Study on the Evaluation and Optimization Strategy of Tourism Environmental Suitability in China Based on the AHP-TOPSIS Algorithm

Abstract: The condition of the tourism environment is the key factor that affects the tourism experience. A comprehensive evaluation of the tourism environmental suitability score is of great significance for guiding tourism planning and decision-making, improving the suitability score of the tourism environment in a targeted manner and guaranteeing the sustainable development of tourist cities. By adopting various indicators, such as the Universal Thermal Climate Index, the amount of precipitation, the vegetation index, the concentration of fine particulate matter in the atmosphere, and the ultraviolet radiation intensity index, this study quantifies the comfort level of weather, the weather impacts, the vegetation status, the atmospheric environment, ultraviolet radiation, and other key factors. Based on employing the AHP-TOPSIS algorithm, this study then conducts a comprehensive evaluation of China's tourism environmental suitability score and a comprehensive comparative analysis of the tourism environmental suitability scores of three typical tourist areas: the Beijing-Tianjin-Tangshan area, the Yangtze River Delta and the Pearl River Delta. The results show that the tourism environmental suitability score in China has obvious characteristics of spatial differentiation: the scores in East and South China are the highest while the score in the north-west inland area is the lowest. Among the three typical tourist areas, the Pearl River Delta region has the highest tourism environmental suitability score, followed by the Yangtze River Delta region, and the Beijing-Tianjin-Tangshan region has the lowest score. The northern regions of the Beijing-Tianjin-Tangshan area, the southern regions of the Yangtze River Delta and the surrounding areas of the Pearl River Delta are more suitable for the sustainable development of the tourism industry. PM2.5 is the main factor limiting the tourism environmental suitability scores in the Beijing-Tianjin-Tangshan area and the Yangtze River Delta, so atmospheric environment management will be an effective way to improve their tourism environmental suitability scores.

[1]  K. Duan,et al.  Efficiency of tourism development in China’s major cities under the constraint of PM2.5 , 2021, PloS one.

[2]  H. Tatli,et al.  Land use suitability analysis of rural tourism activities: Yenice, Turkey , 2020 .

[3]  Jun Yang,et al.  Spatial differentiation of China’s summer tourist destinations based on climatic suitability using the Universal Thermal Climate Index , 2018, Theoretical and Applied Climatology.

[4]  Mehdi Keshavarz Ghorabaee,et al.  Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach , 2018 .

[5]  Q. Ge,et al.  Application of UTCI in China from tourism perspective , 2017, Theoretical and Applied Climatology.

[6]  U. Gretzel,et al.  Smart tourism challenges , 2017 .

[7]  S. Phinn,et al.  Assessment of multi-resolution image data for mangrove leaf area index mapping , 2016 .

[8]  A. Setianto,et al.  COMPARISON OF KRIGING AND INVERSE DISTANCE WEIGHTED (IDW) INTERPOLATION METHODS IN LINEAMENT EXTRACTION AND ANALYSIS , 2015 .

[9]  Alan D. Lopez,et al.  A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010 , 2012, The Lancet.

[10]  Ravi Shankar,et al.  A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain , 2011, Expert Syst. Appl..

[11]  R. Knutti,et al.  Future climate resources for tourism in Europe based on the daily Tourism Climatic Index , 2010 .

[12]  T. Seager,et al.  Application of Multicriteria Decision Analysis in Environmental Decision Making , 2005, Integrated environmental assessment and management.

[13]  Wietze Lise,et al.  Impact of Climate on Tourist Demand , 2001 .

[14]  Piotr Jankowski,et al.  Integrating Geographical Information Systems and Multiple Criteria Decision-Making Methods , 1995, Int. J. Geogr. Inf. Sci..

[15]  Thomas L. Saaty,et al.  How to Make a Decision: The Analytic Hierarchy Process , 1990 .

[16]  P. Vincke,et al.  Note-A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making , 1985 .

[17]  Frederick R. Steiner,et al.  Resource suitability: Methods for analyses , 1983 .

[18]  George W. Torrance,et al.  Application of Multi-Attribute Utility Theory to Measure Social Preferences for Health States , 1982, Oper. Res..

[19]  Sun Jing.  The comprehensive evaluation of suitability of marine tourism base in China , 2016 .

[20]  Guo Yong-qua.  Spatial Differentiation of Human Settlement Environment Suitability in Chinese Typical Tourist Cities , 2015 .

[21]  K. Cherkauer,et al.  Weather, climate, and tourism performance: A quantitative analysis , 2013 .

[22]  L. D. Hopkins,et al.  Methods for Generating Land Suitability Maps : A Comparative Evaluation , 2013 .

[23]  Wu Mengshan.  Models of Integrated Development of Coastal Tourism of China Based on Its Connotation , 2012 .

[24]  YI Xiao-li.  Tourism Competitiveness Evaluation Study of Coastal Cities , 2010 .

[25]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .