Markov Chain Analysis Of Tourist Spatial-temporal Behavior

Tourism has become the leading service industry today. The study of the tourist market has always captured much more attention of foreign scholars. As Tourist behavior is extremely complex, different research disciplines also showed different focus on tourist's behavior research. Generally, academic includes tourism policy, tourism motivation, tourism consumption, space-time behavior, empirical research, market segments behavior, etc. Among these area, from tourists behavioral point of view we can explore the law of supply and demand balance in the development of tourism and acquire a scientific basis for the tourism product design and market development; tourist behavior analysis can provide effective reference and be directly utilized for tourist destination development, planning, management, marketing strategy, for example, research on travel space behavior plays an important role on how to plan for tourism development and product development, marketing, how to select an object.A broad definition illustrates spatial behavior of tourists as "travel behavior during a tour of geographical movement, including tourists from the collection of information about tourism products, generation of tourism motivation, to make (rravel decisions, purchase, ecnsumption, and assess the behavior of tourism prola(?)s and psychological processes. It equals to behavior of visitors in scope, including tourists motivated behavior, decision-making behavior and spatial movement (three interrelated behavior process. Here we call it the broad behavior of tourists. Narrow spatial behavior of tourists means travel behavior during a tour of the geographical movement, specifically the behavior of spatial mobility performance (tourist flow). The projection of spatial behavior of tourists in the geographical space of, that is, the formation of a different behavior space, that space acts location. Range of spatial behavior in space travel can be divided into three scales, large, medium and small. Small-scale travel behavior always performed in the form of multi-day trips. Large-scale space travel behavior involves inter-provincial, national and international spatial extent, which can form a series of urban centers based on a number of tourist traffic. Medium-Scale involved a spatial extent of province and city areas. Tourist attractions can constitute a complete tourist routes based on traffic series, and are manifested in the behavior of the discrete process the time dimensionBased on a travel to be considered as the space tourist behavior, this thesis tried to explore characteristics of tourists combining tourists behavior in the space with behavioi in the time, and quantify tourists behavior in large and medium-scale as a discrete process, and make use of the relevant theory of discrete Markov chain to model for tourists space-time behavior, provide practical reference to tourist destination management, product line design and market development. This thesis looks forward to further enrich the research of tourists' behavior.This study has been divided into five parts to describe:The first part is a brief introduction of background of this research, and then clear research themes and research purposes.The second part summarized the literature analysis about the tourists' space-time behavior of domestic and foreign scholars, whilst summarizing the Markov chain on tourism-related research literature and pointed out that the starting point of this article. It also Introduced theories involved, and identified the subjective and objective existence of tourists through the space-time behavior of tourists ontology analysis, and the MC theory was briefly introduced.The third part is about study design, including the Markov modeling of a tourist spatial and temporal behavior. It setted the variables required for the model, and model validation methods; analysis of trends in the use of forecasting tourist behavior data requirements to establish a database and made preliminary hypothesis; then descibed questionnaire design and selection object.The fourth part is the use of space-time Markov model to analyze the behavior of tourists, and then using SPSS 16.0 for descriptive statistical analysis, the use of EXCEL to calculate one step transition probability matrix, then to identify the important spatial-temporal behavior of tourists according to the size of the probability, then test the validity of this method of Markov model.The fifth part concluded with research findings and weaknesses, and then pointed out f prospects in the future.The innovation of this paper is a model for predicting tourists'spatial and temporal behavior based on the relative theory of Markov chain, from which we can calculate transition probability, and then identify the most important pattern, combined with time element provide direct and practical market information, looking forward to help with tourism managers in increasing the market numbers and improving service quality.