SavedAdd your journal

Journals / Dumlupınar Üniversitesi Sosyal Bilimler Dergisi / 2026 / Sayı: 81

Analysis of Passenger Satisfaction in Airlines Using the LOPCOW-AROMAN Model: An Application of Star Alliance Strategic Partnership

Havayolu İşletmelerinde Yolcu Memnuniyetinin LOPCOW-AROMAN Modeliyle Analizi: Star Alliance Stratejik Ortaklığı Uygulaması

Mahmut Bakır(SAMSUN ÜNİVERSİTESİ)0000-0002-3898-4987
Ferhat İnce(ESKİŞEHİR TEKNİK ÜNİVERSİTESİ)0000-0003-3220-8909
Pages
168–189
Publication Date
2024-07-26
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings revealed that the most important satisfaction criteria are foods and beverages, value for money, and cabin staff service, respectively.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the aviation industry, customer satisfaction plays a critical role in business success.
📊
Key Findings & Data:As consumer expectations change post-pandemic, monitoring and improving the performance of airlines is becoming increasingly important.
💡
Conclusion & Impact:The findings revealed that the most important satisfaction criteria are foods and beverages, value for money, and cabin staff service, respectively.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Havayolları · Müşteri memnuniyeti · ÇKKV

Abstract

In the aviation industry, customer satisfaction plays a critical role in business success. As consumer expectations change post-pandemic, monitoring and improving the performance of airlines is becoming increasingly important. As such, this study aims to examine the performance of airlines in terms of passenger satisfaction, focusing on the Star Alliance strategic network. To this end, secondary data obtained from online passenger reviews by Skytrax was used to measure passenger satisfaction. In the study, Multi Criteria Decision-Making methods (MCDM) were used, namely the LOPCOW method to determine the importance levels of satisfaction criteria and the AROMAN method to rank the performance of airline alternatives. The findings revealed that the most important satisfaction criteria are foods and beverages, value for money, and cabin staff service, respectively. In addition, Air New Zealand was identified as the airline with the highest passenger satisfaction. Finally, a rigorous two-stage sensitivity analysis was conducted to test the consistency of the ranking, and it was concluded that the ranking was largely consistent. This study provides airlines with a robust and consistent model for evaluating their performance in the post-pandemic period.

Özet

Havacılık sektöründe müşteri memnuniyeti işletme başarısı üzerinde kritik bir role sahiptir. Pandemi sonrası tüketici beklentilerinin değişmesiyle birlikte, havayolu işletmelerinin performansının izlenmesi ve geliştirilmesi giderek daha önemli hale gelmiştir. Bu çalışma, Star Alliance stratejik ortaklığına odaklanarak yolcu memnuniyeti bakımından havayolu işletmelerinin performanslarını incelemeyi amaçlamaktadır. Bu doğrultuda, yolcu memnuniyetini ölçmek için Skytrax’ın çevrimiçi yolcu değerlendirmelerinden elde edilen ikincil veriler kullanılmıştır. Çalışmada, memnuniyet kriterlerinin önem düzeylerini belirlemek için LOPCOW yöntemi ve havayolu alternatiflerinin performanslarını sıralamak için AROMAN yöntemi olmak üzere Çok Kriterli Karar Verme yöntemleri (ÇKKV) kullanılmıştır. Bulgular, en önemli memnuniyet kriterlerinin sırasıyla yiyecek ve içecek, fiyat-fayda dengesi ve kabin ekibi hizmeti olduğunu ortaya koymuştur. Ayrıca, en yüksek yolcu memnuniyetine sahip havayolu işletmesinin Air New Zealand olduğu belirlenmiştir. Son olarak, elde edilen sıralamanın tutarlılığını test etmek amacıyla iki aşamalı duyarlılık analizi gerçekleştirilmiş ve sıralamanın büyük ölçüde tutarlı olduğu gözlemlenmiştir. Bu çalışma, havayolu işletmelerine pandemi sonrası dönemde performanslarını değerlendirmek için güçlü ve tutarlı bir model sağlamaktadır.

