Research On The Tourism Competitiveness Of Smart Tourism City

With the increasing combination of tourism and information technology, the second revolution of tourism is coming and smart tourism is becoming the development trend of modern tourism. In the smart tourism, tourism market is featured by main consumer popularity, FIT travel way. consumer demand personalized and smart marketing. In order to increase the popularity, expand the market and enhance the core competitiveness, intense competition is spreading between smart tourist cities. However, compared to the ardent response and fast development of smart tourist city construction, the theoretical research of smart tourism lags far behind practical demand. Currently, research for the smart tourist city especially for the competitiveness evaluation of smart tourist city is scares, which has caused haphazard investment and homogeneous competition between smart tourist cities. So a scientific evaluation system and model which can accurately measure the construction progress and competitiveness level of smart tourist city’is urgently established to facilitate a healthy development of our smart tourism.Based on the literature review of smart city, smart tourism, smart tourist city and its competitiveness, an evaluation system and model of smart tourist city is built in this article, then the empirical analysis is performed.Firstly, building evaluation system. The design scheme and literature of tourism competitiveness index system at home and abroad are researched first, then the competitiveness index system of smart tourist city is established preliminary and screened considering the accessibility and quantization of some indexes. Eventually a four-hierarchy competitiveness indexes system of smart tourist city with 14 tertiary indexes and 43 specific indexes is set up, which evaluates the competitiveness from five levels:economic development power, scientific and technological innovation, intellectual potential competitive, environment supporting force and development security.Secondly, determining evaluation criteria. The commonly used evaluation criteria of smart tourist city competitiveness include single-index evaluation, expertise and so on. In this study, the single-index evaluation is selected. For quantitative indexes, the national, local and industry standard values are used, and for qualitative indexes, five different levels marked Ⅰ, Ⅱ, Ⅲ, IV and V is used and the five levels are corresponding to five different scores:≤50; 50-59; 60-69; 70-89 and≥90. Thus, the evaluation criteria of smart tourist city competitiveness is built.Thirdly, setting up evaluation model. For the evaluation of smart tourist city competitiveness, the BP neural network model is adopted, and for the simulation of evaluation model, the software Matlab 7.0 is used. The BP neural network model can reflect the integrated competitiveness of each smart tourist city roundly and objectively.Finally, performing empirical analysis.12 cities identified as "national wisdom tourism pilot cities" by the National Tourism Administration are used for the network learning samples, including Beijing, Wuhan, Chengdu, Nanjing, Fuzhou, Dalian, Xiamen, Luoyang, Huangshan, Wenzhou, Yantai and Zhenjiang. The evaluation results of smart tourist city are calculated by the BP neural network model using the sample expectations. Then feasible strategies are proposed based on the analysis of evaluation results of smart tourist city competitiveness.