本文選題：鄉(xiāng)村旅游　切入點(diǎn)：網(wǎng)絡(luò)關(guān)注度　出處：《上海師范大學(xué)》2017年碩士論文

【摘要】：鄉(xiāng)村旅游是近年來旅游研究的熱點(diǎn)之一,本文在前人研究的基礎(chǔ)上探究國內(nèi)鄉(xiāng)村旅游網(wǎng)絡(luò)關(guān)注度、虛擬信息流時(shí)空網(wǎng)絡(luò)格局,為預(yù)測鄉(xiāng)村旅游客流量、提升鄉(xiāng)村旅游示范點(diǎn)質(zhì)量、旅游者與管理者行為決策提供參考依據(jù),因此具有重要的理論與現(xiàn)實(shí)意義。本文借助百度指數(shù)平臺,選取260個(gè)有效鄉(xiāng)村旅游示范點(diǎn)作為樣本數(shù)據(jù),搜集樣本年度、季度日均網(wǎng)絡(luò)關(guān)注度的初始數(shù)據(jù),利用泰森多邊形進(jìn)行權(quán)重得出數(shù)據(jù)進(jìn)行分析。首先,結(jié)合SPSS統(tǒng)計(jì)分析關(guān)注度時(shí)間特征,探討鄉(xiāng)村旅游網(wǎng)絡(luò)關(guān)注度的時(shí)間變化趨勢,對網(wǎng)絡(luò)關(guān)注度進(jìn)行時(shí)間序列模型預(yù)測并得出結(jié)論。其次,利用ArcGIS空間分析方法來探討關(guān)注度空間特征,確定636個(gè)示范點(diǎn)的空間分布范圍及集聚區(qū)域,分析260個(gè)樣本示范點(diǎn)網(wǎng)絡(luò)關(guān)注度的空間分布集聚性、重心、核密度、層級等空間特征。第三,運(yùn)用UCINET社會網(wǎng)絡(luò)分析方法,對鄉(xiāng)村旅游網(wǎng)絡(luò)信息流進(jìn)行直觀可視化分析,分別分析網(wǎng)絡(luò)密度、網(wǎng)絡(luò)中心性、網(wǎng)絡(luò)凝聚子群等網(wǎng)絡(luò)特征,從而對中國大陸鄉(xiāng)村旅游示范點(diǎn)進(jìn)行網(wǎng)絡(luò)時(shí)空格局研究。研究結(jié)論為:(1)國內(nèi)636個(gè)鄉(xiāng)村旅游示范點(diǎn)的時(shí)空分布特征是隨著時(shí)間的增長示范點(diǎn)數(shù)量不斷增長,空間上主要分布在東部、中部地區(qū),華東地區(qū)較多,西北與東北地區(qū)較少;(2)選取的260個(gè)鄉(xiāng)村旅游示范點(diǎn)時(shí)間上呈現(xiàn)關(guān)注度不斷上升的趨勢,但有的地區(qū)出現(xiàn)隨著時(shí)間的增長關(guān)注度下降的趨勢,網(wǎng)絡(luò)關(guān)注度季度上夏季最高、冬季最低,關(guān)注度最大值是7月、8月;(3)休閑度假類鄉(xiāng)村旅游示范點(diǎn)網(wǎng)絡(luò)關(guān)注度較高,其次為開發(fā)較好的古村落、民俗古鎮(zhèn)等;(4)示范點(diǎn)網(wǎng)絡(luò)關(guān)注度空間分布上具有集聚性、方向性,關(guān)注度重心主要在湖北東北部,京津冀、長三角、珠三角的網(wǎng)絡(luò)關(guān)注度密度最大;(5)鄉(xiāng)村旅游網(wǎng)絡(luò)信息流的網(wǎng)絡(luò)密度較高,“互為目的地、互為客源地”的現(xiàn)象普遍,呈現(xiàn)核心邊緣化趨勢,各省市凝聚力較高,呈現(xiàn)6大組團(tuán);(6)鄉(xiāng)村旅游實(shí)際客流量與網(wǎng)絡(luò)關(guān)注度在時(shí)間、空間上都具有相關(guān)性,網(wǎng)絡(luò)關(guān)注度是旅游者出游的前兆反映。社會經(jīng)濟(jì)、互聯(lián)網(wǎng)普及率、旅游交通、客源市場、閑暇時(shí)間因素是影響鄉(xiāng)村旅游網(wǎng)絡(luò)關(guān)注度高低的重要因素。本研究注重定性與定量相結(jié)合,理論與實(shí)踐相結(jié)合的思想,分析鄉(xiāng)村旅游信息流的網(wǎng)絡(luò)時(shí)空格局,不僅豐富了鄉(xiāng)村旅游的研究內(nèi)容、定量研究方法,而且還為我國鄉(xiāng)村旅游的發(fā)展提供實(shí)際借鑒意義。
[Abstract]:Rural tourism is one of the hotspots of tourism research in recent years. Based on the previous studies, this paper probes into the pattern of domestic rural tourism network attention, virtual information flow and space-time network, in order to predict the rural tourism passenger flow. To improve the quality of rural tourism demonstration sites, tourists and managers provide a reference for decision-making, so it has important theoretical and practical significance. With the help of Baidu index platform, 260 effective rural tourism demonstration sites are selected as sample data. Collect the initial data of annual and quarterly network attention, and use the weight of Tyson polygon to get the data for analysis. First, combined with SPSS statistics to analyze the time characteristics of concern, This paper probes into the trend of time change of rural tourism network attention, forecasts the time series model of network attention and draws a conclusion. Secondly, we use ArcGIS spatial analysis method to explore the spatial characteristics of attention. The spatial distribution range and agglomeration area of the 636 demonstration sites are determined, and the spatial characteristics of the network concerns of 260 sample demonstration sites are analyzed, such as the spatial distribution and agglomeration, the center of gravity, the nuclear density and the hierarchy. Thirdly, the UCINET social network analysis method is used. Visual analysis of rural tourism network information flow, analysis of network density, network centrality, network aggregation sub-group and other network characteristics, The conclusion is that the spatial and temporal distribution of 636 rural tourism demonstration sites in China is characterized by the increasing number of demonstration sites with the increase of time and time. Spatial distribution is mainly in the eastern, central, eastern China, the northwest and northeast of the less than two) selected 260 rural tourism demonstration sites show a rising trend of attention in the time, However, in some areas, there is a downward trend of concern with the increase of time. The online attention is highest in summer, lowest in winter, and highest in July. In August, there is a high degree of concern in rural tourism demonstration sites such as leisure and vacation. Secondly, for the development of better ancient villages, folklore ancient towns, etc.) the spatial distribution of network attention at demonstration sites is concentrated and directional. The focus of attention is mainly in northeast Hubei, Beijing-Tianjin-Hebei, and the Yangtze River Delta. The density of rural tourism network information flow is high, the phenomenon of "mutual destination and mutual source of tourists" is common, showing the trend of core marginalization, and the cohesion of provinces and cities is high. There is a correlation between the actual passenger flow of rural tourism and the degree of network attention in time and space. The degree of network attention is a precursor reflection of tourists going out. Social economy, Internet popularization rate, tourism transportation, tourist market, Leisure time is an important factor influencing the attention of rural tourism network. This study focuses on the combination of qualitative and quantitative thinking, theory and practice, and analyzes the network space-time pattern of rural tourism information flow. It not only enriches the research contents and quantitative research methods of rural tourism, but also provides practical reference for the development of rural tourism in China.
【學(xué)位授予單位】：上海師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F592;F323

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