北京入境集聚扩散旅游流时空演变规律及动力机制研究
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摘要
旅游流作为旅游学研究的重点内容,多年来一直受到国内外学者的关注,在理论和实践方面都取得了丰硕的成果。随着我国改革开放政策的实施,入境旅游业更是取得了快速稳固的发展,从发展趋势来看,我国入境旅游业未来还将有更广阔的发展前景。而北京作为我国政治文化中心和七大古都之一,入境旅游人数和收入长期以来一直在我国居于首位,因此选择北京入境旅游流为对象,对其时空演化规律及机理进行系统全面的分析,一方面将对旅游学、旅游地理学理论起到一定的丰富和完善作用,另一方面也将从实践方面为我国旅游产业发展、旅游管理、旅游资源开发规划、旅游市场拓展、区域旅游形象塑造、游客管理等提供科学依据,为旅游产品及路线设计提供指导意见,辅助政府部门进行科学决策。
文章依托国家自然科学基金项目《中国典型区域入境旅游流东－西递进演化机理研究》(NO.40771058),在界定我国典型旅游区的基础上,利用2008年作者参与调查的全国13个入境旅游省市7379份有效市场调查数据和多年来国家权威部门入境旅游统计数据,从旅游流流量、流向、流质和流势四方面分析了北京入境集聚扩散流在国际、典型区之间、典型区内部三个尺度上的时空演化规律,并运用归纳法和专家打分法,从北京入境集聚扩散旅游流特征中总结出影响入境旅游流集聚扩散的核心因素。分析了不同流质北京入境集聚扩散流所受内推力、外推力、拉力、阻力及总动力,同时借助系统动力学模型分析了旅游流所受动力之间的内在耦合关系。在分析各典型省市入境旅游流核心影响因素发展趋势的基础上,运用时间序列分析、多元回归分析和BP神经网络等方法模拟了北京集聚扩散旅游流流量发展趋势,最后,文章结合北京入境集聚扩散旅游流的特征及动力机制结论提出了一些有针对性的旅游流系统管理调控策略。
本文分别从北京集聚扩散旅游流特征、旅游流动力机制以及旅游流预测和调控方面得出如下结论：
一是北京集聚扩散旅游流特征方面。北京的集聚流主要是直接源自客源国的入境旅游流,流向方面主要表现为日韩→北京、北美→北京、欧洲→北京三条入境流。从北京国内典型区的集聚旅游流来看,北向集聚流显著强于东向集聚流。其中上海→北京、广东→北京入境旅游流是北京集聚流中流量最大的两条旅游流。从各集聚流所占北京总体集聚流比例发展趋势来看,国际集聚流层面上,日韩、东南亚集聚流的所占比例呈下降趋势,北美、欧洲和大洋洲集聚流呈现递增趋势。从典型省市层面来看,上海、广州、贵州、河北和辽宁集聚流均呈现递减趋势,而江苏、浙江、福建、广西、陕西、四川、重庆、云南、天津和山东集聚流均呈现递增趋势,总体呈现出区域均衡发展的趋势。流质方面不同群体和不同流向集聚流之间存在一定差异,总体表现为以无旅华经历的25-44岁的单身男性游客为主,职业以专业技术人员为主,学历以大专及本科为主；从北京集聚流流势对比来看,国际层面上,日韩依然是北京强势集聚流,而从发展趋势来看,欧洲、北美及大洋洲集聚流增长速度较快。从典型省市层面来看,上海和广东流向北京的集聚流流势长期以来一直是最强流势集聚流。从集聚流流势发展趋势来看,北京集聚流流势总体呈现出增长趋势,仅有贵州和福建出现一定的下降趋势；
从北京扩散旅游流来看,占北京扩散流比例最大的几条旅游流分别为北京→上海、北京→广东、北京→广西和北京→陕西,流势方面北京→上海扩散流的流势相对最强。从北京入境扩散流的二级扩散分析来看,北京的二级扩散流中东部沿海典型旅游区绝大部分是直接出境,而西部典型旅游区二级扩散流向总体呈现出国内东向流动趋势。从各扩散流所占北京总体扩散流比例发展趋势来看,除了北京→山东扩散流所占比例有所下降外,扩散到各典型省市的流量所占比例均呈现递增趋势；流质方面同样是不同群体和不同流向扩散流之间存在一定差异,但总体和北京集聚流流势相似；从北京扩散流流势对比来看,北京扩散到上海的流势长期以来一直是最强的,属于极强流势扩散流。从发展趋势来看,北京扩散到长三角典型旅游区的流势总体呈现出逐年递增的趋势。而北京扩散到珠三角典型旅游区的流势呈现出递减趋势。北京扩散到大西安、蜀渝和云贵等典型旅游区旅游流流势也总体呈现递增趋势。
从北京集聚扩散旅游流平衡点转移规律来看,总体表现出逐年向北京趋近的态势,说明北京扩散旅游流增长趋势强于集聚旅游流增长趋势。网络分析的中心性、中介性和结构洞均体现出北京在我国入境旅游市场中具有重要的地位和作用；总体来看,北京集聚扩散入境旅游流在时空方面表现出明显的经济导向性、区位导向性、资源导向性。而旅游流多年发展趋势表现出,北京扩散效应逐年增强,而集聚效应相对在逐年减弱。
