Author
Listed:
- Susan Rugoi
(Scholar, Jomo Kenyatta University of Agriculture and Technology)
- Dr. Miriam Thogori Nyambura, (PhD)
(Senior Lecturer: Jomo Kenyatta University of Agriculture and Technology)
Abstract
Humanitarian supply chains play a crucial role in ensuring the timely delivery of aid in disaster-affected regions, particularly in Kenya, which frequently experiences both natural and human-made disasters. During the 2022–2023 Horn of Africa drought, over 4.4 million Kenyans required humanitarian assistance, yet relief NGOs reported response delays averaging 18 to 28 days due to supply chain breakdowns, a pattern repeated during the 2023 El Niño floods that disrupted transport corridors and caused supply delays of up to 21 days. These recurring failures have been widely attributed to limited supply chain agility, weak flexibility mechanisms, inadequate inventory pre-positioning, and insufficient redundancy planning. Therefore, this study examined the effect of supply chain resilience practices on the performance of relief non-governmental organizations in Nairobi City County, Kenya. The specific objectives were to assess the influence of supply chain agility, supply chain flexibility, inventory pre-positioning, and supply chain redundancy planning on the performance of relief NGOs. The study was underpinned by the Dynamic Capability View, Resource-Based View, Contingency Theory, and Risk Management Theory. A cross-sectional survey research design was adopted, targeting a sampling frame of 100 staff drawn from logistics officers, procurement managers, supply chain staff, operations managers, and senior management across 20 relief NGOs operating in Nairobi City County. A sample of 80 respondents was selected using stratified random sampling, and data were collected through semi-structured questionnaires, then analyzed using descriptive and inferential statistics presented in tables. The study found that supply chain agility had a significant positive influence on the performance of relief NGOs (r = 0.431, Beta = 0.386, p
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