Do We Scapegoat The Pandemic? Investigating The Changes in Satisfaction Drivers of Air Passengers With DWLS-SEM

Yıl 2024, Cilt: 8 Sayı: 2, 117 - 127, 27.06.2024

Ferhat İnce , Özlem Atalık

https://doi.org/10.30518/jav.1464379

Öz

This paper aims to investigate whether there is an alteration in the drivers of air passenger satisfaction before and after COVID-19. We conducted the multigroup structural equation modelling with the diagonally weighted least squares estimation method as the variables are categorical. Lastly, we performed ANOVA to spot if there is a change in the drivers of passenger satisfaction between before and after the pandemic. The results suggest all service attributes have a significant impact on satisfaction in the pre-COVID-19 era. Even if it seems that in-flight entertainment and in-flight WiFi are not as influential as before in the post-pandemic, ANOVA results revealed the difference between the pre-pandemic and the new-normal period was not statistically significant. Accordingly, airlines should not ignore the need to improve service attributes, called premium services, and holistically improve service design. In addition, after value for money, the most important attribute for passengers is ground handling. Hence, speeding up the boarding process would return carriers in the form of more satisfied customers. To the best of our knowledge, this is the first paper employing Multigroup DWLS SEM to focus on changes in determinants of air passenger satisfaction in a holistic approach, focusing on pandemic periods.

Anahtar Kelimeler

Airlines, Customer satisfaction, COVID-19, Diagonally weighted least squares, Structural equation modeling

Kaynakça

• Afaq, A., Gaur, L., Singh, G., & Dhir, A. (2023). COVID-19: transforming air passengers’ behaviour and reshaping their expectations towards the airline industry. Tourism Recreation Research, 48(5), 800–808.
• Aksoy, S., Atilgan, E., & Akinci, S. (2003). Airline services marketing by domestic and foreign firms: differences from the customers’ viewpoint. Journal of Air Transport Management, 9(6), 343–351.
• Albuquerque, P., Pavlidis, P., Chatow, U., Chen, K. Y., & Jamal, Z. (2012). Evaluating promotional activities in an online two-sided market of user-generated content. Marketing Science, 31(3), 406–432.
• Alkhatib, S. F., & Migdadi, Y. K. A. (2018). Operational determinants of airline service quality: Worldwide cross- regional analysis. Quality Management Journal, 25(4), 186–200.
• An, M., & Noh, Y. (2009). Airline customer satisfaction and loyalty: Impact of in-flight service quality. Service Business, 3(3), 293–307.
• Anderson, C. R., & Zeithaml, C. P. (1984). Stage of the Product Life Cycle, Business Strategy, and Business Performance. The Academy of Management Journal, 27(1), 5–24.
• Anitsal, M. M., Anitsal, I., & Anitsal, S. (2019). Is your business sustainable? A sentiment analysis of air passengers of top 10 US-based airlines. Journal of Global Scholars of Marketing Science, 29(1), 25–41.
• Atalay, K. D., Atalay, B., & Isin, F. B. (2019). FIPIA with information entropy: A new hybrid method to assess airline service quality. Journal of Air Transport Management, 76, 67–77.
• Atalık, Ö., Bakır, M., & Akan, Ş. (2019). The Role of In-Flight Service Quality on Value for Money in Business Class: A Logit Model on the Airline Industry. Administrative Sciences, 9(1), 26.
• Babbar, S., & Koufteros, X. (2008). The human element in airline service quality: Contact personnel and the customer. International Journal of Operations and Production Management, 28(9), 804–830.
• Badanik, B., Remenysegova, R., & Kazda, A. (2023). Sentimental Approach to Airline Service Quality Evaluation. Aerospace, 10(10), 883.
• Bagheri, A., Habshah, M., & Imon, R. H. M. R. (2012). A Novel Collinearity-Influential Observation Diagnostic Measure Based on a Group Deletion Approach. Communications in Statistics - Simulation and Computation, 41(8), 1379–1396.
• Bakır, M., Akan, S., & Atalik, O. (2020). An Evaluation for Long-Haul Low-Cost Carriers Using User-Generated Content: The Impact of Perceived Service Quality on Value for Money. In C. Ramos, C. Almeida, & P. Fernandes (Eds.), Handbook of Research on Social Media Applications for the Tourism and Hospitality Sector (pp. 231– 251). IGI Global.
