Araştırma Makalesi
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Decoding User Reviews for Low-Cost Airlines Marketing: A Global Analysis of Passenger Preferences

Yıl 2025, Cilt: 9 Sayı: 1, 41 - 52, 26.02.2025

Fatih Pınarbaşı , Fatma Zeybek

https://doi.org/10.30518/jav.1547777

Öz

The airline industry is a key component in the transportation and tourism sectors thanks to its economic potential and global scope, and the complex structure of customer preferences, competitive environment, and changing dynamics require examination of the marketplace. In this context, it has been determined that many studies have focused on user studies in the airline market, while only a few studies have examined the Low-cost airline sub-context in the airline market. This study aims to investigate the factors affecting consumer recommendation and rating scores through user reviews in the context of Low-cost airlines. In the study, regression analyzes and difference tests were used on 5672 user reviews on airlinequality.com about 20 airline brands on Skytrax’s World’s Best Low-cost Airlines 2023 list. In the regression analysis, it was seen that value for money was the most important determining factor in recommendation status and rating scoring, followed by ground service, cabin crew service, seat comfort and food and beverage variables. Difference tests reveal that solo leisure travelers tend to rate and recommend higher. It is also concluded that first-class passengers using LCC airlines have higher tendency for rating scores higher and recommending.

Anahtar Kelimeler

Aviation Low-cost airline Airline industry Airline Marketing Airline service

Kaynakça

  • Abirami, A. M., & Askarunisa, A. (2017). Sentiment analysis model to emphasize the impact of online reviews in healthcare industry. Online Information Review, 41(4), 471-486.
  • Alanazi, M. S. M., Li, J., & Jenkins, K. W. (2024). Evaluating airport service quality based on the statistical and predictive analysis of Skytrax passenger reviews. Applied Sciences, 14(20), 1-17.
  • Alexander, M. W. (1976). The estimation of attitudes in two occupational groups: A test of four expectancy- evaluation attitude models. The Journal of Psychology, 93(1), 31-41.
  • Allsop, D. T., Bassett, B. R., & Hoskins, J. A. (2007). Word-of-mouth research: Principles and applications. Journal of Advertising Research, 47(4), 398-411.
  • Ateşoğlu, İ., & Bayraktar, S. (2011). The effect of word-of-mouth marketing on tourists' destination choice. International Journal of Management Economics and Business, 7(14), 95-108.
  • Aydın, A. (2024). The importance of brand equity and branding in terms of product/service preference and internationalization: An analysis of civil air transportation with marketing strategies. Journal of Aviation, 8(2), 182-191.
  • Ban, H. J., & Kim, H. S. (2019). Understanding customer experience and satisfaction through airline passengers’ online review. Sustainability, 11(15), 4066.
  • Bogicevic, V., Yang, W., Bilgihan, A., & Bujisic, M. (2013). Airport service quality drivers of passenger satisfaction. Tourism Review, 68(4), 3-18.
  • Brochado, A., Duarte, M., & Mengyuan, Z. (2023). Passengers’ perceptions of Chinese airlines’ service quality: A mixed methods analysis of user-generated content. Journal of China Tourism Research, 19(3), 677-699.
  • Chang, L. Y., & Hung, S. C. (2013). Adoption and loyalty toward low-cost carriers: The case of Taipei-Singapore passengers. Transportation research Part E: Logistics and transportation review, 50, 29-36.
  • Chen, H. T., & Chao, C. C. (2015). Airline choice by passengers from Taiwan and China: A case study of outgoing passengers from Kaohsiung International Airport. Journal of Air Transport Management, 49, 53-63.
  • Cheung, C. M., & Lee, M. K. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision support systems, 53(1), 218-225.
  • Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470.
  • Cui, G., Lui, H. K., & Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), 39-58.