二是旅游流动力机制方面。从旅游流特征中可以总结出入境集聚扩散流所受影响因素主要包括旅游者系统、旅游产业系统、旅游经济系统、其他影响因素等4个方面。根据四个旅游流影响系统作用力方式将旅游流动力机制归纳为：由内推力、外推力、拉力和阻力组合而成的一个自组织复杂综合动力系统。其中源自游客自身的内驱力是入境旅游流西向扩散的核心动力,而源自旅游地资源的拉力是西向扩散的必要动力,源自旅游通道的摩擦力或助动力是入境旅游流西向扩散的阻力。从北京入境集聚扩散流所受动力大小总体来看,拉力因素是旅游流所受动力中相对最大的动力因素,而阻力作用均相对较小。其中北京的集聚扩散流总动力得分均在5-10分之间,均属于较大动力。从北京入境集聚流和入境扩散流总动力对比来看,北京入境扩散流总动力相对较大,这也正好说明北京入境旅游流的扩散效应强于其集聚效应,而且在不断扩大。
三是旅游流流量预测及调控策略方面。从北京集聚扩散旅游流预测结果来看,未来北京集聚旅游流和扩散流流量还将呈现出增长的趋势,其中扩散流的增长速度将高于集聚流,东部典型旅游区增长速度高于西部典型旅游区。最后文章根据旅游流与各个因素之间的关系及发展趋势提出在保持北京与东部典型区之间旅游流快速发展的前提下,大力发展北京与西部典型旅游区之间的入境旅游流。具体提出从旅游产业、旅游市场营销和旅游经济三个大的方面对北京集聚扩散旅游流进行管理调控。
本文在撰写过程中,主要在以下三个方面取得了一定创新：
研究方法方面,将物理学理论及方法运用到我国入境旅游流研究中。文章借助物理学中的静止势能、杠杆原理和受力分析分别研究了北京集聚扩散旅游流流势、平衡点演变规律和动力机制。
研究视角方面,采用了多角度细化的研究视角。首先,将北京入境旅游流分为集聚流和扩散流两个方面,分别从国际、典型区间、典型旅游区内部3个层面分析其流量、流向、流质和流势4个特征,从而总结出北京集聚扩散旅游流时空演化规律；其次,将北京集聚扩散旅游流动力机制分为内推力、外推力、拉力、阻力和合力5个方面,分别从不同旅游方式、不同性别、不同年龄段、不同年收入、不同文化背景和不同典型旅游区6个角度进行分析。
研究内容方面,系统界定了中国典型旅游区范围及内涵,提出了多级递减集聚扩散入境旅游流模式；在传统的旅游流流量、流向和时间的基础上提出流质和流势两个特征因素；系统分析了入境集聚扩散旅游流影响因素,并构建了由内推力、外推力、拉力、阻力和合力组成的旅游流动力机制；提出入境旅游流调控概念、方法及战略。
As one of the hot spots in tourism research, the study of tourists flow concerns researchers home and abroad for years. With the implementation of reform and opening-up policy, the inbound tourism of China has developed rapidly and is promising as well. Being the political and cultural center of china, as well as a famous ancient capital, Beijing has long been at the top of China in terms of inbound tourists and receipts. So to study the tempo-spatial variation and dynamic mechanism of the inbound aggregating and diffusing tourists flows of Beijing are essential and significant, which not only contributes to the theories of Tourism and Tourism Geography, but also provides scientific basis for the practice of tourism industry, tourism resource planning and exploitation, tourism marketing, regional tourism image building, tourist management, tourism products and routes designing.