• Bakır, M., Akan, Ş., & Durmaz, E. (2019). Exploring service quality of low-cost airlines in Europe: An integrated MCDM approach. Economics and Business Review, 5(2), 109–130.
• Bakır, M., Akan, Ş., Özdemir, E., Nguyen, P. H., Tsai, J. F., & 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), 2151.
• Ban, H. J., & Kim, H. S. (2019). Understanding Customer Experience and Satisfaction through Airline Passengers’ Online Review. Sustainability, 11(15), 4066.
• Baumeister, S., Nyrhinen, J., Kemppainen, T., & Wilska, T. A. (2022). Does airlines’ eco-friendliness matter? Customer satisfaction towards an environmentally responsible airline. Transport Policy, 128, 89–97.
• Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.
• Bin Taliah, A. R., & Zervopoulos, P. D. (2023). Using a Bayesian meta-frontier approach to evaluate airline performance: The nexus between airline efficiency and customer satisfaction. Heliyon, 9(10), e20391.
• Biswakarma, D. G., & Gnawali, A. (2021). Service Quality of domestic airlines in the face of COVID-19 in Nepal. International Journal of Scientific Research and Management (IJSRM), 9(02), 2061–2171.
• Brochado, A., Rita, P., Oliveira, C., & Oliveira, F. (2019). Airline passengers’ perceptions of service quality: themes in online reviews. International Journal of Contemporary Hospitality Management, 31(2), 855–873.
• Bronstein, J., & Aharony, N. (2009). Views and Dreams: A Delphi Investigation into Library 2.0 Applications. Journal of Web Librarianship, 3(2), 89–109.
• Byrne, B. M. (2016). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming (3rd ed.). Routledge.
• Byun, H. J., & Lee, B. C. (2016). Classifying service quality attributes of low-cost carriers and full-service carriers based on an analytical kano model. Global Business and Finance Review, 21(2), 34–46.
• Çallı, L., & Çallı, F. (2023). Understanding Airline Passengers during Covid-19 Outbreak to Improve Service Quality: Topic Modeling Approach to Complaints with Latent Dirichlet Allocation Algorithm. Transportation Research Record, 2677(4), 656–673.
• Chang, Y. H., & Yeh, C. H. (2002). A survey analysis of service quality for domestic airlines. European Journal of Operational Research, 139(1), 166–177.
• Chatterjee, S., & Mandal, P. (2020). Traveler preferences from online reviews: Role of travel goals, class and culture. Tourism Management, 80, 104108.
• Chen, F. Y., & Chang, Y. H. (2005). Examining airline service quality from a process perspective. Journal of Air Transport Management, 11(2), 79–87.
• Choi, J. H. (2021). Changes in airport operating procedures and implications for airport strategies post- COVID-19. Journal of Air Transport Management, 94, 102065.
• Chonsalasin, D., Jomnonkwao, S., Chanpariyavatevong, K., Laphrom, W., & Ratanavaraha, V. (2022). Modeling of airline passenger loyalty: A comparison of leisure and business travelers. Research in Transportation Business & Management, 43, 100735.
• Chou, C. C., Liu, L. J., Huang, S. F., Yih, J. M., & Han, T. C. (2011). An evaluation of airline service quality using the fuzzy weighted SERVQUAL method. Applied Soft Computing, 11(2), 2117–2128.
• Chow, C. K. W. (2014). Customer satisfaction and service quality in the Chinese airline industry. Journal of Air Transport Management, 35, 102–107.
• Cunningham, L. F., Young, C. E., & Lee, M. (2004). Perceptions of Airline Service Quality: Pre and Post 9/11. Public Works Management & Policy, 9(1), 10–25.
• Dike, S. E., Davis, Z., Abrahams, A., Anjomshoae, A., & Ractham, P. (2023). Evaluation of passengers’ expectations and satisfaction in the airline industry: an empirical performance analysis of online reviews. Benchmarking: An International Journal.
• Fan, J., Zhong, D., Zhang, Y., Yu, S., Chu, J., Yu, M., Zhao, H., & Huang, Y. (2022). A hybrid approach based on rough-AHP for evaluation in-flight service quality. Multimedia Tools and Applications, 81(21), 30797–30819.
