| Continuous technological advancements,such as high-speed railways,have led to more frequent tourist flows through the diversification,rapidity,and convenience of transportation.As a result,the spatial interaction of tourism elements has grown stronger,leading to the continuous reconstruction of the spatial structure and element configuration of tourism destinations.The communication and interaction among tourists across regions also promote the evolution of the spatial structure of destination cities and even reconstruct their functions and positioning.In this context,tourist flows have become a core issue in tourism geography,and tourist mobility is an important factor affecting changes in the territorial spatial structure within a region.Regional tourism now faces new opportunities as well as new challenges.The relationship between tourist flows among different tourism destinations and the relationships between tourists and destinations have become a focal point of attention for tourism enterprises.There is an urgent need for theoretical and empirical research support,which is not only a significant practical requirement for regional tourist flows,but also an important scientific proposition for regional tourism research.To enhance the scope and depth of research on tourist flows in major tourist destinations and to offer guidance on the optimization of spatial organization and destination development,this study encompasses the Northeast China.By combining network data and statistical data,we apply exploratory spatial analysis,network analysis,machine learning,and natural language processing techniques to comprehensively investigate and analyze the patterns,processes,modes,mechanisms,and routes of tourist flows in the region from 2000 to 2022,taking into account both source-destination relationships and flow channels.The study uncovers the following discoveries:(1)The evolution of tourist flows at a large scale demonstrates differences and complexities in terms of geographic distribution.The significance of cities is measured through their degree centrality,closeness centrality,and betweenness centrality in the tourism flow network.Major hub cities like Harbin,Changchun,Shenyang and Dalian have a substantial impact on tourist flows of other cities.Conversely,smaller and less conspicuous cities,such as Liaoyuan,Liaoyang,Siping and Fuxin,have a weaker influence in the network.At the meso scale,the connectivity pattern of tourist flow nodes has altered from random connections to a multi-core linear network.Contact strength has gradually increased and developed towards balance.Additionally,cities in the Northeast China can be classified into3-4 clusters based on the grouping principle.Cities within each cluster tend to adhere to the neighboring principle rather than the proximity principle.At the micro scale,the tourist flow network can be divided into two stages: an early disturbance period and a later stable period.The correlation coefficient of the node importance profile indicates that the network structure is gradually stabilizing,and the distribution of node importance is becoming stable too.This new foundation and reference framework provides insight into the evolution patterns and optimization strategies.(2)Over time,the tourist source market in the Northeast China has gradually expanded to the entire country,but distance decay still plays a significant role.The source market is gradually shifting to lower-level cities,but high-level cities remain the main source of tourists.Geographic distance also has a significant impact on the source market,as it is mainly concentrated within 600 kilometers of the Northeast China and focused on nearby markets.Beyond 600 kilometers,the number of tourists gradually decreases,and beyond 1000 kilometers,the number is even smaller.Therefore,in order to expand the tourism market and target customers effectively,both of these factors need to be considered carefully.(3)Objective and subjective factors both play important roles in influencing tourist flow in the Northeast China.Objective factors include the structure and nodes of the tourist flow.The structure is influenced by spatial proximity,tourism resource endowments,tourism income,information exchange level,transportation accessibility,and policies.The nodes are influenced by the destination’s socio-economic conditions,population size,infrastructure,and the level of the tourist source city and industrial structure.These factors have complex and non-linear effects on tourist flow nodes.Subjective factors are influenced by tourist preferences and emotional profiles.These include the number of travelers,time,type of attractions,service level,local culture,and perception of the tourist.Different tourism resources have significantly different effects on tourists’ emotional profiles.For instance,natural ecological and historical cultural tourism resources have a high centrality,and tourists tend to focus on their attractions.Moreover,emotional expression varies among tourists visiting different types of attractions.These factors can directly or indirectly affect tourists’ perceptions,thus influencing their travel behavior and ultimately impacting the spatial structure of the tourist flow.(4)The tourist flow mechanism involves interactions and mutual influences among the demand system,supply system,and carrying capacity system.The demand system includes both endogenous and exogenous driving forces.The supply system comprises four elements:transportation,accommodation,attractions,and tourism regulations.The tourism carrying capacity system refers to the material conditions that facilitate the smooth operation of tourist flow,including tourism destinations,infrastructures,and transportation.The interactions among these systems collectively constitute the tourism system,which deepens our understanding of the role of tourist flow in the tourism system.This provides a scientific,systematic,and comprehensive reference for planning and decision-making in tourism regions.(5)The current study has identified numerous challenges that impede the growth of the tourism industry in the Northeast China.Firstly,a “Matthew Effect” resulting from the high tourist demand in major cities has created a significant imbalance in the supply and demand of low-level cities,causing inadequate incentives for their tourism development.Secondly,the radiative driving effect of major cities on the surrounding lower-level cities has limitations,and there is evidence of a siphoning effect.Finally,tourism products in the Northeast China are relatively uniform,with insufficient service quality and a lack of cultural characteristics.To address these issues,this study proposes strategies to promote tourism development in Northeast China. |
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