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Automatic video analytics in tourism: A methodological review

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  • Zhu, Jingjie
  • Cheng, Mingming

Abstract

While there has been a growing interest in adopting videos as a data source, the use of video analytics, as a method, in gaining deep insights into tourism and hospitality theories and practices is still in its infancy. This study provides a critical review of the progress of automatic video analytics in tourism and hospitality and a guiding framework by detailing theoretical and methodological issues with this new form of knowledge production. The research offers a blueprint for future tourism research endeavors tapping into the potential of videos as a data source.

Suggested Citation

  • Zhu, Jingjie & Cheng, Mingming, 2024. "Automatic video analytics in tourism: A methodological review," Annals of Tourism Research, Elsevier, vol. 108(C).
    • Handle: RePEc:eee:anture:v:108:y:2024:i:c:s016073832400077x
    DOI: 10.1016/j.annals.2024.103800
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    1. Kar, Arpan Kumar & Dwivedi, Yogesh K., 2020. "Theory building with big data-driven research – Moving away from the “What” towards the “Why”," International Journal of Information Management, Elsevier, vol. 54(C).
    2. Rubin, Dan & Mohr, Iris & Kumar, V., 2022. "Beyond the box office: A conceptual framework for the drivers of audience engagement," Journal of Business Research, Elsevier, vol. 151(C), pages 473-488.
    3. Julie Masset & Alain Decrop & Isabelle Frochot, 2024. "Videography in tourism research: An analytical review," Post-Print hal-04550890, HAL.
    4. Schwenzow, Jasper & Hartmann, Jochen & Schikowsky, Amos & Heitmann, Mark, 2021. "Understanding videos at scale: How to extract insights for business research," Journal of Business Research, Elsevier, vol. 123(C), pages 367-379.
    5. Li, Shanshi & Sung, Billy & Lin, Yuxia & Mitas, Ondrej, 2022. "Electrodermal activity measure: A methodological review," Annals of Tourism Research, Elsevier, vol. 96(C).
    6. Vujičić, Miroslav D. & Kennell, James & Stankov, Uglješa & Gretzel, Ulrike & Vasiljević, Đorđije A. & Morrison, Alastair M., 2022. "Keeping up with the drones! Techno-social dimensions of tourist drone videography," Technology in Society, Elsevier, vol. 68(C).
    7. Made Handijaya Dewantara & Sarah Gardiner & Xin Jin, 2023. "Travel vlog ecosystem in tourism digital marketing evolution: a narrative literature review," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(19), pages 3125-3139, October.
    8. Gillovic, Brielle & McIntosh, Alison & Cockburn-Wootten, Cheryl & Darcy, Simon, 2024. "Intellectual disability and care during travel," Annals of Tourism Research, Elsevier, vol. 105(C).
    9. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
    10. Xiang, Keheng & Huang, Wei-Jue & Gao, Fan & Lai, Qin, 2022. "COVID-19 prevention in hotels: Ritualized host-guest interactions," Annals of Tourism Research, Elsevier, vol. 93(C).
    11. Hsu, Cathy H.C. & Tan, Guoxiong & Stantic, Bela, 2024. "A fine-tuned tourism-specific generative AI concept," Annals of Tourism Research, Elsevier, vol. 104(C).
    12. Anja Dinhopl & Ulrike Gretzel, 2016. "Conceptualizing tourist videography," Information Technology & Tourism, Springer, vol. 15(4), pages 395-410, January.
    13. Zecong Ma & Sergio Palacios, 2021. "Image-mining: exploring the impact of video content on the success of crowdfunding," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(4), pages 265-285, December.
    14. Hildebrand, Christian & Efthymiou, Fotis & Busquet, Francesc & Hampton, William H. & Hoffman, Donna L. & Novak, Thomas P., 2020. "Voice analytics in business research: Conceptual foundations, acoustic feature extraction, and applications," Journal of Business Research, Elsevier, vol. 121(C), pages 364-374.
    15. Pan, Steve & Tsai, Henry & Lee, Jinsoo, 2011. "Framing New Zealand: Understanding tourism TV commercials," Tourism Management, Elsevier, vol. 32(3), pages 596-603.
    16. Li, Xi & Shi, Mengze & Wang, Xin (Shane), 2019. "Video mining: Measuring visual information using automatic methods," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 216-231.
    17. Qiang Zhang & Wenbo Wang & Yuxin Chen, 2020. "Frontiers: In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments," Marketing Science, INFORMS, vol. 39(2), pages 285-295, March.
    18. Mingming Cheng & Carmel Foley, 2018. "Understanding the distinctiveness of Chinese Post-80s tourists through an exploration of their formative experiences," Current Issues in Tourism, Taylor & Francis Journals, vol. 21(11), pages 1312-1328, July.
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