A Spatial DEA-Based Framework for Analyzing the Effectiveness of Disaster Risk Reduction Policy Implementation: A Case Study of Earthquake-Oriented Urban Renewal Policy in Yongkang, Taiwan

Abstract

Due to the many large earthquakes that have occurred in recent years, the role of seismic risk reduction in building resilient cities has become a matter of concern. The serious disaster damage brought by seismic hazards causes the adoption of migration policies such as building control in the preparedness phase. However, the restricted budget of governments resulting from the global state of economic distress generates a prioritization problem. A decision support framework could be helpful for governments to systematically integrate the complex information when implementing disaster risk reduction policies toward sustainable development. The purpose of this study was to construct an analytical framework based on Geographic Information System (GIS) and Data Envelopment Analysis (DEA) for addressing the prioritization problem by calculating policy efficiency. The spatial DEA-based framework combines indices calculation, spatial database construction, and DEA. Taiwan is an island located in the Circum-Pacific Belt, and has paid long-term attention to adopting policies for earthquake disaster prevention. A policy of earthquake-oriented urban renewal combining enhanced building capacity and city resilience has recently been implemented. A case study of the Yongkang district of the Tainan Metropolis in Taiwan was conducted in this study. The results show an operable framework and propose a suggestion for planning efficient policy priorities in each decision-making unit. In sum, the analytical framework proposed in this study could be a component of a decision support system for governments to adopt disaster risk reduction policies in the process of policy-making and implementation.

Application of a Hybrid Method in Disaster Prevention and Relief Evaluation

“…Üstün (2016) used DEA to evaluate the disaster resilience capacity to earthquakes in 30 districts in İstanbul. Cheng and Chang (2018) combined the geographic information system (GIS) and DEA to address the prioritization problem by calculating policy efficiency. Another application of DEA related to DPR is vulnerability analysis; Zou and Wei (2009) used DEA to assess the performance of coastal hazards from 1995 to 2005 in eight Southeast Asian countries.…”

Evaluation of natural disaster treatment efficiency in 27 Chinese provinces

“…There have also been many studies focused on natural disaster prevention and treatment, management efficiency, risk control, and assessments, most of which employed Super‐DEA (data envelopment analysis) or CCR (Charnes, Cooper, and Rhodes model) DEA models (Cheng & Chang, 2018; Kawamoto & Kim, 2016; Li, Hu, Hu, He, & Tu, 2019; Liu, Wei, & Xu, 2018; Xiang, Wang, & Deng, 2017; Yu, Chen, & Li, 2019; Zhang, Xiang, Chen, & Mao, 2018). However, as neither of these models allow for the input and output proportions to independently change, they are incompatible with reality.…”

“…Wu, Chen, Zhao, Guo, and Ma (2019) used a DEA model to assess haze emissions efficiencies in different provinces in China, finding that the efficiencies in east China were low Yu et al (2019). used a super-efficiency DEA model to assess typhoon vulnerabilities in the coastal areas of Shanghai, Zhejiang, Guangdong, Fujian, and Hainan and found that typhoon fragility in Shanghai and Fujian was low.As can be seen in this literature review, most studies using DEA to analyse disaster governance use traditional radial models, such asXiang et al (2017),Shi (2018),Cheng and Chang (2018), andLi et al (2019). Traditional radial models have the disadvantage that input and output must change in the same proportion, which is not conducive to variable adjustment.…”

“…reduction decisions. The study also took the Yongkang district in Tainan, Taiwan as an example Cheng and Chang (2018). built an analytical framework based on a geographic information system (GIS) and DEA to solve a prioritization problem and assess policy effectiveness.…”

Implementation Efficiency of Corporate Social Responsibility in the Construction Industry: A China Study

“…In these studies, the data envelopment analysis (DEA) model is a popular and practical method adopted to evaluate efficiency performance because it has advantages in terms of measuring efficiency performance based on multiple inputs and outputs without assigning prior weight to indicators [ 25 , 26 ]. Nowadays, the DEA model has been successfully applied in different fields, such as energy efficiency [ 27 ], education efficiency [ 28 ], policy efficiency [ 29 ], operational efficiency [ 30 ], investment efficiency [ 31 ] and urbanization efficiency [ 32 ]. Besides, after justifying DEA approach’s advantages in calculating CSR efficiency scores based on a comparison between DEA model and other approaches [ 33 ], a few CSR studies have attempted to adopt the DEA model to analyze CSR efficiency [ 34 ].…”