| Since the completion of the wuhan-guangzhou high-speed railway in 2009,China has officially entered the high-speed railway era.The era of high-speed rail is an era that greatly shortens the travel time and space,greatly shortening the transportation time between regions.Making people feel that the space distance between the two places is reduced.So the time-space compression effect is obvious.The construction of high-speed rail in China not only fundamentally alleviated the pressure of the Spring Festival travel rush,but also on all walks of life has a huge impact.'High-speed rail tourism' has also emerged as a new highlight of tourism,and many tourists choose to travel along the route by high-speed rail.With the continuous construction of high-speed rail,high-speed rail tourism has been popularized in many regions,and high-speed rail tourism has gradually become a popular tourism mode.People will leave traces of data when they search for information and web pages on the Internet.That allows us to analyze their preferences and demands.Tourist will search kinds of information about the destination online before the trip.They might share their experience on the Internet when they finished the trip.These data related to tourism activities we called digital footprint of tourism.The reliance of mobile made people leave digital footprints when they travel.Which are used in scientific research because of their authentic and credible characteristics.Through the perspective of digital footprint,this paper studies the change of tourist market structure caused by the high-speed railway.Focus on the change of tourist behavior,and provides suggestions for the development of tourist destinations,which is significant to the development of high-speed railway tourism.With the rapid development of the network,the network has become the carrier of massive information storage.For this reason,the focused crawler of directed crawling web page arises at the right moment.Python,as a computer programming language,has been gradually applied to crawling web data with the addition of functions.Python coding can select specific parts of the web content and set rules for circular crawling of the web page,which provides an accurate and high school method for the acquisition of the digital footprint.This article selects the typical city of huangshan city as a case to quality tourism resources,such as ctrip,hornet's nest mainstream reviews and social platform website is a collection of tourist travel,eligible travel by Python and scraping of the page text,to changes in customer market analysis and the use of tourists attracted radius curve analysis,and targeted marketing management Suggestions to the huangshan city tourism development.This paper expounds the influence of high-speed rail opening on the structure of passenger market from three perspectives,explores its mechanism analysis and studies the interaction mechanism between influencing factors.This paper mainly includes three parts,specific as follows:the first part(chapter 1 and chapter 2),the part is basic theory part of the thesis,the first chapter is the introduction,this part from era background analysis the paper selected topic background and the topic selection basis,this paper expounds the thesis related concepts involved,and to define the research object,defining the scope of study,and expounded in this paper,the research method adopted,the process of research methods and significance.The second part(chapter 3,chapter 4 and chapter 5)is an empirical study,this part is the core content of this article,mainly expounds the data acquisition and processing steps,from three aspects:analyzing the change of the tourism market structure,then analyzes its main influencing factors,through geographical probe method and mechanism of interaction between the factors.The third part(chapter six)is the conclusion and Suggestions of this paper.This part puts forward some Suggestions based on the content of the previous chapter,summarizes the research results of this paper,points out the existing deficiencies of this study,and puts forward new problems and new ideas that should be paid attention to in the future research in related directions.In this paper,the main conclusions are:(1)from the point of tourist market attracting radius,based on digital footprint of huangshan city high iron tourist flow has a wide distribution and tourism market space structure,the opening of the high-speed rail to group time compression effect is obvious,over a long distance to close group time compression effect,high iron accounts for the vast majority of the endpoint and the surrounding provinces and cities.(2)from the perspective of the cumulative space use curve,after the opening of the high-speed rail,the tourist market space scope such as 60%and 80%of the tourist market has a trend of outward expansion.(3)from the perspective of the spatial attraction of tourist source market,the opening of high-speed rail improves accessibility and increases the attraction of tourist destinations.The farther the distance from tourist destinations,the more significant the change of attraction is before and after the opening of high-speed rail.(4)from the perspective of transit node,hefei,as the starting point of he-fu high-speed railway,replaces hangzhou as an important node for long-distance tourists to enter huangshan mountain.Besides,shangrao,wuyuan and other places along the high-speed railway have significantly improved their status as transit nodes,and the aggregation effect of tourist destinations is significant.(5)the interaction between various influencing factors,formation mechanism of the effect of high-speed rail travel:the rapid development of the economy makes to raise the level of disposable income and high-speed rail construction and the improvement of their own needs,the government's attention and promotion,high-speed rail travel,external cause under the effect of rapid development,through the interaction of various impact factors to lead to more high iron tourist activities,the influence mechanism is a process of accumulation of cause and effect. |
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