and Floyd, 89 Wizemann, T., Reeve, M., Altevogt, B., 2014. Preparedness, Response, and Recovery Considerations for Children and Families, https://doi.org/10.17226/18550. Wong, S., Shaheen, S., Walker, J., 2018. Understanding evacuee behavior: A case study of hurricane Irma. https://doi.org/10.7922/G2FJ2F00. (Accessed: September 12, 2020). Wood, 2018, Milling and Public Warnings, Environ. Behav., 50, 535, 10.1177/0013916517709561 Wu, 2013, Logistics of hurricane evacuation in Hurricane Ike, 127 Wu, 2012, Logistics of hurricane evacuation in Hurricanes Katrina and Rita, Transp. Res. Part F Traffic Psychol. Behav., 15, 445, 10.1016/j.trf.2012.03.005 Wu, 2015, Process tracing analysis of hurricane information displays, Risk Anal., 35, 2202, 10.1111/risa.12423 Yang, 2016, Modeling evacuation behavior under hurricane conditions, Transp. Res. Rec., 2599, 63, 10.3141/2599-08 Yin, 2014, Statistical analysis of the number of household vehicles used for Hurricane Ivan evacuation, J. Transp. Eng., 140, 1, 10.1061/(ASCE)TE.1943-5436.0000713 Yin, 2014, An agent-based modeling system for travel demand simulation for hurricane evacuation, Transp. Res. Part C Emerg. Technol., 42, 44, 10.1016/j.trc.2014.02.015 Zhu, 2018, Hurricane evacuation modeling using behavior models and scenario-driven agent-based simulations, Procedia Comput. Sci., 130, 836, 10.1016/j.procs.2018.04.074