Research On Configuration Identification And Potential Type Prediction Of Cultural Tourism Town Failure

Despite the rapid development of cultural tourism towns supported by multiple favorable policies such as rural revitalization,new urbanization and high-quality development of county economy,its failure has always been the focus of social attention.At the moment of the "blowout" expansion of the development and construction of cultural and tourism towns,various failure problems emerge one after another,such as homogenization,inaccurate development positioning and non-characteristic tourism products.In addition,some cultural and tourism towns excessively pursue economic benefits in the process of development and construction,ignoring the protection of cultural relics,as well as poor infrastructure and poor tourist experience.But at the same time,due to the short development process of cultural tourism towns in China,the research results on the failure of cultural tourism towns are relatively scarce,and its failure has become a key challenge to be clarified.Since qualitative comparative analysis（QCA）is a method to explore different paths leading to the same result from an overall perspective,which can investigate the sufficient and necessary subset relationship between antecedent conditions and results,and explore the "how" of complex social problems induced by multiple concurrent causalities as a whole,and support vector machine（SVM）can solve support classification and regression problems,the main research content of this study can be divided into two parts,First,qualitative comparative analysis is used to analyze and summarize the failed configuration of cultural tourism towns in China;Second,SVM vector machine analysis technology is used to predict the possible failure problems.Therefore,this study first condenses the influencing factors of cultural tourism town failure,and uses QCA analysis method for empirical analysis to clarify the configuration of cultural tourism town failure in China;Secondly,the existing case information is supplemented and improved,the database is constructed by using the method of SVM vector machine in machine learning,and the feasibility and accuracy of the model are determined through verification and analysis;Finally,the prediction platform is developed and tested with the Guazhou cultural tourism development project as an example,and the most likely potential failure types in Guazhou cultural tourism development are obtained.Based on set theory and Boolean algebra,this study analyzes the complex causality of the failure of wenlv Town,focuses on the interaction between multiple failure influencing factors and results,and predicts and judges the potential failure types based on machine learning algorithm.The research results can help to understand the complex causality of cultural tourism town failure and judge the potential types of cultural tourism town failure.On the one hand,it enriches and expands the relevant theories of the failure of cultural tourism towns in China.On the other hand,it can also guide the development and construction process of cultural tourism towns,actively avoid the risk of failure,and provide reference for improving the successful implementation of cultural tourism town projects...