Supported by the National Natural Science Foundation [Project The Study of the East-West Progressive and Evolutional Mechanism of Inbound Tourists Flow of Representative Regions in China (NO.40771058)] and based on the statistical data of the National Tourism Administration of the PR China, this dissertation first defines the representative tourism regions of China, then with the aspects of quantity, market structure, direction and potential energy, the tempo-spatial variation of Beijing inbound aggregating and diffusing tourists flows is analyzed, including international, inter-region and inner-region tempo-spatial variation. With the use of Induction and Delphi Method, the core influential factors of inbound aggregating and diffusing tourists flows are concluded. As to the quantitative analysis of dynamic mechanism of tourists flow※(data sources:market research on 13 inbound tourism destination in China,2008) This dissertation analyzed the internal thrust, external thrust, pull, push and motive power of Beijing inbound aggregating and diffusing tourists flows with different market structures,and using the systematic dynamic model,the internal relation among those powers is also discussed. Besides, the trend of the quantity of Beijing inbound aggregating and diffusing tourists flows is simulated based on Time Series Analysis, Back-Propagation Artificial Neural Networks and Multiple Regression Analysis. From above, strategies for regulating and controlling the tourists flow are suggested.
According to the characteristics of aggregating and diffusing tourists flows of Beijing, the dynamic mechanism of tourists flow and the forecasting and controlling strategy of tourists flow, this dissertation draws three conclusions as below.
Firstly, on the characteristics of aggregating and diffusing tourists flows of Beijing. The aggregating flows in Beijing are mainly inbound tourists flows from source countries, including Japan and South Korea→Beijing, North America→Beijing and Europe→Beijing. As to the aggregating flows in Beijing from representative domestic tourism regions, aggregating flow from the north was significantly stronger than that from the east. Among them, Shanghai→Beijing and Guangdong→Beijing tourists flows are the largest ones. As to the developing trend of the aggregating flows of Beijing, on one hand, on the international level, the proportion of aggregating flows from Japan, South Korea and Southeast Asia shows a declining trend, while it from North America, Europe and Oceania shows an increasing trend. On the other hand, on the representative tourism regions level, aggregating flows from Shanghai, Guangzhou, Guizhou, Hebei and Liaoning show a declining trend, while those from Jiangsu, Zhejiang, Fujian, Guangxi, Shaanxi, Sichuan, Chongqing, Yunnan, Tianjin and Shandong show an increasing trend. In aspect of the tourists flow's market structure, there are some differences among different groups and different directions of aggregating flows. In general, it shows that people who don't have visiting experience in China are mainly single male, whose occupation are mainly professional and technical personnel, and whose educational level are mainly college degree and bachelor degree. As to the comparison among the aggregating flows'potential energy of Beijing, on one hand, on the international level, the aggregating flows from Japan and South Korea are still the major ones, while those from North America, Europe and Oceania have a higher growth rate. On the other hand, on the representative tourism region level, the potential energy of aggregating flows from Shanghai and Guangdong has been the strongest for a long time. As to the developing trend of aggregating flow's potential energy, Beijing's shows an increasing trend generally, while Guizhou's and Fujian's show a declining trend. As to the diffusing flows of Beijing, the largest ones are Beijing→Shanghai, Beijing→Guangdong, Beijing→Guangxi and Beijing→Shaanxi. Among them, Beijing→Shanghai tourists flow has the strongest potential energy. As to the secondary analysis of Beijing inbound diffusing flow, for most representative eastern tourism regions, the secondary diffusing flows are direct outbound, while the secondary diffusing flows of representative western tourism regions generally show the trend of flowing to the east domestically. As to the developing trend of the diffusing flows of Beijing, there is an increasing trend of the diffusing tourists flows from Beijing to other representative tourism regions, except to Shandong. In aspect of the tourists flow's market structure, there are also some differences among different groups and different directions of diffusing flows, but on the whole, it is similar to the potential energy of Beijing aggregating flow. As to the comparison among the diffusing flows' potential energy of Beijing, Beijing to Shanghai is always the strongest, which belongs to the diffusing flow with strongest potential energy. As to the developing trend of diffusing flow's potential energy, the potential energy of Beijing spreading to the Yangtze River Delta region generally shows an increasing trend in recent years, while that of Beijing spreading to the Pearl River Delta region shows a declining trend. Besides, the potential energy of Beijing spreading to Big Xi'an, Sichuan, Chongqing, Yunnan and Guizhou representative tourism regions show an increasing trend.
