Evaluating Airline Service Quality Using Fuzzy DEMATEL and ANP

Year 2017, Volume: 3 Issue: 6, 57 - 77, 28.12.2017

Navid Haghighat

https://doi.org/10.25069/spmj.351296

Cited By: 3

Abstract

A hybrid fuzzy MADM method is proposed in this paper for
evaluating airline service quality. Fuzzy set theory is used since it helps in
measuring the ambiguity of concepts associated with human being’s subjective
judgment. After reviewing service quality evaluation models especially in the
airline industry, SSQAI model was adopted as a construct for evaluating airline
service quality in Iran. Fuzzy DEMATEL was applied to determine the degree of
influence and impact of criteria on each other and extract cause and effect
relations between them that helped in ranking criteria based on the degree of
relationship. Then, ANP network map was constructed based on the relation map
generated from Fuzzy DEMATEL analysis. Fuzzy ANP approach assisted in
prioritizing criteria based on the need for improvement and enabled in a more
accurate measurement in decision-making process taking the advantage of using
linguistic variables. Fuzzy DEMATEL results demonstrate that expertise,
Problem-solving, and conduct has the most influence on other factors and in
opposite Valence, Waiting Time, Comfort are the factors which get the most
impact from other factors and according to Fuzzy ANP analysis Valence,
Convenience, Problem-solving, and Safety&Security are the factors with most
priorities that need improvement.

Keywords

Airline Service Quality, Fuzzy Theory, FMADM, Fuzzy DEMATEL

Evaluating Airline Service Quality Using Fuzzy DEMATEL and ANP

Abstract

A hybrid fuzzy MADM method is proposed in this paper for evaluating airline service quality. Fuzzy set theory is used since it helps in measuring the ambiguity of concepts associated with human being’s subjective judgment. After reviewing service quality evaluation models especially in the airline industry, SSQAI model was adopted as a construct for evaluating airline service quality in Iran. Fuzzy DEMATEL was applied to determine the degree of influence and impact of criteria on each other and extract cause and effect relations between them that helped in ranking criteria based on the degree of relationship. Then, ANP network map was constructed based on the relation map generated from Fuzzy DEMATEL analysis. Fuzzy ANP approach assisted in prioritizing criteria based on the need for improvement and enabled in a more accurate measurement in decision-making process taking the advantage of using linguistic variables. Fuzzy DEMATEL results demonstrate that expertise, Problem-solving, and conduct has the most influence on other factors and in opposite Valence, Waiting Time, Comfort are the factors which get the most impact from other factors and according to Fuzzy ANP analysis Valence, Convenience, Problem-solving, and Safety&Security are the factors with most priorities that need improvement.

Keywords

Airline Service Quality, Fuzzy Theory, FMADM, Fuzzy DEMATEL

References

• 1. Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing science, 12(2), 125-143. 2. Andotra, N., Gupta, S., & Pooja. (2008). Airline service effectiveness: an analysis of value addition, quality and risk perception. Abhigyan, 26(2), 10-19. 3. Ayag, Z., & Ozdemir, R.G. (2012). Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP. Int. J. Production Economics, 140, 630–636 4. Bellman, R. E., & Zadeh, L. A. (1970). Decision making in a fuzzy environment. Management Science, 17(4), 141–164. 5. Brady, M. K., & Cronin, J. J. (2001). Some New Thoughts on Conceptualizing Perceived Service Quality: A Hierarchical Approach. The Journal of Marketing, 65(7), 34-49. 6. Chen, J. K., & Chen, I. S. (2010). Using a novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education. Expert Systems with Applications, 37(3), 1981–1990. 7. Chow, C.K.W. (2014). Customer satisfaction and service quality in the Chinese airline industry. Journal of Air Transport Management, 35, 102-107. 8. 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. 9. Cronin Jr, J. J., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. The journal of marketing, 55-68. 10. Dabholkar, P. A., Thorpe, D. I., & Rentz, J. O. (1996). A measure of service quality for retail stores: scale development and validation. Journal of the Academy of marketing Science, 24(1), 3-16. 11. Ghobadian, A., & Speller, S., & Jones, M. (1994). Service quality concepts and models, International Journal of Quality & Reliability management, 11(9), 43-66. 12. Gilbert, D., & Wong, R. K. C. (2003). Passenger expectations and airline service: a Hong Kong based study. Tourism Management, 24(5), 519-532. 13. Grönroos, C. (1984). A service quality model and its marketing implications. European Journal of marketing, 18(4), 36-44. 14. Wu, H. C., & Cheng, C. C. (2013). A hierarchical model of service quality in the airline industry. Journal of Hospitality and Tourism Management, 20, 13-22. 15. Kotler, P. (1991). Marketing Management: Analysis, Planning, Implementation, and Control-7/E. 16. Kuo, M. S., & Liang, G. S. (2011). Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Systems with Applications, 38(3), 1304-1312. 17. Kuo, C. W., & Jou, R. C. (2014). Asymmetric response model for evaluating airline service quality: An empirical study in cross-strait direct flights. Transportation Research Part A: Policy and Practice, 62, 63-70. 18. Laming, C., & Mason, K., (2014). Customer experience-An analysis of the concept and its performance in airline brands. Research in Transportation Business & Management, 10, 15-25. 19. Lee, A. H., Kang, H. Y., Yang, C. Y., & Lin, C. Y. (2010). An evaluation framework for product planning using FANP, QFD and multi-choice goal programming. International Journal of Production Research, 48(13), 3977-3997. 20. 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. 21. Liou, J. J.H., Tzeng, G.-H., (2007), A non-additive model for evaluating airline service quality. Journal of Air Transport Management, 13(3), 131-138. 22. Nadiri, H., & Hussain, K. (2005). Perceptions of service quality in North Cyprus hotels. International Journal of Contemporary Hospitality Management, 17(6), 469-480. 23. Nathanail, E. (2008). Measuring the quality of service for passengers on the Hellenic railways. Transportation Research Part A: Policy and Practice, 42(1), 48-66. 24. Ostrowski, R. L., O’Brien, T. V., & Gordon, G. L. (1993). Service quality and customer loyalty in the commercial airline industry. Journal of Travel Research, 32(2), 16-24. 25. 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. 26. Pakdil, F., & Aydin, O. (2007). Expectations and perceptions in airline service: an analysis using weighted SERVQUAL scores. Journal of Air Transport Management, 13(4), 229-237. 27. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 41-50. 28. Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process (Vol. 4922). Pittsburgh: RWS publications. 29. Suki, N.M. (2014). Passenger satisfaction with airline service quality in Malaysia: A structural equation modeling approach. Research in Transportation Business & Management, 10(4), 26-32. 30. Tiernan, S., Rhoades, D., & Waguespack, B. (2008). Airline alliance service quality performance—An analysis of US and EU member airlines. Journal of Air Transport Management, 14(2), 99-102. 31. 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. 32. Wu, W. W., & Lee, Y. T. (2007). Developing global managers’ competencies using the fuzzy DEMATEL method. Expert systems with applications, 32(2), 499-507. 33. Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338–353. 34. Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—II. Information sciences, 8(4), 301-357. 35. Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46. 36. Zhou, X. (2012). Fuzzy analytical network process implementation with matlab. MATLAB–A fundamental tool for scientific computing and engineering applications, 3, 133-160.