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Permanent record · RIR–2069

Modeling Resilience and Recovery Dynamics in Behavior-Dependent Business Networks Following Major Regional Disasters

Post-disaster recovery is heavily influenced by the behavioral interdependencies within business networks. This research explores how these network dynamics facilitate or hinder long-term economic resilience.

Open to researchMBA suitableQualified 79/100P4 provenance
Primary research question

What behavioral factors within business networks most significantly influence the speed of post-disaster economic recovery?

Knowledge gap

What remains worth asking

The source suggests that network behavior is a critical variable, so it remains useful to test how specific network structures impact recovery outcomes.

Potential contribution

Why it may matter

Understanding these dynamics helps businesses and governments build more resilient economic recovery strategies.

Academic placement

OECD fields and topic tags

Business AdministrationNetwork ScienceDisaster Management

Scope: Business network recovery following regional disaster events. · Method signals: Network analysis, Longitudinal case studies

Possible study pathways

One question, different levels

Professional master’s / MBA

Supply chain resilience and crisis management

Doctoral

Complex systems and organizational resilience

originalityAdvanced
methodologyAdvanced
Data accessModerate
ethicsAccessible

Qualification signal

79/100

  • Requires access to post-disaster business data.
  • Open-access scholarly source and DOI metadata verified

Provenance

Research Idea Registry curation

  • DOI and bibliographic metadata independently resolved
  • Open-access status verified
  • The research direction is transparently marked as AI-inferred
The public contributor code contains no name or account email.

APA 7 source

Liu, C. F., Hsu, C. W., & Mostafavi, A. (2025). Dynamics of post-disaster recovery in behavior-dependent business networks. Humanities and Social Sciences Communications, 12(1), Article 1812. https://doi.org/10.1057/s41599-025-06092-0

Paper abstract and discussion context; AI-inferred direction

Open source ↗