According to the variation of the fulcrum between Beijing aggregating and diffusing tourists flows, it shows that tourists flows are approaching Beijing year by year, so the increasing trend of diffusing flow is stronger than aggregating flow. The Network Analysis of centrality, intermediary and structural holes indicates that Beijing plays an important role in Chinese inbound tourism industry. Generally, the tempo-spatial variation of the inbound aggregating and diffusing tourist flows of Beijing shows the orientation of economy, location and resource. For years, the developing trend of tourists flows of Beijing indicates that the diffusing effect is gradually strengthening, while the aggregating effect is weakening year by year.
Secondly, on the dynamic mechanism of tourists flow. The inbound aggregating and diffusing tourists flow are influenced by four factors as tourists, tourism industry, tourism economy and other influential system. Based on the four influential systems, the dynamic mechanism of tourists flow can be reduced to a complex self-organizing dynamic mechanism made up of internal push, external push, pull, resistance and motive power. The internal thrust from tourists themselves is the central power for inbound tourists flows to diffuse to the west, and the pull from tourism attractions is the essential power, whereas the friction force from tourism channels is the push for inbound tourists flows to diffuse to the west. As to the case of inbound aggregating and diffusing tourists flow of Beijing, the pull is comparatively the strongest in all motive powers of tourists flow, and the push is weaker. The score of the motive power of aggregating and diffusing tourists flow of Beijing is between 5 to 10, which belongs to the major motive power. Comparing the motive power of aggregating flow with that of diffusing flow, the motive power of diffusing flow is stronger, which shows that the diffusing effect of Beijing inbound tourists flow is stronger than the aggregating effect, and it is strengthening continuously.
Thirdly, on forecasting and controlling the quantity of tourists flow. From the prediction of the quantity of aggregating and diffusing flows of Beijing, the quantity will show an increasing trend, and the growth rate of diffusing flow will be higher than that of aggregating flow, and eastern region's growth rate will be higher than western region's. Finally, this dissertation suggests developing the tourists flow between Beijing and western region while maintaining the development of tourism flow between Beijing and eastern region. The regulation and control of tourists flow should be made in terms of tourism industry, tourism marketing and tourism economy.
Innovations are made mainly from the three aspects below in this dissertation.
As to the research methods, the Theory of Leverage in Physics has been introduced to study the tempo-spatial variation of the fulcrum between Beijing aggregating and diffusing tourists flows. Force Analysis has been used to study the motive power of aggregating and diffusing tourists flows of Beijing, Systematic Dynamics has been applied to analyze the relations among the powers of tourists flow, and Back-Propagation Artificial Neural Networks has been used to forecast the quantity of aggregating and diffusing tourists flow.
As to the research aspects, this research divided the inbound tourists flows of Beijing into aggregating tourists flow and diffusing tourists flow. The characteristics of tourists flow has been analyzed from the following four aspects of quantity, direction, market structure and potential energy, and the international, inter-region and inner-region tempo-spatial variation are all included. The dynamics of tourists flow has been divided into 5 aspects as internal push, external push, pull, resistance and motive power, and Force Analysis are made on different ways of traveling, genders, ages, incomes, culture backgrounds and representative tourism regions.
