Analysis of Satisfaction Level Based on eWOM in Airlines through SWARA and MABAC Methods

Öz

In this study, the main goal is to evaluate the satisfaction level of the major airlines in Europe. For this purpose, electronic consumer reviews on the TripAdvisor website are used as secondary data. In this study, SWARA and MABAC methods are used integrally, firstly, criteria weights are determined by the SWARA method, and then the airlines are evaluated by the MABAC method. As a result of the study, it is found that the most important attribute on satisfaction is ‘’value for money’’ and the least important attribute is ‘’food and beverage’’. Additionally, the X7 airline has the highest satisfaction level.

Anahtar Kelimeler

• Airline,Electronic Word of Mouth,SWARA,MABAC

SWARA ve MABAC Yöntemleri İle Havayolu İşletmelerinde eWOM’ a Dayalı Memnuniyet Düzeyinin Analizi

Öz

Bu çalışmada, Avrupa’ da faaliyet gösteren başlıca havayolu işletmelerine yönelik memnuniyet düzeyinin değerlendirilmesi amaçlanmıştır. Bu amaçla TripAdvisor web sitesinde yer alan elektronik tüketici deneyimleri ikincil veri olarak kullanılmıştır. SWARA ve MABAC yöntemlerinin bütünleşik olarak kullanıldığı bu çalışmada öncelikle kriter ağırlıkları SWARA yöntemi ile belirlenmiş, ardından havayolu işletmeleri MABAC yöntemiyle değerlendirilmiştir. Çalışma sonucunda memnuniyet üzerindeki en belirleyici kriterin ‘’paranın karşılığı’’ olduğu, en önemsiz kriterin ise ‘’yemek ve içecek’’ olduğu görülmüştür. X7 havayolu ise en yüksek memnuniyet düzeyine sahip havayolu olarak belirlenmiştir.

Anahtar Kelimeler

• Havayolu,Elektronik Ağızdan Ağıza İletişim,SWARA,MABAC

Kaynakça

1. AMARAL, F., TIAGO, T., & TIAGO, F. (2014). User-generated content: tourists' profiles on Tripadvisor. International Journal of Strategic Innovative Marketing, 1(3), 137-145.
2. AYEH, J. K., AU, N., & LAW, R. (2013). “Do we believe in TripAdvisor?” Examining credibility perceptions and online travelers’ attitude toward using user-generated content. Journal of Travel Research, 52(4), 437-452.
3. BAHARUN, R., WAHID, A., SAZREEN, H., & AWANG, Z. (2015). Mystery of Aircraft MH370: Electronic Word-of-Mouth Towards Malaysia Airline Reputation. Advanced Science Letters, 21(5), 1170-1172.
4. BENEKE, J., MILL, J., NAIDOO, K., & WICKHAM, B. (2015). The impact of willingness to engage in negative electronic word-of-mouth on brand attitude: a study of airline passengers in South Africa. Journal of Business and Retail Management Research, 9(2), 69-84.
5. BISWAS, T. K., & DAS, M. C. (2018). Selection of Commercially Available Electric Vehicle using Fuzzy AHP-MABAC. Journal of The Institution of Engineers (India): Series C, 1-7.
6. BOLLENBERG, S. A. (2017). A comparative analysis of the moves British Airways and Lufthansa use to counter negative eWOM on Twitter - Strategic moves contributing to service recovery (Yayımlanmamış Yüksek Lisans Tezi). Universiteit Gent.
7. CARL, W. J. (2006). What's all the buzz about? Everyday communication and the relational basis of word-of-mouth and buzz marketing practices. Management Communication Quarterly, 19(4), 601-634.
8. CHOU, C. C., LİU, L. J., HUANG, S. F., YİH, 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.

