Intelligent Social Forecast in the Olympic Program of La Laguna: A Multicultural Perspective

Abstract

In this research, three multicriteria decisions (MCDM) analyses are applied using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methodology in managing the Olympic program of La Laguna. The model is structured and conceptualized as an intelligent social forecast system and integrates KPI`s (Key Performance Indicator) such as PISA (Programme for International Student Assessment) test, cultural cohesion metrics, and Olympic medals as an output of the entire model and program. Multivariate statistical and other qualitative techniques such as structured modeling equation (SEM) and paradigms such as Cultural algorithm, social portfolio problem, and demographic data are used. The model is ennobled with social theories, and the concept of aleph places is presented and introduced. It is pointed out how the MCDM decisions integrate the intelligent support system within the intelligent component, with high potential for other artificial intelligence applications. Finally, as next steps, it is established that a data set with the profile and history of each medal winner along with a case study is necessary to establish several scenarios that will help model social capital processes. These qualitative methods must be addressed in the context of the Imaginary Institution of Society.