Abstract
Online travel reviews have been extensively used as an important data source in tourism research. Typically, data for online travel review research is collected only from one platform. However, drawing definite conclusions based on single platform analyses may thus produce biases and lead to erroneous conclusions and decisions. Therefore, this research verifies whether or not there are discrepancies and commonalities between different travel review platforms. In this study, five native Chinese travel review platforms were selected: Ctrip; Qyer; Mafengwo; Tuniu; and Qunar. Using a mixed content analysis method, the destination image of Finland was extracted from 10,197 travel reviews in Simplified Chinese as the destination image is a popular topic in online review research. Results show Finland’s destination image representation varies between Chinese travel review platforms. This discrepancy is especially prominent in the dimension of functional and mixed functional-psychological destination attributes. Significant theoretical contributions and managerial implications for the analysis of online travel reviews and destination image research are discussed.
Highlights
Today, online travel reviews (OTRs) have a huge influence on the tourist decision-making process, because they are often used when tourists compare various options and make travel-related decisions
Using a single platform is a potential source of sampling bias that potentially complicates the interpretation of the research findings (Tufekci 2014)
Many earlier studies adopted a single platform as a data source, but they ignored that using single data sources may induce a sampling bias that potentially complicates the interpretation of the research findings
Summary
Online travel reviews (OTRs) have a huge influence on the tourist decision-making process, because they are often used when tourists compare various options and make travel-related decisions. OTRs are gaining increasing attention in tourism research and destination marketing. Earlier studies involving OTRs have relied on a single data source (Xiang et al 2017). In using a single data source for OTR research, researchers ignore platform-specific biases such as differences in platform design, user base, platform-specific behavior, and storage strategy (Pfeffer 2014). This study aims to explore whether or not platform-specific biases in OTRs should be accounted for in tourism research and practice, and if so how. Earlier studies have mainly used statistical analyses, natural language processing techniques, or algorithms to explore the length of the review, frequently words, topics, and review sentiment (Xiang et al 2017; Zhang and Cole 2016), or have analyzed the functional features of different websites (Pai et al 2014)
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