As to the research contents, the research defined the range and connotation of representative tourism region in China, and suggested that the inbound tourists flow of China be a multi-level declining pattern of aggregation and diffusion. The research introduced market structure and potential energy as two characteristics of tourists flow based on quantity, direction and time. The influential factors have been analyzed systematically, and classified as internal push, external push, pull, resistance and motive power. The research has forecasted the quantity of aggregating and diffusing tourists flows of Beijing, and the controlling strategy of tourists flow has been proposed.
文章依托国家自然科学基金项目《中国典型区域入境旅游流东－西递进演化机理研究》(NO.40771058),在界定我国典型旅游区的基础上,利用2008年作者参与调查的全国13个入境旅游省市7379份有效市场调查数据和多年来国家权威部门入境旅游统计数据,从旅游流流量、流向、流质和流势四方面分析了北京入境集聚扩散流在国际、典型区之间、典型区内部三个尺度上的时空演化规律,并运用归纳法和专家打分法,从北京入境集聚扩散旅游流特征中总结出影响入境旅游流集聚扩散的核心因素。分析了不同流质北京入境集聚扩散流所受内推力、外推力、拉力、阻力及总动力,同时借助系统动力学模型分析了旅游流所受动力之间的内在耦合关系。在分析各典型省市入境旅游流核心影响因素发展趋势的基础上,运用时间序列分析、多元回归分析和BP神经网络等方法模拟了北京集聚扩散旅游流流量发展趋势,最后,文章结合北京入境集聚扩散旅游流的特征及动力机制结论提出了一些有针对性的旅游流系统管理调控策略。
本文分别从北京集聚扩散旅游流特征、旅游流动力机制以及旅游流预测和调控方面得出如下结论：
一是北京集聚扩散旅游流特征方面。北京的集聚流主要是直接源自客源国的入境旅游流,流向方面主要表现为日韩→北京、北美→北京、欧洲→北京三条入境流。从北京国内典型区的集聚旅游流来看,北向集聚流显著强于东向集聚流。其中上海→北京、广东→北京入境旅游流是北京集聚流中流量最大的两条旅游流。从各集聚流所占北京总体集聚流比例发展趋势来看,国际集聚流层面上,日韩、东南亚集聚流的所占比例呈下降趋势,北美、欧洲和大洋洲集聚流呈现递增趋势。从典型省市层面来看,上海、广州、贵州、河北和辽宁集聚流均呈现递减趋势,而江苏、浙江、福建、广西、陕西、四川、重庆、云南、天津和山东集聚流均呈现递增趋势,总体呈现出区域均衡发展的趋势。流质方面不同群体和不同流向集聚流之间存在一定差异,总体表现为以无旅华经历的25-44岁的单身男性游客为主,职业以专业技术人员为主,学历以大专及本科为主；从北京集聚流流势对比来看,国际层面上,日韩依然是北京强势集聚流,而从发展趋势来看,欧洲、北美及大洋洲集聚流增长速度较快。从典型省市层面来看,上海和广东流向北京的集聚流流势长期以来一直是最强流势集聚流。从集聚流流势发展趋势来看,北京集聚流流势总体呈现出增长趋势,仅有贵州和福建出现一定的下降趋势；
从北京扩散旅游流来看,占北京扩散流比例最大的几条旅游流分别为北京→上海、北京→广东、北京→广西和北京→陕西,流势方面北京→上海扩散流的流势相对最强。从北京入境扩散流的二级扩散分析来看,北京的二级扩散流中东部沿海典型旅游区绝大部分是直接出境,而西部典型旅游区二级扩散流向总体呈现出国内东向流动趋势。从各扩散流所占北京总体扩散流比例发展趋势来看,除了北京→山东扩散流所占比例有所下降外,扩散到各典型省市的流量所占比例均呈现递增趋势；流质方面同样是不同群体和不同流向扩散流之间存在一定差异,但总体和北京集聚流流势相似；从北京扩散流流势对比来看,北京扩散到上海的流势长期以来一直是最强的,属于极强流势扩散流。从发展趋势来看,北京扩散到长三角典型旅游区的流势总体呈现出逐年递增的趋势。而北京扩散到珠三角典型旅游区的流势呈现出递减趋势。北京扩散到大西安、蜀渝和云贵等典型旅游区旅游流流势也总体呈现递增趋势。
