A Bayesian Network Method for Humanitarian Supply Chain Performance Evaluation. Issue 10 (2022)

• Record Type: Journal Article
• Authors: Wang, Lu; Ding, Yueyu; Wang, Yunfeng
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 10(2022)
• Page Start: 3088
• Page End: 3093
• Publication Date: 2022
• Subjects: Humanitarian supply chain -- Risk factors -- Bayesian Network -- Performance evaluation; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.10.203
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The increasing risk of natural disasters has a direct impact on the survival of the affected people and further seriously jeopardizes the sustainability of the country's economic growth and development. The high volatility of disasters and the skyrocketing demand for relief operations pose enormous challenges to the humanitarian supply chain (HSC). At present, most developing countries lack resilient and effective HSCs. Therefore, in this work, by qualitatively tapping into HSC risk factors, a Bayesian Network (BN) model is developed for quantitatively evaluating the performance of HSC in the context of the rising threat of tropical cyclones in Zimbabwe. The BN model would also further help humanitarian relief organizations to gain some management insights.