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

doi:10.1145/2955129.2955151

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

Graduate Institute of Sport, Leisure and Hospitality Management

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings of the 3rd Multidisciplinary International Social Networks Conference, SocialInformatics 2016, Data Science 2016, MISNC, SI, DS 2016
Publisher	Association for Computing Machinery
ISBN (Print)	9781450341295
DOIs	https://doi.org/10.1145/2955129.2955151
Publication status	Published - 2016 Aug 15
Event	3rd 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 15 → 2016 Aug 17

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	3rd 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
Country/Territory	United States
City	Union
Period	2016/08/15 → 2016/08/17

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

Access to Document

10.1145/2955129.2955151

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 Article a13 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/2955129.2955151

The open data application on determining main types of activities to predict tourist population and ticket sales in Taiwan National Forestry Recreation Areas. / Li, Ching; Hsia, Ping Feng.
Proceedings of the 3rd Multidisciplinary International Social Networks Conference, SocialInformatics 2016, Data Science 2016, MISNC, SI, DS 2016. Association for Computing Machinery, 2016. a13 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, C & Hsia, PF 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, 3rd 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, 2016/08/15. https://doi.org/10.1145/2955129.2955151

Li C, Hsia PF. 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. Association for Computing Machinery. 2016. a13. (ACM International Conference Proceeding Series). doi: 10.1145/2955129.2955151

Li, Ching ; Hsia, Ping Feng. / The open data application on determining main types of activities to predict tourist population and ticket sales in Taiwan National Forestry Recreation Areas. Proceedings of the 3rd Multidisciplinary International Social Networks Conference, SocialInformatics 2016, Data Science 2016, MISNC, SI, DS 2016. Association for Computing Machinery, 2016. (ACM International Conference Proceeding Series).

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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.",

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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