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Service Quality Assessment via Enhanced Data-Driven MCDM Model

  • Vahab VahdatEmail author
  • Seyedmohammad Salehi
  • Nima Ahmadi
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

Tourism and hospitality industry has brought large economical revenue for both developing and developed countries. However, with the increase in tourists’ diversity, needs, and expectations, the need for hotels with higher quality of services has emerged. This research evaluates and compares the quality of service in two different types of hotels that exist in the historic cities: first, hotels that are located in the historic sites of the city offering mostly the city architecture, culture, life style, and local cuisines second, modern hotels that are outside the buffer zone of the historic site, equipped with modern technology and offer more standardized services and international cuisines. In this research, a stylized multi-phase framework is used to assess the quality of service from a modified-SERVQUAL model. Two sets of surveys are distributed among the hotel administrators and travelers. Using Analytic Hierarchy Process (AHP), fuzzy set theory, and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), the relative importance of each SERVQUAL dimension in the hotel industry is investigated and the hotel types are ranked accordingly. Our results indicate that hotels that are located in historic sites are more favorable for the tourists.

References

  1. 1.
    Ramsaran-Fowdar RR. Developing a service quality questionnaire for the hotel industry in Mauritius. J Vac Market. 2007;13:19–27.CrossRefGoogle Scholar
  2. 2.
    Moutinho L, Curry B. Modelling site location decisions in tourism. J Travel Tour Market. 1994;3:35–57.CrossRefGoogle Scholar
  3. 3.
    Tsaur S-H, Chang T-Y, Yen C-H. The evaluation of airline service quality by fuzzy MCDM. Tour Manag. 2002;23:107–15.CrossRefGoogle Scholar
  4. 4.
    Cali M, Ellis K, te Velde DW. The contribution of services to development: the role of regulation and trade liberalisation. Overseas Development Institute London, England;2008.Google Scholar
  5. 5.
    Esmailpour A, Salehi S, Safavi N. Quality of service differentiation measurements in 4G networks. Wirel Telecommun Symp (WTS). 2013;2013:1–5.Google Scholar
  6. 6.
    Salehi S, Li L, Shen C-C, Cimini L, Graybeal J. Traffic differentiation in dense WLANs with CSMA/ECA-DR MAC protocol. 2018. arXiv:1806.09582.
  7. 7.
    Mobin M, Li Z, Amiri M. Performance evaluation of tehran-qom highway emergency medical service system using hypercube queuing model. In: IIE annual conference. Proceedings;2015, p. 1175.Google Scholar
  8. 8.
    Vahdat V, Griffin J, Stahl JE. Decreasing patient length of stay via new flexible exam room allocation policies in ambulatory care clinics. Health Care Manage Sci. 2017;1–25.Google Scholar
  9. 9.
    Zada VV, Abbasi S, Barazesh F, Abdi R. E-service websites quality measurement through a revised ES-QUAL. Global J Technol. 1;2013.Google Scholar
  10. 10.
    Saeedpoor M, Vafadarnikjoo A, Mobin M, Rastegari A. A servqual model approach integrated with fuzzy AHP and fuzzy topsis methodologies to rank life insurance firms. In: Proceedings of the international annual conference of the American society for engineering management;2015, p. 1.Google Scholar
  11. 11.
    Gronroos C. Service management and marketing: customer management in service competition, vol. 3. Wiley Chichester;2007.Google Scholar
  12. 12.
    Lehtinen U, Lehtinen JR. Service quality: a study of quality dimensions. Service Management Institute;1982.Google Scholar
  13. 13.
    Zeithaml VA, Parasuraman A, Berry LL. Delivering quality service: balancing customer perceptions and expectations. Simon and Schuster;1990.Google Scholar
  14. 14.
    Parasuraman A, Zeithaml VA, Berry LL. Servqual: a multiple-item scale for measuring consumer perc. J Retail. 1988;64:12.Google Scholar
  15. 15.
    Babakus E, Mangold WG. Adapting the SERVQUAL scale to health care environment: an empirical assessment. Enhan Knowl Develop Market. 1989;9:67–8.Google Scholar
  16. 16.
    Parasuraman A, Berry LL, Zeithaml VA. Refinement and reassessment of the SERVQUAL scale. J Retail. 1991;67:420.Google Scholar
  17. 17.
    Bojanic DC, Drew Rosen L Measuring service quality in restaurants: an application of the SERVQUAL instrument. Hospit Res J. 1994;18:3–14.CrossRefGoogle Scholar
  18. 18.
    Saleh F, Ryan C. Client perceptions of hotels: A multi-attribute approach. Tour Manag. 1992;13:163–8.CrossRefGoogle Scholar
  19. 19.
    Saaty TL. Analytic hierarchy process. In: Encyclopedia of operations research and management science. Springer;2013, pp. 52–64.CrossRefGoogle Scholar
  20. 20.
    Bolloju N. Aggregation of analytic hierarchy process models based on similarities in decision makers’ preferences. Eur J Oper Res. 2001;128:499–508.CrossRefGoogle Scholar
  21. 21.
    Chen S-H, Wang H-H, Yang K-J. Establishment and application of performance measure indicators for universities. The TQM J. 2009;21:220–35.CrossRefGoogle Scholar
  22. 22.
    Chiu Y-C, Chen B, Shyu JZ, Tzeng G-H. An evaluation model of new product launch strategy. Technovation. 2006;26:1244–52.CrossRefGoogle Scholar
  23. 23.
    Dağdeviren M, Yavuz S, Kılınç N. Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Syst Appl. 2009;36:8143–51.CrossRefGoogle Scholar
  24. 24.
    Tzeng G-H, Huang J-J. Multiple attribute decision making: methods and applications. Chapman and Hall/CRC;2011.Google Scholar
  25. 25.
    Zadeh LA. Fuzzy sets. Inf Control. 1965;8:3.CrossRefGoogle Scholar
  26. 26.
    Kahraman C, Cebeci U, Ulukan Z. Multi-criteria supplier selection using fuzzy AHP. Logist Inf Manage. 2003;16:382–94.CrossRefGoogle Scholar
  27. 27.
    Sakawa M. “Fuzzy multi objective and multilevel optimization: multiple criteria optimization” state of the art annotated bibliographic surveys. Kluwer Academic Publishers;2002, pp. 172–226.Google Scholar
  28. 28.
    Chamodrakas I, Alexopoulou N, Martakos D. Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS. Expert Syst Appl. 2009;36:7409–15.CrossRefGoogle Scholar
  29. 29.
    Abdolvand M, Toloie A, Taghiouryan M. The evaluation of custom service quality by SERVQUAL fuzzy. In: Applied international business conference. Sarawak, Malaysia;2008, pp. 367–80.Google Scholar
  30. 30.
    Friedlob GT, Schleifer LL. Fuzzy logic: application for audit risk and uncertainty. Manag Audit J. 1999;14:127–37.CrossRefGoogle Scholar
  31. 31.
    Chen C-T. A fuzzy approach to select the location of the distribution center. Fuzzy Sets Syst. 2001;118:65–73.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Vahab Vahdat
    • 1
    Email author
  • Seyedmohammad Salehi
    • 2
  • Nima Ahmadi
    • 3
  1. 1.Department of Mechanical and Industrial EngineeringNortheastern UniversityBostonUSA
  2. 2.Computer and Information SciencesUniversity of DelawareNewarkUSA
  3. 3.Department of Industrial Engineering and Engineering ManagementWestern New England UniversitySpringfieldUSA

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