🔖

Cite This Article

Bakır, M., İnce, F. (2024). Analysis of Passenger Satisfaction in Airlines Using the LOPCOW-AROMAN Model: An Application of Star Alliance Strategic Partnership. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, Sayı: 81, 168–189. https://doi.org/10.51290/dpusbe.1432572

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (98)

  1. Abdi, Y., Li, X., ve Càmara-Turull, X. (2020). Impact of sustainability on firm value and financial performance in the air transport industry. Sustainability (Switzerland), 12(23), 1–22. https://doi.org/10.3390/su12239957
  2. Akdag, H., Kalayci, T., Karagöz, S., Zülfikar, H., ve Giz, D. (2014). The evaluation of hospital service quality by fuzzy MCDM. Applied Soft Computing, 23, 239–248. https://doi.org/10.1016/j.asoc.2014.06.033
  3. Aleksić, M., Popov Raljić, J., Gajić, T., Blešić, I., Dragosavac, M., Penić, M., ve Bugarčić, J. (2022). Factors of airline selection and reflight ıntention during the pandemic/case of serbian airlines users. Frontiers in Psychology, 13, 915321. https://doi.org/10.3389/fpsyg.2022.915321
  4. Alkharabsheh, A., ve Duleba, S. (2021). Public transportation service quality evaluation during the COVID-19 pandemic in Amman city using ıntegrated approach Fuzzy AHP-Kendall model. Vehicles, 3(3), 330–340. https://doi.org/10.3390/vehicles3030020
  5. Arif, M., Gupta, A., ve Williams, A. (2013). Customer service in the aviation industry - An exploratory analysis of UAE airports. Journal of Air Transport Management, 32, 1–7. https://doi.org/10.1016/j.jairtraman.2013.05.001
  6. Bakır, M. (2019). SWARA ve MABAC Yöntemleri ile havayolu işletmelerinde eWOM’ a dayalı memnuniyet düzeyinin analizi. Dokuz Eylul Universitesi Iktisadi ve Idari Bilimler Dergisi, 34(1), 51–66. https://doi.org/10.24988/ije.2019341787
  7. Bakır, M., Akan, Ş., ve Atalık, Ö. (2020). An evaluation for Long-Haul Low-Cost carriers using user-generated content: The Impact of perceived service quality on value for money. C. M. Q. Ramos, C. R. de Almeida, ve P. O. Fernandes (Ed.), Handbook of Research on Social Media Applications for the Tourism and Hospitality Sector in (ss. 231–251). Hershey PA: IGI Global. https://doi.org/10.4018/978-1-7998-1947-9.ch014
  8. Bakır, M., Akan, Ş., ve Durmaz, E. (2019). Exploring service quality of low-cost airlines in europe: An integrated MCDM approach. Economics and Business Review, 5(2), 109–130. https://doi.org/10.18559/ebr.2019.2.6
  9. Bakır, M., Akan, Ş., ve Özdemir, E. (2021). Regional aircraft selection with fuzzy PIPRECIA and Fuzzy MARCOS: A case study of the Turkish Airline industry. Facta Universitatis, Series: Mechanical Engineering, 19(3), 423–445. https://doi.org/10.22190/FUME210505053B
  10. Bakır, M., Akan, Ş., Özdemir, E., Nguyen, P.-H., Tsai, J.-F., ve Pham, H.-A. (2022). How to achieve passenger satisfaction in the airport? Findings from regression analysis and necessary condition analysis approaches through online airport Reviews. Sustainability, 14(4), 1–20. https://doi.org/10.3390/su14042151
  11. Bakır, M., ve Atalık, Ö. (2021). Application of fuzzy AHP and fuzzy MARCOS approach for the evaluation of e-service quality in the airline ındustry. Decision Making: Applications in Management and Engineering, 4(1), 127–152. https://doi.org/10.31181/dmame2104127b
  12. Ban, H. J., ve Kim, H. S. (2019). Understanding customer experience and satisfaction through airline passengers’ online review. Sustainability, 11(15), 1–17. https://doi.org/10.3390/su11154066
  13. Baradaran, V., ve Ghorbani, E. (2020). Development of fuzzy exploratory factor analysis for designing an e-learning service quality assessment model. International Journal of Fuzzy Systems, 22(6), 1772–1785. https://doi.org/10.1007/s40815-020-00901-1
  14. Bektaş, S. (2022). Türk sigorta sektörünün 2002-2021 dönemi için MEREC, LOPCOW, COCOSO, EDAS ÇKKV Yöntemleri ile performansının değerlendrilmesi. BDDK Bankacılık ve Finansal Piyasalar Dergisi, 16(2), 247–283. https://doi.org/10.46520/bddkdergisi.1178359
