Assessing the Sustainable Development of the Tourism Industry Based on Fuzzy AHP and Grey Relational TOPSIS

As tourism develops, more study focuses on tourism sustainable development assessment. To solve ambiguous indicators and subjective weight distributions in such evaluations, this paper proposes a hybrid model combining Fuzzy AHP (FAHP) and Grey Relational TOPSIS (GR-TOPSIS). A 13-secondary-indicator evaluation system is established across four dimensions (economy, society, environment, culture), distinguishing positive/negative indicators based on tourism’s local impacts. FAHP builds a triangular fuzzy judgment matrix, with confidence ranking to determine index weights and consistency tests to ensure weight rationality. Grey relational theory improves TOPSIS, which integrates Euclidean distance and grey relational degree to form a hybrid closeness index, overcoming traditional TOPSIS’s poor fuzzy data handling. Verified with seven tourist regions in our cases, the method yields indicator weights and final superiority–inferiority rankings. Among the seven evaluated regions, Lijiang Qinghsui (P4) achieves the highest sustainable development level (hybrid closeness: 0.693), while P6 performs the poorest. Among the 13 indicators, Tourism Revenue Contribution is the most important (weight: 0.189) and Tourists’ Cultural Respect Degree (F13) is the least important (weight: 0.015). Compared with traditional TOPSIS, this innovative model quantifies sustainable tourism development levels, offering a scientific basis for regional tourism decision-making.