  • Dalla Valle, L., & Kenett, R. (2018). Social media big data integration: A new approach based on calibration. Expert Systems with Applications, 111, 76-90.
  • De Maeyer, P. (2012). Impact of online consumer reviews on sales and price strategies: A review and directions for future research. Journal of Product & Brand Management, 21(2), 132-139.
  • Duan, W., Gu, B., & Whinston, A. B. (2008). Do online reviews matter? -An empirical investigation of panel data. Decision support systems, 45(4), 1007-1016.
  • Duran, C., Uray, N., & Alkilani, S. (2024). The impact of the characteristics of self-service technologies on customer experience quality: Insights for airline companies. Journal of Tourism and Services, 15(29), 46-71.
  • Ezzatirad, H. (2014). The effect of word-of-mouth marketing on customer purchase decision process: An application among the students of Faculty of Economics and Administrative Sciences of State Universities in Ankara, Gazi University Institute of Social Sciences, Ankara.
  • Farzadnia, S., & Vanani, I. R. (2022). Identification of opinion trends using sentiment analysis of airlines passengers’ reviews. Journal of Air Transport Management, 103, 102232.
  • Filieri, R., Lin, Z., Pino, G., Alguezaui, S., & Inversini, A. (2021). The role of visual cues in eWOM on consumers’ behavioral intention and decisions. Journal of Business Research, 135, 663-675.
  • Floyd, K., Freling, R., Alhoqail, S., Cho, H. Y., & Freling, T. (2014). How online product reviews affect retail sales: A meta-analysis. Journal of retailing, 90(2), 217-232.
  • Haddara, M., Hsieh, J., Fagerstrøm, A., Eriksson, N., & Sigurðsson, V. (2020). Exploring customer online reviews for new product development: The case of identifying reinforcers in the cosmetic industry. Managerial and Decision Economics, 41(2), 250-273.
  • Harris, A., & Prideaux, B. (2017). The potential for eWOM to affect consumer behaviour in tourism In: The Routledge handbook of consumer behaviour in hospitality and tourism (pp. 366-376). Routledge.
  • Harwood, J. (2020). Social identity theory. The international encyclopedia of media psychology, 1-7.
  • Heinonen, K. (2011). Consumer activity in social media: Managerial approaches to consumers’ social media behavior. Journal of consumer behaviour, 10(6), 356-364.
  • Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer- opinion platforms: What motivates consumers to articulate themselves on the internet?. Journal of interactive marketing, 18(1), 38-52.
  • Hosmer Jr, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression. John Wiley & Sons.
  • IATA. (2022, 10 July). One size does not fit all: A study of how airline business models have evolved to meet demand in Europe. https://www.iata.org/en/iata-repository/publications/economic-reports/one-size-does- not-fit-all---airline-business-models/
  • Kalaycı, Ş. (2010). SPSS Applied Multivariate Statistical Techniques. Turkey: Ankara / Asil Publication Distribution.
  • Kanje, P., Charles, G., Tumsifu, E., Mossberg, L., & Andersson, T. (2020). Customer engagement and eWOM in tourism. Journal of Hospitality and Tourism Insights, 3(3), 273-289.
  • 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.
  • Lee, K., & Yu, C. (2018). Assessment of airport service quality: A complementary approach to measure perceived service quality based on Google reviews. Journal of Air Transport Management, 71, 28-44.
  • 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.
  • Li, L., Mao, Y., Wang, Y., & Ma, Z. (2022). How has airport service quality changed in the context of COVID-19: A data-driven crowdsourcing approach based on sentiment analysis. Journal of Air Transport Management, 105, 102298.
  • Liu, H., Wu, S., Zhong, C., & Liu, Y. (2023). The effects of customer online reviews on sales performance: The role of mobile phone’s quality characteristics. Electronic Commerce Research and Applications, 57, 101229.
  • Leong, L. Y., Hew, T. S., Lee, V. H., & Ooi, K. B. (2015). An SEM-artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among Low-costand full-service airline. Expert Systems with Applications, 42(19), 6620-6634.
