STUDY ON NUMERICAL TAXONOMY AND DIFFERENCE ANALYSIS OF RURAL TOURISM——A CASE OF LIAONING PROVINCE
In recent years,the theoretical research of domestic rural tourism mainly focused on the rural tourism exploitation,the current situation of the development of the rural tourism,the tourism needs and motivation of tourists,and the tourists consuming behavior and satisfaction,etc.However,few research focused on the tourist numerical taxonomy and the differentiation in product design.For this reason,this paper constructed the specific index system in the tourist numerical taxonomy of the rural tourism in Liaoning province,based on the tourists information of tourism motivation,characteristics of traveling and personal information and so on.What's more,this paper applied several mathematical analysis methods,such as descriptive statistical analysis method,factor analysis method,cluster analysis method,analysis of variance method and so on,to make a specific scientific analysis of the sample data.The results showed that factor analysis method will deeply affect the 9 factors extracted from the 22 indicators and have influence on tourists traveling in rural tourism.The rural tourists can be divided specifically into four categories in the genetic distance of 18 by using the method of system clustering analysis.The variance analysis method can analyze the main characteristics of different rural tourists,as a consequence,it divided the tourists into four specific types,i.e.,the entertainment and recreation type,cultural experience type,relaxation and sightseeing type,and health and fitness protection type.The traveling characteristics of tourists had differences in two fields,i.e.,the time of traveling and the average individual consume of tourists in the cultural experience type and the health and fitness protection.The ways of traveling,the season of traveling and the number of traveling people had no significant difference.Besides of that,the personal information,personal gender,personal age,personal degree of education,personal occupation,personal habitual residence,and so on,also showed no remarkable difference.
NETL
NSTL
万方数据
维普
