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Study On Spatial Behavior Of Rural Tourists Based On Digital Footprint

Posted on:2019-06-06Degree:MasterType:Thesis
Country:ChinaCandidate:Q ZhangFull Text:PDF
GTID:2429330569996778Subject:Tourism Management
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In recent years,with the rapid development of mobile communication technology,internet technology and geographic information technology,individual spatial behavior analysis based on digital footprints has gradually become the hotspot of scholars at home and abroad,behavioral data of the tourists in the area is very important for the analysis of tourist demand,improvement of the scenic area planning and management.To a certain extent,it affects the sustainable development of local tourism.This study selected Dandong Dalishu ecological sightseeing agricultural tourist area in Liaoning province as the research area,using GPS tracking and questionnaire method to get the data,through descriptive statistical analysis,spatial analysis,factor analysis,cluster analysis,variance analysis and other methods,focus on the research of spatial behavior rule study,the classification of the tourists and tourist spatial behavior pattern and differentiation.The main research contents and conclusions are as follows:Study on spatial behavior of rural tourists.Using GPS and GSM locator to get accurate data of tourists spatial behavior during the travel process,after dealing with the ArcGIS spatial analysis and mathematical statistical analysis,it preliminary determines the basic rule of rural tourist activities.The analysis result shows that rural tourists travel activity time is concentrated in the 9:00-11:00am,the end of the activity time is between 11:00 and 13:00,visiting time is given priority to with 2 or 3 hours,moving rate from 15 to 25 km/h,the number of stops is 6-10 times.Research on the classification of rural tourists.Through questionnaire to survey in the study area,the data is collated and quantified,use the results of the questionnaire survey on the questionnaire survey to obtain the influence factors from 30 variable factor,extract the 12 common factor,the cumulative variance contribution rate is 70.856%.Do cluster analysis for principal component of 12 common factor values,it is divided into four types,according to the characters of each type of tourists travel preferences,preliminary dividing country tourists into the country characteristic culture experience respectively,rural natural scenery experience respectively,rural recreation activities experience respectively,and rural social life experience respectively and so on.Study on the spatial behavior pattern of rural tourists.Will be determined before the spatial behavior of rural tourists types and corresponding data of variance analysis,analysis the differences of the time in the park,leave time,time of tour,moving speed and stop times and so on,so as to determine the spatial behavior patterns.From the perspective of spatial behavior,it divides tourist spatial behavior patterns into fast and slow,travel a part of scenic spots and travel comprehensive scenic spots,based on the further explore of different types of rural tourist spatial behavior model,it can be divided into rural characteristic cultural experience-quick part tour type,rural natural scenery experience-slow part tour type,the countryside recreation activity experience-fast comprehensive tour type,rural social life experience-slow comprehensive tour type.The results show that rural tourists are composed of groups with different tourism motives and different spatial characteristics.Therefore,on the basis of the research results,this paper puts forward some suggestions for the development of rural tourism planning and product development in different types of rural tourists.The method of combining GPS and questionnaire in this study has certain advantages in data accuracy compared with traditional data acquisition methods.In the future,the study of tourist spatial behavior based on digital footprint will become a new research trend and a hot spot.
Keywords/Search Tags:Digital footprint, Rural tourist, Spatial behavior
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