ASSESSMENT OF CHINESE CITIES’ INTERNATIONAL TOURISM COMPETITIVENESS USING AN INTEGRATED ENTROPY-TOPSIS AND GRA MODEL

Amid fierce competition in the international tourism market, enhancing the tourism competitiveness of Chinese cities has become a pressing issue. However, existing studies often face limitations in evaluation methodologies and indicator selection. This study proposes an integrated evaluation model combining the Entropy Weight Method, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Grey Relational Analysis (GRA) to assess and rank the attractiveness of Chinese cities to foreign tourists. Using data from 352 cities, the analysis incorporates six critical factors: city scale, environmental protection, cultural heritage, transportation accessibility, climate, and cuisine. The data underwent preprocessing through linear regression and Kaiser-Meyer-Olkin (KMO) tests, with Principal Component Analysis (PCA) and Locally Linear Embedding (LLE) employed as dimensionality reduction techniques for different data categories based on R2 values. To ensure consistency across variables, normalization was applied, and indicator weights were objectively calculated using the Entropy Weight Method. The integrated TOPSIS and GRA approach was then utilized to evaluate and rank the 352 cities, ultimately deriving their composite scores. The findings reveal that the top 37 towns exhibit relatively concentrated scores, while scores for subsequent cities show a gradual downward trend. This study provides a systematic evaluation framework and decision-making support for Chinese cities to develop differentiated strategies in the global tourism market.