Bridging Diversity and Fidelity Through a Multi-Attribute AI Framework for Collaborative Calligraphy Artistic Services Quality Evaluation

Traditional calligraphy is a treasure of Chinese culture, distinguished by its long history and profound cultural significance. However, with the development of modern society, traditional calligraphy now faces the dual challenges of inheritance and innovation. The collaborative calligraphy artistic services quality evaluation constitutes a quintessential multi-attribute decision-making (MADM) challenge. Contemporary research has progressively integrated methodologies like TODIM approach and entropy to address such complex assessments and employs Z-numbers as a robust mechanism for representing vague and partially reliable information. The Z-number TODIM (ZN-TODIM) framework is constructed and specifically used to resolve MADM problems within Z-number information environments. The practical applicability and computational efficacy of this proposed technique are subsequently validated through a detailed numerical case study focusing on the collaborative calligraphy artistic services quality evaluation, demonstrating its utility in real-world educational management scenarios.