从北京集聚扩散旅游流平衡点转移规律来看,总体表现出逐年向北京趋近的态势,说明北京扩散旅游流增长趋势强于集聚旅游流增长趋势。网络分析的中心性、中介性和结构洞均体现出北京在我国入境旅游市场中具有重要的地位和作用；总体来看,北京集聚扩散入境旅游流在时空方面表现出明显的经济导向性、区位导向性、资源导向性。而旅游流多年发展趋势表现出,北京扩散效应逐年增强,而集聚效应相对在逐年减弱。
二是旅游流动力机制方面。从旅游流特征中可以总结出入境集聚扩散流所受影响因素主要包括旅游者系统、旅游产业系统、旅游经济系统、其他影响因素等4个方面。根据四个旅游流影响系统作用力方式将旅游流动力机制归纳为：由内推力、外推力、拉力和阻力组合而成的一个自组织复杂综合动力系统。其中源自游客自身的内驱力是入境旅游流西向扩散的核心动力,而源自旅游地资源的拉力是西向扩散的必要动力,源自旅游通道的摩擦力或助动力是入境旅游流西向扩散的阻力。从北京入境集聚扩散流所受动力大小总体来看,拉力因素是旅游流所受动力中相对最大的动力因素,而阻力作用均相对较小。其中北京的集聚扩散流总动力得分均在5-10分之间,均属于较大动力。从北京入境集聚流和入境扩散流总动力对比来看,北京入境扩散流总动力相对较大,这也正好说明北京入境旅游流的扩散效应强于其集聚效应,而且在不断扩大。
三是旅游流流量预测及调控策略方面。从北京集聚扩散旅游流预测结果来看,未来北京集聚旅游流和扩散流流量还将呈现出增长的趋势,其中扩散流的增长速度将高于集聚流,东部典型旅游区增长速度高于西部典型旅游区。最后文章根据旅游流与各个因素之间的关系及发展趋势提出在保持北京与东部典型区之间旅游流快速发展的前提下,大力发展北京与西部典型旅游区之间的入境旅游流。具体提出从旅游产业、旅游市场营销和旅游经济三个大的方面对北京集聚扩散旅游流进行管理调控。
本文在撰写过程中,主要在以下三个方面取得了一定创新：
研究方法方面,将物理学理论及方法运用到我国入境旅游流研究中。文章借助物理学中的静止势能、杠杆原理和受力分析分别研究了北京集聚扩散旅游流流势、平衡点演变规律和动力机制。
研究视角方面,采用了多角度细化的研究视角。首先,将北京入境旅游流分为集聚流和扩散流两个方面,分别从国际、典型区间、典型旅游区内部3个层面分析其流量、流向、流质和流势4个特征,从而总结出北京集聚扩散旅游流时空演化规律；其次,将北京集聚扩散旅游流动力机制分为内推力、外推力、拉力、阻力和合力5个方面,分别从不同旅游方式、不同性别、不同年龄段、不同年收入、不同文化背景和不同典型旅游区6个角度进行分析。
研究内容方面,系统界定了中国典型旅游区范围及内涵,提出了多级递减集聚扩散入境旅游流模式；在传统的旅游流流量、流向和时间的基础上提出流质和流势两个特征因素；系统分析了入境集聚扩散旅游流影响因素,并构建了由内推力、外推力、拉力、阻力和合力组成的旅游流动力机制；提出入境旅游流调控概念、方法及战略。
As one of the hot spots in tourism research, the study of tourists flow concerns researchers home and abroad for years. With the implementation of reform and opening-up policy, the inbound tourism of China has developed rapidly and is promising as well. Being the political and cultural center of china, as well as a famous ancient capital, Beijing has long been at the top of China in terms of inbound tourists and receipts. So to study the tempo-spatial variation and dynamic mechanism of the inbound aggregating and diffusing tourists flows of Beijing are essential and significant, which not only contributes to the theories of Tourism and Tourism Geography, but also provides scientific basis for the practice of tourism industry, tourism resource planning and exploitation, tourism marketing, regional tourism image building, tourist management, tourism products and routes designing.
