A Fuzzy Approach to Assessing Progress Towards the Sustainable Development Goals Using Choquet Integral Aggregation

The monitoring of the Sustainable Development Goals (SDGs) poses a significant challenge and strategic opportunity for stakeholders (Sachs et al., in 2018) developed the SDG Index to track progress against a series of goals with multiple targets and indicators. While their index is robust, it overlooks the “balanced” and “integrated” nature of the SDGs. To address these gaps, we propose a new approach that distinguishes between means and end goals using Keeney's theory of value, “Value-Focused Thinking.” Additionally, to account for the objective weights of each indicator, we will employ entropy information theory. Using indicators from the official list of SDGs, we will construct indices measuring the achievement of sustainable development goals in a sample of 93 middle- and low-income countries for the period from 2014 to 2018. To consider the interconnected and indivisible nature of the SDGs, we will utilize a fuzzy nonlinear aggregation method known as the Choquet integral. Our model enables the identification of key areas of action for advancing the SDGs. Furthermore, it facilitates the identification of weaknesses in each country, allowing for the prioritization and analysis of relevant policies to address these shortcomings.