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Natural Hazards

, Volume 90, Issue 3, pp 1377–1406 | Cite as

The role of social capital, personal networks, and emergency responders in post-disaster recovery and resilience: a study of rural communities in Indiana

  • Arif Mohaimin Sadri
  • Satish V. Ukkusuri
  • Seungyoon Lee
  • Rosalee Clawson
  • Daniel Aldrich
  • Megan Sapp Nelson
  • Justin Seipel
  • Daniel Kelly
Original Paper

Abstract

The factors that explain the speed of recovery after disaster remain contested. While many have argued that physical infrastructure, social capital, and disaster damage influence the arc of recovery, empirical studies that test these various factors within a unified modeling framework are few. We conducted a mail survey to collect data on household recovery in four small towns in southern Indiana that were hit by deadly tornadoes in March 2012. The recovery effort is ongoing; while many of the homes, businesses, and community facilities were rebuilt in 2013, some are still under construction. We investigate how households in these communities are recovering from damage that they experienced and the role of social capital, personal networks, and assistance from emergency responders on the overall recovery experience. We used an ordered probit modeling framework to test the combined as well as relative effects of (a) damage to physical infrastructures (houses, vehicles, etc.); (b) recovery assistance from emergency responders (FEMA) as well as friends and neighbors; (c) personal network characteristics (size, network density, proximity, length of relationship); (d) social capital (civic engagement, contact with neighbors, trust); and (e) household characteristics. Results show that while households with higher levels of damage experienced slower recovery, those with recovery assistance from neighbors, stronger personal networks, and higher levels of social capital experienced faster recovery. The insights gained in this study will enable emergency managers and disaster response personnel to implement targeted strategies in facilitating post-disaster recovery and community resilience.

Keywords

Social capital Personal networks Emergency responders Resilience Post-disaster recovery Ordered probit 

Notes

Acknowledgements

This study was funded by an Andrew W. Mellon Foundation grant to Purdue University to address grand challenges through supporting interdisciplinary collaborations, especially between the liberal arts and STEM disciplines. The second and third authors’ work is partially funded by the NSF grant 1638311. The authors are grateful for this support. The authors would also like to acknowledge two students from Courtney Page of Purdue University, Indiana, and Pedro Henrique dos Reis Rezende of FUMEC University, Brazil, for their participation in the earlier part of the project. The authors are also grateful to the reviewers’ valuable comments, which improved the manuscript. However, the authors are solely responsible for the findings presented in this study.

