热带地理 ›› 2021, Vol. 41 ›› Issue (5): 1110-1119.doi: 10.13284/j.cnki.rddl.003384

• 旅游地理 • 上一篇    

基于游客感知的成都旅游目的地认知形象演变研究

雷雅钦1(), 王波1,3,4(), 刘俊5, 赵莹b   

  1. 1.中山大学 a. 地理科学与规划学院
    b.旅游学院,广州 510275
    2.南海海洋科学与工程广东实验室(珠海),广东 珠海 519000
    3.广东省城市化与地理环境空间模拟重点实验室,广州 510275
    4.四川大学 旅游学院,成都 610085]
  • 收稿日期:2020-12-03 修回日期:2021-06-08 出版日期:2021-09-22 发布日期:2021-09-22
  • 通讯作者: 王波 E-mail:leiyq8@mail2.sysu.edu.cn;wangbo68@mail.sysu.edu.cn
  • 作者简介:雷雅钦(1998-),女,山西平遥人,硕士研究生,主要研究方向为大数据与智慧城市研究,(E-mail)leiyq8@mail2.sysu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41901191);中央高校基本科研业务费项目(19lgpy42)

Spatiotemporal Evolution of the Cognitive Image of a Tourism Destination: An Explorative Analysis in Chengdu Based on Online Reviews

Yaqin Lei1(), Bo Wang1,3,4(), Jun Liu5, Ying Zhaob   

  1. 1.a School of Geography and Planning
    b.School of Tourism Management, Sun Yat-sen University, Guangzhou 510275, China
    2.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
    3.Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Guangzhou 510275, China
    4.Tourism School, Sichuan University, Chengdu 610085, China
  • Received:2020-12-03 Revised:2021-06-08 Online:2021-09-22 Published:2021-09-22
  • Contact: Bo Wang E-mail:leiyq8@mail2.sysu.edu.cn;wangbo68@mail.sysu.edu.cn

摘要:

基于在携程旅行网(Ctrip.com)上收集的2000-2019年成都相关游记,通过构建旅游目的地认知形象维度分析框架与专属的分词词库,运用游客感知偏好标准差椭圆(SDE)和文本分析,从时空维度探究成都近20年旅游目的地认知形象的演变。总体上,认知形象呈现丰富化趋势,其时空演变具有以下特征:1)游客偏好向“体验游”转变,SDE向东南(市区)偏移,旅游吸引物、旅游休闲和娱乐中“体验式消费”维度占比提高;2)“悠闲”的城市气质更加鲜明,浓烈的地方氛围促进市区吸引力的提高,推动SDE向市区方向进一步偏移;3)“去地震化”的旅游响应明显,表现在公共基础设施、旅游基础设施和旅游环境维度,受灾景区及恢复重建影响SDE方向偏移。

关键词: 旅游目的地, 认知形象, 时空特征, 网络游记, 文本挖掘, 成都

Abstract:

It has become increasingly common for tourists to share their personal travel experiences on social media. This user-generated content with spatial references provides a rich database for tracing the evolution of the cognitive image of a tourism destination over a long period of time. This is helpful for local authorities to improve destination management and marketing by prompting image adjustment and tourism product optimization to satisfy tourists' expectations. In this study, data on online travels on Ctrip.com, one of the most popular tourism websites in China, were collected and analyzed to reveal the spatiotemporal evolution of the cognitive image of Chengdu from 2000 to 2019. Based on a specific tourism-related lexicon, keywords were identified and grouped in a list, following a framework comprising six dimensions: tourism attraction, tourism leisure and entertainment, public infrastructure, tourism infrastructure, tourism environment, and local atmosphere. The six dimensions were further divided into 18 sub-dimensions. Under this framework, the general trends and spatiotemporal evolution characteristics of Chengdu's cognitive image during this period were analyzed. Specifically, changes in the shares of identified keywords related to the six dimensions during the period explained the general trend characteristics, while changes in the standard deviational ellipse (SDE) of the distribution of identified keywords with spatial reference, together with changes in the shares of identified keywords related to the 18 sub-dimensions in detail, were adopted to vividly show the spatiotemporal evolution of Chengdu's cognitive image. Our findings revealed that Chengdu's cognitive image has experienced obvious spatiotemporal evolution across different sub-dimensions over the past 20 years. Generally, the cognitive image has became substantial during this period, with a continuous increase in the total share of identified keywords related to the cognitive image of online travels. In addition, the shares of keywords related to the six dimensions and 18 sub-dimensions varied across different stages. Particularly, the spatiotemporal evolution shows that (1) there is an evident shift from sightseeing tourism to experience tourism, as SDE shifts toward the southeastern urban area and the share of identified keywords highly related to experience consumption increases; (2) the city tends to be more "leisurely and carefree" in tourism, as SDE tends to be more concentrated in the urban area with a relatively high density of leisure attractions; and (3) the cognitive image responds to natural hazards promptly, as the size and directions of SDE vary accordingly, and the share of identified keywords related to public infrastructure, tourism infrastructure, and tourism environment reached a peak after the Wenchuan earthquake. Based on our findings, the mechanism forming Chengdu's cognitive image was further discussed from the perspectives of government, residents, and commercial organizations. Methodologically, this study proposes an approach based on text mining and analysis of online travel, typical spatial big data generated by tourists, to examine the cognitive image, which could be applied to other tourism destinations. Moreover, the mechanism framework based on the Chengdu case provides recommendations on tourism destination image management and marketing to improve responses to tourists' changing expectations regarding other tourism destinations.

Key words: tourism destination, cognitive image, spatiotemporal characteristics, online travels, text mining, Chengdu

中图分类号: 

  • F592.7