• Fan, Y., Chen, J., Shirkey, G., John, R., Wu, S. R., Park, H., & Shao, C. (2016). Applications of structural equation modeling (SEM) in ecological studies: an updated review. Ecological Processes, 5(1), 1–12.
• Farooq, M. S., Salam, M., Fayolle, A., Jaafar, N., & Ayupp, K. (2018). Impact of service quality on customer satisfaction in Malaysia airlines: A PLS-SEM approach. Journal of Air Transport Management, 67, 169–180.
• Finney, S. J., & DiStefano, C. (2013). Nonnormal and Categorical Data in Structural Equation Modeling. In G. R. Hancock & R. O. Mueller (Eds.), Structural Equation Modeling: A Second Course (2nd ed., pp. 439–492). Information Age Publishing.
• Flecha-Ortíz, J., Santos-Corrada, M., Dones-González, V., López-González, E., & Vega, A. (2021). Millennials & Snapchat: Self-expression through its use and its influence on purchase motivation. Journal of Business Research, 125, 798–805.
• Fu, Y.-K. (2023). Airline brand image, passenger perceived value and loyalty towards full-service and low- cost carriers. Tourism Review, 78(6), 1433–1451.
• Gao, K., Yang, Y., & Qu, X. (2021). Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction. Transportation Research Part D: Transport and Environment, 97, 102957.
• Garner, B., & Kim, D. (2022). Analyzing user-generated content to improve customer satisfaction at local wine tourism destinations: an analysis of Yelp and TripAdvisor reviews. Consumer Behavior in Tourism and Hospitality, 17(4), 413–435.
• Gazi, Md. A. I., Mamun, A. Al, Masud, A. Al, Senathirajah, A. R. bin S., & Rahman, T. (2024). The Relationship between CRM, Knowledge Management, Organization Commitment, Customer Profitability and Customer Loyalty in Telecommunication Industry: The Mediating Role of Customer Satisfaction and the Moderating Role of Brand Image. Journal of Open Innovation: Technology, Market, and Complexity, 100227.
• Geraldine, O., & David, C. (2013). Effects of airline service quality on airline image and passengers’ loyalty: Findings from Arik Air Nigeria passengers. Journal of Hospitality Management and Tourism, 4(2), 19–28.
• Goetz, A. R., & Vowles, T. M. (2009). The good, the bad, and the ugly: 30 years of US airline deregulation. Journal of Transport Geography, 17(4), 251–263.
• Gupta, H. (2018). Evaluating service quality of airline industry using hybrid best worst method and VIKOR. Journal of Air Transport Management, 68, 35–47.
• Gürçam, S. (2022). Global commercial aviation policies in the context of the climate crisis and an analysis of these approaches from the perspective of Türkiye. Environmental Research and Technology, 5(3), 227–240.
• Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). Sage.
• Halliday, S. V. (2016). User-generated content about brands: Understanding its creators and consumers. Journal of Business Research, 69(1), 137–144.
• Handoyo, S., Suharman, H., Ghani, E. K., & Soedarsono, S. (2023). A business strategy, operational efficiency, ownership structure, and manufacturing performance: The moderating role of market uncertainty and competition intensity and its implication on open innovation. Journal of Open Innovation, 9(2), 100039.
• Hassan, T. H., & Salem, A. E. (2022). Impact of service quality of low-cost carriers on airline image and consumers’ satisfaction and loyalty during the covid-19 outbreak. International Journal of Environmental Research and Public Health, 19(1), 83.
• Hong, A. C. Y., Khaw, K. W., Chew, X., & Yeong, W. C. (2023). Prediction of US airline passenger satisfaction using machine learning algorithms. Data Analytics and Applied Mathematics (DAAM), 4(1), 7–22.
• Hu, H. H., Kandampully, J., & Juwaheer, D. D. (2009). Relationships and impacts of service quality, perceived value, customer satisfaction, and image: an empirical study. The Service Industries Journal, 29(2), 111–125.
• Huang, Y. C. (2023). Low-Cost Airlines Not So Low-Cost – Exploring the Relationships among Travel Motivation, Service Quality and Satisfaction: The Moderating Roles of Perceived Value. Research in Transportation Business & Management, 49, 101008.