References

  1. Adger WN (2000) Social and ecological resilience: are they related? Prog Hum Geogr 24(3):347–364CrossRefGoogle Scholar
  2. Adger WN (2010) Social capital, collective action, and adaptation to climate change. Econ Geogr 79:4Google Scholar
  3. Adger WN, Hughes TP, Folke C, Carpenter SR, Rockström J (2005) Social-ecological resilience to coastal disasters. Science 309(5737):1036–1039CrossRefGoogle Scholar
  4. Aldrich DP (2010) Fixing recovery, social capital in post-crisis resilience. J Homeland Secur 6:1–10Google Scholar
  5. Aldrich DP (2011) The externalities of strong social capital, post-tsunami recovery in Southeast India. J Civil Soc 7:81–99.  https://doi.org/10.1080/17448689 CrossRefGoogle Scholar
  6. Aldrich DP (2012a) Building resilience: Social capital in post-disaster recovery. University of Chicago Press, ChicagoCrossRefGoogle Scholar
  7. Aldrich DP (2012b) Social, not physical, infrastructure: the critical role of civil society after the 1923 Tokyo earthquake. Disasters 36(3):398–419CrossRefGoogle Scholar
  8. Aldrich DP, Crook K (2008) Strong civil society as a double-edged sword: siting trailers in post-katrina New Orleans. Polit Res Q 61(3):379–389CrossRefGoogle Scholar
  9. Aldrich DP, Sawada Y (2015) The physical and social determinants of mortality in the 3.11 tsunami. Soc Sci Med 124:66–75CrossRefGoogle Scholar
  10. Andrews AC, Clawson RA, Gramig BM, Raymond L (2013) Why do farmers adopt conservation tillage? An experimental investigation of framing effects. J Soil Water Conserv 68(6):501–511CrossRefGoogle Scholar
  11. Bailey S, Marsden PV (1999) Interpretation and interview context: examining the general social survey name generator using cognitive methods. Soc Netw 21(3):287–309CrossRefGoogle Scholar
  12. Baker EJ (1991) Hurricane evacuation behavior. Int J Mass Emerg Disasters 9(2):287–310Google Scholar
  13. Bastani S (2007) Family comes first: men’s and women’s personal networks in Tehran. Soc Netw 29:357–374CrossRefGoogle Scholar
  14. Ben-Akiva M, Lerman S (1985) Discrete choice analysis. MIT Press, CambridgeGoogle Scholar
  15. Bjørnskov, C., and Svendsen, G.T. (2003). Measuring social capital–Is there a single underlying explanation? (No. 03–5)Google Scholar
  16. Bolin R, Stanford L (1998) The northridge earthquake: community-based approaches to unmet recovery needs. Disasters 22(1):21–38CrossRefGoogle Scholar
  17. Borgatti, S.P. (2009). E-Net 0.023 [Computer program]. Harvard, MA: Analytic TechnologiesGoogle Scholar
  18. Borgatti SP, Halgin DS (2011) On network theory. Organ Sci 22(5):1168–1181CrossRefGoogle Scholar
  19. Borgatti SP, Halgin DS (2012) An introduction to personal network analysis and Tie Churn statistics using E-NET. Connections 32(1):37–48Google Scholar
  20. Borgatti SP, Jones C, Everett MG (1998) Network measures of social capital. Connections 21(2):27–36Google Scholar
  21. Brewer DD (2000) Forgetting in the recall-based elicitation of personal and social networks. Soc Netw 22(1):29–43CrossRefGoogle Scholar
  22. Burt RS (1984) Network items and the general social survey. Soc Netw 6(4):293–339CrossRefGoogle Scholar
  23. Burt RS (2000) The network structure of social capital. In: Sutton Robert, Staw Barry (eds) Research in organizational behavior greenwich. JAI Press, CT, pp 345–423Google Scholar
  24. Carrasco, J. A., Bustos, C., and Cid-Aguayo, B. (2013) Affective personal networks versus daily contacts: analyzing different name generators in an social activity-travel behaviour context. In Transport survey methods: best practice for decision making, pp. 409–426Google Scholar
  25. Chamlee-Wright E (2010) The Cultural and political economy of eecovery: social learning in a post-disaster environment. Routledge 2010:12Google Scholar
  26. Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Q 84(2):242–261CrossRefGoogle Scholar
  27. Dacy D, Kunreuther H (1969) The economics of natural disasters: implications for federal policy. The Free Press, New YorkGoogle Scholar
