Service Quality Assessment via Enhanced Data-Driven MCDM Model

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.

[1]  C. Grönroos Service Management and Marketing: Customer Management in Service Competition , 2007 .

[2]  Chen-Tung Chen,et al.  A fuzzy approach to select the location of the distribution center , 2001, Fuzzy Sets Syst..

[3]  C. Kahraman,et al.  Multi‐criteria supplier selection using fuzzy AHP , 2003 .

[4]  Narasimha Bolloju,et al.  Aggregation of analytic hierarchy process models based on similarities in decision makers' preferences , 2001, Eur. J. Oper. Res..

[5]  A. Parasuraman,et al.  Refinement and reassessment of the SERVQUAL scale. , 1991 .

[6]  George Thomas Friedlob,et al.  Fuzzy logic: application for audit risk and uncertainty , 1999 .

[7]  King-Jang Yang,et al.  Establishment and application of performance measure indicators for universities , 2009 .

[8]  Li Li,et al.  Traffic Differentiation in Dense WLANs with CSMA/ECA-DR MAC Protocol , 2018, 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall).

[9]  Jacqueline A. Griffin,et al.  Decreasing patient length of stay via new flexible exam room allocation policies in ambulatory care clinics , 2018, Health care management science.

[10]  Rooma Roshnee Ramsaran-Fowdar,et al.  Developing a service quality questionnaire for the hotel industry in Mauritius , 2007 .

[11]  Zheng Gu,et al.  Diversification, Financial Performance, and Stability of Foodservice Firms , 1994 .

[12]  David C. Bojanic,et al.  Measuring Service Quality in Restaurants: an Application of the Servqual Instrument , 1994 .

[13]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[14]  A. Parasuraman,et al.  SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. , 1988 .

[15]  Jian-Bo Yang,et al.  Multiple Attribute Decision Making , 1998 .

[16]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[17]  C. Ryan,et al.  Client perceptions of hotels: A multi-attribute approach , 1992 .

[18]  Serkan Yavuz,et al.  Weapon selection using the AHP and TOPSIS methods under fuzzy environment , 2009, Expert Syst. Appl..

[19]  Samira Abbasi,et al.  E-service websites quality measurement through a revised E-S-Qual , 2013 .

[20]  Zhaojun Li,et al.  Performance Evaluation of Tehran-Qom Highway Emergency Medical Service System Using Hypercube Queuing Model , 2015 .

[21]  A. Parasuraman,et al.  Delivering quality service : balancing customer perceptions and expectations , 1990 .

[22]  Sheng-Hshiung Tsaur,et al.  The evaluation of airline service quality by fuzzy MCDM. , 2002 .

[23]  Gwo-Hshiung Tzeng,et al.  An evaluation model of new product launch strategy , 2006 .

[24]  Amir Esmailpour,et al.  Quality of service differentiation measurements in 4G networks , 2013, 2013 Wireless Telecommunications Symposium (WTS).

[25]  Mahdi Saeedpoor,et al.  A SERVQUAL MODEL APPROACH INTEGRATED WITH FUZZY AHP AND FUZZY TOPSIS METHODOLOGIES TO RANK LIFE INSURANCE FIRMS , 2015 .

[26]  Drakoulis Martakos,et al.  Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS , 2009, Expert Syst. Appl..

[27]  Luiz Moutinho,et al.  Modelling Site Location Decisions in Tourism , 1994 .