  15. Bošković, S., Švadlenka, L., Dobrodolac, M., Jovčić, S., ve Zanne, M. (2023a). An extended AROMAN method for cargo bike delivery concept selection. Decision Making Advances, 1(1), 1–9. https://doi.org/10.31181/v120231
  16. Bošković, S., Švadlenka, L., Jovčić, S., Dobrodolac, M., Simić, V., ve Bacanin, N. (2023b). An alternative ranking order method accounting for two-step normalization (AROMAN) - A Case study of the electric vehicle selection problem. IEEE Access, 11, 39496–39507. https://doi.org/10.1109/ACCESS.2023.3265818
  17. Bouwer, J., Saxon, S., ve Wittkamp, N. (2021). Back to the future? Airline sector poised for change post-COVID-19. Erişim adresi: https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/back-to-the-future-airline-sector-poised-for-change-post-covid-19
  18. Brochado, A., Duarte, M., ve Mengyuan, Z. (2022). Passengers’ perceptions of Chinese Airlines’ service quality: A mixed methods analysis of user-generated content. Journal of China Tourism Research. https://doi.org/10.1080/19388160.2022.2122647
  19. Button, K. (2001). Deregulation and liberalization of European air transport markets. Innovation: The European Journal of Social Science Research, 14(3), 255–275. https://doi.org/10.1080/13511610120102619
  20. Calisir, N., Basak, E., ve Calisir, F. (2016). Key drivers of passenger loyalty: A case of Frankfurt-Istanbul flights. Journal of Air Transport Management, 53, 211–217. https://doi.org/10.1016/j.jairtraman.2016.03.002
  21. Chakrabarti, S., Trehan, D., ve Makhija, M. (2018). Assessment of service quality using text mining – evidence from private sector banks in India. International Journal of Bank Marketing, 36(4), 594–615. https://doi.org/10.1108/IJBM-04-2017-0070
  22. Chang, Y. H., ve Yeh, C. H. (2002). A survey analysis of service quality for domestic airlines. European Journal of Operational Research, 139(1), 166–177. https://doi.org/10.1016/S0377-2217(01)00148-5
  23. Chi, J., ve Baek, J. (2013). Dynamic relationship between air transport demand and economic growth in the United States: A new look. Transport Policy, (29), 257–260. https://doi.org/10.1016/j.tranpol.2013.03.005
  24. Chow, C. K. W. (2015). On-time performance, passenger expectations and satisfaction in the Chinese airline industry. Journal of Air Transport Management, 47, 39–47. https://doi.org/10.1016/j.jairtraman.2015.04.003
  25. Čubranić-Dobrodolac, M., Jovčić, S., Bošković, S., ve Babić, D. (2023). A decision-making model for professional drivers selection: A Hybridized Fuzzy–AROMAN–Fuller approach. Mathematics, 11(13), 2831. https://doi.org/10.3390/math11132831
  26. De Oña, J., De Oña, R., Eboli, L., ve Mazzulla, G. (2013). Perceived service quality in bus transit service: A structural equation approach. Transport Policy, 29, 219–226. https://doi.org/10.1016/j.tranpol.2013.07.001
  27. Dehnavi, M. N., Yazdian, S. A., ve Sadjadi, S. J. (2023). Evaluating effective criteria on customer satisfaction using the best-worst method and optimizing resource allocation, case study Iran aseman airlines. Journal of Air Transport Management, 109. https://doi.org/10.1016/j.jairtraman.2023.102375
  28. Doğan, S., Özkul, E., ve Kaya, G. (2022). Investigating which services are effective on recommendation of the airline companies. Advances in Hospitality and Tourism Research, 10(1), 109–129. https://doi.org/10.30519/ahtr.915136
  29. Dožić, S. (2019). Multi-criteria decision making methods: Application in the aviation industry. Journal of Air Transport Management, 79, 1–22. https://doi.org/10.1016/j.jairtraman.2019.101683
  30. Eboli, L., ve Mazzulla, G. (2009). An ordinal logistic regression model for analysing airport passenger satisfaction. EuroMed Journal of Business, 4(1), 40–57. https://doi.org/10.1108/14502190910956684
  31. Ecer, F., ve Pamucar, D. (2022). A novel LOPCOW-DOBI multi-criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 102690. https://doi.org/10.1016/j.omega.2022.102690
