中国生态旅游 ›› 2022, Vol. 12 ›› Issue (5): 814-830.doi: 10.12342/zgstly.20220060

• 海洋旅游 • 上一篇    下一篇

中国海岸带A级旅游景区百度关注度空间差异及影响因素

李晗(), 丁志伟(), 刘卓林, 张希阳   

  1. 河南大学 地理与环境学院/黄河中下游数字地理技术教育部重点实验室/区域发展与规划研究中心/环境与规划国家级实验教学示范中心,开封 475004
  • 收稿日期:2022-05-09 修回日期:2022-10-13 出版日期:2022-10-28 发布日期:2022-12-06
  • 通讯作者: *丁志伟(1983-),男,博士,副教授,博士生导师,研究方向为城市-区域综合发展。E-mail: dingzhiwei1216@163.com
  • 作者简介:李晗(1999-),女,硕士研究生,研究方向为城市-区域综合发展。E-mail: hanl_9@163.com
  • 基金资助:
    国家自然科学基金项目(42271213);河南省高校科技创新人才支持计划项目(人文社科类:2021-CX-016);河南省哲学社会科学规划年度项目(2020BJJ018);河南省社会科学界联合会调研课题(SKL-2022-2625);河南大学本科教学改革研究与实践项目(HDXJJG2021-034);河南大学研究生教育教学改革研究与实践项目(YJSJG2022XJ028);河南大学研究生培养创新与质量提升行动计划项目资助(SYLKC2022003)

Spatial differences and influencing factors of Baidu’s attention on A-level tourist attractions in China’s coastal zone

Li Han(), Ding Zhiwei(), Liu Zhuolin, Zhang Xiyang   

  1. The College of Geography and Environmental Science / Key Laboratory of Geospatial Technology for the Middle and Lower Reaches of the Yellow River, Ministry of Education / Research Center of Regional Development and Planning / National Demonstration Center for Environment and Planning, Henan University, Kaifeng 475004, China
  • Received:2022-05-09 Revised:2022-10-13 Published:2022-10-28 Online:2022-12-06

摘要:

基于百度检索量指标,运用空间分类、核密度、探索性空间数据分析等方法,对中国海岸带A级旅游景区百度关注度的空间差异及影响因素进行分析,以探索海岸带旅游景区网络软实力的差异及其与旅游景区实体建设的关系。结果表明:(1)整体呈现“双核并进”格局并在江浙沪形成“众星捧月”态势。低、较低关注度旅游景区占比高达95%且低值连绵分布状态明显,高关注度旅游景区主要分布在黄海北部和渤海湾。(2)空间关联类型以低低集聚为主,高高集聚仅以渤海湾和江浙沪为中心形成双核集聚态势。高低集聚数量少且主要在高高集聚区附近,体现出局部的极化效应。(3)与实体旅游经济对比,两者吻合度整体较高,但百度关注度下的集聚能力更强且局部核心区有明显收缩,反映网络空间的极化与倍增效应。与新冠肺炎疫情前相比,近期多数旅游景区进行网络化转型且注重运营水平的提升,渤海湾和长江入海口旅游景区表现突出,辽宁省东部与福建省次之,其他地区效应不明显。(4)从影响因素看,实体建设水平与短视频推广是核心影响因素,游客评价与舆论扩散的耦合效应有较大影响,而交通、通讯、区位等基础因子则作用不明显。

关键词: 海洋旅游, 旅游景区, 网络关注度, 空间差异, 新冠肺炎疫情, 百度检索量

Abstract:

Based on the index of Baidu search volume, this paper adopts spatial classification, kernel density, exploratory spatial data analysis (ESDA) and other methods to analyze the spatial differences and influencing factors of Baidu's attention on A-level attractions in China’s coastal zone and to explore the differences in the network soft power of tourist attractions in the study area and its relationship with the physical construction of those attractions. The results show that: (1) The overall pattern of “dual core development” is presented, and the trend of “stars crowding the moon” is formed in Jiangsu, Zhejiang and Shanghai. Low level attention attractions account for 95% of the total and the value of the level is distributed continuously. High level attention attractions are mainly distributed in the northern Yellow Sea and Bohai Bay. (2) The spatial association type is dominated by LL agglomeration, while HH agglomeration only takes Bohai Bay and Jiangsu, Zhejiang and Shanghai as the center to form a dual core agglomeration trend. The number of HL types is small and mainly near the HH region, reflecting the local polarization effect. (3) Compared with the tourism economy, the degree of coincidence between the two is high as a whole, but the gathering ability under Baidu’s attention is stronger and local core areas have significantly contracted, reflecting the polarization and multiplication effect of cyberspace. Compared with that before the epidemic, most attractions have undergone network transformation and paid attention to the improvement of operation level in the near future. The Bohai Bay and Yangtze River estuary attractions have shown outstanding performance, followed by eastern Liaoning and Fujian, with no obvious effect in other regions. (4) Physical construction level and short video promotion act as the core influencing factors. The coupling effect of tourist evaluation and public opinion diffusion also has a great impact, while the basic factors such as transportation, communication and location have no obvious effect.

Key words: marine tourism, tourist attractions, network attention, spatial differences, epidemic, Baidu retrieval volume