Study on Spatial-Temporal Characteristics of Tourist Behavior Based on Digital Footprints:Taking Nanjing for Example

  • ZHANG Xianxian ,
  • LI Jinghan ,
  • ZUO Yin ,
  • ZHANG Huimin ,
  • JIN Xiulong
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  • 1. School of Geographic Information and Tourism,Chuzhou University,Chuzhou 239000,Anhui,China;
    2. Anhui Engineering Lab of Geo-information Smart Sensing and Services,Chuzhou 239000,Anhui,China;
    3. Chuzhou BCTS Travel Service,Chuzhou 239000,Anhui,China

Received date: 2018-03-28

  Revised date: 2018-08-31

  Online published: 2025-04-01

Abstract

Because of its high timeliness and strong interaction, digital footprint becomes a research topic on the spatial-temporal characteristics of tourist behavior. Taking Nanjing as a study area and based on online travel note, this article analyzes the spatial-temporal characteristics of tourist behavior in Nanjing on the perspective of the tourism image, the temporal variation and spatial pattern of tourist behavior by the use of text analysis and GIS temporal-spatial analysis. The analysis results show that: 1) The word of history can be used as the overall cognition of Nanjing tourism image, and tourists choose to travel in spring and summer influenced by the factors of temperature and holiday. 2) The nearest neighbor index of visited tourist attractions in Nanjing is 0.48, and the core of Nanjing city becomes the gathering area of scenic spots and tourists. 3) Tourism trajectories of Nanjing radiates outward from the core city in the spatial distribution, and the spatial structure of tourist flow with Confucius Temple as a core expands outward. On these basis, the optimization measures of tourism development in Nanjing are discussed from the aspects of tourism image enhancement, tourist capacity control and tourism marketing.

Cite this article

ZHANG Xianxian , LI Jinghan , ZUO Yin , ZHANG Huimin , JIN Xiulong . Study on Spatial-Temporal Characteristics of Tourist Behavior Based on Digital Footprints:Taking Nanjing for Example[J]. Economic geography, 2018 , 38(12) : 226 -233 . DOI: 10.15957/j.cnki.jjdl.2018.12.029

References

[1] Girardin F,Blat J,Calabrese F,et al.Digital Footprinting:Un-covering Tourists with User-Generated Content[J]. IEEE Pervasive Computing,2008,7(4):36-43.
[2] 李春明,王亚军,刘尹,等. 基于地理参考照片的景区游客时空行为研究[J]. 旅游学刊,2013,28(10):30-36.
[3] 韩冬,黄丽华. 基于旅游数字足迹的旅游流网络结构研究——以内蒙古自治区为例[J]. 干旱区资源与环境,2018,32(3):192-197.
[4] 马丽君,龙云. 基于网络关注度的湖南省居民旅游需求时空特征[J]. 经济地理,2017,37(2):201-208.
[5] 梁保尔,潘植强. 基于旅游数字足迹的目的地关注度与共现效应研究——以上海历史街区为例[J]. 旅游学刊,2015,7(30):80-90.
[6] 郭风华,王琨,张建立,等. 成都“五朵金花”乡村旅游地形象认知——基于博客游记文本的分析[J]. 旅游学刊,2015,4(20):84-94.
[7] 刘超,胡梦晴,林文敏. 山岳型景区旅游形象感知研究:基于2014—2016年黄山网络游记分析[J]. 山地学报,2017,35(4):566-571.
[8] 张妍妍,李君轶,杨敏. 基于旅游数字足迹的西安旅游流网络结构研究[J]. 人文地理,2014,29(4):111-118.
[9] Girardin F,Blat J,Calabrese F,et al.Digital footprinting:uncov-ering tourists with user-generated content[J]. IEEE Pervasive Computing,2008,7(4):36-43.
[10] Vaccari A,Liu L,Biderman A,et al.A holistic framework forthe study of urban traces and the profiling of urban processes and dynamics[C]. Intelligent Transportation Systems,2009. ITSC'09. 12th International IEEE Conference on. IEEE,2009:1-6.
[11] 吴静,杨兴柱,孙井东. 基于新地理信息技术的南京市游客流动性空间特征研究[J]. 人文地理,2015,30(2):148-154.
[12] 王波,甄峰,魏宗财. 南京市区活动空间总体特征研究——基于大数据的实证分析[J]. 人文地理,2014,29(3):14-21,55.
[13] 张子昂,黄震,靳诚. 基于微博签到数据的景区旅游活动时空行为特征研究——以南京中山风景名胜区为例[J]. 地理与地理信息科学,2015,31(4):121-126.
[14] 靳诚,徐菁. 南京市对外交通节点与酒店之间游客流动空间特征分析[J]. 人文地理,2016,31(5):55-62.
[15] 王永明,王美霞,李瑞,等. 基于网络文本内容分析的凤凰古城旅游地意象感知研究[J]. 地理与地理信息科学,2015,31(1):64-67,79.
[16] 吴江,张秀香,叶玲翠,等. 不同时间尺度周期的旅游客流量波动特征研究——以西藏林芝市为例[J]. 地理研究,2016,35(12):2347-2362.
[17] 刘锐,胡伟平,王红亮,等. 基于核密度估计的广佛都市区路网演变分析[J]. 地理科学,2011,31(1):81-86.
[18] 杨兴柱,顾朝林,王群. 南京市旅游流网络结构构建[J]. 地理学报,2007,62(6):609-620.
[19] 杨敏,李君轶,杨利. 基于旅游数字足迹的城市入境游客时空行为研究——以成都市为例[J]. 旅游科学,2015,29(3):59-68.
[20] 申怀飞,郑敬刚,唐国沛,等. 河南省A级旅游景区空间分布特征分析[J]. 经济地理,2013,33(2):179-183.
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