  32. Feng, Z., ve Chen, M. (2022). Platformance-based cross-border ımport retail e-commerce service quality evaluation using an artificial neural network analysis. Journal of Global Information Management, 30(11). https://doi.org/10.4018/JGIM.306271
  33. Fida, B. A., Ahmed, U., Al-Balushi, Y., ve Singh, D. (2020). Impact of service quality on customer loyalty and customer satisfaction in Islamic Banks in the Sultanate of Oman. SAGE Open, 10(2). https://doi.org/10.1177/2158244020919517
  34. Forsyth, P. (1998). The gains from the liberalisation of air transport: A review of reform. Journal of Transport Economics and Policy, 32(1), 73–92.
  35. Fu, X., Oum, T. H., ve Zhang, A. (2010). Air transport liberalization and its impacts on airline competition and air passenger traffic. Transportation Journal, 49(4), 24–41. https://doi.org/10.5325/transportationj.49.4.0024
  36. Garrido, C., De Oña, R., ve De Oña, J. (2014). Neural networks for analyzing service quality in public transportation. Expert Systems with Applications, 41(15), 6830–6838. https://doi.org/10.1016/j.eswa.2014.04.045
  37. German, J. D., Redi, A. A. N. P., Prasetyo, Y. T., Persada, S. F., Ong, A. K. S., Young, M. N., ve Nadlifatin, R. (2022). Choosing a package carrier during COVID-19 pandemic: An integration of pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL). Journal of Cleaner Production, 346, 131123. https://doi.org/10.1016/j.jclepro.2022.131123
  38. Görçün, Ö. F., Tirkolaee, E. B., Küçükönder, H., ve Garg, C. P. (2024). Assessing and selecting sustainable refrigerated road vehicles in food logistics using a novel multi-criteria group decision-making model. Information Sciences, 661, 120161. https://doi.org/10.1016/j.ins.2024.120161
  39. Güreş, N., Arslan, S., ve Yılmaz, H. (2015). E-Service quality, passenger satisfaction and passenger loyalty relationship in airline ındustry. Journal of Management, Marketing and Logistics, 2(1), 44–56. https://doi.org/10.17261/pressacademia.2015111604
  40. Hu, Y. C., Lee, P. C., Chuang, Y. S., ve Chiu, Y. J. (2018). Improving the sustainable competitiveness of service quality within air cargo terminals. Sustainability (Switzerland), 10(7), 2319. https://doi.org/10.3390/su10072319
  41. Hussain, R. (2016). The mediating role of customer satisfaction: evidence from the airline industry. Asia Pacific Journal of Marketing and Logistics, 28(2), 234–255. https://doi.org/10.1108/APJML-01-2015-0001
  42. IATA. (2022). Convenience is top priority for passengers post pandemic. https://www.iata.org/en/pressroom/2022-releases/2022-11-01-01/
  43. Jomnonkwao, S., ve Ratanavaraha, V. (2016). Measurement modelling of the perceived service quality of a sightseeing bus service: An application of hierarchical confirmatory factor analysis. Transport Policy, 45, 240–252. https://doi.org/10.1016/j.tranpol.2015.04.001
  44. Kalia, P., Kaushal, R., Singla, M., ve Parkash, J. (2021). Determining the role of service quality, trust and commitment to customer loyalty for telecom service users: a PLS-SEM approach. TQM Journal, 33(7), 377–396. https://doi.org/10.1108/TQM-04-2021-0108
  45. Kara, K., Yalçın, G. C., Acar, A. Z., Simic, V., Konya, S., ve Pamucar, D. (2024). The MEREC-AROMAN method for determining sustainable competitiveness levels: A case study for Turkey. Socio-Economic Planning Sciences, 91, 101762. https://doi.org/10.1016/j.seps.2023.101762
  46. Keleş, N. (2023). Lopcow ve Cradis yöntemleriyle G7 ülkelerinin ve Türkiye’nin yaşanabilir güç merkezi şehirlerinin değerlendirilmesi. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(3), 727–747. https://doi.org/10.25287/ohuiibf.1239201
  47. Kim, J. J., Hwang, J., ve Kim, I. (2020). Congruent charitable cause sponsorship effect: Air travelers’ perceived benefits, satisfaction and behavioral intention. Journal of Hospitality and Tourism Management, 42, 190–198. https://doi.org/10.1016/j.jhtm.2020.01.004