  • 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.
  • Maldonado, A. C. B. (2024). Customer experience in luxury airlines: Global and segmented analysis by type of traveler and recommendation, Iscte - Instituto Universitário de Lisboa, Repositório Iscte, Dissertação de mestrado.
  • Mutlu, S., & Sertoğlu, A. E. (2018). Comparison of service quality expectations of customers of low-cost and full- service airlines. Journal of Business Research, 10(1), 528-550.
  • Oh, A. H., & Park, H. Y. (2020). Marketing strategies for improving customer attitude using airline advertising model: Focusing on corporate image and brand loyalty. Journal of Distribution Science, 18(4), 13-26.
  • Oktay, E., & Orçanlı, K. (2014). Determining the factors affecting the use of internet banking at Atatürk University. Uşak University Journal of Social Sciences, 7(2), 57-91.
  • O’reilly, T. (2009, 12 June). What is web 2.0. O’Reilly Media. http://www. oreillynet. com/pub/a/oreilly/tim/news /2005/09/30/what-is-web-20. htm.
  • Park, J. W., Robertson, R., & Wu, C. L. (2004). The effect of airline service quality on passengers’ behavioural intentions: A Korean case study. Journal of Air Transport Management, 10(6), 435-439.
  • Punel, A., Hassan, L. A. H., & Ermagun, A. (2019). Variations in airline passenger expectation of service quality across the globe. Tourism Management, 75, 491-508.
  • Rossum, G. (1995). Python reference manual. ACM Digital Library.
  • Sezgen, E., Mason, K. J., & Mayer, R. (2019). Voice of airline passenger: A text mining approach to understand customer satisfaction. Journal of Air Transport Management, 77, 65-74.
  • Skytrax. (2023, 6 October). World’s Best Low-cost Airlines 2023. https://www.worldairlineawards.com/worlds- best-low-cost-airlines-2023/
  • Skytrax. (2024, 4 March). World Airline and Airport Ratings. https://skytraxratings.com/
  • Streiner, D. L. (1994). Regression in the service of the superego: The do’s and don’ts of stepwise multiple regression. The Canadian Journal of Psychiatry, 39(4), 191-196.
  • Song, C., Guo, J., & Zhuang, J. (2020). Analyzing passengers’ emotions following flight delays-a 2011–2019 case study on SKYTRAX comments. Journal of Air Transport Management, 89, 101903.
  • Sotiriadis, M. D., & Van Zyl, C. (2013). Electronic word-of-mouth and online reviews in tourism services: The use of twitter by tourists. Electronic Commerce Research, 13, 103-124.
  • Tabachnick, B. G. & Fidell, L. S. (2007). Using Multivariate Statistics. Boston: Pearson Education Inc.
  • UNWTO. (2023, 8 April). Global And Regional Tourism Performance. https://www.unwto.org/tourism- data/global-and-regional-tourism-performance
  • Verma, J. P. (2012). Data analysis in management with SPSS software. Springer Science & Business Media.
  • Wang, R., & Chan-Olmsted, S. (2020). Content marketing strategy of branded YouTube channels. Journal of Media Business Studies, 17(3-4), 294-316.
  • Wang, S., Lin, Y., & Zhu, G. (2023a). Online reviews and high-involvement product sales: Evidence from offline sales in the Chinese automobile industry. Electronic Commerce Research and Applications, 57, 101231.
  • Wang, X., Zheng, J., Tang, L. R., & Luo, Y. (2023b). Recommend or not? The influence of emotions on passengers’ intention of airline recommendation during COVID-19. Tourism Management, 95, 104675.
  • We Are Social & Meltwater (2023, 16 February). Digital 2023 Global Overview Report. https://datareportal.com /reports/digital-2023-global-overview-report
  • Westbrook, R. A. (1987). Product/consumption-based affective responses and postpurchase processes. Journal of Marketing Research, 24(3), 258-270.
  • Yan, Z., Xing, M., Zhang, D., & Ma, B. (2015). EXPRS: An extended pagerank method for product feature extraction from online consumer reviews. Information & Management, 52(7), 850-858.
  • Zauner, A., Koller, M., & Hatak, I. (2015). Customer perceived value-Conceptualization and avenues for future research. Cogent psychology, 2(1), 1-17.
  • Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2), 133-148.

