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Harnessing the power of crowdsourcing and Internet of Things in disaster response

Author

Listed:
  • Shuihua Han

    (Xiamen University)

  • Hu Huang

    (Xiamen University)

  • Zongwei Luo

    (Southern University of Science and Technology)

  • Cyril Foropon

    (Montpellier Business School)

Abstract

Crowdsourcing and Internet of Things (IoT) are gaining more and more attention both in industry and academia in order to explore their effects on disaster relief. The current state of the literature shows a clear focus on the extent to which crowdsourcing on one hand, or IoT on the other hand, can individually make a difference regarding disaster response, but very few studies have considered the integration of both crowdsourcing and internet of things in order to link them with disaster response. Accordingly, in this paper, the authors have attempted to develop a crowdsourcing and IoT integration model which could help improving disaster response by using important value derived from using both social media and RFID technology. Furthermore, despite the fact that disaster relief offers similarities with epidemic transmission, (especially the SIR model), the application of SIR model in disaster relief still remains unexplored, which has led the authors to conduct a series of SIR model-based simulations to investigate the extent to which such integration model helps improving disaster response.

Suggested Citation

  • Shuihua Han & Hu Huang & Zongwei Luo & Cyril Foropon, 2019. "Harnessing the power of crowdsourcing and Internet of Things in disaster response," Annals of Operations Research, Springer, vol. 283(1), pages 1175-1190, December.
  • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-018-2884-1
    DOI: 10.1007/s10479-018-2884-1
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    References listed on IDEAS

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    1. Ivo Blohm & Ulrich Bretschneider & Jan Marco Leimeister & Helmut Krcmar, 2011. "Does collaboration among participants lead to better ideas in IT-based idea competitions? An empirical investigation," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 9(2), pages 106-122.
    2. Christian Burkart & Pamela C. Nolz & Walter J. Gutjahr, 2017. "Modelling beneficiaries’ choice in disaster relief logistics," Annals of Operations Research, Springer, vol. 256(1), pages 41-61, September.
    3. Yisha Xiang & Jun Zhuang, 2016. "A medical resource allocation model for serving emergency victims with deteriorating health conditions," Annals of Operations Research, Springer, vol. 236(1), pages 177-196, January.
    4. Feng Yang & Qianqian Yuan & Shaofu Du & Liang Liang, 2016. "Reserving relief supplies for earthquake: a multi-attribute decision making of China Red Cross," Annals of Operations Research, Springer, vol. 247(2), pages 759-785, December.
    5. Sukho Jin & Sukjae Jeong & Jangyeop Kim & Kyungsup Kim, 2015. "A logistics model for the transport of disaster victims with various injuries and survival probabilities," Annals of Operations Research, Springer, vol. 230(1), pages 17-33, July.
    6. V. Yadavalli & Diatha Sundar & Swaminathan Udayabaskaran, 2015. "Two substitutable perishable product disaster inventory systems," Annals of Operations Research, Springer, vol. 233(1), pages 517-534, October.
    7. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    8. Xihui Wang & Yunfei Wu & Liang Liang & Zhimin Huang, 2016. "Service outsourcing and disaster response methods in a relief supply chain," Annals of Operations Research, Springer, vol. 240(2), pages 471-487, May.
    9. Lei Lei & Michael Pinedo & Lian Qi & Shengbin Wang & Jian Yang, 2015. "Personnel scheduling and supplies provisioning in emergency relief operations," Annals of Operations Research, Springer, vol. 235(1), pages 487-515, December.
    10. Jomon Paul & Govind Hariharan, 2012. "Location-allocation planning of stockpiles for effective disaster mitigation," Annals of Operations Research, Springer, vol. 196(1), pages 469-490, July.
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    Cited by:

    1. Narayan Prasad Nagendra & Gopalakrishnan Narayanamurthy & Roger Moser, 2022. "Management of humanitarian relief operations using satellite big data analytics: the case of Kerala floods," Annals of Operations Research, Springer, vol. 319(1), pages 885-910, December.
    2. Sachin Modgil & Rohit Kumar Singh & Cyril Foropon, 2022. "Quality management in humanitarian operations and disaster relief management: a review and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 1045-1098, December.
    3. Vahideh Manshadi & Scott Rodilitz, 2022. "Online Policies for Efficient Volunteer Crowdsourcing," Management Science, INFORMS, vol. 68(9), pages 6572-6590, September.

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