  48. Kohli, C. S., ve Habibi, M. R. (2023). The mysterious world of airline pricing: innovative practices and strategies for profit. Journal of Business Strategy. https://doi.org/10.1108/JBS-12-2020-0270
  49. Kos Koklic, M., Kukar-Kinney, M., ve Vegelj, S. (2017). An investigation of customer satisfaction with low-cost and full-service airline companies. Journal of Business Research, 80, 188–196. https://doi.org/10.1016/j.jbusres.2017.05.015
  50. Krumm, J., Davies, N., ve Narayanaswami, C. (2008). User-Generated Content. IEEE Pervasive Computing, 7(4), 10–11. https://doi.org/10.1109/MPRV.2008.85
  51. Leon, S., ve Dixon, S. (2023). Airline satisfaction and loyalty: Assessing the influence of personality, trust and service quality. Journal of Air Transport Management, 113, 102487. https://doi.org/10.1016/j.jairtraman.2023.102487
  52. Li, W., Yu, S., Pei, H., Zhao, C., ve Tian, B. (2017). A hybrid approach based on fuzzy AHP and 2-tuple fuzzy linguistic method for evaluation in-flight service quality. Journal of Air Transport Management, 60, 49–64. https://doi.org/10.1016/j.jairtraman.2017.01.006
  53. Li, X., de Groot, M., ve Bäck, T. (2023). Using forecasting to evaluate the impact of COVID-19 on passenger air transport demand. Decision Sciences, 54(4), 394–409. https://doi.org/10.1111/deci.12549
  54. Lin, Z., ve Vlachos, I. (2018). An advanced analytical framework for improving customer satisfaction: A case of air passengers. Transportation Research Part E: Logistics and Transportation Review, 114, 185–195. https://doi.org/10.1016/j.tre.2018.04.003
  55. Liu, L., ve Fang, J. (2019). Study on potential factors of patient satisfaction: Based on exploratory factor analysis. Patient Preference and Adherence, 13, 1983–1994. https://doi.org/10.2147/PPA.S228073
  56. Lucini, F. R., Tonetto, L. M., Fogliatto, F. S., ve Anzanello, M. J. (2020). Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews. Journal of Air Transport Management, 83, 101760. https://doi.org/10.1016/j.jairtraman.2019.101760
  57. Malighetti, P., Meoli, M., Paleari, S., ve Redondi, R. (2011). Value determinants in the aviation industry. Transportation Research Part E: Logistics and Transportation Review, 47(3), 359–370. https://doi.org/10.1016/j.tre.2010.11.007
  58. Marine-Roig, E., ve Anton Clavé, S. (2015). Tourism analytics with massive user-generated content: A case study of Barcelona. Journal of Destination Marketing and Management, 4(3), 162–172. https://doi.org/10.1016/j.jdmm.2015.06.004
  59. Mazzeo, M. J. (2003). Competition and service quality in the U.S. airline industry. Review of Industrial Organization, 22(4), 275–296. https://doi.org/10.1023/A:1025565122721
  60. Naab, T. K., ve Sehl, A. (2017). Studies of user-generated content: A systematic review. Journalism, 18(10), 1256–1273. https://doi.org/10.1177/1464884916673557
  61. Nadiri, H., Hussain, K., Ekiz, E. H., ve Erdoǧan, Ş. (2008). An investigation on the factors influencing passengers’ loyalty in the North Cyprus national airline. TQM Journal, 20(3), 265–280. https://doi.org/10.1108/17542730810867272
  62. Nikolić, I., Milutinović, J., Božanić, D., ve Dobrodolac, M. (2023). Using an interval Type-2 Fuzzy AROMAN decision-making method to ımprove the sustainability of the postal network in rural areas. Mathematics, 11(14), 3105. https://doi.org/10.3390/math11143105
  63. Noviantoro, T., ve Huang, J. P. (2022). Investigating airline passenger satisfaction: Data mining method. Research in Transportation Business and Management, 43, 100726. https://doi.org/10.1016/j.rtbm.2021.100726
  64. O’Reilly, D., ve Sweet, A. (1998). The liberalization and reregulation of air transport. Journal of European Public Policy, 5(3), 447–466. https://doi.org/10.1080/135017698343910
  65. Okumuş, A., ve Asil, H. (2007). Havayolu taşımacılığında yerli ve yabancı yolcuların memnuniyet düzeylerine göre beklentilerinin incelenmesi. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 13, 152–175.
