Permanent record
RIR-2069 · Logged 13 July 2026
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.
In plain words
After a major disaster, businesses depend on each other to get back on their feet. Which ways businesses behave toward one another speed up or slow down recovery, and how could knowing this help firms and governments plan?
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
Academic fields and topic tags
Study frame: 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
- originality
- Advanced
- methodology
- Advanced
- Data access
- Moderate
- ethics
- Accessible
Quality and audit
79/100 quality
Safeguard-based audit was not recorded under the prior standard.
- Requires access to post-disaster business data.
- Open-access scholarly source and DOI metadata verified
This older record can be checked against the current standard on request. It changes only if every academic gate and independent safeguard passes.
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Research Idea 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
This is an AI-inferred direction. The source authors did not state it as a recommendation.
Open source ↗