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 Mainland China. 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.
Highlights
Over the past two decades, globalization has made tourism a popular global leisure activity, and international tourism has become one of the largest and fastest growing industries in the world. Guodong Ju is with the Department of Social Policy, London Jiankun Liu is with the Department of Sociology, HarbinEngineering University, Harbin 150001, China
Our study demonstrates that literary destination familiarity as measured by word-search dynamics in Google Books English fiction corpus significantly affects the inflows of international tourists to Mainland China —namely, the higher the degree of literary destination familiarity with a province in the previous year, the larger the number of inbound tourists the following year
Our results show that after controlling for the destination familiarity constructed from contemporary media, destination familiarity constructed from fiction —even with low circulation and low exposure based on our operationalization compared with contemporary media—still exerts a significantly positive impact on inbound tourism, offering strong evidence to support our theory
Summary
Over the past two decades, globalization has made tourism a popular global leisure activity, and international tourism has become one of the largest and fastest growing industries in the world. To measure affection-based literary destination familiarity quantitatively, we extracted the appearance frequency of Chinese province names from the Englishfiction dataset of the Google Books corpus, a text corpora containing a large volume of digitalized English fiction books; likewise, we extracted the same information from the New York Times annotated corpus and the Time magazine corpus to measure knowledgebased literary destination familiarity In this analysis, we focus exclusively on English-language corpus, as English is the most widely used lingua franca, which plays a critical role in international communication and global policies[27]. Our study demonstrates that literary destination familiarity as measured by word-search dynamics in Google Books English fiction corpus significantly affects the inflows of international tourists to Mainland China —namely, the higher the degree of literary destination familiarity with a province in the previous year, the larger the number of inbound tourists the following year
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