Tourist Behaviour Analysis Based on Digital Pattern of Life—An Approach and Case Study
The tourism industry has been rapidly growing over the last years and IT technologies have had a great affect on tourists as well. Tourist behaviour analysis has been the subject of different research studies in recent years. This paper presents the digital pattern of life concept which simplifies t...
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| Published in | Future internet Vol. 12; no. 10; p. 165 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
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01.10.2020
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| Online Access | Get full text |
| ISSN | 1999-5903 1999-5903 |
| DOI | 10.3390/fi12100165 |
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| Abstract | The tourism industry has been rapidly growing over the last years and IT technologies have had a great affect on tourists as well. Tourist behaviour analysis has been the subject of different research studies in recent years. This paper presents the digital pattern of life concept which simplifies the tourist behaviour models’ construction and usage. The digital pattern of life defines the general concepts of tourist behaviour, connects the tourist and the digital world and allows us to track behaviour changes over time. A literature review of the current state of the research in selected fields is performed for identifying the existing problems. The case studies of behaviour analysis based on classification, clustering and time series events behaviour models are shown. An ontological approach and artificial neural networks are used during behaviour model construction, training and evaluation. The gathered results can be used by smart tourism service developers and business stakeholders. |
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| AbstractList | The tourism industry has been rapidly growing over the last years and IT technologies have had a great affect on tourists as well. Tourist behaviour analysis has been the subject of different research studies in recent years. This paper presents the digital pattern of life concept which simplifies the tourist behaviour models’ construction and usage. The digital pattern of life defines the general concepts of tourist behaviour, connects the tourist and the digital world and allows us to track behaviour changes over time. A literature review of the current state of the research in selected fields is performed for identifying the existing problems. The case studies of behaviour analysis based on classification, clustering and time series events behaviour models are shown. An ontological approach and artificial neural networks are used during behaviour model construction, training and evaluation. The gathered results can be used by smart tourism service developers and business stakeholders. The tourism industry has been rapidly growing over the last years and IT technologies have had a great affect on tourists as well. Tourist behaviour analysis has been the subject of different research studies in recent years. This paper presents the digital pattern of life concept which simplifies the tourist behaviour models' construction and usage. The digital pattern of life defines the general concepts of tourist behaviour, connects the tourist and the digital world and allows us to track behaviour changes over time. A literature review of the current state of the research in selected fields is performed for identifying the existing problems. The case studies of behaviour analysis based on classification, clustering and time series events behaviour models are shown. An ontological approach and artificial neural networks are used during behaviour model construction, training and evaluation. The gathered results can be used by smart tourism service developers and business stakeholders. Keywords: neural networks; behaviour analysis; tourism; digital pattern of life |
| Audience | Academic |
| Author | Kashevnik, Alexey Mikhailov, Sergei |
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| SubjectTerms | Algorithms Applied research Artificial neural networks behaviour analysis Big Data Case studies Clustering Consumer behavior Decomposition Deep learning digital pattern of life Information technology Internet Literature reviews Methods Neural networks Public sector Sensors Smartphones Social networks Technology application Time series Tourism Tourism promotion Tourist attractions Trends User generated content |
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