The aim of this paper is to understand how resilience builds to achieve a management model for sustainable resilience, as advocated by sustainable development goals (SDGs), in distressed communities. The topic is addressed with the case of Macerata, an Italian city located at the epicentre of the devastating earthquake in 1997 and later, in a short time interval between August 2016 and January 2017. Necessary knowledge on modes and places of engagement and collaboration is delivered in the attempt to demonstrate that social and cultural factors have stronger impacts on devastated communities as they contribute to resilience for future incidents.
The paper uses a quantitative econometric approach. It unfolds in two steps. The first uses the estimation method through factor analysis of an index of resilience, a latent variable, and reveals that it comes from social, cultural, political and economic latent factors. The second uses a reduced equation model that elaborates and integrates two models: the one estimating the relationship between the level of development and the impacts due to natural disasters and the other containing the index of resilience, but only its most relevant ones. A rotated component matrix, which is the elaboration of the model, will be created.
Although measuring resilience, in practice, is hampered by both conceptual and methodological challenges, including finding reliable and meaningful data, the attempt to measure resilience in this research has helped in testifying two important research hypotheses. According to H1 , resilience is a fundamental variable to ensure faster economic recovery and has a negative impact on the dependent variable (deaths); hence, it is considered statistically significant. According to H2 , social resilience develops and increases at the event’s recurrence and leverages on the adaptive, self-organising community capacities in recovering from traumatic circumstances and episodes of distress.
The limitation of this paper is that the comparison between the two earthquakes is biased by the interviewees’ misleading responses on the provided questionnaires due to lack of memory about the 1997 shock and a more higher perception of the latest quakes that occurred recently in 2016 and 2017. There is a strong awareness of the fact that future research will improve the analysis suggested in this paper by attempting a quantification of the perception about the difference between the two occurred earthquakes by replacing the dummy variable (β 6 improvement) with a cluster analysis.
The paper fills the gap in the empirical literature on risk management and organisational resilience. This research represents a guide to support and accelerate building resilience by people engagement and empowerment, enthusiasm and commitment in a way that conventional politics is failing to do. In particular, it aims to support public organisations and policymakers at the front by providing them with reliable information on the factors and concerns that need to be considered to increase community’s level of resilience, coherently with their endogenous characteristics, to ensure a steady, stable and sustainable recovery from the crisis.
This research teaches that resilience depends on the existence of minimum preconditions for building resilience – political and economic opportunities, as well as cultural and social factors – as the measurement of tangible factors such as assets and financial capital may not capture everything that influences resilience. However, although it is common sense that disaster recovery processes are significantly hard to bear, it is important to acknowledge that they can offer a series of unique and valuable opportunities to improve on the status quo. Capitalizing on these opportunities means to well-equip communities to advance long-term health, resilience and sustainability and prepare them for future challenges.
This paper contributes to the discussion over the development of sustainable cities and communities by providing a resilience measurement framework in terms of indicators and dimensions of resilience. It emphasises on the endogenous adaptation capacity of territories partially analysed in the empirical literature with regard to resilience. The originality relates to the suggested model being a tool for social and territorial analysis, useful for ensuring a summary and comprehensive assessment of socioeconomic resilience; comparing different timelines (the first earthquake occurred in 1997 and the other two, occurring in a short time interval from one another, in August 2016 and January 2017).