Fuzzy Multi-criteria Decision-Making for Children’s Book Selection: A Decomposed Fuzzy ARAS Approach

Abstract

Selecting appropriate books for children involves evaluating multiple subjective criteria, such as age appropriateness, educational value, cultural relevance, and engagement. These criteria are often imprecise and difficult to quantify, making the decision-making process inherently fuzzy. This paper introduces a novel approach to children’s book selection using the decomposed fuzzy Additive Ratio Assessment System (ARAS) method, a multi-criteria decision-making (MCDM) technique that incorporates fuzzy logic to handle uncertainty and subjectivity. By applying fuzzy logic, the method captures the vagueness in assessing criteria and helps decision-makers weigh trade-offs between conflicting factors systematically. This approach offers a structured, transparent tool for educators, librarians, and parents to make informed, context-sensitive decisions that align with both the developmental needs of children and educational goals. The proposed methodology provides an effective solution to the challenges of children’s book selection, facilitating decisions that promote children’s cognitive and emotional growth while adhering to specific educational and cultural objectives. © 2025 Elsevier B.V., All rights reserved.