The Type and Path Selection of Tourism Industry Development from the Perspective of Configuration:An Exploration Based on Machine Learning Methods
At present,the contradiction of inadequate and unbalanced regional development is still prominent.Developing a regional economy in a new way is related to the well-being of the people;it is also a major theoretical and practical problem to be solved urgently in our economic and social development in the new era.The 20th National Congress of the Communist Party of China once again wrote the goal of common prosperity into the report and continued to promote the coordinated development of regions to better meet the broad masses of people's yearning for a better life.As a strategic pillar industry of our country,the tourism industry is an important driving force that promotes high-quality regional economic development and optimization and upgrading of industrial structure.Moreover,it will also promote the shared prosperity of our country.Combined with production function theory and a literature review,eight feature variables are selected from resource,technology and institution dimensions based on the reviewed research to examine the tourism industry's personalized and differentiated driving path in different types of cities.Next,we obtain the field index data of 298 cities at the prefecture level or above and filter them.The entropy weight method is used to measure variables.After the corresponding feature variables are standardized by min-max normalization,the K-means algorithm is used to classify cities with similar characteristics into clusters(i.e.,hindered,stable and fully radiant).The feature difference radar map is drawn according to the mean value of the overall features of different city clusters,which are named to identify the overall heterogeneity of different types of cities.Lastly,taking the tourism industry development as the decision attribute and eight feature variables as the conditional attribute,the classification and regression tree algorithm is used to explore the potential decision rules of the tourism industry development in three types of city clusters.The results show that 1)the driving factors of the tourism industry have a coupling and coordination effect,reflected in the lateral coupling consistency and longitudinal hierarchical stratification of the multidimensional feature variables of different types of cities;2)highly similar cities obtain different levels of tourism industry development due to the differentiated allocation of factors,indicating that each city type has its configuration conditions suitable for its own development,providing a realistic basis for promoting regional coordinated development;and 3)the driving factors of high-level development of tourism industry in different city types are different in combination,showing the effect of the same destination on the whole.The hindered cities are driven by"technological foundation-regional opening-cultural attraction,"the stable cities by"economic guidance-technological innovation-digital empowerment,"and the fully radiant cities by"cultural attraction-transportation enhanced."These conclusions provide a new development idea and reference basis for the Chinese urban tourism industry in response to national policies.
tourism industry developmentmultidimensional feature variableconfiguration perspectivepath selectionmachine learning
NETL
NSTL
万方数据
