Sustainable Competitiveness: Application of Data Modeling to Identify Predictive Factors by Country

Autor: Cesar Felipe Henao Villa, Julio Cesar Martínez Zarate, Federico Henao Villa
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Sustainable Development and Planning. 17:2319-2325
ISSN: 1743-761X
1743-7601
DOI: 10.18280/ijsdp.170733
Popis: Competitiveness as a concept has had a significant impact on the development not only of individual companies, but also of the national and international economy. This article contributes to the analysis of competitiveness framed in the context of sustainability, responding to the call of the United Nations in relation to the Sustainable Development Goals (SDG), and more specifically in the framework of SDG 11, which mentions the importance of working in pursuit of “sustainable cities and communities”. The mixed-cut methodology starts from a conceptual inquiry into the competitiveness of states according to the World Economic Forum, highlighting its main components and a detailed examination of the associated indices to collect data that were later analyzed for the construction of models for understanding of the dynamics of the sustainable competitiveness index, thus contributing to the knowledge of the main competitive advantages and disadvantages of the states in this matter. As a result, a factor analysis of 1196 country records is obtained, which, after being contrasted with structural equation models, allowed the identification of five factors with their respective regression values, thereby identifying classification scenarios by countries with their respective predictor variables. Finally is concluded that there are different variables such as intellectual capital, social capital, natural capital and governance that are needed for a better sustainable society. The methodology approach for this paper presents a novel KDD approach in order to have a more suitable and proper results.
Databáze: OpenAIRE
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