  66. Pamučar, D., Yazdani, M., Montero-Simo, M. J., Araque-Padilla, R. A., ve Mohammed, A. (2021). Multi-criteria decision analysis towards robust service quality measurement. Expert Systems with Applications, 170, 114508. https://doi.org/10.1016/j.eswa.2020.114508
  67. Parasuraman, A., Zeithaml, V. A., ve Berry, L. L. (1985). A conceptual model of service quality and ıts ımplications for future research. Journal of Marketing, 49(4), 41–50. https://doi.org/10.2307/1251430
  68. Parasuraman, A., Zeithaml, V. A., ve Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
  69. Pishahang, M., Jovcic, S., Hashemkhani Zolfani, S., Simic, V., ve Görçün, Ö. F. (2023). MCDM-Based wildfire risk assessment: A case study on the State of Arizona. Fire, 6(12), 449. https://doi.org/10.3390/fire6120449
  70. Punel, A., Al Hajj Hassan, L., ve Ermagun, A. (2019). Variations in airline passenger expectation of service quality across the globe. Tourism Management, 75, 491–508. https://doi.org/10.1016/j.tourman.2019.06.004
  71. Qin, H., Prybutok, V. R., ve Zhao, Q. (2010). Perceived service quality in fast-food restaurants: Empirical evidence from China. International Journal of Quality and Reliability Management, 27(4), 424–437. https://doi.org/10.1108/02656711011035129
  72. Qiu, S., Dooley, L. M., ve Xie, L. (2020). How servant leadership and self-efficacy interact to affect service quality in the hospitality industry: A polynomial regression with response surface analysis. Tourism Management, 78, 104051. https://doi.org/10.1016/j.tourman.2019.104051
  73. Rahim, A. I. A., Ibrahim, M. I., Musa, K. I., Chua, S. L., ve Yaacob, N. M. (2021). Assessing patient-perceived hospital service quality and sentiment in malaysian public hospitals using machine learning and facebook reviews. International Journal of Environmental Research and Public Health, 18(18). https://doi.org/10.3390/ijerph18189912
  74. Rey, M. B. (2003). Structural changes in the Spanish scheduled flights market as a result of air transport deregulation in Europe. Journal of Air Transport Management, 9(3), 195–200. https://doi.org/10.1016/S0969-6997(02)00097-2
  75. Rong, Y., Yu, L., Liu, Y., Simic, V., ve Garg, H. (2024). The FMEA model based on LOPCOW-ARAS methods with interval-valued Fermatean fuzzy information for risk assessment of Rveamp;D projects in industrial robot offline programming systems. Computational and Applied Mathematics, 43(1), 25. https://doi.org/10.1007/s40314-023-02532-2
  76. Sancho-Esper, F. M., ve Mas-Ruiz, F. J. (2019). Competition in the Spanish domestic airline sector: Market deregulation, switching costs and route cost behaviour. Academia Revista Latinoamericana de Administracion, 32(2), 282–302. https://doi.org/10.1108/ARLA-10-2017-0293
  77. Santos, M. L. B. dos. (2022). The “so-called” UGC: an updated definition of user-generated content in the age of social media. Online Information Review, 46(1), 95–113. https://doi.org/10.1108/OIR-06-2020-0258
  78. Sarılgan, A. E., ve Bakır, M. (2023). Havayolu taşımacılığında havayolu işletmesi seçimi ve memnuniyetin belirleyicileri: Üniversite öğrencileri üzerine bir araştırma. İzmir İktisat Dergisi, 38(1), 158–174. https://doi.org/10.24988/ije.1101367
  79. Sezgen, E., Mason, K. J., ve Mayer, R. (2019). Voice of airline passenger: A text mining approach to understand customer satisfaction. Journal of Air Transport Management, 77, 65–74. https://doi.org/10.1016/j.jairtraman.2019.04.001
  80. Skytrax. (2024). About Skytrax Ratings. https://skytraxratings.com/about
  81. Song, C., Ma, X., Ardizzone, C., ve Zhuang, J. (2024). The adverse impact of flight delays on passenger satisfaction: An innovative prediction model utilizing wide ve deep learning. Journal of Air Transport Management, 114, 102511. https://doi.org/10.1016/j.jairtraman.2023.102511
  82. Sulu, D., Arasli, H., ve Saydam, M. B. (2022). Air-travelers’ perceptions of service quality during the COVID-19 pandemic: Evidence from tripadvisor sites. Sustainability, 14(1). https://doi.org/10.3390/su14010435