9. ÇETİNTÜRK, İ. (2017). Müşteri Değeri, Müşteri Tatmini ve Marka Sadakati: Üniversite Sosyal Tesisleri Üzerine Bir Araştırma. Seyahat ve Otel İşletmeciliği Dergisi, 14(2), 93-109.
10. DEBNATH, A., ROY, J., KAR, S., ZAVADSKAS, E. K., & ANTUCHEVICIENE, J. (2017). A hybrid mcdm approach for strategic project portfolio selection of agro by-products. Sustainability, 9(8), 1302-1335.
11. ERDOĞAN, E. Ç., DEMİREL, E. Ü., & YILDIZ, E. (2018). Turistik Tatminin Destinasyon İmajı ve Subjektif Bilgi Aracılığıyla Ağızdan Ağıza Pazarlama Üzerindeki Etkilerinin Yapısal Eşitlik Modeli ile İncelenmesi. Öneri Dergisi, 13(50), 211-228.
12. EREN, R., & ÇELİK, M. (2017). Çevrimiçi Gastronomi İmajı: Türkiye Restoranlarının Tripadvisor Yorumlarının İçerik Analizi. Turizm Akademik Dergisi, 4(2), 121-138.
13. GIGOVIĆ, L., PAMUČAR, D., BOŽANIĆ, D., & LJUBOJEVIĆ, S. (2017). Application of the GIS-DANP-MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable Energy (103), 501-521.
14. GILLEN, D. (2017). Aviation economics and forecasting. L. Budd, & S. Ison içinde, Air Transport Management: An international perspective (s. 23-40). New York: Routledge.
15. GOYETTE, I., RICARD, L., BERGERON, J., & MARTICOTTE, F. (2010). e‐WOM Scale: word‐of‐mouth measurement scale for e‐services context. Canadian Journal of Administrative Sciences, 27(1), 5-23.
16. GUPTA, S., & KIM, H. W. (2004). Virtual Community Concepts, Implications, and Future Research Directions. The Tenth Americas Conference on Information Systems, (s. 2679-2687). New York.
17. GUPTA, H. (2018). Evaluating service quality of airline industry using hybrid best worst method and VIKOR. Journal of Air Transport Management, 68, 35-47.
18. 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.
19. HUANG, C. Y., CHOU, C. J., & LIN, P. C. (2010). Involvement theory in constructing bloggers’ intention to purchase travel products. Tourism Management (31), 513-526.
20. JI, P., ZHANG, H. Y., & WANG, J. Q. (2018). Selecting an outsourcing provider based on the combined MABAC–ELECTRE method using single-valued neutrosophic linguistic sets. Computers & Industrial Engineering, 120, 429-441.
21. KAHRAMAN, C., GHORABAEE, M. K., ZAVADSKAS, E. K., ONAR, S. C., YAZDANİ, M., & OZTAYSİ, B. (2017). Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection. Journal of Environmental Engineering and Landscape Management, 25(1), 1-12.
22. KARABASEVIC, D., ZAVADSKAS, E. K., TURSKIS, Z., & STANUJKIC, D. (2016). The framework for the selection of personnel based on the SWARA and ARAS methods under uncertainties. Informatica, 27(1), 49-65.
23. KERŠULIENE, V., ZAVADSKAS, E. K., & TURSKIS, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258.
24. KIM, Y. S., & PARK, J. W. (2017). A Study on the Impact of Online Word-of-Mouth for Airlines on Customer Behavior. The Open Transportation Journal, 11(1), 81-89.
25. KOÇAK, B. B., & ATALIK, Ö. (2017). Negatif Elektronik Ağızdan Ağıza İletişim (eWOM) Yayılımının Kontrolüne Yönelik Bir Sistem Önerisi ve Türkiye Havayolu Sektöründe Bir Uygulama. 22. Ulusal Pazarlama Kongresi, (s. 310-325). Trabzon.
26. KURTULMUŞOĞLU, F. B., CAN, G. F., & TOLON, M. (2016). A voice in the skies: Listening to airline passenger preferences. Journal of Air Transport Management, 57, 130–137.
27. LEE, C. K., LEE, Y. C., CHUANG, Y. S., & WU, W. L. (2014). The Effect of Electronic Word-of-Mouth, Customer Expectations, and Emotions on Intention to Take Low Cost Airlines. J. Sobecki, V. Boonjing, & S. Chittayasothorn içinde, Advanced Approaches to Intelligent Information and Database Systems (Vol. 551) (s. 69-75). Springer.
