A Study on Sentiment Analysis on Airline Quality Services: A Conceptual Paper
Keywords:
Sentiment Analysis, Airline Quality Service, Customer Review
Abstract
Airline quality service is crucial for airlines to remain competitive in the industry. The quality of the services of these airlines must meet customer satisfaction and other aspects of the overall service experience. The levels of service quality in an airline service may impact satisfaction and loyalty which may influence customer sentiment. Concerning the importance of airline quality service, customer sentiment towards the service must be investigated and one of the ways to analyze it is by using sentiment analysis. Sentiment analysis is the chosen tool nowadays to analyze comments or reviews made on these services, which may be positive, negative, or neutral. Using sentiment analysis, will not only help potential customers to view the overall sentiment portrayed, but organizations can also use the findings to improve their organization to be more competitive. Thus, this paper will focus on reviewing several recent works related to sentiment analysis as a tool for assisting organizations in assessing the quality of services in the airline industry. As a result, a new framework for assessing the quality of service for the organizations, especially the airline company will be proposed.
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References
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El Haddad, R. (2019). Exploring service quality of low-cost airlines. Services Marketing Quarterly, 40(4), 301-315. DOI: 10.1080/15332969.2019.1665901.
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. https://doi.org/10.1016/j.jairtraman.2017.12.008
Farzadnia, S., & Raeesi Vanani, I. (2022). Identification of opinion trends using sentiment analysis of airline passengers' reviews. Journal of Air Transport Management, 103(C).
Georgiadou, E., Angelopoulos, S., & Drake, H. (2020). Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes. International Journal of Information Management, 51, 102048. DOI: 10.1016/j.ijinfomgt.2019.102048.
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Majumder, N., Poria, S., Peng, H., Chhaya, N., Cambria, E., & Gelbukh, A. (2019). Sentiment and sarcasm classification with multitask learning. IEEE Intelligent Systems, 34(3), 38-43.
Malik, S., El-Sayed, H., Khan, M., & Ignatious, H. (2020). Application of containerized microservice approach to airline sentiment analysis. 2020 14th International Conference on Innovations in Information Technology (IIT). https://doi.org/10.1109/IIT50501.2020.9299043.
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Ozuem, W., Chiemeke, A. C., & Arikpo, C. C. (2023). Assessing the impact of social media on airline service quality: A systematic literature review. Journal of Air Transport Management, 102450.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.
Park, J.W., Robertson, R., & Wu, C.-L. (2004). The effect of airline service quality on passengers’ behavioral intentions: A Korean case study. Journal of Air Transport Management, 10(6), 435-439.
Park, J.W., Robertson, R., & Wu, C.L. (2006). The effects of individual dimensions of airline service quality: Findings from Australian domestic air passengers. Journal of Hospitality and Tourism Management, 13(2), 161-176. https://doi.org/10.1375/jhtm.13.2.161.
Patel, K. (2018). Factors influencing customer satisfaction in low-cost carriers and full-service carriers: A comparative study. International Journal of Aviation Studies, 16(1), 42-60.
Patel, A., Oza, P., & Agrawal, S. (2023). Sentiment analysis of customer feedback and reviews for airline services using language representation model. Procedia Computer Science, 218, 2459-2467.
Puschmann, C., & Powell, A. (2018). Turning words into consumer preferences: How sentiment analysis is framed in research and the news media. Social Media + Society, 4(3). https://doi.org/10.1177/2056305118797724
Ractham, P., Abrahams, A., Gruss, R., & Kim, E. (2021). A comparative evaluation of airline service quality using online content analysis: A case study of Korean vs. International airlines. Asia Pacific Journal of Information Systems, 31(4), 491-526. DOI: 10.14329/apjis.2021.31.4.491
Rasheed, F. A., & Abadi, M. F. (2014). Impact of service quality, trust and perceived value on customer loyalty in Malaysia services industries. Procedia - Social and Behavioral Sciences, 164, 298-304.
Rumelli?, M., Akku?, D., Kart, Ö., & I?ik, Z. (2019). Sentiment analysis in Turkish text with machine learning algorithms. 2019 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-5.
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Suchánek, P., & Králová, M. (2019). Customer satisfaction, loyalty, knowledge and competitiveness in the food industry. Economic Research-Ekonomska Istraživanja, 32(1), 1237-1255. DOI: 10.1080/1331677X.2019.1627893.
Sudhir, P., & Deshakulkarni Suresh, V. (2021). Comparative study of various approaches, applications and classifiers for sentiment analysis. Global Transitions Proceedings, 2(2), 205-211. https://doi.org/10.1016/j.gltp.2021.08.004
Sukri, S., Abdullah, F., & Waemustafa, W. (2014). Customer satisfaction and loyalty in the airline industry: A case study of Malaysia Airlines (MAS) and AirAsia. In International Case Study Conference, Putra World Trade Centre, Malaysia, 18-19 August 2014 (ICSC 2014) (pp. 43).
