Beyond the Quality of Service: Exploring the Evaluation Criteria of Airlines

Wang, Ray

  • Received : 2014.01.24
  • Accepted : 2014.03.07
  • Published : 2014.06.30


With the progress and prosperity of commerce and industry, time and money increasingly form an equal partnership. Using air carriers to shorten the round-trip time has become an important choice for many people in the tourism process. Faced with increasing competition within the aviation service environment, airline evaluation criteria and the requirements of customers are gradually dominating the evaluation mechanism for air transport service quality. Over the past few years, attention on the transport quality of service has been primarily focused more on land-based transport, and less on the relevant evaluation criteria of airlines. Many studies have shown that quality of service will directly affect customer satisfaction, resulting in the fact that good quality aviation services have become increasingly important. Therefore, in practical industrial operations with limited resources, there is an urgent need to delve into the assessment guidelines that have an impact on customers when they choose an airline, which can be used as a basis for improving customer satisfaction. Through a literature review and a reliability and validity analysis, this study summarized 19 evaluation criteria, using the purposive sampling method and the decision laboratory method (DEMATEL). In addition, this study viewed the causal relationship between the evaluation criteria and the degree of association as a continuing project for airlines. This study selected appropriate empirical samples from two domestic airlines. The conclusions may provide recommendations for all airlines.


Quality of Service;Evaluation Criteria;Decision-Making Trail and Evaluation Laboratory (DEMATEL)


  1. Prentice, C. (2013), Service quality perceptions and customer loyalty in casinos, International Journal of Contemporary Hospitality Management, 25(1), 49-64.
  2. Wittman, M. D. and Swelbar, W. S. (2013), Trends and market forces shaping small community air service in the United States, Report no. ICAT-2013-02, MIT International Center for Air Transportation, Cambridge, MA.
  3. Zadeh, L. A. (1975), The concept of a linguistic variable and its application to approximate reasoning I, Information Sciences, 8(3), 199-249.
  4. Zeithaml, V. A., Berry, L. L., and Parasuraman, A. (1988), Communication and control processes in the delivery of service quality, Journal of Marketing, 52, 35-48.
  5. Parasuraman, A., Berry, L. L., and Zeithaml, V. A. (1985), A conceptual model of service quality and its implications for future research, Journal of Marketing, 49, 41-50.
  6. Parasuraman, A., Zeithaml, V. A., and Berry, L. L. (1988), SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality, Journal of Retailing, 64(1), 12-40.
  7. Seyed-Hosseini, S. M., Safaei, N., and Asgharpour, M. J. (2006), Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique, Reliability Engineering and System Safety, 91(8), 872-881.
  8. Steven, A. B., Dong, Y., and Dresner, M. (2012), Linkages between customer service, customer satisfaction and performance in the airline industry: investigation of non-linearities and moderating effects, Transportation Research Part E: Logistics and Transportation Review, 48(4), 743-754.
  9. Torres, E. N. and Kline, S. (2013), From customer satisfaction to customer delight: creating a new standard of service for the hotel industry, International Journal of Contemporary Hospitality Management, 25(5), 642-659.
  10. Tseng, M. L. (2010), An assessment of cause and effect decision-making model for firm environmental knowledge management capacities in uncertainty, Environmental Monitoring and Assessment, 161(1-4), 549-564.
  11. Tseng, M. L. and Chiu, A. S. (2013), Evaluating firm's green supply chain management in linguistic preferences, Journal of Cleaner Production, 40, 22-31.
  12. Tseng, M. L., Wu, W. W., Lin, Y. H., and Liao, C. H. (2008), An exploration of relationships between environmental practice and manufacturing performance using the PLS path modeling, WSEAS Transactions on Environment and Development, 4(6), 487-502.
  13. Wang, R. (2011), Cause-effect relationships and the service quality evaluation criteria of portal sites, African Journal of Business Management, 5(6), 2432-2444.
  14. Wang, R., Lin, Y. H., and Tseng, M. L. (2011), Evaluation of customer perceptions on airline service quality in uncertainty, Procedia-Social and Behavioral Sciences, 25, 419-437.
  15. Jeon, S. and Kim, M. S. (2012), The effect of the servicescape on customers' behavioral intentions in an international airport service environment, Service Business, 6(3), 279-295.
  16. Fontela, E. and Gabus, A. (1976), The DEMATEL observer, DEMATEL 1976 Report, Battelle Geneva Research Center, Geneva, Switzerland.
  17. Fuller, J. and Matzler, K. (2008), Customer delight and market segmentation: an application of the threefactor theory of customer satisfaction on life style groups, Tourism Management, 29(1), 116-126.
  18. Han, S., Ham, S. S., Yang, I., and Baek, S. (2012), Passengers' perceptions of airline lounges: importance of attributes that determine usage and service quality measurement, Tourism Management, 33(5), 1103-1111.
  19. Kano, N., Seraku, N., Takahashi, F., and Tsuji, S. (1984), Attractive quality and must-be quality, Journal of the Japanese Society for Quality Control, 14(2), 39-48.
  20. Khameneh, S. M. and Motamedi, N. (2014), Vendor selection with multi criteria decision making approach with application in steel industry, Applied Mathematics in Engineering, Management and Technology, (Special Issue), 46-58.
  21. Liou, J. J., Tzeng, G. H., and Chang, H. C. (2007), Airline safety measurement using a hybrid model, Journal of Air Transport Management, 13(4), 243-249.
  22. Liu, N. and Song, N. (2001), The fuzzy association degree in semantic data models, Fuzzy Sets and Systems, 117(2), 203-208.
  23. Matarazzo, B. and Munda, G. (2001), New approaches for the comparison of L-R fuzzy numbers: a theoretical and operational analysis, Fuzzy Sets and Systems, 118(3), 407-418.
  24. Nagar, K. (2013), Perceived service quality with frill and no-frill airlines: an exploratory research among Indian passengers, Prestige International Journal of Management and Information Technology-Sanchayan, 2(1), 63-74.
  25. Nunnally, J. C. (1978), Psychometric Theory (2nd ed.), McGraw-Hill, New York, NY.
  26. Okeudo, G. and Chikwendu, D. U. (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.
  27. Bamber, G. J., Gittell, J. H., Kochan, T. A., and Nordenflycht, A. (2009), Up in the Air: How Airlines Can Improve Performance by Engaging Their Employees. ILR Press, Ithaca, NY.
  28. Berry, L. L., Zeithaml, V. A., and Parasuraman, A. (1985), Quality counts in services, too, Business Horizons, 28(3), 44-52.
  29. Chen, C. T. (2001), A fuzzy approach to select the location of the distribution center, Fuzzy Sets and Systems, 118(1), 65-73.
  30. Chen, W. J. (2013), Factors influencing internal service quality at international tourist hotels, International Journal of Hospitality Management, 35, 152-160.
  31. Cho, Y. C. and Pan, J. Y. (2014), Hybrid network defense model based on fuzzy evaluation, The Scientific World Journal, 2014, article no. 178937.
  32. Cooper, D. R. and Emory, W. C. (1995), Business Research Methods (5th ed.), Irwin, Chicago, IL.
  33. Correia, A. R., Wirasinghe, S. C., and de Barros, A. G. (2008), Overall level of service measures for airport passenger terminals, Transportation Research Part A: Policy and Practice, 42(2), 330-346.

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