Kutuplaşmış Misafir Deneyimleri Karşısında Çevrim İçi İtibar Yönetimi: Lüks Otel Yorumlarından Kanıtlar

Öz

Bu çalışma; Türkiye'nin dört büyük turizm ve iş şehri olan İstanbul, Ankara, İzmir ve Antalya'daki lüks otellerin çevrimiçi müşteri yorumlarını ve otel yönetimlerinin yanıtlarını incelemektedir. Aynı otel için çok olumlu ve son derece olumsuz yorumların bir arada bulunması, kritik bir sorunu vurgulamaktadır: misafir beklentileri ile hizmet sunumu arasındaki uyumsuzluk. Geleneksel anketlerde genellikle gözden kaçan bu kutuplaşmış deneyimleri daha iyi anlamak için çalışma, NLP (Doğal Dil İşleme) kullanarak içerik analizi ve duygu analizini birleştiren karma yöntemli bir yaklaşım benimsemiştir. TripAdvisor'dan toplam 200 müşteri yorumu ve bunlara karşılık gelen yönetim yanıtları analiz edilmiştir. Tüm yorumlar Ocak ile Haziran 2025 tarihleri arasında toplanmış olup, bunların 177’si yönetici yanıtı içerirken 23’ü yanıtsız kalmıştır. Sonuçlar; hizmet kalitesindeki tutarsızlıkların, personel etkileşimindeki farklılıkların, altyapı sorunlarının ve çeşitli yanıt stratejilerinin kutuplaşmaya katkıda bulunduğunu göstermektedir. Yönetim yanıtları ayrıca otellerin dijital şikâyetleri nasıl ele aldığını değerlendirmek için içerik ve üslup açısından kategorilere ayrılmıştır. Çalışma "kutuplaşmış deneyimler" kavramını tanıtarak ve çevrimiçi yorum analizinin konaklama araştırmalarında geleneksel yöntemlere göre daha derin bilgiler sağlayabileceğini göstererek literatüre katkıda bulunmaktadır.

Anahtar Kelimeler

• Çevrimiçi Yorumlar
• Dijital Şikayetler
• Doğal Dil İşleme
• Duygu Analizi
• kutuplaşmış deneyimler

Managing Online Reputation amid Polarized Guest Experiences: Evidence from Luxury Hotel Reviews in Turkiye

Öz

This study examines online customer reviews and hotel management responses from luxury hotels in Turkey’s four major tourism and business cities: Istanbul, Ankara, Izmir, and Antalya. The co-occurrence of very positive and highly negative reviews for the same hotel highlights a critical issue: the mismatch between guest expectations and service delivery. To better understand these polarized experiences—often overlooked by traditional surveys—the study adopts a mixed-methods approach combining content analysis and sentiment analysis using NLP (Natural Language Processing). A total of 200 customer reviews and their corresponding managerial responses from TripAdvisor were analyzed. Results show that inconsistencies in service quality, differences in staff interaction, infrastructure problems, and varied response strategies contribute to polarization. Management responses were also categorized by content and tone to evaluate how hotels handle digital complaints. The study contributes to the literature by introducing the concept of “polarized experiences” and showing that online review analysis can provide deeper insights than conventional methods in hospitality research.

Anahtar Kelimeler

• Natural Language Processing
• Polarized experiences
• Digital Complaints
• Sentiment Analysis
• Online Review

Kaynakça

1. Anagnostopoulou, S. C., Buhalis, D., Kountouri, I., Manousakis, E., & Tsekrekos, A. (2020). The impact of online reputation on hotel profitability. International Journal of Contemporary Hospitality Management, 32(1), 20–39.
2. Ayvaz-Çavdaroğlu, N., Iyanna, S., & Foster, M. (2024). Smart service quality in hospitality – A quantitative assessment using MCDM and clustering methods. International Journal of Hospitality Management, 123, 103931.
3. Bolton, R. N., McColl-Kennedy, J. R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., & Zaki, M. (2018). Customer experience challenges: bringing together digital, physical and social realms. Journal of Service Management, 29(5), 776–808.
4. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
5. Casado-Díaz, A. B., Andreu, L., Beckmann, S. C., & Miller, C. (2020). Negative online reviews and webcare strategies in social media: Effects on hotel attitude and booking intentions. Current Issues in Tourism, 23(4), 418–422.
6. Fidan, A. (2013). Kişisel ve Kurumsal Açıdan İmaj Oluşturma, İmaj Yaratma ve İmaj Yenileme Süreçlerine İlişkin Tespitler ve Bireysel / Kurumsal İmaj Oluşturma ve İmaj Koruma Modeli Önerisi. Kent Akademisi, 6(15), 63-73.
7. Filieri, R., Lin, Z., Pino, G., Alguezaui, S., & Inversini, A. (2021). The role of visual and verbal cues in eWOM on consumers’ behavioral intention and decisions. Journal of Business Research, 135, 663–675.
8. Gong, C., Liu, J., Law, R., & Ye, Q. (2022). Exploring the effects of official-structured managerial responses on hotel online popularity. International Journal of Hospitality Management, 106, 103293.

9. Han, S., Anderson, C. K., & Chung, K. (2023). Do managerial communications improve customer satisfaction and eWOM? The moderating effect of response authenticity. Humanities & Social Sciences Communications, 10(1), 473.
10. Harrison-Walker, L. J. (2019). The critical role of customer forgiveness in successful service recovery. Journal of Business Research, 95, 376–391.
11. Kandampully, J., Zhang, T., & Bilgihan, A. (2015). Customer loyalty: A review and future directions with a special focus on the hospitality industry. International Journal of Contemporary Hospitality Management, 27(3), 379–414.
12. Kim, B., Kim, S., & Heo, C. Y. (2016). Analysis of satisfiers and dissatisfiers in online hotel reviews on social media. International Journal of Contemporary Hospitality Management, 28(9), 1915–1936.
13. Kirilenko, A. P., Stepchenkova, S. O., Kim, H., & Li, X. (2018). Automated Sentiment Analysis in Tourism: Comparison of Approaches. Journal of Travel Research, 57(8), 1012–1025.
14. Ku, C.-H., Chang, Y.-C., & Wang, Y. (2024). How to strategically respond to online hotel reviews: A strategy-aware deep learning approach. Information & Management, 61(5), 103970.
15. Ladhari, R., & Michaud, M. (2015). eWOM effects on hotel booking intentions, attitudes, trust, and website perceptions. International Journal of Hospitality Management, 46, 36-45.
16. Le, L. H., & Ha, Q. A. (2021). Effects of negative reviews and managerial responses on consumer attitude and subsequent purchase behavior: An experimental design. Computers in Human Behavior, 124, 106912.
17. Lee, C. K. H., Tse, Y. K., Zhang, M., & Wang, Y. (2022). What have hosts overlooked for improving stay experience in accommodation-sharing? Empirical evidence from Airbnb customer reviews. International Journal of Contemporary Hospitality Management, 35(2), 765-784.
18. Lopes, A. I., Malthouse, E. C., Dens, N., & De Pelsmacker, P. (2024). Is webcare good for business? A study of the effect of managerial response strategies to online reviews on hotel bookings. Journal of Service Management, 35(6), 22–41.
19. Olawuyi, O. S., & Adediran, O. (2025). A bibliometric analysis of service quality in the hospitality industry (2014–2024). Administrative Sciences, 15(6), 215.
20. Oliver, R. L. (1997). Satisfaction: A behavioral perspective on the consumer. New York: McGraw-Hill.
21. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
22. Park, S., & Nicolau, J. L. (2015). Asymmetric effects of online consumer reviews. Annals of Tourism Research, 50, 67–83.
23. Rose, M., Blodgett, J. G., & DeMaeyer, P. (2016). Should Hotels Respond to Negative Online Reviews? Cornell Hospitality Quarterly, 57(4), 396–410.
24. Roozen, I., & Raedts, M. (2018). The effects of online customer reviews and managerial responses on travelers’ decision-making processes. Journal of Hospitality Marketing & Management, 27(8), 974–996.
25. Salehi-Esfahani, S., Torres, E. N., & Hua, N. (2023). Responding to negative reviews? The interplay of management response strategy and service failure type. Journal of Hospitality Marketing & Management, 32(7), 833–858.
26. Simon, F. (2013). The influence of empathy in complaint handling: Evidence of gratitudinal and transactional routes to loyalty. Journal of Retailing and Consumer Services, 20(6), 599–608.
27. Sparks, B. A., & Browning, V. (2010). Complaining in cyberspace: The motives and forms of hotel guests’ complaints online. Journal of Hospitality Marketing & Management, 19(7), 797–818.
28. Sparks, B. A., So, K. K. F., & Bradley, G. L. (2016). The effects of hotel responses on customer ınferences of trust and concern. Tourism Management, 53, 74-85.
29. Wang, Y., & Chaudhry, A. (2018). When and How Managers’ Responses to Online Reviews Affect Subsequent Reviews. Journal of Marketing Research, 55(2), 163–177.
30. Xie, K. L., So, K. K. F., & Wang, W. (2017). Joint effects of management responses and online reviews on hotel financial performance: A data-analytics approach. International Journal of Hospitality Management, 62, 101–110.
31. Xiang, Z., Schwartz, Z., Gerdes Jr., J. H., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44, 120–130.
32. Yang, K., Wu, T., & Zhang, W. (2025). Customer care meets technology: Investigating the role of AI in managerial responses to online reviews. In Proceedings of the 2024 5th International Conference on Computer Science and Management Technology (ICCSMT 2024) (pp. 232–237). Association for Computing Machinery.