시스템 사고를 이용한 커뮤니티 리질리언스 구성요소 간 인과구조 탐색

Abstract

Modern society is faced with multiple uncertainties from internal or external events. Although some disasters may be preventable in some degree, global health issues like COVID-19 or natural disasters including earthquakes and floods cannot be fully predictable accurately. The paper explores the concept of “Community Resilience”, which allows the society to recover to a better-than-before status upon facing an unavoidable disaster. Due to complex and dynamic features of a local community, it is difficult to calculate variables affecting Community Resilience as previous studies sought to identify its components and evaluation methods in various aspects. The purpose of this paper is to analyze causal relationship among the core elements of community resilience through Causal Loop Analysis. The results are as follows. First, when a disaster occurs, resource performance, resource diversity, and resource redundancy have a positive feedback structure for community resilience. Second, resource diversity affects institutional memory, and as such experiences and information are accumulated, the connectedness is strengthened. In addition, as institutional memories accumulate, innovative learning is more likely to be systematic and continuous. Third, innovative learning has a positive effect on the formation of consensus among the members and the internal bonds of the community, which in turn affects interactions with external organizations with a positive feedback on the resource performance. As a result, a community with high community resilience show less damage and shorter recovery times than those with low community resilience. That is, even if a disaster of similar type and magnitude occurs, the damage scale and recovery time may differ depending on the level of community resilience in the community. In order to reinforce community resilience, it is important to create a virtuous cycle amongst the components of Community Resilience.