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Hidden theorizing in big data analytics: With a reference to tourism design research

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  • Mazanec, Josef A.

Abstract

As demonstrated in Xiang and Fesenmaier's (2017) collection of articles Tourism Design involves the application of Big Data Analytics. This raises the question whether the tourism researchers' struggle for theory building may (have) come to an end since Big Data is doing it for them. Addressing several misunderstandings, the author discusses most recent studies, mainly from the field of Tourism Design, and identifies the masked elements of theory hidden in heavily data-driven big data analytical approaches.

Suggested Citation

  • Mazanec, Josef A., 2020. "Hidden theorizing in big data analytics: With a reference to tourism design research," Annals of Tourism Research, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:anture:v:83:y:2020:i:c:s016073832030075x
    DOI: 10.1016/j.annals.2020.102931
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    References listed on IDEAS

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    1. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    2. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    3. Ferguson, Graham & Megehee, Carol M. & Woodside, Arch G., 2017. "Culture, religiosity, and economic configural models explaining tipping-behavior prevalence across nations," Tourism Management, Elsevier, vol. 62(C), pages 218-233.
    4. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    5. repec:jda:journl:vol.53:year:2019:issue4:pp217-228 is not listed on IDEAS
    6. Xiang, Zheng & Magnini, Vincent P. & Fesenmaier, Daniel R., 2015. "Information technology and consumer behavior in travel and tourism: Insights from travel planning using the internet," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 244-249.
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    Cited by:

    1. Montserrat Jiménez-Partearroyo & Ana Medina-López & Sudhir Rana, 2024. "Business intelligence and business analytics in tourism: insights through Gioia methodology," International Entrepreneurship and Management Journal, Springer, vol. 20(3), pages 2287-2321, September.
    2. Yu, Joanne & Egger, Roman, 2021. "Color and engagement in touristic Instagram pictures: A machine learning approach," Annals of Tourism Research, Elsevier, vol. 89(C).
    3. Yanan Jia & Anshul Garg & Peihua Shi, 2024. "Research on Factors Influencing Hotel Consumers’ Health: A Systematic Review and Ways Forward," Sustainability, MDPI, vol. 16(5), pages 1-17, March.
    4. Papatheodorou, Andreas, 2021. "A review of research into air transport and tourism," Annals of Tourism Research, Elsevier, vol. 87(C).
    5. Omid Oshriyeh, 2023. "Applied data science in tourism (Interdisciplinary approaches, methodologies, and applications," Information Technology & Tourism, Springer, vol. 25(1), pages 133-136, March.
    6. Weaver, Adam, 2021. "Tourism, big data, and a crisis of analysis," Annals of Tourism Research, Elsevier, vol. 88(C).

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