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Integrating big data and marketing concepts into tourism, hospitality operations and strategy development

Author

Listed:
  • Chih-Hsing Liu

    (National Open University)

  • Jeou-Shyan Horng

    (National Open University)

  • Sheng-Fang Chou

    (National Open University)

  • Tai-Yi Yu

    (National Open University)

  • Yung-Chuan Huang

    (National Open University)

  • Jun-You Lin

    (National Open University)

Abstract

Big data (BD) research articles are on new issues, this study sought to fill the knowledge gap of linkage the relationships between big data and marketing strategy with comprehensive viewpoints across different research fields in tourism and hospitality literatures. Content analysis was conducted to gather materials from the particular studies. For each study, the content analysis included the title, abstract, journal, type of sample, exploration design, statistical and analytical techniques, data collection process and keywords was also conducted to confirm the main results of the criteria. The research shows that big data adds value to marketing strategies by using social media to collect information from consumers, which is complemented with appropriate evidence relevant to predicting their needs and behaviors.

Suggested Citation

  • Chih-Hsing Liu & Jeou-Shyan Horng & Sheng-Fang Chou & Tai-Yi Yu & Yung-Chuan Huang & Jun-You Lin, 2023. "Integrating big data and marketing concepts into tourism, hospitality operations and strategy development," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1905-1922, April.
    • Handle: RePEc:spr:qualqt:v:57:y:2023:i:2:d:10.1007_s11135-022-01426-5
    DOI: 10.1007/s11135-022-01426-5
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    References listed on IDEAS

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    1. Mingming Cheng & Deborah Edwards, 2019. "A comparative automated content analysis approach on the review of the sharing economy discourse in tourism and hospitality," Current Issues in Tourism, Taylor & Francis Journals, vol. 22(1), pages 35-49, January.
    2. Anton Oleinik & Irina Popova & Svetlana Kirdina & Tatyana Shatalova, 2014. "On the choice of measures of reliability and validity in the content-analysis of texts," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2703-2718, September.
    3. Li, Xin & Pan, Bing & Law, Rob & Huang, Xiankai, 2017. "Forecasting tourism demand with composite search index," Tourism Management, Elsevier, vol. 59(C), pages 57-66.
    4. Zhang, Lingyun & Lan, Chaoying & Qi, Fei & Wu, Ping, 2017. "Development pattern, classification and evaluation of the tourism academic community in China in the last ten years: From the perspective of big data of articles of tourism academic journals," Tourism Management, Elsevier, vol. 58(C), pages 235-244.
    5. Buhalis, Dimitrios & Volchek, Katerina, 2021. "Bridging marketing theory and big data analytics: The taxonomy of marketing attribution," International Journal of Information Management, Elsevier, vol. 56(C).
    6. Robert Hogenraad & Dean Mckenzie & Normand Péladeau, 2003. "Force and Influence in Content Analysis: The Production of New Social Knowledge," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 221-238, August.
    7. Hanen Khaldi & Vicente Prado-Gascó, 2021. "Bibliometric maps and co-word analysis of the literature on international cooperation on migration," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1845-1869, October.
    8. Emma Davidson & Rosalind Edwards & Lynn Jamieson & Susie Weller, 2019. "Big data, qualitative style: a breadth-and-depth method for working with large amounts of secondary qualitative data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 363-376, January.
    9. Piera Centobelli & Valentina Ndou, 2019. "Managing customer knowledge through the use of big data analytics in tourism research," Current Issues in Tourism, Taylor & Francis Journals, vol. 22(15), pages 1862-1882, September.
    10. Carmela Iorio & Giuseppe Pandolfo & Antonio D’Ambrosio & Roberta Siciliano, 2020. "Mining big data in tourism," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1655-1669, December.
    11. A. E. Opperhuizen & K. Schouten, 2021. "Dynamics and tipping point of issue attention in newspapers: quantitative and qualitative content analysis at sentence level in a longitudinal study using supervised machine learning and big data," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(1), pages 19-37, February.
    12. Dominique M. Hanssens & Koen H. Pauwels & Shuba Srinivasan & Marc Vanhuele & Gokhan Yildirim, 2014. "Consumer Attitude Metrics for Guiding Marketing Mix Decisions," Marketing Science, INFORMS, vol. 33(4), pages 534-550, July.
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