On the tourists’ cognitive image network and its evolution: a case of Guizhou province of China

ABSTRACT

Tourist’s cognitive image network unveils the relationship among the touring cognitive experiences. The cognitive image network evolution reflects the tourists’ destination image change, which further implicates the subtle changes in behavior. The tourists’ online reviews and experience sharing could effectively help management build the cognitive image network of tourism destinations. Based on crawled travelogues in Guizhou, China from Ctrip.com, with LDA topic mining techniques, this study first constructs the image of a tourism destination, then constructs the tourist’s cognitive image network that explores the evolution of the network before and after the COVID-19 pandemic. Research results show that the cognitive image network in Guizhou mainly consists of 10 dimensions: Accommodation, diet, natural landscapes, social environment, and culture dimensions, followed by entertainment, natural environment, history, infrastructure, and economic environment. The cognitive image network evolution shows that tourists have different preferences before and after the COVID-19 pandemic. The study provides a new perspective for the study of destination image theory, which can help destination tourism enterprises to identify the tourist’s behavior choices and develop unique marketing strategies.

KEYWORDS:

• Tourism destination image
• cognitive image
• cognitive image network tourism marketing
• Asia Pacific
• cognitive image evolution
• LDA

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China: [grant number 72371007]; Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations.