The Impact of Social Media on the Reputational Capital of Restaurant Establishments
DOI:
https://doi.org/10.32515/2663-1636.2026.15(48).185-195Keywords:
reputation capital, social networks, restaurant business, digital reputation, managementAbstract
The aim of this article is to develop theoretical foundations and provide practical recommendations for assessing the impact of social networks on the formation and development of reputational capital among restaurant establishments in the digital economy. Reputational capital is considered a strategic intangible asset that determines the level of consumer trust, competitiveness, and sustainability of the business. Special attention is paid to social networks and their correlation with brand perception and customer behavior. The key points of digital interaction between restaurant establishments and their audience are summarized, including online reviews and ratings, user-generated content (UGC), comments, the activities of micro- and nano-influencers, crisis messages, and the timeliness of response factor.
An applied analytical framework for assessing digital reputation is proposed, which enables the evaluation of communication effectiveness and the application of tools for attributing the impact of social networks, specifically cross-platform comparisons, campaign tags, and quasi-experimental approaches. The results obtained indicate that systematic work with content and reviews, clear moderation rules, prompt and empathetic response to complaints, as well as transparency in crisis situations, are statistically associated with improved online ratings and increased intentions to visit establishments. The feasibility of integrating the proposed indicators into regular analytical dashboards for PR and restaurant marketing, as well as their connection with financial KPIs, is determined.
The need to consider the noise of public digital data, differences in platform methodologies, and potential sample biases is substantiated. Prospects for further research include the development of attribution models that consider offline conversions, assessing the long-term impact of UGC on repeat visits and average check, as well as a comparative analysis of the effectiveness of different influencer levels depending on content scenarios.
References
1. Batchenko, L., & Honchar, L. (2018). Reputational capital as the basis for economic growth of enterprises in the hotel and restaurant business. Restorannyi I hotelnyi konsaltynh. Innovatsii, (2), 64-80 [in Ukrainian]. https://doi.org/10.31866/2616-7468.2.2018.157170
2. Sushchenko, O. A., Akhmedova, O. O., & Yermakov, I. O. (2023). The impact of reputation on the security of restaurant business enterprises. Tsentralnoukrainskyi naukovyi visnyk. Ekonomichni nauky, 10(43), 88-98 [in Ukrainian]. https://doi.org/10.32515/2663-1636.2023.10(43).88-98
3. Sushchenko O., Chaikovskyi S. (2024). Peculiarities of determining and ensuring the business reputation of a tourist enterprise. Tsentralnoukrainskyi naukovyi visnyk. Ekonomichni nauky, 12 (45), 149-161. [in Ukrainian]. https://doi.org/10.32515/2663-1636.2024.12(45).149-161
4. Chaika, I. M., & Dnistryanska, N. I. (2023). The influence of social networks on the formation of the image and reputation of restaurant enterprises. Industria turyzmu ta hostynnosti v Tsentralnii ta skhidnii Yevropi, (8), 65-71 [in Ukrainian]. https://doi.org/10.32782/tourismhospcee-8-9
5. Anderson, M., & Magruder, J. (2012). Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database. The Economic Journal, 122(563), 957-989. [in English]. https://doi.org/10.1111/j.1468-0297.2012.02512.
6. Anggani, M., & Suherlan, H. (2020). E-reputation Management of Hotel Indusrty. Preprints. [in English] https://doi.org/10.20944/preprints202002.0173.v1.
7. Chen, J., Zhang, Y., Cai, H., Liu, L., Liao, M., & Fang, J. (2024). A Comprehensive Overview of Micro-Influencer Marketing: Decoding the Current Landscape, Impacts, and Trends. Behavioral Sciences, 14(3), 243. [in English] https://doi.org/10.3390/bs14030243.
8. Coombs, W. (2007). Protecting Organization Reputations During a Crisis: The Development and Application of Situational Crisis Communication Theory. Corporate Reputation Review. 10. 163-176. [in English] https://doi.org/10.1057/palgrave.crr.1550049.