Supriyanto, A., Wiyono, B. B., Burhanuddin, B., & Olan, F. (2021). Effects of service quality and customer satisfaction on the loyalty of bank customers. Cogent Business & Management, 8(1).
Symeonidis, S., Effrosynidis, D., & Arampatzis, A. (2018). A comparative evaluation of pre-processing techniques and their interactions for Twitter sentiment analysis. Expert Systems with Applications, 110, 298-310. doi: 10.1016/j.eswa.2018.06.022.
Vizcarra, J., Kozaki, K., Torres Ruiz, M., et al. (2021). Knowledge-based sentiment analysis and visualization on social networks. New Generation Computing, 39, 199-229. DOI: 10.1007/s00354-020-00103-1.
Vizcarra, I., López-Herrera, A. G., Sánchez-Rada, J. F., & Herrera, F. (2021). Analyzing the impact of airline service quality on customer satisfaction and loyalty: A social media perspective. Journal of Business Research, 128, 802-814.
Vu, T. (2021). Service quality and its impact on customer satisfaction (Bachelor's thesis). The University of Northampton.
Wang, J., Gui, T., Cheng, M., Wu, X., Ruan, R., & Du, M. (2023). A survey on emotional visualization and visual analysis. Journal of Visualization, 26(1), 177-198. DOI: 10.1007/s12650-022-00872-5.
Wang, X., He, J., Jin, Z., Yang, M., Wang, Y., & Qu, H. (2022). M2Lens: Visualizing and explaining multimodal models for sentiment analysis. IEEE Transactions on Visualization and Computer Graphics, 28(1), 802-812. doi: 10.1109/TVCG.2021.3114794.
Wankhade, M., Rao, A.C.S. & Kulkarni, C. (2022). A survey on sentiment analysis methods, applications, and challenges. Artif Intell Rev 55, 5731–5780. https://doi.org/10.1007/s10462-022-10144-1
Waramontri, R. (2021). Service quality in tourism management: Comparison between traditional and low-cost airlines. The EUrASEANs Journal on Global Socio-Economic Dynamics, 1(26), 43-51.
Wu, B., Park, J., & Robertson, T. (2011). The moderating role of customer sentiment in the service quality-customer satisfaction relationship. Journal of Business Research, 64(11), 1245-1251.
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46.
Ahmed, A. Z., & Rodríguez-Díaz, M. (2020). Significant labels in sentiment analysis of online customer reviews of airlines. Sustainability, 12(20), 8683. https://doi.org/10.3390/su12208683
Aljedaani, W., Rustam, F., Mkaouer, M. W., Ghallab, A., Rupapara, V., Washington, P. B., Lee, E., & Ashraf, I. (2022). Sentiment analysis on Twitter data integrating TextBlob and deep learning models: The case of US airline industry. Knowledge-Based Systems, 255, 109780.
Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. Journal of Marketing, 58(3), 53-66.
Duong, H. T., & Nguyen-Thi, T. A. (2021). A review: preprocessing techniques and data augmentation for sentiment analysis. Computer Society of Vietnam Journal, 8(1).
El Haddad, R. (2019). Exploring service quality of low-cost airlines. Services Marketing Quarterly, 40(4), 301-315. DOI: 10.1080/15332969.2019.1665901.
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. https://doi.org/10.1016/j.jairtraman.2017.12.008
Farzadnia, S., & Raeesi Vanani, I. (2022). Identification of opinion trends using sentiment analysis of airline passengers' reviews. Journal of Air Transport Management, 103(C).
Georgiadou, E., Angelopoulos, S., & Drake, H. (2020). Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes. International Journal of Information Management, 51, 102048. DOI: 10.1016/j.ijinfomgt.2019.102048.
Hal, M.T., Nguyen, G.D., & Doan, B.S. (2023). Understanding the mediating effect of switching costs on service value, quality, satisfaction, and loyalty. Humanities and Social Sciences Communications, 288. https://doi.org/10.1057/s41599-023-01797-6
Gupta, N., & Bhargav, R. (2022). Sentiment analysis in the airline industry using machine learning techniques. In A. Pradhan, M. S. Obaidat, S. Kharel, & V. Mishra (Eds.), Emerging Technologies in Data Mining and Information Security (pp. 99-111). Singapore: Springer. DOI: 10.1007/978-981-19-4052-1_12.
