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Exploratory analyses of relief and development operations using social networks

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  • Urrea, Gloria
  • Villa, Sebastián
  • Gonçalves, Paulo

Abstract

We use social networks to explore how structural factors affect humanitarian organizations’ performance in relief and development operations. Analyses of two recent humanitarian disasters show that having pre-established partnerships among implementers, a central coordinator, high connectivity, and few structural holes facilitates coordination and improves performance. Similarly, cost efficiency analyses of 757 development programs reveal that (i) high performance of donors and beneficiaries is positively related to the amount of implementers they interact with, and (ii) programs connected by common actors are more cost efficient. Finally, short path lengths and frequent connections among actors or programs improve performance in humanitarian operations.

Suggested Citation

  • Urrea, Gloria & Villa, Sebastián & Gonçalves, Paulo, 2016. "Exploratory analyses of relief and development operations using social networks," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 27-39.
    • Handle: RePEc:eee:soceps:v:56:y:2016:i:c:p:27-39
    DOI: 10.1016/j.seps.2016.05.001
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    References listed on IDEAS

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    Cited by:

    1. Yingxin Chen & Jing Zhang & Pandu R. Tadikamalla & Lei Zhou, 2019. "The Mechanism of Social Organization Participation in Natural Hazards Emergency Relief: A Case Study Based on the Social Network Analysis," IJERPH, MDPI, vol. 16(21), pages 1-20, October.
    2. Jakub Marcinkowski, 2022. "Humanitarian Actors’ Cooperation Network in the Social Sustainability Context. Evidence from Poland," Sustainability, MDPI, vol. 14(9), pages 1-17, May.
    3. Zobel, Christopher W. & Baghersad, Milad, 2020. "Analytically comparing disaster resilience across multiple dimensions," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    4. R. K. Jana & Chandra Prakash Chandra & Aviral Kumar Tiwari, 2019. "Humanitarian aid delivery decisions during the early recovery phase of disaster using a discrete choice multi-attribute value method," Annals of Operations Research, Springer, vol. 283(1), pages 1211-1225, December.

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