A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China

Tao Liu, Ying Zhang, Huan Zhang and Xiping Yang
Additional contact information
Tao Liu: College of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450002, China
Ying Zhang: College of Economics and Management, Henan Agricultural University, Zhengzhou 450046, China
Huan Zhang: Key Laboratory of New Materials and Facilities for Rural Renewable Energy (MOA of China), Henan Agricultural University, Zhengzhou 450002, China
Xiping Yang: School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China

Sustainability, 2021, vol. 13, issue 9, 1-15

Abstract: Insights into the association rules of destinations can help to understand the possibility of tourists visiting a destination after having traveled from another. These insights are crucial for tourism industries to exploit strategies and travel products and offer improved services. Recently, tourism-related, user-generated content (UGC) big data have provided a great opportunity to investigate the travel behavior of tourists on an unparalleled scale. However, existing analyses of the association of destinations or attractions mainly depend on geo-tagged UGC, and only a few have utilized unstructured textual UGC (e.g., online travel reviews) to understand tourist movement patterns. In this study, we derive the association of destinations from online textual travel reviews. A workflow, which includes collecting data from travel service websites, extracting destination sequences from travel reviews, and identifying the frequent association of destinations, is developed to achieve the goal. A case study of Yunnan Province, China is implemented to verify the proposed workflow. The results show that the popular destinations and association of destinations could be identified in Yunnan, demonstrating that unstructured textual online travel reviews can be used to investigate the frequent movement patterns of tourists. Tourism managers can use the findings to optimize travel products and promote destination management.

Keywords: online travel review; user-generated content; association rule; movement pattern of tourist (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/9/4720/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/9/4720/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:9:p:4720-:d:541778

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().