  83. Sureshchandar, G. S., Rajendran, C., ve Anantharaman, R. N. (2002). Determinants of customer-perceived service quality: A confirmatory factor analysis approach. Journal of Services Marketing, 16(1), 9–34. https://doi.org/10.1108/08876040210419398
  84. Tahanisaz, S., ve shokuhyar, S. (2020). Evaluation of passenger satisfaction with service quality: A consecutive method applied to the airline industry. Journal of Air Transport Management, 83. https://doi.org/10.1016/j.jairtraman.2020.101764
  85. Thongmak, M. (2024). Twitter content strategies to maximize engagement: The case of Thai Banks. Computers in Human Behavior, 152, 108081. https://doi.org/10.1016/j.chb.2023.108081
  86. Torkayesh, A. E., Ecer, F., Pamucar, D., ve Karamaşa, Ç. (2021). Comparative assessment of social sustainability performance: Integrated data-driven weighting system and CoCoSo model. Sustainable Cities and Society, 71, 102975. https://doi.org/10.1016/j.scs.2021.102975
  87. Tsafarakis, S., Kokotas, T., ve Pantouvakis, A. (2018). A multiple criteria approach for airline passenger satisfaction measurement and service quality improvement. Journal of Air Transport Management, 68, 61–75. https://doi.org/10.1016/j.jairtraman.2017.09.010
  88. Ulutaş, A., Balo, F., ve Topal, A. (2023). Identifying the most efficient natural fibre for common commercial building ınsulation materials with an ıntegrated PSI, MEREC, LOPCOW and MCRAT Model. Polymers, 15(6), 1500. https://doi.org/10.3390/polym15061500
  89. Van Dijck, J. (2009). Users like you? Theorizing agency in user-generated content. Media, Culture and Society, 31(1), 41–58. https://doi.org/10.1177/0163443708098245
  90. Vera-Martínez, J., Trujillo-León, A., ve Vásquez-García, F. (2022). Domestic confinement crisis and its un-intensifying effect on service quality expectations towards e-stores: the case of the COVID-19 pandemic in Mexico. International Review of Retail, Distribution and Consumer Research, 32(2), 167–183. https://doi.org/10.1080/09593969.2022.2048412
  91. Wang, J., Li, Y., Wu, B., ve Wang, Y. (2021). Tourism destination image based on tourism user generated content on internet. Tourism Review, 76(1), 125–137. https://doi.org/10.1108/TR-04-2019-0132
  92. Wu, S., ve Gao, Y. (2023). Machine learning approach to analyze the sentiment of airline passengers’ tweets. Transportation Research Record. https://doi.org/10.1177/03611981231172948
  93. Xie, C., ve Sun, Z. (2021). Influence of perceived quality on customer satisfaction in different stages of services. Nankai Business Review International, 12(2), 258–280. https://doi.org/10.1108/NBRI-01-2020-0004
  94. Yaşar, E., ve Ünlü, M. (2023). Üniversitelerde sürdürülebilirliğin incelenmesi: LOPCOW ve MEREC tabanlı CoCoSo yöntemleriyle çevreci üniversitelerin analizi. Journal of Business Academy, 4(2), 125–142. https://doi.org/10.26677/TR1010.2023.1246
  95. Yıldız, B., ve Çiğdem, Ş. (2018). Havayolu hizmet kalitesinin müşteri memnuniyeti üzerindeki etkisinin yapısal eşitlik modeli ile analizi. Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 8(16), 235–254. https://doi.org/10.29029/busbed.423829
  96. Yu, C. M. J., Wu, L. Y., Chiao, Y. C., ve Tai, H. S. (2005). Perceived quality, customer satisfaction, and customer loyalty: The case of lexus in Taiwan. Total Quality Management and Business Excellence, 16(6), 707–719. https://doi.org/10.1080/14783360500077393
  97. Zahraee, S. M., Shiwakoti, N., Jiang, H., Qi, Z., He, Y., Guo, T., ve Li, Y. (2023). A study on airlines’ responses and customer satisfaction during the COVID-19 pandemic. International Journal of Transportation Science and Technology, 12(4), 1017–1037. https://doi.org/10.1016/j.ijtst.2022.11.004
  98. Zhang, S., Zhong, H., Wei, C., ve Zhang, D. (2022). Research on logistics service assessment for smart city: A Users’ Review sentiment analysis approach. Electronics (Switzerland), 11(23), 4018. https://doi.org/10.3390/electronics11234018.