Han, H., Zhang, Y., Zhang, J., Yang, J., & Zou, X. (2018). Improving the performance of lexicon-based review sentiment analysis method by reducing additional introduced sentiment bias. Plos One, 13(8), e0202523. DOI: 10.1371/journal.pone.0202523.
Hasib, K. M., Habib, M. A., Towhid, N. A., & Showrov, M. I. H. (2021). A novel deep learning-based sentiment analysis of Twitter data for US Airline service. In 2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) (pp. 450-455). Dhaka, Bangladesh: IEEE. DOI: 10.1109/ICICT4SD50815.2021.9396879.
Hemmatian, F., & Sohrabi, M.K. (2017). A survey on classification techniques for opinion mining and sentiment analysis. Artificial Intelligence Review, 48(4), 499-527. https://doi.org/10.1007/s10462-017-9599-6
Kang, H. W., Chye, K. K., Ong, Z. Y., & Tan, C. W. (2022). Sentiment analysis on Malaysian Airlines with BERT. The Journal of The Institution of Engineers, Malaysia, 82. DOI: 10.54552/v82i3.98.
Kaur, G., & Malik, K. (2021). A sentiment analysis of airline system using machine learning algorithms. International Journal of Advanced Research in Engineering, 12(1), 731-742.
Kumar, S., & Zymbler, M. (2019). A machine learning approach to analyze customer satisfaction from airline tweets. Journal of Big Data, 6(1), 62. https://doi.org/10.1186/s40537-019-0224-1
Kwon, H.-J., Ban, H.-J., Jun, J.-K., & Kim, H.-S. (2021). Topic modeling and sentiment analysis of online reviews for airlines. Information, 12(2), 78. https://doi.org/10.3390/info12020078
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.
Ligthart, A., Catal, C. & Tekinerdogan, B. (2021). Systematic reviews in sentiment analysis: a tertiary study. Artif Intell Rev 54, 4997–5053. https://doi.org/10.1007/s10462-021-09973-3
Lin, L., Osman, Z., Zahir, I., & Shiqian, W. (2018). The indirect effect of trust on customer satisfaction and customer loyalty in the Malaysian Airline industry. Journal of Economics and Business, 1(2), 134-142. ISSN 2615-3726. DOI: 10.31014/aior.1992.01.02.12.
Lucini, F., Tonetto, L. M., Fogliatto, F. & Anzanello, M. (2019). Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews. Journal of Air Transport Management, 83. 10.1016/j.jairtraman.2019.101760.
Majumder, N., Poria, S., Peng, H., Chhaya, N., Cambria, E., & Gelbukh, A. (2019). Sentiment and sarcasm classification with multitask learning. IEEE Intelligent Systems, 34(3), 38-43.
Malik, S., El-Sayed, H., Khan, M., & Ignatious, H. (2020). Application of containerized microservice approach to airline sentiment analysis. 2020 14th International Conference on Innovations in Information Technology (IIT). https://doi.org/10.1109/IIT50501.2020.9299043.
Md Suhaimin, Mohd Suhairi, Suhaimin, Md, Hanafi, Mohd, Hijazi, Mohd, Alfred, Rayner, & Coenen, Frans. (2019). Modified framework for sarcasm detection and classification in sentiment analysis. TELKOMNIKA Indonesian Journal of Electrical Engineering, 13, 1175-1183. doi: 10.11591/ijeecs.v13.i3.pp1175-1183.
Net Promoter Score. (2018). The Net Promoter System: How to convert customers into promoters. Harvard Business Review Press.
Ozuem, W., Chiemeke, A. C., & Arikpo, C. C. (2023). Assessing the impact of social media on airline service quality: A systematic literature review. Journal of Air Transport Management, 102450.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.
Park, J.W., Robertson, R., & Wu, C.-L. (2004). The effect of airline service quality on passengers’ behavioral intentions: A Korean case study. Journal of Air Transport Management, 10(6), 435-439.
Park, J.W., Robertson, R., & Wu, C.L. (2006). The effects of individual dimensions of airline service quality: Findings from Australian domestic air passengers. Journal of Hospitality and Tourism Management, 13(2), 161-176. https://doi.org/10.1375/jhtm.13.2.161.
Patel, K. (2018). Factors influencing customer satisfaction in low-cost carriers and full-service carriers: A comparative study. International Journal of Aviation Studies, 16(1), 42-60.
Patel, A., Oza, P., & Agrawal, S. (2023). Sentiment analysis of customer feedback and reviews for airline services using language representation model. Procedia Computer Science, 218, 2459-2467.