• IATA. (2022). Convenience is Top Priority for Passengers Post Pandemic. 2022 Press Releases. https://www.iata.org/en/pressroom/2022-releases/2022-11-01-01/
• Imroz, S. M., Curtis, T., & Ambrose, S. C. (2023). Perception of Crisis Management, Service Quality, and Loyalty Programs on Airline Travel Intention: What Roles Do Fear of COVID-19 and Risk Attitude Play? Sustainability, 15(18), 13753.
• Ismail, A. Bin, & Jiang, H. (2019). Comparing Service Quality for Long-Haul Low-Cost Carriers – Case for Asia and Australia Routes. Journal of Quality Assurance in Hospitality & Tourism, 20(6), 647–680.
• Jeong, E., Lee, B., Li, Q., & Kim, J. (2023). The Effect of Perceived Customer Value on Customer Satisfaction with Airline Services Using the BERTopic Model. Knowledge Management Research, 24(3), 95–125.
• Jiang, H., & Zhang, Y. (2016). An investigation of service quality, customer satisfaction and loyalty in China’s airline market. Journal of Air Transport Management, 57, 80–88.
• Josephy, H., Loeys, T., & Rosseel, Y. (2016). A Review of R-packages for Random-Intercept Probit Regression in Small Clusters. Frontiers in Applied Mathematics and Statistics, 2.
• Kassir, A. M. (2024). Role of alliance brand awareness on customer’s behavioural response and satisfaction: case of “sky team” global airline alliance. EuroMed J. of Management, 6(1), 72–99.
• Kim, A. J., & Johnson, K. K. P. (2016). Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook. Computers in Human Behavior, 58, 98–108.
• Kim, D., Lim, C., & Ha, H. K. (2024). Comparative analysis of changes in passenger’s perception for airline companies’ service quality before and during COVID-19 using topic modeling. Journal of Air Transport Management, 115, 102542.
• Kim, S. B., & Park, J. W. (2017). A study on the importance of airline selection attributes by airline type: An emphasis on the difference of opinion in between Korean and overseas aviation experts. Journal of Air Transport Management, 60, 76–83.
• Kline, R. B. (2023). Principles and Practice of Structural Equation Modeling (5th ed.). Guilford Press.
• Koçak, B. B., & Atalık, Ö. (2019). Perceptual maps of Turkish airline services for different periods using supervised machine learning approach and multidimensional scaling. International Journal of Sustainable Aviation, 5(3), 205.
• Koçak, B. B. (2020). Exploring and identification of passengers’ web search goals using “ticket” related queries in the airline market: a google trends study. Pazarlama ve Pazarlama Araştırmaları Dergisi, 3, 443-460.
• Koçak, C. B., Atalık, Ö., & Koçak, B. B. (2024). The effect of figurative language on consumer engagement: case of turkish airline instagram pages. Pazarlama Ve Pazarlama Araştırmaları Dergisi, 17(1), 1-38.
• Koğar, H., & Yilmaz Koğar, E. (2015). Comparison of Different Estimation Methods for Categorical and Ordinal Data in Confirmatory Factor Analysis. Journal of Measurement and Evaluation in Education and Psychology, 6(2), 351–364.
• Korfiatis, N., Stamolampros, P., Kourouthanassis, P., & Sagiadinos, V. (2019). Measuring service quality from unstructured data: A topic modeling application on airline passengers’ online reviews. Expert Systems with Applications, 116, 472–486.
• Kwon, H. J., Ban, H. J., Jun, J. K., & Kim, H. S. (2021). Topic Modeling and Sentiment Analysis of Online Review for Airlines. Information, 12(2), 78.
• Lai, K., & Green, S. B. (2016). The Problem with Having Two Watches: Assessment of Fit When RMSEA and CFI Disagree. Multivariate Behavioral Research, 51(2–3), 220–239.
• Lamb, T. L., Winter, S. R., Rice, S., Ruskin, K. J., & Vaughn, A. (2020). Factors that predict passengers’ willingness to fly during and after the COVID-19 pandemic. Journal of Air Transport Management, 89, 101897.
• Law, C. C. H., Zhang, Y., & Gow, J. (2022). Airline service quality, customer satisfaction, and repurchase Intention: Laotian air passengers’ perspective. Case Studies on Transport Policy, 10(2), 741–750.
• Leon, S., & Dixon, S. (2023). Airline satisfaction and loyalty: Assessing the influence of personality, trust and service quality. Journal of Air Transport Management, 113, 102487.
