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Journal of Social Computing

Keywords

inbound tourism, tourist, destination familiarity, Chinese mainland, Google Books

Abstract

Destination familiarity is an important non-economic determinant of tourists’ destination choice that has not been adequately studied. This study posits a literary dimension to the concept of destination familiarity—that is, the extent to which tourists have gained familiarity with a given destination through literature—and seeks to investigate the impact of this form of familiarity on inbound tourism to Chinese mainland. Employing the English fiction dataset of the Google Books corpus, the New York Times annotated corpus, and the Time magazine corpus, we construct two types of destination familiarity based on literary texts: affection-based destination familiarity and knowledge-based destination familiarity. The results from dynamic panel estimation (1994–2004) demonstrate that the higher the degree of affection-based destination familiarity with a province in the previous year, the larger the number of inbound tourists the following year. Examining the influence of literature and its consumption on tourism activities sheds light on the dynamics of sustainable tourism development in emerging markets.

Publisher

Tsinghua University Press

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