Tourism companies' risk exposures on text disclosure. (September 2020)

• Record Type: Journal Article
• Authors: Li, Jianping; Feng, Yuyao; Li, Guowen; Sun, Xiaolei
• Is Part Of: Annals of tourism research. Volume 84(2020)
• Publication Date: 2020-09
• Subjects: Risk identification -- Company risk exposure -- Tourism risk -- Text mining -- Form 10-K; Tourism -- Periodicals
• DOI: 10.1016/j.annals.2020.102986
• Languages: English
• ISSNs: 0160-7383

Abstract

Abstract: Tourism is a risk-prone industry. But most studies focus on tourist risk perception while ignoring company risk exposure. As service providers, the companies play an important role in tourism activities, and systematically identifying the risks they face is vital to the development of the tourism industry. This paper attempts to identify tourism companies' risk exposures based on textual risk disclosure of financial statements. Using 51, 008 risk headings of 255 public companies, we adopt Sentence-Latent Dirichlet Allocation (Sent-LDA) method to discover 30 risk exposures of the tourism industry. Further, we discuss the universality and industry representativeness of these risk exposures, as well as risk differences between different sub-industries and years. Findings can help stakeholders develop reasonable and timely risk management strategies. Highlights: This paper systematically identifies the risk exposures of the tourism industry. The text risk disclosures in financial statements are introduced into our work. Identifies the internal differences and industry representativeness of risks. Depicts the risk evolution trends in different years from time perspective. Our work is useful for stakeholders to develop sound risk management strategies.