• Lim, J., & Lee, H. C. (2020). Comparisons of service quality perceptions between full service carriers and low cost carriers in airline travel. Current Issues in Tourism, 23(10), 1261–1276.
• Lin, Y. H., Wu, H., He, H., & Tsui, K. W. H. (2023). Changes in perceptions of airport services’ attributes: An assessment of the impacts of COVID-19. Transport Policy, 141, 116–128.
• Lin, Y. H., & Zhang, C. (2021). Investigating air travellers’ travel motivation during a pandemic crisis. Journal of Air Transport Management, 97, 102138.
• Liou, J. J. H., Hsu, C. C., Yeh, W. C., & Lin, R. H. (2011). Using a modified grey relation method for improving airline service quality. Tourism Management, 32(6), 1381–1388.
• Lippitt, P., Itani, N., O’Connell, J. F., Warnock-Smith, D., & Efthymiou, M. (2023). Investigating Airline Service Quality from a Business Traveller Perspective through the Integration of the Kano Model and Importance– Satisfaction Analysis. Sustainability, 15(8), 6578.
• Lucini, F. R., Tonetto, L. M., Fogliatto, F. S., & 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.
• Ma, G., Ding, Y., & Ma, J. (2022). The Impact of Airport Physical Environment on Perceived Safety and Domestic Travel Intention of Chinese Passengers during the COVID-19 Pandemic: The Mediating Role of Passenger Satisfaction. Sustainability, 14(9), 5628.
• Marcoulides, K. M., Foldnes, N., & Grønneberg, S. (2020). Assessing Model Fit in Structural Equation Modeling Using Appropriate Test Statistics. Structural Equation Modeling: A Multidisciplinary Journal, 27(3), 369–379.
• Mason, K. J. (2001). Marketing low-cost airline services to business travellers. Journal of Air Transport Management, 7(2), 103–109.
• Mendes-Filho, L., Mills, A. M., Tan, F. B., & Milne, S. (2018). Empowering the traveler: an examination of the impact of user-generated content on travel planning. Journal of Travel & Tourism Marketing, 35(4), 425–436.
• Mikulić, J., Šerić, M., & Matas Milković, L. (2017). Airline loyalty determinants among business travelers: empirical evidence from Croatia. Transportation Letters, 9(3), 177–183.
• Mîndrilă, D. (2010). Maximum Likelihood (ML) and Diagonally Weighted Least Squares (DWLS) Estimation Procedures: A Comparison of Estimation Bias with Ordinal and Multivariate Non-Normal Data. International Journal of Digital Society, 1(1), 60–66.
• Misopoulos, F., Mitic, M., Kapoulas, A., & Karapiperis, C. (2014). Uncovering customer service experiences with Twitter: The case of airline industry. Management Decision, 52(4), 705–723.
• Muthén, L. K., & Muthén, B. O. (2002). How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power. Structural Equation Modeling: A Multidisciplinary Journal, 9(4), 599–620.
• Naab, T. K., & Sehl, A. (2017). Studies of user-generated content: A systematic review. Journalism, 18(10), 1256– 1273.
• Namukasa, J. (2013). The influence of airline service quality on passenger satisfaction and loyalty the case of Uganda airline industry. TQM Journal, 25(5), 520–532.
• O’Hern, M. S., & Kahle, L. R. (2013). The Empowered Customer: User-Generated Content and the Future of Marketing. Global Economics and Management Review, 18(1), 22–30.
• Opengart, R., M. Ralston, P., & LeMay, S. (2018). Labor markets: preventing rivalry and myopia through HRM. Journal of Organizational Effectiveness, 5(4), 346–360.
• Özden, A. T., Çelik, E., & Gül, M. (2023). Evaluation of Service Quality in the Airline Industry: The Case of Turkey and Azerbaijan. Pazarlama ve Pazarlama Araştırmaları Dergisi, 16(2), 551–584.
• Pamplona, D. A., & Alves, C. J. P. (2020). An overview of air delay: A case study of the Brazilian scenario. Transportation Research Interdisciplinary Perspectives, 7, 100189.
• Pappachan, J. (2023). Influence of service quality, loyalty programme and perceived value on word-of- mouth behavior of domestic and international airline passengers in India. Vilakshan - XIMB Journal of Management, 20(2), 247–257.