Yıl 2025, Cilt: 9 Sayı: 1, 41 - 52, 26.02.2025

Fatih Pınarbaşı , Fatma Zeybek

https://doi.org/10.30518/jav.1547777

Öz

Kaynakça

  • Abirami, A. M., & Askarunisa, A. (2017). Sentiment analysis model to emphasize the impact of online reviews in healthcare industry. Online Information Review, 41(4), 471-486.
  • Alanazi, M. S. M., Li, J., & Jenkins, K. W. (2024). Evaluating airport service quality based on the statistical and predictive analysis of Skytrax passenger reviews. Applied Sciences, 14(20), 1-17.
  • Alexander, M. W. (1976). The estimation of attitudes in two occupational groups: A test of four expectancy- evaluation attitude models. The Journal of Psychology, 93(1), 31-41.
  • Allsop, D. T., Bassett, B. R., & Hoskins, J. A. (2007). Word-of-mouth research: Principles and applications. Journal of Advertising Research, 47(4), 398-411.
  • Ateşoğlu, İ., & Bayraktar, S. (2011). The effect of word-of-mouth marketing on tourists' destination choice. International Journal of Management Economics and Business, 7(14), 95-108.
  • Aydın, A. (2024). The importance of brand equity and branding in terms of product/service preference and internationalization: An analysis of civil air transportation with marketing strategies. Journal of Aviation, 8(2), 182-191.
  • Ban, H. J., & Kim, H. S. (2019). Understanding customer experience and satisfaction through airline passengers’ online review. Sustainability, 11(15), 4066.
  • Bogicevic, V., Yang, W., Bilgihan, A., & Bujisic, M. (2013). Airport service quality drivers of passenger satisfaction. Tourism Review, 68(4), 3-18.
  • Brochado, A., Duarte, M., & Mengyuan, Z. (2023). Passengers’ perceptions of Chinese airlines’ service quality: A mixed methods analysis of user-generated content. Journal of China Tourism Research, 19(3), 677-699.
  • Chang, L. Y., & Hung, S. C. (2013). Adoption and loyalty toward low-cost carriers: The case of Taipei-Singapore passengers. Transportation research Part E: Logistics and transportation review, 50, 29-36.
  • Chen, H. T., & Chao, C. C. (2015). Airline choice by passengers from Taiwan and China: A case study of outgoing passengers from Kaohsiung International Airport. Journal of Air Transport Management, 49, 53-63.
  • Cheung, C. M., & Lee, M. K. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision support systems, 53(1), 218-225.
  • Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470.
  • Cui, G., Lui, H. K., & Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), 39-58.
  • Dalla Valle, L., & Kenett, R. (2018). Social media big data integration: A new approach based on calibration. Expert Systems with Applications, 111, 76-90.
  • De Maeyer, P. (2012). Impact of online consumer reviews on sales and price strategies: A review and directions for future research. Journal of Product & Brand Management, 21(2), 132-139.
  • Duan, W., Gu, B., & Whinston, A. B. (2008). Do online reviews matter? -An empirical investigation of panel data. Decision support systems, 45(4), 1007-1016.
  • Duran, C., Uray, N., & Alkilani, S. (2024). The impact of the characteristics of self-service technologies on customer experience quality: Insights for airline companies. Journal of Tourism and Services, 15(29), 46-71.
  • Ezzatirad, H. (2014). The effect of word-of-mouth marketing on customer purchase decision process: An application among the students of Faculty of Economics and Administrative Sciences of State Universities in Ankara, Gazi University Institute of Social Sciences, Ankara.
  • Farzadnia, S., & Vanani, I. R. (2022). Identification of opinion trends using sentiment analysis of airlines passengers’ reviews. Journal of Air Transport Management, 103, 102232.
  • Filieri, R., Lin, Z., Pino, G., Alguezaui, S., & Inversini, A. (2021). The role of visual cues in eWOM on consumers’ behavioral intention and decisions. Journal of Business Research, 135, 663-675.