9. Cunningham, Scott (2021). Causal inference: the mixtape. London: Yale University Press. [in English]
10. Deephouse, D.L.. (2000). Media Reputation as a Strategic Resource: An Integration of Mass Communication and Resource-Based Theories. Journal of Management. 26. 1091-1112. [in English] https://doi.org/10.1177/014920630002600602.
11. Edelman. (2025). 2025 Edelman Trust Barometer global report. Edelman. https://www.edelman.com/sites/g/files/aatuss191/files/2025-01/2025%20Edelman%20Trust%20Barometer_Final.pdf [in English]
12. European Commission. (2017). Online reputation management: Training manual for the hospitality sector (Erasmus+ project materials). Publications Office of the European Union. https://op.europa.eu/. [in English]
13. Fombrun, C. J. (1996). Reputation: Realizing value from the corporate image. Harvard Business School Press. [in English]
14. Hansen, B. E. (2022). Econometrics. Princeton University Press. [in English]
15. Hernán, M. A., & Robins, J. M. (2025). Causal inference: What if. Chapman & Hall/CRC Press. [in English]
16. Javed, A. & Vardarsuyu, M. & Can, A.& Ekinci, Y. (2025). Social media influencers in tourism and hospitality: a comprehensive review combining bibliometric analysis and systematic literature review. Anatolia. 36. 1-31. [in English] https://doi.org/10.1080/13032917.2025.2531563.
17. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59-68. [in English] https://doi.org/10.1016/j.bushor.2009.09.003.
18. Kohavi, Ron & Longbotham, Roger & Sommerfield, Dan & Henne, Randal. (2009). Controlled experiments on the web: Survey and practical guide. Data Mining and Knowledge Discovery. 18. 140-181. [in English] https://doi.org/10.1007/s10618-008-0114-1.
19. Luca, M. (2016). Reviews, reputation, and revenue: The case of Yelp.com (Harvard Business School NOM Unit Working Paper No. 12-016). Harvard Business School. [in English] https://doi.org/10.2139/ssrn.1928601.
20. Luo, Y., & Xu, X. (2019). Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp. Sustainability, 11(19), 5254. [in English] https://doi.org/10.3390/su11195254.
21. Park, J., & Park, H. (2025). Understanding the Impact of Inconsistency on the Helpfulness of Online Reviews. Journal of Theoretical and Applied Electronic Commerce Research, 20(2), 80. [in English] https://doi.org/10.3390/jtaer20020080.
22. Pateli, A., Mylonas, N., & Spyrou, A. (2020). Organizational Adoption of Social Media in the Hospitality Industry: An Integrated Approach Based on DIT and TOE Frameworks. Sustainability, 12(17), 7132. [in English] https://doi.org/10.3390/su12177132.
23. Sushchenko, O., Kasenkova, K. and Sushchenko, S. (2022). Innovative Marketing Technologies in the Development of the Tourism Specialized Types. Business Management, 3, 5-16. [in English]
24. Szakal, A. C., Brătucu, G., Ciobanu, E., Chițu, I. B., Mocanu, A. A., Bălășescu, M., & Ialomițianu, G. (2024). Evaluating the Impact and Perception of Influencer Marketing Among Romanian Consumers -Insights from Quantitative Research. Administrative Sciences, 14(11), 276. [in English] https://doi.org/10.3390/admsci14110276.
25. Walker, K. (2010). A Systematic Review of the Corporate Reputation Literature: Definition, Measurement, and Theory. Corporate Reputation Review. 12(4). [in English] https://doi.org/10.1057/crr.2009.26.
26. Xia, Y., Kang, J., & Ding, J. (2022). Do online reviews encourage customers to write reviews? Evidence from restaurant revisit phases. Sustainability, 14(8), 4612. [in English] https://doi.org/10.3390/su14084612.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Olena Sushchenko, Taras Yukhym
This work is licensed under a Creative Commons Attribution 4.0 International License.