  28. DeJordy R, Halgin D (2008) Introduction to ego network analysis. Boston College and the Winston Center for Leadership and Ethics, Academy of Management PDW, MassachusettsGoogle Scholar
  29. Dillman DA (2007) Mail and internet surveys: the tailored design method, 2nd edn. Wiley, New YorkGoogle Scholar
  30. Dillman DA, Smyth JD, Christian LM (2014) Internet, phone, mail, and mixed-mode surveys: the tailored design method. Wiley, New YorkGoogle Scholar
  31. Dixit VV, Wilmot C, Wolshon B (2012) Modeling risk attitudes in evacuation departure choices. Trans Res Rec: J Trans Res Board 2312(2012):159–163CrossRefGoogle Scholar
  32. Duncan C, Khattak A, Council F (1999) Applying the ordered probit model to injury severity in truck-passenger car rear-end collisions, vol. 1635 (pp. 63–71). Transportation Research Board, National Research Council, Washington, DCGoogle Scholar
  33. Dynes, R. (2006). Social capital: dealing with community emergencies. Homeland Security Affairs, 2(2)Google Scholar
  34. Elliott JR, Haney TJ, Sams-Abiodun P (2010) Limits to social capital: comparing network assistance in two New Orleans neighborhoods devastated by Hurricane Katrina. Sociolog Q 51(4):624–648Google Scholar
  35. Fischer CS (1982) To dwell among friends: personal networks in town and city. University of Chicago, ChicagoGoogle Scholar
  36. Gaziano C (2005) Comparative analysis of within-household respondent selection techniques. Public Opinion Quarterly 69(1):124–157CrossRefGoogle Scholar
  37. Granovetter M (1973) The strength of weak ties. Am J Sociol 78(6):1360–1380CrossRefGoogle Scholar
  38. Greene W (1997) Econometric analysis, 3rd edn. Macmillan, New YorkGoogle Scholar
  39. Grootaert, C., Narayan, D., Jones, V. N., and Woolcock, M. (2003). Integrated questionnaire for the measurement of social capital. The World Bank Social Capital Thematic GroupGoogle Scholar
  40. Hasan S, Ukkusuri SV, Gladwin H, Murray-Tuite P (2011) A behavioral model to understand household-level hurricane evacuation decision making. J Trans Eng 137(5):341–348CrossRefGoogle Scholar
  41. Hawkins RL, Maurer K (2010) Bonding, bridging and linking: how social capital operated in New Orleans following Hurricane Katrina. Br J Soc Work 40(6):1777–1793CrossRefGoogle Scholar
  42. Haythornthwaite C (2005) Social networks and internet connectivity effects. Inf Commun Soc 8(2):125–147CrossRefGoogle Scholar
  43. Ibarra H (1993) Network centrality, power, and innovation involvement: determinants of technical and administrative roles. Acad Manag J 36:471–501CrossRefGoogle Scholar
  44. Jones EC, Faas AJ, Murphy AD, Tobin GA, Whiteford LM, McCarty C (2013) Cross-cultural and site-based influences on demographic, well-being, and social network predictors of risk perception in hazard and disaster settings in Ecuador and Mexico. Hum Nat 24(1):5–32CrossRefGoogle Scholar
  45. Kamel N, Loukaitou-Sideris A (2004) Residential assistance and recovery following the Northridge earthquake. Urban Studies 41(3):533CrossRefGoogle Scholar
  46. Kowald M, Frei A, Hackney JK, Illenberger J, Axhausen KW (2010) Collecting data on leisure travel: the link between leisure contacts and social interactions. Procedia-Soc Behav Sci 4:38–48CrossRefGoogle Scholar
  47. Krackhardt D, Stern RN (1988) Informal networks and organizational crises: an experimental simulation. Soc Psychol Q 51(2):123–140CrossRefGoogle Scholar
  48. Laumann EO (1966) Prestige and association in an urban community. Bobbs-Merrill, New YorkGoogle Scholar
  49. Laumann EO (1973) Bonds of pluralism: The form and substance of urban social networks. Wiley, New YorkGoogle Scholar
  50. Link MW, Battaglia MP, Frankel MR, Osborn L, Mokdad AH (2008) A comparison of address-based sampling (ABS) versus random-digit dialing (RDD) for general population surveys. Public Opin Q 72(1):6–27CrossRefGoogle Scholar
  51. Lozares, C., Verd, J. M., Cruz, I., and Barranco, O. (2013). Homophily and heterophily in personal networks. From mutual acquaintance to relationship intensity. Quality and Quantity, 1–14Google Scholar