Supported by the National Natural Science Foundation [Project The Study of the East-West Progressive and Evolutional Mechanism of Inbound Tourists Flow of Representative Regions in China (NO.40771058)] and based on the statistical data of the National Tourism Administration of the PR China, this dissertation first defines the representative tourism regions of China, then with the aspects of quantity, market structure, direction and potential energy, the tempo-spatial variation of Beijing inbound aggregating and diffusing tourists flows is analyzed, including international, inter-region and inner-region tempo-spatial variation. With the use of Induction and Delphi Method, the core influential factors of inbound aggregating and diffusing tourists flows are concluded. As to the quantitative analysis of dynamic mechanism of tourists flow※(data sources:market research on 13 inbound tourism destination in China,2008) This dissertation analyzed the internal thrust, external thrust, pull, push and motive power of Beijing inbound aggregating and diffusing tourists flows with different market structures,and using the systematic dynamic model,the internal relation among those powers is also discussed. Besides, the trend of the quantity of Beijing inbound aggregating and diffusing tourists flows is simulated based on Time Series Analysis, Back-Propagation Artificial Neural Networks and Multiple Regression Analysis. From above, strategies for regulating and controlling the tourists flow are suggested.
According to the characteristics of aggregating and diffusing tourists flows of Beijing, the dynamic mechanism of tourists flow and the forecasting and controlling strategy of tourists flow, this dissertation draws three conclusions as below.
Firstly, on the characteristics of aggregating and diffusing tourists flows of Beijing. The aggregating flows in Beijing are mainly inbound tourists flows from source countries, including Japan and South Korea→Beijing, North America→Beijing and Europe→Beijing. As to the aggregating flows in Beijing from representative domestic tourism regions, aggregating flow from the north was significantly stronger than that from the east. Among them, Shanghai→Beijing and Guangdong→Beijing tourists flows are the largest ones. As to the developing trend of the aggregating flows of Beijing, on one hand, on the international level, the proportion of aggregating flows from Japan, South Korea and Southeast Asia shows a declining trend, while it from North America, Europe and Oceania shows an increasing trend. On the other hand, on the representative tourism regions level, aggregating flows from Shanghai, Guangzhou, Guizhou, Hebei and Liaoning show a declining trend, while those from Jiangsu, Zhejiang, Fujian, Guangxi, Shaanxi, Sichuan, Chongqing, Yunnan, Tianjin and Shandong show an increasing trend. In aspect of the tourists flow's market structure, there are some differences among different groups and different directions of aggregating flows. In general, it shows that people who don't have visiting experience in China are mainly single male, whose occupation are mainly professional and technical personnel, and whose educational level are mainly college degree and bachelor degree. As to the comparison among the aggregating flows'potential energy of Beijing, on one hand, on the international level, the aggregating flows from Japan and South Korea are still the major ones, while those from North America, Europe and Oceania have a higher growth rate. On the other hand, on the representative tourism region level, the potential energy of aggregating flows from Shanghai and Guangdong has been the strongest for a long time. As to the developing trend of aggregating flow's potential energy, Beijing's shows an increasing trend generally, while Guizhou's and Fujian's show a declining trend. As to the diffusing flows of Beijing, the largest ones are Beijing→Shanghai, Beijing→Guangdong, Beijing→Guangxi and Beijing→Shaanxi. Among them, Beijing→Shanghai tourists flow has the strongest potential energy. As to the secondary analysis of Beijing inbound diffusing flow, for most representative eastern tourism regions, the secondary diffusing flows are direct outbound, while the secondary diffusing flows of representative western tourism regions generally show the trend of flowing to the east domestically. As to the developing trend of the diffusing flows of Beijing, there is an increasing trend of the diffusing tourists flows from Beijing to other representative tourism regions, except to Shandong. In aspect of the tourists flow's market structure, there are also some differences among different groups and different directions of diffusing flows, but on the whole, it is similar to the potential energy of Beijing aggregating flow. As to the comparison among the diffusing flows' potential energy of Beijing, Beijing to Shanghai is always the strongest, which belongs to the diffusing flow with strongest potential energy. As to the developing trend of diffusing flow's potential energy, the potential energy of Beijing spreading to the Yangtze River Delta region generally shows an increasing trend in recent years, while that of Beijing spreading to the Pearl River Delta region shows a declining trend. Besides, the potential energy of Beijing spreading to Big Xi'an, Sichuan, Chongqing, Yunnan and Guizhou representative tourism regions show an increasing trend.
