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Social Media Analytics for Customer Satisfaction Based on User Engagement and Interactions in the Tourism Industry

In: Computational and Strategic Business Modelling

Author

Listed:
  • Damianos P. Sakas

    (BICTEVAC LABORATORY Business Information and Communication Technologies in Value Chains laboratory, School of Applied Economics and Social Sciences, Agricultural University of Athens)

  • Dimitrios P. Reklitis

    (BICTEVAC LABORATORY Business Information and Communication Technologies in Value Chains laboratory, School of Applied Economics and Social Sciences, Agricultural University of Athens)

  • Panagiotis Trivellas

    (Organizational Innovation and Management Systems, School of Applied Economics and Social Sciences, Agricultural University of Athens)

Abstract

How social media big data can be beneficial for hospitality companies to promote customer satisfaction indirectly? This chapter attempts to respond to this question by extracting and analyzing big data and web analytics from eight world-leading hospitality social media pages. The extracted data have been analyzed statistically, and an FCM has been adopted to create useful optimization scenarios for social media administrators. The findings suggest investing in interactivity by uploading posts regularly will be more beneficial for customer satisfaction than having numerous fans on social media that remain inactive.

Suggested Citation

  • Damianos P. Sakas & Dimitrios P. Reklitis & Panagiotis Trivellas, 2024. "Social Media Analytics for Customer Satisfaction Based on User Engagement and Interactions in the Tourism Industry," Springer Proceedings in Business and Economics, in: Damianos P. Sakas & Dimitrios K. Nasiopoulos & Yulia Taratuhina (ed.), Computational and Strategic Business Modelling, pages 103-109, Springer.
    • Handle: RePEc:spr:prbchp:978-3-031-41371-1_11
    DOI: 10.1007/978-3-031-41371-1_11
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