Puschmann, C., & Powell, A. (2018). Turning words into consumer preferences: How sentiment analysis is framed in research and the news media. Social Media + Society, 4(3). https://doi.org/10.1177/2056305118797724
Ractham, P., Abrahams, A., Gruss, R., & Kim, E. (2021). A comparative evaluation of airline service quality using online content analysis: A case study of Korean vs. International airlines. Asia Pacific Journal of Information Systems, 31(4), 491-526. DOI: 10.14329/apjis.2021.31.4.491
Rasheed, F. A., & Abadi, M. F. (2014). Impact of service quality, trust and perceived value on customer loyalty in Malaysia services industries. Procedia - Social and Behavioral Sciences, 164, 298-304.
Rumelli?, M., Akku?, D., Kart, Ö., & I?ik, Z. (2019). Sentiment analysis in Turkish text with machine learning algorithms. 2019 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-5.
Seyler, D., Shen, J., Xiao, J., Wang, Y., & Zhai, C. (2020). Leveraging personalized sentiment lexicons for sentiment analysis. In Proceedings of the 2020 ACM SIGIR on International Conference on Theory of Information Retrieval (ICTIR '20), 109–112. DOI: 10.1145/3409256.3409850.
Shayaa, S. et al. (2018). Sentiment analysis of big data: Methods, applications, and open challenges. IEEE Access, 6, 37807-37827. doi: 10.1109/ACCESS.2018.2851311.
Suchánek, P., & Králová, M. (2019). Customer satisfaction, loyalty, knowledge and competitiveness in the food industry. Economic Research-Ekonomska Istraživanja, 32(1), 1237-1255. DOI: 10.1080/1331677X.2019.1627893.
Sudhir, P., & Deshakulkarni Suresh, V. (2021). Comparative study of various approaches, applications and classifiers for sentiment analysis. Global Transitions Proceedings, 2(2), 205-211. https://doi.org/10.1016/j.gltp.2021.08.004
Sukri, S., Abdullah, F., & Waemustafa, W. (2014). Customer satisfaction and loyalty in the airline industry: A case study of Malaysia Airlines (MAS) and AirAsia. In International Case Study Conference, Putra World Trade Centre, Malaysia, 18-19 August 2014 (ICSC 2014) (pp. 43).
Supriyanto, A., Wiyono, B. B., Burhanuddin, B., & Olan, F. (2021). Effects of service quality and customer satisfaction on the loyalty of bank customers. Cogent Business & Management, 8(1).
Symeonidis, S., Effrosynidis, D., & Arampatzis, A. (2018). A comparative evaluation of pre-processing techniques and their interactions for Twitter sentiment analysis. Expert Systems with Applications, 110, 298-310. doi: 10.1016/j.eswa.2018.06.022.
Vizcarra, J., Kozaki, K., Torres Ruiz, M., et al. (2021). Knowledge-based sentiment analysis and visualization on social networks. New Generation Computing, 39, 199-229. DOI: 10.1007/s00354-020-00103-1.
Vizcarra, I., López-Herrera, A. G., Sánchez-Rada, J. F., & Herrera, F. (2021). Analyzing the impact of airline service quality on customer satisfaction and loyalty: A social media perspective. Journal of Business Research, 128, 802-814.
Vu, T. (2021). Service quality and its impact on customer satisfaction (Bachelor's thesis). The University of Northampton.
Wang, J., Gui, T., Cheng, M., Wu, X., Ruan, R., & Du, M. (2023). A survey on emotional visualization and visual analysis. Journal of Visualization, 26(1), 177-198. DOI: 10.1007/s12650-022-00872-5.
Wang, X., He, J., Jin, Z., Yang, M., Wang, Y., & Qu, H. (2022). M2Lens: Visualizing and explaining multimodal models for sentiment analysis. IEEE Transactions on Visualization and Computer Graphics, 28(1), 802-812. doi: 10.1109/TVCG.2021.3114794.
Wankhade, M., Rao, A.C.S. & Kulkarni, C. (2022). A survey on sentiment analysis methods, applications, and challenges. Artif Intell Rev 55, 5731–5780. https://doi.org/10.1007/s10462-022-10144-1
Waramontri, R. (2021). Service quality in tourism management: Comparison between traditional and low-cost airlines. The EUrASEANs Journal on Global Socio-Economic Dynamics, 1(26), 43-51.
Wu, B., Park, J., & Robertson, T. (2011). The moderating role of customer sentiment in the service quality-customer satisfaction relationship. Journal of Business Research, 64(11), 1245-1251.
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46.
Published
2023-11-16
How to Cite
Idris, S. L., & Mohamad, M. (2023). A Study on Sentiment Analysis on Airline Quality Services: A Conceptual Paper. Information Management and Business Review, 15(4(SI)I), 564-576. https://doi.org/10.22610/imbr.v15i4(SI)I.3638
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Research Paper
Copyright (c) 2023 Sheema Liza Idris, Masurah Mohamad
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