  52. Marin A (2004) Are respondents more likely to list alters with certain characteristics? Implications for name generator data. Soc Netw 26(4):289–307CrossRefGoogle Scholar
  53. Marin A, Hampton KN (2007) “Simplifying the personal network name generator alternatives to traditional multiple and single name generators. Field Methods 19(2):163–193CrossRefGoogle Scholar
  54. Mathbor GM (2007) Enhancement of community preparedness for natural disasters the role of social work in building social capital for sustainable disaster relief and management. Int Soc Work 50(3):357–369CrossRefGoogle Scholar
  55. McKelvey W, Zavoina T (1975) A statistical model for analysis of ordinal level dependent variables. J Math Sociol 4(1):103–120CrossRefGoogle Scholar
  56. McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Ann Rev Sociol 27:415–444CrossRefGoogle Scholar
  57. Monge P, Contractor N (2003) Theories of communication networks. Oxford University Press, OxfordGoogle Scholar
  58. Murphy BL (2007) Locating social capital in resilient community-level emergency management. Nat Hazards 41(2):297–315CrossRefGoogle Scholar
  59. Murray-Tuite PM, Mahmassani HS (2004) Methodology for Determining Vulnerable Links in a Transportation Network. Trans Res Rec: J Trans Res Board 1882(1):88–96CrossRefGoogle Scholar
  60. Nakagawa Y, Shaw R (2004) Social capital: a missing link to disaster recovery. Int J Mass Emerg Disasters 22(1):5–34Google Scholar
  61. Natioanal Ocean Service website, 2016. What is resilience? Retrieved May 20, 2016 from <http://oceanservice.noaa.gov/facts/resilience.html>
  62. National Research Council (2012) Disaster resilience: A national imperative. The National Academies Press, Washington, DCGoogle Scholar
  63. NOAA National Centers for Environmental Information (2013). State of the climate: Tornadoes for annual 2012. Retrieved on March 28, 2017 from http://www.ncdc.noaa.gov/sotc/tornadoes/201213
  64. Norris FH, Stevens SP, Pfefferbaum B, Wyche KF, Pfefferbaum RL (2008) Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. Am J Commun Psychol 41(1–2):127–150CrossRefGoogle Scholar
  65. Park N, Lee S, Kim JH (2012) Individuals’ personal network characteristics and patterns of Facebook use: a social network approach. Comput Hum Behav 28(5):1700–1707CrossRefGoogle Scholar
  66. Peacock, W. G., Grover, H., Mayunga, J., Van Zandt, S., Brody, S. D., Kim, H. J., & Center, R. (2011). The status and trends of population social vulnerabilities along the Texas Coast with special attention to the Coastal Management Zone and Hurricane Ike: The Coastal Planning Atlas and Social Vulnerability Mapping Tools. Hazard Reduction & Recovery Center, 1–56Google Scholar
  67. Putnam RD (1995) Bowling alone: America’s declining social capital. J Democr 6(1):65–78CrossRefGoogle Scholar
  68. Putnam, R. D. (2001). Bowling alone: the collapse and revival of American community. Simon and SchusterGoogle Scholar
  69. Quarantelli, E. L., & Dynes, R. R. (1977). Response to social crisis and disaster. Annual review of sociology, 23–49Google Scholar
  70. Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2013a) How to evacuate: model for understanding the routing strategies during hurricane evacuation. J Trans Eng 140(1):61–69CrossRefGoogle Scholar
  71. Sadri AM, Ukkusuri SV, Murray-Tuite P (2013b) A random parameter ordered probit model to understand the mobilization time during hurricane evacuation. Trans Res Part C: Emerg Technol 32:21–30CrossRefGoogle Scholar
  72. Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2014) Analysis of hurricane evacuee mode choice behavior. Trans Res Part C: Emerg Technol 48:37–46CrossRefGoogle Scholar
  73. Sadri AM, Lee S, Ukkusuri SV (2015a) Modeling social network influence on joint trip frequency for regular activity travel decisions. Trans Res Rec: J Trans Res Board 2495:83–93CrossRefGoogle Scholar
  74. Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2015b) Hurricane evacuation route choice of major bridges in Miami Beach, Florida. Trans Res Rec: J Trans Res Board 2532:164–173CrossRefGoogle Scholar
