Modelo conceptual de análisis de factores que influyen en la adopción de prácticas de economía circular en empresas textiles en Colombia

Abstract

This research focused on the implementation of the circular economy in the Colombian textile sector, aiming to design a conceptual analytical model that would allow the identification of the variables influencing the adoption of circular economy practices, both from a theoretical and empirical perspective. To this end, exploratory research was conducted using a mixed methodology. In the first phase, a comprehensive global literature review was conducted to identify the theoretically dependent and independent variables. Subsequently, a non-probabilistic sample of textile manufacturers in Colombia was analyzed, examining the content of their sustainability reports issued in 2023, which allowed us to define the variables to be studied from an empirical perspective. Models were then designed and validated using data processing, econometric modeling, and machine learning algorithms. In this phase, it was necessary to synthesize the multiple dimensions of the circular economy into an intensity index (INTENSITY_INDEX). Through the specification, evaluation, and analysis of predictor importance and robustness of the models, the variables TECHNOLOGY, INNOVATION, COMMITMENT, and SCALED_CERTIFICATIONS were identified as the most relevant. Finally, it is concluded that the conceptual analysis model, constructed from the identification of relevant variables through machine learning techniques, contributes significantly to the study of the circular economy in the textile sector and provides a useful basis for future research.