• Park, E., Jang, Y., Kim, J., Jeong, N. J., Bae, K., & del Pobil, A. P. (2019). Determinants of customer satisfaction with airline services: An analysis of customer feedback big data. Journal of Retailing and Consumer Services, 51, 186–190.
• Perçin, S. (2018). Evaluating airline service quality using a combined fuzzy decision-making approach. Journal of Air Transport Management, 68, 48–60.
• Pereira, F., Costa, J. M., Ramos, R., & Raimundo, A. (2023). The impact of the COVID-19 pandemic on airlines’ passenger satisfaction. Journal of Air Transport Management, 112, 102441.
• Pholsook, T., Wipulanusat, W., & Ratanavaraha, V. (2024). A Hybrid MRA-BN-NN Approach for Analyzing Airport Service Based on User-Generated Contents. Sustainability, 16(3), 1164.
• Punel, A., Al Hajj Hassan, L., & Ermagun, A. (2019). Variations in airline passenger expectation of service quality across the globe. Tourism Management, 75, 491–508.
• Rajaguru, R. (2016). Role of value for money and service quality on behavioural intention: A study of full service and low cost airlines. Journal of Air Transport Management, 53, 114–122.
• Rauchfleisch, A., Artho, X., Metag, J., Post, S., & Schäfer, M. S. (2017). How journalists verify user-generated content during terrorist crises. Analyzing Twitter communication during the Brussels attacks. Social Media + Society, 3(3), 205630511771788.
• Ravishankar, B., & Christopher, P. B. (2023). Examining the Impact of Service Quality on Repurchase Intent: A Study of Foreign International Airlines. Journal of Law and Sustainable Development, 11(11), e826.
• Roma, P., & Aloini, D. (2019). How does brand-related user-generated content differ across social media? Evidence reloaded. Journal of Business Research, 96, 322–339.
• Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1–36.
• Samanci, S., Didem Atalay, K., & Bahar Isin, F. (2021). Focusing on the big picture while observing the concerns of both managers and passengers in the post-covid era. Journal of Air Transport Management, 90, 101970.
• Samir, H. A., Abd-Elmegid, L., & Marie, M. (2023). Sentiment analysis model for Airline customers’ feedback using deep learning techniques. International Journal of Engineering Business Management, 15.
• Samosir, J., Purba, O., Ricardianto, P., Triani, D., Adi, E. N., Wibisono, E., Rusmiyati, C., Udiati, T., Listyawati, A., & Endri, E. (2024). The role of service quality, facilities, and prices on customer satisfaction in Indonesia aviation in the COVID-19 pandemic. Uncertain Supply Chain Management, 12(1), 91–100.
• Sari, K., & Sener, A. A. (2022). Service quality and intention to recommend in low-cost and full-service airlines in Turkey. Decision, 49(3), 297–309.
• Šebjan, U., Tominc, P., & Širec, K. (2017). Multiple Conceptual Modelling of Perceived Quality of In-flight Airline Services. Promet - Traffic&Transportation, 29(3), 311–319.
• Shadiyar, A., Ban, H. J., & Kim, H. S. (2020). Extracting Key Drivers of Air Passenger’s Experience and Satisfaction through Online Review Analysis. Sustainability, 12(21), 9188.
• Shi, D., Lee, T., & Maydeu-Olivares, A. (2019). Understanding the Model Size Effect on SEM Fit Indices. Educational and Psychological Measurement, 79(2), 310–334.
• Shi, D., Lee, T., & Terry, R. A. (2018). Revisiting the Model Size Effect in Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 25(1), 21–40.
• Siering, M., Deokar, A. V., & Janze, C. (2018). Disentangling consumer recommendations: Explaining and predicting airline recommendations based on online reviews. Decision Support Systems, 107, 52–63.
• Skytrax. (2022). About Skytrax Ratings. https://skytraxratings.com/about
• Smith, M. J., Buckton, C., Patterson, C., & Hilton, S. (2023). User-generated content and influencer marketing involving e-cigarettes on social media: a scoping review and content analysis of YouTube and Instagram. BMC Public Health, 23(1), 1–10.