According to the variation of the fulcrum between Beijing aggregating and diffusing tourists flows, it shows that tourists flows are approaching Beijing year by year, so the increasing trend of diffusing flow is stronger than aggregating flow. The Network Analysis of centrality, intermediary and structural holes indicates that Beijing plays an important role in Chinese inbound tourism industry. Generally, the tempo-spatial variation of the inbound aggregating and diffusing tourist flows of Beijing shows the orientation of economy, location and resource. For years, the developing trend of tourists flows of Beijing indicates that the diffusing effect is gradually strengthening, while the aggregating effect is weakening year by year.
Secondly, on the dynamic mechanism of tourists flow. The inbound aggregating and diffusing tourists flow are influenced by four factors as tourists, tourism industry, tourism economy and other influential system. Based on the four influential systems, the dynamic mechanism of tourists flow can be reduced to a complex self-organizing dynamic mechanism made up of internal push, external push, pull, resistance and motive power. The internal thrust from tourists themselves is the central power for inbound tourists flows to diffuse to the west, and the pull from tourism attractions is the essential power, whereas the friction force from tourism channels is the push for inbound tourists flows to diffuse to the west. As to the case of inbound aggregating and diffusing tourists flow of Beijing, the pull is comparatively the strongest in all motive powers of tourists flow, and the push is weaker. The score of the motive power of aggregating and diffusing tourists flow of Beijing is between 5 to 10, which belongs to the major motive power. Comparing the motive power of aggregating flow with that of diffusing flow, the motive power of diffusing flow is stronger, which shows that the diffusing effect of Beijing inbound tourists flow is stronger than the aggregating effect, and it is strengthening continuously.
Thirdly, on forecasting and controlling the quantity of tourists flow. From the prediction of the quantity of aggregating and diffusing flows of Beijing, the quantity will show an increasing trend, and the growth rate of diffusing flow will be higher than that of aggregating flow, and eastern region's growth rate will be higher than western region's. Finally, this dissertation suggests developing the tourists flow between Beijing and western region while maintaining the development of tourism flow between Beijing and eastern region. The regulation and control of tourists flow should be made in terms of tourism industry, tourism marketing and tourism economy.
Innovations are made mainly from the three aspects below in this dissertation.
As to the research methods, the Theory of Leverage in Physics has been introduced to study the tempo-spatial variation of the fulcrum between Beijing aggregating and diffusing tourists flows. Force Analysis has been used to study the motive power of aggregating and diffusing tourists flows of Beijing, Systematic Dynamics has been applied to analyze the relations among the powers of tourists flow, and Back-Propagation Artificial Neural Networks has been used to forecast the quantity of aggregating and diffusing tourists flow.
As to the research aspects, this research divided the inbound tourists flows of Beijing into aggregating tourists flow and diffusing tourists flow. The characteristics of tourists flow has been analyzed from the following four aspects of quantity, direction, market structure and potential energy, and the international, inter-region and inner-region tempo-spatial variation are all included. The dynamics of tourists flow has been divided into 5 aspects as internal push, external push, pull, resistance and motive power, and Force Analysis are made on different ways of traveling, genders, ages, incomes, culture backgrounds and representative tourism regions.
As to the research contents, the research defined the range and connotation of representative tourism region in China, and suggested that the inbound tourists flow of China be a multi-level declining pattern of aggregation and diffusion. The research introduced market structure and potential energy as two characteristics of tourists flow based on quantity, direction and time. The influential factors have been analyzed systematically, and classified as internal push, external push, pull, resistance and motive power. The research has forecasted the quantity of aggregating and diffusing tourists flows of Beijing, and the controlling strategy of tourists flow has been proposed.
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