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Critical Success Factors for Enhancing Performance of Agile Humanitarian Logistics Using CVI Method: Evidence from the 2024 Bangladesh Flood

IMPACT SIGNAL70/100
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Information from the abstract

Background: Agile humanitarian logistics (HL) has emerged as an imperative approach for improving preparedness, response, and recovery in flood disasters. However, achieving agility in HL depends on identifying and implementing critical strategies that enhance logistics performance. Using the 2024 Bangladesh flash flood as an empirical case, this study provides an early investigation into the critical success factors (CSFs) required to strengthen agile HL performance. Methods: First, a PRISMA-guided review was conducted to systematically identify the most relevant CSFs and their associated dimensions from prior studies. Next, the Content Validity Index (CVI) method was applied to evaluate and refine the CSFs through expert consensus, ensuring strong content validity. Results: The results indicate that 12 CSFs, organized across five dimensions—collaboration, managerial, operational, strategic, and technological—collectively contribute to improving HL performance and supporting long-term agility. Conclusions: This study offers a structured set of validated factors that can guide policymakers and humanitarian organizations in prioritizing interventions, strengthening coordination, improving decision-making and resource utilization during flood emergencies. These insights extend agile HL knowledge by linking validated CSFs to performance enhancement in a real-world, high-impact disaster context.

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Why this record is monitored

This record has an Impact Signal of 70/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.

Related topics: Facility Location and Emergency Management · Supply Chain Resilience and Risk Management · Disaster Response and Management

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Thai researcher and institutional participation

Israt Jahan Hridi · Chawis Boonmee · Chiang Mai University

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Data limitations

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