28. LEE, S. H., & RO, H. (2016). The impact of online reviews on attitude changes: The differential effects of review attributes and consumer knowledge. International Journal of Hospitality Management (56), 1-9.
29. LERRTHAITRAKUL, W., & PANJAKAJORNSAK, V. (2014). Channels of Electronic Word-of-mouth Affecting Consumers’ Buying Decision-making Process in the Low Cost Carriers (LCCs). Research Journal of Business Management (8), 367-378.
30. MILOSAVLJEVIĆA, M., BURSAĆA, M., & TRIČKOVIĆA, G. (2018). Selection of the railroad container terminal in Serbia based on multi criteria decision-making methods. Decision Making: Applications in Management and Engineering, 1(2), 1-15.
31. MORALES-ARROYO, M., & PANDEY, T. (2010). Identification of critical eWOM dimensions for music albums. International Conference on Management of Innovation and Technology (ICMIT) (s. 1230-1235). Singapore: IEEE.
32. ÖZBEK, A. (2017). Çok Kriterli Karar Verme Yöntemleri ve Excel ile Problem Çözümü, Seçkin Yayıncılık, Ankara.
33. PAMUČAR, D., & ĆIROVIĆ, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016-3028.
34. PAMUČAR, D., STEVIĆ, Z., & ZAVADSKAS, E. K. (2018). Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages. Applied Soft Computing, 67, 141-163.
35. RAJAGURU, R. (2016). Role of value for money and service quality on behavioral intention: A study of full service and low cost airlines. Journal of Air Transport Management, 53, 114-122.
36. SAATY, T. L. (1980). The Analytic Hierarchy Process, McGraw-Hill, New York.
37. SARIIŞIK, M., & ÖZBAY, G. (2012). Elektronik ağızdan ağıza iletişim ve turizm endüstrisindeki uygulamalara ilişkin bir yazın incelemesi. Uluslararası Yönetim İktisat ve İşletme Dergisi, 8(16), 1-22.
38. SCHUCKERT, M., LIU, X., & LAW, R. (2016). Insights into suspicious online ratings: direct evidence from TripAdvisor. Asia Pacific Journal of Tourism Research, 21(3), 259-272.
39. SHI, H., LIU, H. C., LI, P., & XU, X. G. (2017). An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder. Waste Management, 59, 508-517.
40. STANUJKIC, D., KARABASEVIC, D., & ZAVADSKAS, E. K. (2015). A framework for the selection of a packaging design based on the SWARA method. Inzinerine Ekonomika-Engineering Economics, 26(2), 181-187.
41. ŠEBJAN, U., TOMİNC, P., & ŠİREC, K. (2017). Multiple conceptual modelling of perceived quality of in-flight airline services. Promet-Traffic&Transportation, 29(3), 311-319.
42. 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.
43. VESKOVIĆ, S., STEVIĆ, Ž., STOJIĆ, G., VASILJEVIĆ, M., & MILINKOVIĆ, S. (2018). Evaluation of the railway management model by using a new integrated model DELPHI-SWARA-MABAC. Decision Making: Applications in management and Engineering, 1(2), 1-17.
44. WAHBA, G. (2017). Measuring the effect of Viral Negative Sentiment on Market Value: Case Study on United Airlines Crisis 2017 (Yayımlanmamış Yüksek Lisans Tezi). Stockholm: KTH School of Industrial Engineering and Management.
45. YILDIZ, S., & TEHCİ, A. (2014). Ağızdan Ağıza İletişimde Müşteri Tatmini ve Müşteri Sadakati ile Mağaza İmajı Boyutları: Ordu İlinde Bir Uygulama. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18(1), 441-460.
46. YU, S. M., WANG, J., & WANG, J. Q. (2017). An interval type-2 fuzzy likelihood-based MABAC approach and its application in selecting hotels on a tourism website. International Journal of Fuzzy Systems, 19(1), 47-61.