  • Floyd, K., Freling, R., Alhoqail, S., Cho, H. Y., & Freling, T. (2014). How online product reviews affect retail sales: A meta-analysis. Journal of retailing, 90(2), 217-232.
  • Haddara, M., Hsieh, J., Fagerstrøm, A., Eriksson, N., & Sigurðsson, V. (2020). Exploring customer online reviews for new product development: The case of identifying reinforcers in the cosmetic industry. Managerial and Decision Economics, 41(2), 250-273.
  • Harris, A., & Prideaux, B. (2017). The potential for eWOM to affect consumer behaviour in tourism In: The Routledge handbook of consumer behaviour in hospitality and tourism (pp. 366-376). Routledge.
  • Harwood, J. (2020). Social identity theory. The international encyclopedia of media psychology, 1-7.
  • Heinonen, K. (2011). Consumer activity in social media: Managerial approaches to consumers’ social media behavior. Journal of consumer behaviour, 10(6), 356-364.
  • Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer- opinion platforms: What motivates consumers to articulate themselves on the internet?. Journal of interactive marketing, 18(1), 38-52.
  • Hosmer Jr, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression. John Wiley & Sons.
  • IATA. (2022, 10 July). One size does not fit all: A study of how airline business models have evolved to meet demand in Europe. https://www.iata.org/en/iata-repository/publications/economic-reports/one-size-does- not-fit-all---airline-business-models/
  • Kalaycı, Ş. (2010). SPSS Applied Multivariate Statistical Techniques. Turkey: Ankara / Asil Publication Distribution.
  • Kanje, P., Charles, G., Tumsifu, E., Mossberg, L., & Andersson, T. (2020). Customer engagement and eWOM in tourism. Journal of Hospitality and Tourism Insights, 3(3), 273-289.
  • 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.
  • Lee, K., & Yu, C. (2018). Assessment of airport service quality: A complementary approach to measure perceived service quality based on Google reviews. Journal of Air Transport Management, 71, 28-44.
  • 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.
  • Li, L., Mao, Y., Wang, Y., & Ma, Z. (2022). How has airport service quality changed in the context of COVID-19: A data-driven crowdsourcing approach based on sentiment analysis. Journal of Air Transport Management, 105, 102298.
  • Liu, H., Wu, S., Zhong, C., & Liu, Y. (2023). The effects of customer online reviews on sales performance: The role of mobile phone’s quality characteristics. Electronic Commerce Research and Applications, 57, 101229.
  • Leong, L. Y., Hew, T. S., Lee, V. H., & Ooi, K. B. (2015). An SEM-artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among Low-costand full-service airline. Expert Systems with Applications, 42(19), 6620-6634.
  • 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.
  • Maldonado, A. C. B. (2024). Customer experience in luxury airlines: Global and segmented analysis by type of traveler and recommendation, Iscte - Instituto Universitário de Lisboa, Repositório Iscte, Dissertação de mestrado.
  • Mutlu, S., & Sertoğlu, A. E. (2018). Comparison of service quality expectations of customers of low-cost and full- service airlines. Journal of Business Research, 10(1), 528-550.
  • Oh, A. H., & Park, H. Y. (2020). Marketing strategies for improving customer attitude using airline advertising model: Focusing on corporate image and brand loyalty. Journal of Distribution Science, 18(4), 13-26.
  • Oktay, E., & Orçanlı, K. (2014). Determining the factors affecting the use of internet banking at Atatürk University. Uşak University Journal of Social Sciences, 7(2), 57-91.
  • O’reilly, T. (2009, 12 June). What is web 2.0. O’Reilly Media. http://www. oreillynet. com/pub/a/oreilly/tim/news /2005/09/30/what-is-web-20. htm.
