The Meaning Construction, Evolution And Driving Mechanism Of Mountain Biking Tourism Spatial Behavio

In the post-epidemic era,leisure and outdoor activities have become the preferred choices for daily tourist activities.Guizhou Province took the opportunity of the International Mountain Tourism Conference to vigorously promote the development of mountain tourism,and the "flowing turn" of social science research has promoted the innovation of the research paradigm of tourism.Based on this,this study covers multiple data sources such as travelogue data,GPS trajectory data,macro statistical data,and satellite remote sensing data,and uses qualitative and quantitative methods such as grounded theory,GIS spatial analysis,complex network analysis,and geodetector to systematically reveal the flow process,evolution rules,and evolution mechanism of space behavior in mountain biking tourism.The research findings will further deepen the theoretical study of this special type of mountain tourism destination and promote the high-quality development of the tourism industry in mountainous tourism destinations,which will drive the high-quality development of the entire province.This study has drawn the following three conclusions:(1)By using rooted theory analysis method and coding progressively,the research question of "why tourists go mountain biking in the mountains" can be solved.Moreover,this research explores the way that the meaning of mountain biking tourism is constructed in the process of flow.It has been found that the flow process of mountain biking tourism in a mountainous environment involves four stages: situational guidance,emotional response,emotional expression,and self-purification.The way of constructing the meaning of the flow of mountain biking tourism in the mountains includes three experiential paths: perception filling,meaning production,and relationship construction.(2)Through spatiotemporal analysis,we address the research question of what characteristics are exhibited by cycling tourism activities in space,and summarize the spatiotemporal patterns of cycling tourism development.The research reveals that mountain cycling tourism has the characteristics of short-distance,short-duration,seasonality,and volatility,with the high and low seasons being summer and winter,respectively.The spatial distribution of mountain cycling tourism trails exhibits a "central-peripheral" structure,with Guiyang counties always having strong radiation force,while Renhuai and Xishui gradually become radiation centers.The spatial structure of cycling tourism changes from "points" to "axes" and then to "networks",and the development process is based on traffic routes to form a point-axis development mode,where several points near the core area and axis form a growth pole.(3)The problem of "how the spatial characteristics of mountain bike tourism are formed" is solved by constructing the influencing factor model.The study found that over time,the effect of each factor showed an increasing trend and became more significant.In the early stages,factors such as altitude and terrain had a greater impact,while in the later stages,factors such as urban vitality,tourism industry foundation,and ecological environment had a greater impact.All factors interacted to show a dualfactor enhancement or nonlinear enhancement effect.The mechanism of spatial differentiation of mountain bike tourism by analyzing the subject of mountain bike tourists is as follows: social environmental factors are the core driving force for spatial differentiation,industrial foundation is the centripetal force for spatial differentiation,mountain natural conditions are the basic constraint force for the formation of spatial differentiation pattern,and ecological natural environment is the important supporting force that affects the spatial differentiation pattern of mountain bike tourism.Cycling,camping and other niche forms of travel are receiving increasing attention.Using travelogue data can elucidate the flow process of cycling tourism in mountainous environments.GPS trajectory data that records real-time location information can visualize tourism behavior into spatial dynamic graphics.The limitation of this study is that the research content is biased towards overall analysis of the groups,while ignoring the social demographic information of cycling tourists,such as age,gender,and economic level.Future research will attempt to subgroup user groups for further exploration.