Open AccessDisaster risk mitigation design for supply chain activities in Aceh : a case study
Author(s) -
Prima Denny Sentia,
Andriansyah Andriansyah,
Zuhrotun Ulya
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1569/2/022098
Subject(s) - supply chain , supply chain risk management , business , risk management , risk analysis (engineering) , government (linguistics) , stakeholder , natural disaster , supply chain management , risk assessment , environmental resource management , environmental planning , operations management , finance , computer science , computer security , service management , engineering , marketing , economics , geography , linguistics , philosophy , management , meteorology
Indonesia is a country located between three tectonic plates thus very vulnerable to natural disasters. Ensuring that supports for disaster victims arrive on time and precisely in quality and quantity is the responsibility of all the supply chain elements, particularly government board which handled the logistic support. The activities of the supports supply chain when a disaster occurs have several risks that must be asses and the most prioritized risk will need the mitigation design to minimize the impact of these risks. This study aims to investigate risk events and risk agents in the supply chain activities in relation to disaster management in Aceh. This study employs three government boards at the key stakeholder’s group who play a significant role in the disaster risk mitigation in Aceh. Data obtained from questionnaires are used for analysing the supply chain activities using the SCOR model and Fuzzy-Based House of Risk method. The study reveals that there are 25 risk events ad 27 risk agents which might occur in the supply chain activities during disaster in Aceh. The mitigation strategy is proposed in mind map models with a long term solution for each risk agent related to the potential risk events.