  75. Sadri AM, Ukkusuri SV, Gladwin H (2017a) The role of social networks and information sources on hurricane evacuation decision-making. Nat Hazards Rev 18(3):04017005CrossRefGoogle Scholar
  76. Sadri, A. M., Ukkusuri, S. V. and Gladwin, H. (2017b). Modeling joint evacuation decisions in social networks: The case of Hurricane Sandy. J Choice Model (in press)Google Scholar
  77. Sadri, A. M., Hasan, S., Ukkusuri, S. V. and Cebrian, M. (2017c). Crisis Communication Patterns in Social Media during Hurricane Sandy. arXiv preprint arXiv:1710.01887
  78. Sadri, A. M., Hasan, S., Ukkusuri, S.V. and Cebrian, M. (2017d). Understanding Information Spreading in Social Media during Hurricane Sandy: User Activity and Network Properties. arXiv preprint arXiv:1706.03019
  79. Shaw R, Goda K (2004) From disaster to sustainable civil society: the Kobe experience. Disasters 28(1):16–40CrossRefGoogle Scholar
  80. Storr VH, Haeffele-Balch S (2012) Post-disaster community recovery in heterogeneous, loosely connected communities. Rev Soc Econ 70(3):295–314CrossRefGoogle Scholar
  81. Ukkusuri SV, Yushimito WF (2008) Location routing approach for the humanitarian prepositioning problem. Trans Res Rec: J Trans Res Board 2089(1):18–25CrossRefGoogle Scholar
  82. Ukkusuri SV, Mathew TV, Waller ST (2007) Robust networks design model using multi objective evolutionary algorithms. Comput Aided Civil Infrastruct Eng 22(1):9–21CrossRefGoogle Scholar
  83. Ukkusuri S, Zhan X, Sadri A, Ye Q (2014) Use of social media data to explore crisis informatics: study of 2013 Oklahoma Tornado. Trans Res Rec: J Trans Res Board 2459:110–118CrossRefGoogle Scholar
  84. Van Zandt S, Peacock WG, Henry DW, Grover H, Highfield WE, Brody SD (2012) Mapping social vulnerability to enhance housing and neighborhood resilience. Housing Policy Debate 22(1):29–55CrossRefGoogle Scholar
  85. Wachtendorf, T., and Kendra, J. M. (2004). Considering convergence, coordination, and social capital in disasters. Disaster Research Center, University of Delaware. Preliminary Paper #342a. Accessed May 19, 2016 from < http://udspace.udel.edu/handle/19716/737>
  86. Washington S, Karlaftis M, Mannering F (2011) Statistical and econometric methods for transportation data analysis, 2nd edn. CRC Press, Boca RatonGoogle Scholar
  87. Wasserman S, Faust K (1994) “Social network analysis: Methods and applications. Cambridge University Press, New YorkCrossRefGoogle Scholar
  88. Wellman B (1979) The community question: the intimate networks of East Yorkers. Am J Sociol 84:1201–1231CrossRefGoogle Scholar
  89. Wellman B (1999) Networks in the global village. Westview Press, Boulder, p 1999Google Scholar
  90. Yamamura E (2010) Effects of interactions among social capital, income and learning from experiences of natural disasters: a case study from Japan. Reg Stud 44(8):1019–1032CrossRefGoogle Scholar
  91. Ye Q, Ukkusuri SV (2015) Resilience as an objective in the optimal reconstruction sequence for transportation networks. J Trans Saf Secur 7(1):91–105Google Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • Arif Mohaimin Sadri
    • 1
  • Satish V. Ukkusuri
    • 2
  • Seungyoon Lee
    • 3
  • Rosalee Clawson
    • 4
  • Daniel Aldrich
    • 5
  • Megan Sapp Nelson
    • 6
  • Justin Seipel
    • 7
  • Daniel Kelly
    • 8
  1. 1.Department of Civil and Environmental EngineeringRose-Hulman Institute of TechnologyTerre HauteUSA
  2. 2.Lyles School of Civil EngineeringPurdue UniversityWest LafayetteUSA
  3. 3.Brian Lamb School of CommunicationPurdue UniversityWest LafayetteUSA
  4. 4.Department of Political SciencePurdue UniversityWest LafayetteUSA
  5. 5.Department of Political ScienceNortheastern UniversityBostonUSA
  6. 6.Library SciencesPurdue UniversityWest LafayetteUSA
  7. 7.Purdue Polytechnic InstitutePurdue UniversityWest LafayetteUSA
  8. 8.Department of PhilosophyPurdue UniversityWest LafayetteUSA

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