Effects of democracy, social inequality and economic growth on climate justice: An analysis with structural equation modelling
Marcelo Furlan,
Enzo Barberio Mariano
Abstract:The purpose of this paper was to assess the effects of social inequality, democracy, and economic growth on the climate justice performance of a nation. To achieve this goal, the research technique Partial Least Squares Structural Equation Modeling (PLS‐SEM) was applied to a sample of 133 countries selected based on indicators available in international databases in 2019. The main results of the analysis were: (a) the effect of democracy on the performance of climate justice is positive; (b) the moderating eff… Show more
Despite efforts towards the accomplishment of the UN 2030 Agenda, the challenges of burgeoning populations, income inequality, difficulty in accessing basic services, among others, remain in several cities around the world. New approaches to measure and assess the sustainability of cities can support the development of actions to improve the different dimensions of sustainability. The research aims to propose an urban sustainability index and a maturity model to evaluate the sustainability of cities and monitor it over time. To achieve this objective, a maturity model was developed based on three different techniques: Data Envelopment Analysis, Artificial Neural Networks, and Analysis of Variance. The proposed index and the maturity model were applied to evaluate a sample of 504 Brazilian cities. The main results observed are: (a) the presence of five distinct levels of city performance (maturity), grouped via machine learning and validated via inferential statistics; (b) no city was considered fully sustainable and only 4.76% of the cities studies are at the highest level of urban sustainability maturity; (c) from a joint application of the three quantitative techniques and specific targets for each indicator could be identified, and the performance of cities classified over time. Based on the results, it is hoped that policy makers will have more objective and standardized tools to collect useful information and be able to reinforce critical strategies or chart new policies towards sustainable urban development. It is also hoped that the joint application of the techniques can shed light on new urban sustainability assessment models.
Despite efforts towards the accomplishment of the UN 2030 Agenda, the challenges of burgeoning populations, income inequality, difficulty in accessing basic services, among others, remain in several cities around the world. New approaches to measure and assess the sustainability of cities can support the development of actions to improve the different dimensions of sustainability. The research aims to propose an urban sustainability index and a maturity model to evaluate the sustainability of cities and monitor it over time. To achieve this objective, a maturity model was developed based on three different techniques: Data Envelopment Analysis, Artificial Neural Networks, and Analysis of Variance. The proposed index and the maturity model were applied to evaluate a sample of 504 Brazilian cities. The main results observed are: (a) the presence of five distinct levels of city performance (maturity), grouped via machine learning and validated via inferential statistics; (b) no city was considered fully sustainable and only 4.76% of the cities studies are at the highest level of urban sustainability maturity; (c) from a joint application of the three quantitative techniques and specific targets for each indicator could be identified, and the performance of cities classified over time. Based on the results, it is hoped that policy makers will have more objective and standardized tools to collect useful information and be able to reinforce critical strategies or chart new policies towards sustainable urban development. It is also hoped that the joint application of the techniques can shed light on new urban sustainability assessment models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.