A novel measure of entropy and COPRAS based on Fermatean fuzzy sets and its analysis of early childhood feeding behaviors

Abstract

This study aims to address early childhood nutritional behaviors from a sustainability perspective, evaluating the multidi-mensional factors that influence them within an integrated decision-making framework. Considering the decisive role ofnutritional habits acquired in early childhood on an individual’s lifelong health status and the sustainability of societal healthsystems, these behaviors need to be considered not only in their biological but also in their environmental, behavioral, andsocioeconomic dimensions. In this context, a novel entropy measure based on Fermatean fuzzy sets has been developed forthe field of early childhood nutrition, where uncertainty and subjective evaluations are intense, and a unique multi-criteriadecision-making approach has been proposed by integrating it with the COPRAS method. To demonstrate the applicabilityof the proposed method, we evaluated sustainable nutritional behaviors for early childhood across four basic alternatives(seasonal feeding, natural feeding, adequate and balanced feeding, and economical feeding) and within a framework ofnumerous criteria that represent these alternatives. We converted linguistic evaluations based on expert opinions into Fer-matean fuzzy numbers, criterion weights were objectively determined using the developed entropy approach, and alternativeswere ranked using the COPRAS method. The findings indicate that the natural feeding approach has the highest priority inestablishing sustainable eating behaviors in early childhood, followed by seasonal feeding, adequate and balanced nutrition,and economically viable nutritional alternatives. The results reveal that sustainability in early childhood is built not throughcognitive awareness, but through repeatable, internalized behaviors in daily life. This study offers a holistic perspective basedon behavioral sustainability to the early childhood nutrition literature. It contributes a new entropy measure and an applicableframework for multi-criteria decision-making to the Fermatean fuzzy sets literature.