• Song, C., Ma, X., Ardizzone, C., & Zhuang, J. (2024). The adverse impact of flight delays on passenger satisfaction: An innovative prediction model utilizing wide & deep learning. Journal of Air Transport Management, 114, 102511.
• Srinivas, S., & Ramachandiran, S. (2023). Passenger intelligence as a competitive opportunity: unsupervised text analytics for discovering airline-specific insights from online reviews. Annals of Operations Research, 1– 31.
• Suki, N. M. (2014). Passenger satisfaction with airline service quality in Malaysia: A structural equation modeling approach. Research in Transportation Business & Management, 10, 26–32.
• Sultan, F., & Simpson, M. (2000). International service variants: airline passenger expectations and perceptions of service quality. Journal of Services Marketing, 14(3), 188–216.
• Sulu, D., Arasli, H., & Saydam, M. B. (2021). Air-Travelers’ Perceptions of Service Quality during the COVID-19 Pandemic: Evidence from Tripadvisor Sites. Sustainability, 14(1), 435.
• Suprapto, D. S., & Oetama, R. (2023). Analysis of Airline Passenger Satisfaction Using Decision Tree and Naïve Bayes Algorithms. Jurnal Informatika Ekonomi Bisnis, 5(4), 1493–1500.
• Tahanisaz, S., & Shokuhyar, S. (2020). Evaluation of passenger satisfaction with service quality: A consecutive method applied to the airline industry. Journal of Air Transport Management, 83, 101764.
• Tanaka, J. S. (1987). “How Big Is Big Enough?”: Sample Size and Goodness of Fit in Structural Equation Models with Latent Variables. Child Development, 58(1), 134–146.
• Tansitpong, P. (2020). Determinants of Recommendation in the Airline Industry: An Application of Online Review Analysis. In J. M. Moreno-Jiménez, I. Linden, F. Dargam, & U. Jayawickrama (Eds.), Decision Support Systems X: Cognitive Decision Support Systems and Technologies (pp. 125–135). Springer.
• The jamovi project. (2023). jamovi (Version 2.3) [Computer Software]. Retrieved from https://www.jamovi.org
• Tiernan, S., Rhoades, D. L., & Waguespack, B. (2008). Airline service quality Exploratory analysis of consumer perceptions and operational performance in the USA and EU. Managing Service Quality: An International Journal, 18(3), 212–224.
• Tsaur, S. H., Chang, T. Y., & Yen, C. H. (2002). The evaluation of airline service quality by fuzzy MCDM. Tourism Management, 23(2), 107–115.
• Vlachos, I., & Lin, Z. (2014). Drivers of airline loyalty: Evidence from the business travelers in China. Transportation Research Part E: Logistics and Transportation Review, 71, 1–17.
• Vollrath, M. D., & Villegas, S. G. (2022). Avoiding digital marketing analytics myopia: revisiting the customer decision journey as a strategic marketing framework. Journal of Marketing Analytics, 10(2), 106–113.
• Wang, J., & Wang, X. (2020). Structural Equation Modeling (2nd ed.). Wiley.
• Wang, R., Shu-Li, Hsu, Lin, Y. H., & Tseng, M.-L. (2011). Evaluation of customer perceptions on airline service quality in uncertainty. Procedia - Social and Behavioral Sciences, 25, 419–437.
• Wesonga, R., Nabugoomu, F., & Masimbi, B. (2014). Airline Delay Time Series Differentials. International Journal of Aviation Systems, Operations and Training, 1(2), 64–76.
• Whittaker, T. A., & Schumacker, R. E. (2022). A Beginner’s Guide to Structural Equation Modeling (5th ed.). Routledge.
• Yalcin Kavus, B., Gulum Tas, P., Ayyildiz, E., & Taskin, A. (2022). A three-level framework to evaluate airline service quality based on interval valued neutrosophic AHP considering the new dimensions. Journal of Air Transport Management, 99, 102179.
• Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52(3), 2–22.
• Zhang, L., Yang, H., Wang, K., Bian, L., & Zhang, X. (2021). The impact of COVID-19 on airline passenger travel behavior: An exploratory analysis on the Chinese aviation market. Journal of Air Transport Management, 95, 102084.
• Zhang, L., Yang, H., Wang, K., Zhan, Y., & Bian, L. (2020). Measuring imported case risk of COVID-19 from inbound international flights - A case study on China. Journal of Air Transport Management, 89, 101918.