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Consumer engagement: the role of social currency in online reviews

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  • Muhammet Kesgin
  • Rajendran S. Murthy

Abstract

We explore the interplay between social currency (SC) and consumer engagement on social networks. We use text analyses based on both human coding and machine learning asisted sentiment analysis on reviews collected from Facebook pages, and we show that SC has a positive effect on ratings and visitor loyalty. First, we find that attractions have varying makeup of SC as represented in the six dimensions of SC. Second, repeat visits increase SC. Third, SC positively impacts revisit intentions even in the absence of prior experience. We also find that prior experience does not appear to yield better ratings, however, it predicts revisit intentions. This study represents the first use of SC in the tourism domain. Theoretical and practical implications alongside limitations and future research are discussed.

Suggested Citation

  • Muhammet Kesgin & Rajendran S. Murthy, 2019. "Consumer engagement: the role of social currency in online reviews," The Service Industries Journal, Taylor & Francis Journals, vol. 39(7-8), pages 609-636, June.
    • Handle: RePEc:taf:servic:v:39:y:2019:i:7-8:p:609-636
    DOI: 10.1080/02642069.2018.1553237
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    Citations

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    Cited by:

    1. Manosso, Franciele Cristina & Domareski Ruiz, Thays Cristina, 2021. "Using sentiment analysis in tourism research: A systematic, bibliometric, and integrative review," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7, pages 16-27.
    2. Bruno Nogueira Silva & Wesley Vieira Silva & Alvaro Fabiano Pereira Macêdo & Natallya Almeida Levino & Luciano Luiz Dalazen & Fabíola Kaczam & Claudimar Pereira Veiga, 2024. "A systematic review on social currency: a one-decade perspective," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(2), pages 636-652, June.
    3. Peter R. J. Trim & Yang-Im Lee & An Vu, 2023. "Insights into How Vietnamese Retailers Utilize Social Media to Facilitate Knowledge Creation through the Process of Value Co-Creation," Future Internet, MDPI, vol. 15(4), pages 1-18, March.
    4. Karine Oganisjana & Konstantins Kozlovskis, 2019. "The Identification of Opportunities for Innovations through Collecting Problems from Citizens," JOItmC, MDPI, vol. 5(4), pages 1-15, September.
    5. Cristina Franciele & Thays Christina Domareski Ruiz, 2021. "Using sentiment analysis in tourism research: A systematic, bibliometric, and integrative review," Post-Print hal-03373984, HAL.
    6. Zixing Shen & Michael J. Pritchard, 2022. "Cognitive engagement on social media: A study of the effects of visual cueing in educational videos," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1253-1267, September.
    7. Moon, Sangkil & Kim, Moon-Yong & Bergey, Paul K., 2019. "Estimating deception in consumer reviews based on extreme terms: Comparison analysis of open vs. closed hotel reservation platforms," Journal of Business Research, Elsevier, vol. 102(C), pages 83-96.
    8. Bailey, Ainsworth Anthony & Bonifield, Carolyn M. & Elhai, Jon D., 2021. "Modeling consumer engagement on social networking sites: Roles of attitudinal and motivational factors," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).

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