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The Geographic Spread and Preferences of Tourists Revealed by User-Generated Information on Jeju Island, South Korea

David M. Fisher (), Spencer A. Wood (), Young-Hee Roh () and Choong-Ki Kim ()
Additional contact information
David M. Fisher: Natural Capital Project, Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA
Spencer A. Wood: Natural Capital Project, Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA
Young-Hee Roh: The Institute for Korean Regional Studies, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
Choong-Ki Kim: Division for Natural Environment, Korea Environment Institute, 370 Sicheong-daero, Sejong-si 30147, Korea

Land, 2019, vol. 8, issue 5, 1-1

Abstract: Recreation and tourism are important ways that people interact with and derive benefits from natural environments. Understanding how and where nature provides recreational opportunities and benefits is necessary for management decisions that impact the environment. This study develops and tests an approach for mapping tourism patterns, and assessing people’s preferences for cultural and natural landscapes, using user-generated geographic content. The volume of geotagged images and tweets shared publicly on Flickr and Twitter and proprietary mobile phone traffic provided by a telecommunications company, are used to map visitation rates to potential tourist destinations across Jeju Island, South Korea. We find that densities of social media posts and mobile phone traffic are all correlated with ticket sales and counts of gate entries at tourist sites. Using multivariate linear regression, we measure the degree to which attributes of the natural and built environment explain variation in visitation rates, and find that tourists to Jeju Island prefer to recreate near beaches, sea cliffs, golf courses and hiking trails. We conclude that high-resolution and spatially-explicit visitation data provided by user-generated content open the door for statistical models that can quantify recreation demand. Managers and practitioners could combine these flexible and relatively inexpensive user-generated data with more traditional survey data to inform sustainable tourism development plans and policy decisions. These methods are especially useful in the context of landscape or regional-scale ecosystem service assessments, where there is a need to map the multiple ecological, economic, and cultural benefits of the environment.

Keywords: user-generated geographic content; social media data; tourism; cultural ecosystem services; revealed preferences (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

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