The open data application on determining main types of activities to predict tourist population and ticket sales in Taiwan National Forestry Recreation Areas

Ching Li, Ping Feng Hsia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The study applied government open data to determine the main types of activities to effect on tourist population and ticket sales in Taiwan National Forestry Recreation Areas. Through multilayer perceptron analysis, the relationship between activity, tourist population, and ticket sales was estimated. The study areas were Basianshan, Alishan, and Taipingshan National Forest Recreation Areas. The data were collected from 2007 to 2011 reported by the Forest Bureau in Taiwan. The results of the investigation showed that tourist population and ticket sales were influenced by different kind of activities. The frequency of large entertaining activity was key factor to influence tourist population, and the frequency of large natural-experience activity was key factor to influence ticket sales. To influence tourist population and ticket sales, the frequency of large entertaining activity and small social activity should be considered.

Original languageEnglish
Title of host publicationProceedings of the 3rd Multidisciplinary International Social Networks Conference, SocialInformatics 2016, Data Science 2016, MISNC, SI, DS 2016
PublisherAssociation for Computing Machinery
ISBN (Print)9781450341295
DOIs
Publication statusPublished - 2016 Aug 15
Externally publishedYes
Event3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016 - Union, United States
Duration: 2016 Aug 152016 Aug 17

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016
CountryUnited States
CityUnion
Period16/8/1516/8/17

Keywords

  • Multilayer perceptron analysis
  • The effect of tourist activity
  • Tourist event management

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Li, C., & Hsia, P. F. (2016). The open data application on determining main types of activities to predict tourist population and ticket sales in Taiwan National Forestry Recreation Areas. In Proceedings of the 3rd Multidisciplinary International Social Networks Conference, SocialInformatics 2016, Data Science 2016, MISNC, SI, DS 2016 [a13] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/2955129.2955151