TY - JOUR
T1 - Post-earthquake debris waste management with interpretive-structural-modeling and decision-making-trial, and evaluation-laboratory under neutrosophic fuzzy sets
AU - Aydin, Nezir
AU - Seker, Sukran
AU - Deveci, Muhammet
AU - Zaidan, Bilal Bahaa
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/12
Y1 - 2024/12
N2 - This study investigates the barriers to managing debris waste in the post-earthquake period in Türkiye following the significant earthquakes of 2023. Debris waste in the aftermath of earthquakes poses significant challenges to society and the environment. Thus, the critical need for effective debris waste management is essential to identifying and prioritizing barriers that impede the process. The study fills a gap in the literature by integrating Interpretive-Structural-Modeling (ISM), Decision-Making-Trial, and Evaluation-Laboratory (DEMATEL) and Neutrosophic Fuzzy Sets (NFSs) methodologies to assess barriers in the management of earthquake debris waste. The integrated approach considers technical, economic, regularity, environmental, and social dynamics influencing debris waste management. The results show that the first causal barrier is the “lack of legal enforcement,” which has the most significant impact. The lack of legal regulations is caused by insufficient financial, technical, and institutional capacity, especially in Turkiye and similar developing countries. Secondly, the “lack of awareness regarding the environment” is another barrier to effectively managing post-earthquake debris. To improve post-earthquake debris management, the study highlights the importance of barriers for policymakers to create effective and sustainable management strategies. It also contributes to advancing circular economy practices and achieving sustainable development goals 3-8-9 and 11. Further, it assists managers and policymakers in effectively managing debris waste after earthquakes by providing insights into the interrelationships of barriers and mitigation strategies.
AB - This study investigates the barriers to managing debris waste in the post-earthquake period in Türkiye following the significant earthquakes of 2023. Debris waste in the aftermath of earthquakes poses significant challenges to society and the environment. Thus, the critical need for effective debris waste management is essential to identifying and prioritizing barriers that impede the process. The study fills a gap in the literature by integrating Interpretive-Structural-Modeling (ISM), Decision-Making-Trial, and Evaluation-Laboratory (DEMATEL) and Neutrosophic Fuzzy Sets (NFSs) methodologies to assess barriers in the management of earthquake debris waste. The integrated approach considers technical, economic, regularity, environmental, and social dynamics influencing debris waste management. The results show that the first causal barrier is the “lack of legal enforcement,” which has the most significant impact. The lack of legal regulations is caused by insufficient financial, technical, and institutional capacity, especially in Turkiye and similar developing countries. Secondly, the “lack of awareness regarding the environment” is another barrier to effectively managing post-earthquake debris. To improve post-earthquake debris management, the study highlights the importance of barriers for policymakers to create effective and sustainable management strategies. It also contributes to advancing circular economy practices and achieving sustainable development goals 3-8-9 and 11. Further, it assists managers and policymakers in effectively managing debris waste after earthquakes by providing insights into the interrelationships of barriers and mitigation strategies.
KW - Cause-effect relationship
KW - Circular economy
KW - Debris waste
KW - Decision making
KW - Earthquakes
KW - Sustainable development goals
UR - http://www.scopus.com/inward/record.url?scp=85203432184&partnerID=8YFLogxK
U2 - 10.1016/j.engappai.2024.109251
DO - 10.1016/j.engappai.2024.109251
M3 - Article
AN - SCOPUS:85203432184
SN - 0952-1976
VL - 138
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
M1 - 109251
ER -