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Open Access

Literary Destination Familiarity and Inbound Tourism: Evidence from Chinese Mainland

Department of Social Policy, London School of Economics and Politial Science, London, WC2A 2AE, UK
Department of Sociology, Harbin Engineering University, Harbin 150001, China
Department of Sociology, Nanjing University, Nanjing 210023, China
Business School, Beijing Language and Culture University, Beijing 100083, China
Department of Sociology, Tsinghua University, Beijing 100084, China

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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.

Keywords

inbound tourismtouristdestination familiarityChinese mainlandGoogle Books

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Journal of Social Computing
Volume 2 Issue 2,
June 2021
Pages 193-206
DOI: 10.23919/JSC.2021.0013
Cite this article:
Ju G, Liu J, He G, et al. Literary Destination Familiarity and Inbound Tourism: Evidence from Chinese Mainland. Journal of Social Computing, 2021, 2(2): 193-206. https://doi.org/10.23919/JSC.2021.0013

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Received: 21 June 2021
Revised: 08 July 2021
Accepted: 12 July 2021
Published: 23 August 2021

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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