IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v84y2016i2d10.1007_s11069-016-2477-8.html
   My bibliography  Save this article

Empirical analysis of volunteer convergence following the 2011 tornado disaster in Tuscaloosa, Alabama

Author

Listed:
  • Emmett J. Lodree

    (University of Alabama)

  • Lauren B. Davis

    (North Carolina A&T State University)

Abstract

Volunteer convergence refers to the mass movement of volunteers toward affected areas following disaster events. Emergency management professionals sometimes refer to volunteer convergence as “the disaster within the disaster,” which is an indicator of the tremendous challenge that managing the post-disaster influx of spontaneous volunteers presents. In order to develop effective strategies for managing volunteer convergence, it is imperative that emergency managers and coordinators understand the nature of convergence from a quantitative perspective. This paper presents a case study of volunteer convergence following the April 2011 tornado disaster in Tuscaloosa, Alabama, and represents the first academic study to rigorously analyze volunteer convergence data. Specifically, we characterize selected stochastic variables that are relevant to volunteer task assignment within the context of a disaster relief warehouse environment using data collected during tornado relief efforts in May 2011. Time series analysis and a hierarchical clustering method based on the Kruskal–Wallis test revealed both non-stationarity and non-homogeneity in the data with respect to time of day, day of the week, and number of weeks past the disaster event. We also discuss the implications of our findings with respect to modeling relief center convergence as a queuing system.

Suggested Citation

  • Emmett J. Lodree & Lauren B. Davis, 2016. "Empirical analysis of volunteer convergence following the 2011 tornado disaster in Tuscaloosa, Alabama," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 1109-1135, November.
  • Handle: RePEc:spr:nathaz:v:84:y:2016:i:2:d:10.1007_s11069-016-2477-8
    DOI: 10.1007/s11069-016-2477-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-016-2477-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-016-2477-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J.A. Goddard & M. Tavakoli, 1998. "Referral rates and waiting lists: some empirical evidence," Health Economics, John Wiley & Sons, Ltd., vol. 7(6), pages 545-549, September.
    2. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    3. Dekimpe, Marnik G. & Degraeve, Zeger, 1997. "The attrition of volunteers," European Journal of Operational Research, Elsevier, vol. 98(1), pages 37-51, April.
    4. Willems, Jurgen & Walk, Marlene, 2013. "Assigning volunteer tasks: The relation between task preferences and functional motives of youth volunteers," Children and Youth Services Review, Elsevier, vol. 35(6), pages 1030-1040.
    5. Hong Chen & J. Michael Harrison & Avi Mandelbaum & Ann Van Ackere & Lawrence M. Wein, 1988. "Empirical Evaluation of a Queueing Network Model for Semiconductor Wafer Fabrication," Operations Research, INFORMS, vol. 36(2), pages 202-215, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria E. Mayorga & Emmett J. Lodree & Justin Wolczynski, 2017. "The optimal assignment of spontaneous volunteers," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1106-1116, September.
    2. Abualkhair, Hussain & Lodree, Emmett J. & Davis, Lauren B., 2020. "Managing volunteer convergence at disaster relief centers," International Journal of Production Economics, Elsevier, vol. 220(C).
    3. Gloria Urrea & Eunae Yoo, 2023. "The role of volunteer experience on performance on online volunteering platforms," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 416-433, February.
    4. Sperling, Martina & Schryen, Guido, 2022. "Decision support for disaster relief: Coordinating spontaneous volunteers," European Journal of Operational Research, Elsevier, vol. 299(2), pages 690-705.
    5. Gabriel Zayas‐Cabán & Emmett J. Lodree & David L. Kaufman, 2020. "Optimal Control of Parallel Queues for Managing Volunteer Convergence," Production and Operations Management, Production and Operations Management Society, vol. 29(10), pages 2268-2288, October.
    6. Paret, Kyle E. & Mayorga, Maria E. & Lodree, Emmett J., 2021. "Assigning spontaneous volunteers to relief efforts under uncertainty in task demand and volunteer availability," Omega, Elsevier, vol. 99(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Claudia Quinteros-Cartaya & Guillermo Solorio-Magaña & Francisco Javier Núñez-Cornú & Felipe de Jesús Escalona-Alcázar & Diana Núñez, 2023. "Microearthquakes in the Guadalajara Metropolitan Zone, Mexico: evidence from buried active faults in Tesistán Valley, Zapopan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 2797-2818, April.
    2. Katarzyna Hampel & Paulina Ucieklak-Jez & Agnieszka Bem, 2021. "Health System Responsiveness in the Light of the Euro Health Consumer Index," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 659-667.
    3. Kim, Junyung & Shah, Asad Ullah Amin & Kang, Hyun Gook, 2020. "Dynamic risk assessment with bayesian network and clustering analysis," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    4. Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
    5. Roberts, Leigh, 2014. "Consistent estimation of breakpoints in time series, with application to wavelet analysis of Citigroup returns," Working Paper Series 18815, Victoria University of Wellington, School of Economics and Finance.
    6. David G Mets & Michael S Brainard, 2018. "An automated approach to the quantitation of vocalizations and vocal learning in the songbird," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-29, August.
    7. Kuroda, M. & Kawada, A., 1995. "Adaptive input control for job-shop type production systems with varying demands using inverse queueing network analysis," International Journal of Production Economics, Elsevier, vol. 41(1-3), pages 217-225, October.
    8. Michael Brusco & J Dennis Cradit & Douglas Steinley, 2021. "A comparison of 71 binary similarity coefficients: The effect of base rates," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-19, April.
    9. Eike Emrich & Christian Pierdzioch, 2016. "Volunteering, Match Quality, and Internet Use," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 136(2), pages 199-226.
    10. Noah E. Friedkin, 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity," Sociological Methods & Research, , vol. 12(3), pages 235-261, February.
    11. David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler, 2011. "Measuring globalization: A hierarchical network approach," CREMA Working Paper Series 2011-11, Center for Research in Economics, Management and the Arts (CREMA).
    12. Balepur, Prashant Narayan, 1998. "Impacts of Computer-Mediated Communication on Travel and Communication Patterns: The Davis Community Network Study," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6cb1f85c, Institute of Transportation Studies, UC Berkeley.
    13. İsmail Güzel & Atabey Kaygun, 2022. "A new non-archimedean metric on persistent homology," Computational Statistics, Springer, vol. 37(4), pages 1963-1983, September.
    14. Lisa Price, 2001. "Demystifying farmers' entomological and pest management knowledge: A methodology for assessing the impacts on knowledge from IPM-FFS and NES interventions," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 18(2), pages 153-176, June.
    15. Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    16. Geert Soete & Wayne DeSarbo & J. Carroll, 1985. "Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 173-192, December.
    17. Silvia Blasi & Edoardo Gobbo & Silvia Rita Sedita, 2022. "Big Data for smart cities and citizen engagement: evidence from Twitter data analysis on Italian municipalities," Working Papers - Business wp2022_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    18. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    19. Dalila B. M. M. Fontes & Seyed Mahdi Homayouni, 2019. "Joint production and transportation scheduling in flexible manufacturing systems," Journal of Global Optimization, Springer, vol. 74(4), pages 879-908, August.
    20. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:84:y:2016:i:2:d:10.1007_s11069-016-2477-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.