  • Park, J. W., Robertson, R., & Wu, C. L. (2004). The effect of airline service quality on passengers’ behavioural intentions: A Korean case study. Journal of Air Transport Management, 10(6), 435-439.
  • Punel, A., Hassan, L. A. H., & Ermagun, A. (2019). Variations in airline passenger expectation of service quality across the globe. Tourism Management, 75, 491-508.
  • Rossum, G. (1995). Python reference manual. ACM Digital Library.
  • Sezgen, E., Mason, K. J., & Mayer, R. (2019). Voice of airline passenger: A text mining approach to understand customer satisfaction. Journal of Air Transport Management, 77, 65-74.
  • Skytrax. (2023, 6 October). World’s Best Low-cost Airlines 2023. https://www.worldairlineawards.com/worlds- best-low-cost-airlines-2023/
  • Skytrax. (2024, 4 March). World Airline and Airport Ratings. https://skytraxratings.com/
  • Streiner, D. L. (1994). Regression in the service of the superego: The do’s and don’ts of stepwise multiple regression. The Canadian Journal of Psychiatry, 39(4), 191-196.
  • Song, C., Guo, J., & Zhuang, J. (2020). Analyzing passengers’ emotions following flight delays-a 2011–2019 case study on SKYTRAX comments. Journal of Air Transport Management, 89, 101903.
  • Sotiriadis, M. D., & Van Zyl, C. (2013). Electronic word-of-mouth and online reviews in tourism services: The use of twitter by tourists. Electronic Commerce Research, 13, 103-124.
  • Tabachnick, B. G. & Fidell, L. S. (2007). Using Multivariate Statistics. Boston: Pearson Education Inc.
  • UNWTO. (2023, 8 April). Global And Regional Tourism Performance. https://www.unwto.org/tourism- data/global-and-regional-tourism-performance
  • Verma, J. P. (2012). Data analysis in management with SPSS software. Springer Science & Business Media.
  • Wang, R., & Chan-Olmsted, S. (2020). Content marketing strategy of branded YouTube channels. Journal of Media Business Studies, 17(3-4), 294-316.
  • Wang, S., Lin, Y., & Zhu, G. (2023a). Online reviews and high-involvement product sales: Evidence from offline sales in the Chinese automobile industry. Electronic Commerce Research and Applications, 57, 101231.
  • Wang, X., Zheng, J., Tang, L. R., & Luo, Y. (2023b). Recommend or not? The influence of emotions on passengers’ intention of airline recommendation during COVID-19. Tourism Management, 95, 104675.
  • We Are Social & Meltwater (2023, 16 February). Digital 2023 Global Overview Report. https://datareportal.com /reports/digital-2023-global-overview-report
  • Westbrook, R. A. (1987). Product/consumption-based affective responses and postpurchase processes. Journal of Marketing Research, 24(3), 258-270.
  • Yan, Z., Xing, M., Zhang, D., & Ma, B. (2015). EXPRS: An extended pagerank method for product feature extraction from online consumer reviews. Information & Management, 52(7), 850-858.
  • Zauner, A., Koller, M., & Hatak, I. (2015). Customer perceived value-Conceptualization and avenues for future research. Cogent psychology, 2(1), 1-17.
  • Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2), 133-148.
Toplam 63 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme , Hava Taşımacılığı ve Nakliye Hizmetleri
Bölüm Araştırma Makaleleri
Yazarlar

Fatih Pınarbaşı 0000-0001-9005-0324

Fatma Zeybek 0000-0003-3525-0520

Erken Görünüm Tarihi 24 Şubat 2025
Yayımlanma Tarihi 26 Şubat 2025
Gönderilme Tarihi 10 Eylül 2024
Kabul Tarihi 9 Ocak 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 1

Kaynak Göster

APA Pınarbaşı, F., & Zeybek, F. (2025). Decoding User Reviews for Low-Cost Airlines Marketing: A Global Analysis of Passenger Preferences. Journal of Aviation, 9(1), 41-52. https://doi.org/10.30518/jav.1547777
 Kapak Resmi İndir

Journal of Aviation - JAV 

www.javsci.com - editor@javsci.com


9210This journal is licenced under a Creative Commons Attiribution-NonCommerical 4.0 İnternational Licence