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Examining Visitors' Characteristics and Behaviors in Tourist Destinations Through Mobile Phone Users' Location Data

Examining Visitors' Characteristics and Behaviors in Tourist Destinations Through Mobile Phone Users' Location Data

Masahide Yamamoto
Copyright: © 2020 |Pages: 32
ISBN13: 9781799801061|ISBN10: 1799801063|ISBN13 Softcover: 9781799815655|EISBN13: 9781799801078
DOI: 10.4018/978-1-7998-0106-1.ch013
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MLA

Yamamoto, Masahide. "Examining Visitors' Characteristics and Behaviors in Tourist Destinations Through Mobile Phone Users' Location Data." Handbook of Research on Big Data Clustering and Machine Learning, edited by Fausto Pedro Garcia Marquez, IGI Global, 2020, pp. 279-310. https://doi.org/10.4018/978-1-7998-0106-1.ch013

APA

Yamamoto, M. (2020). Examining Visitors' Characteristics and Behaviors in Tourist Destinations Through Mobile Phone Users' Location Data. In F. Garcia Marquez (Ed.), Handbook of Research on Big Data Clustering and Machine Learning (pp. 279-310). IGI Global. https://doi.org/10.4018/978-1-7998-0106-1.ch013

Chicago

Yamamoto, Masahide. "Examining Visitors' Characteristics and Behaviors in Tourist Destinations Through Mobile Phone Users' Location Data." In Handbook of Research on Big Data Clustering and Machine Learning, edited by Fausto Pedro Garcia Marquez, 279-310. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-0106-1.ch013

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Abstract

This chapter uses Mobile Kukan Toukei™ (mobile spatial statistics) to collect the location data of mobile phone users in order to count the number of visitors at specific tourist destinations and examine their characteristics. Mobile Kukan Toukei is statistical population data created by an operational data of mobile phone networks. It is possible to estimate the population structure of a region by gender, age, and residence using this service of the company. The locations and characteristics of the individuals obtained herein are derived through a non-identification process, aggregation processing, and concealment processing. Therefore, it is impossible to identify specific individuals. This chapter attempts to identify the number of visitors in different periods and their characteristics based on the location data of mobile phone users collected by the mobile phone company. In addition, it also attempts to demonstrate an alternative method to more accurately infer the number of visitors in specific areas.

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