Applying consistent fuzzy preference relations to measure user perceived service quality of information presenting web portals

The study adopted the method of Herrera-Viedma et al., (2004): consistent fuzzy preference relations (Fuzzy PreRa) to apply the questionnaire which Zhilin Yang et al.(2005) developed. The result shows that the most important of the five-dimension is "Usability" and the most important of the nineteen items is "Relevant information to the customer". Compared to the traditional AHP method, Fuzzy PreRa has the advantages of reducing the comparing times. It is very easy to calculate and improve the inconsistent result. The result provides a useful suggestion for researchers and portal managers.

[1]  Nelson K. H. Tang,et al.  The effectiveness of commercial Internet Web sites: a user's perspective , 1998, Internet Res..

[2]  A. Parasuraman,et al.  A Conceptual Model of Service Quality and Its Implications for Future Research , 1985 .

[3]  Gisela M. von Dran,et al.  User Expectations and Rankings of Quality Factors in Different Web Site Domains , 2001, Int. J. Electron. Commer..

[4]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[5]  J. Steenkamp.  Conceptual model of the quality perception process , 1990 .

[6]  Francisco Herrera,et al.  Some issues on consistency of fuzzy preference relations , 2004, Eur. J. Oper. Res..

[7]  Tien-Chin Wang,et al.  Forecasting the probability of successful knowledge management by consistent fuzzy preference relations , 2007, Expert Syst. Appl..

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

[9]  Sanghyuk Park,et al.  Development of electronic commerce user-consumer satisfaction index (ECUSI) for Internet shopping , 2001, Ind. Manag. Data Syst..

[10]  Ping Zhang,et al.  Expectations and rankings of Web site quality features: results of two studies on user perceptions , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[11]  Zheng Zhou,et al.  Development and validation of an instrument to measure user perceived service quality of information presenting Web portals , 2005, Inf. Manag..

[12]  A. Parasuraman,et al.  Service quality delivery through web sites: A critical review of extant knowledge , 2002, Journal of the Academy of Marketing Science.

[13]  G. R. Dattatreya.  Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS , 2006 .

[14]  Yi-Shun Wang,et al.  An Instrument for Measuring Customer Satisfaction Toward Web Sites That Market Digital Products and Services , 2001, J. Electron. Commer. Res..

[15]  T C Wang,et al.  A NEW METHOD ON DECISION-MAKING USING FUZZY LINGUISTIC ASSESSMENT VARIABLES AND FUZZY PREFERENCE RELATIONS , 2005 .

[16]  C. Grönroos.  An Applied Service Marketing Theory , 1982 .

[17]  Gilbert A. Churchill.  A Paradigm for Developing Better Measures of Marketing Constructs , 1979 .

[18]  Prashant C. Palvia,et al.  Developing and validating an instrument for measuring user-perceived web quality , 2002, Inf. Manag..

[19]  Chang Liu,et al.  Exploring the factors associated with Web site success in the context of electronic commerce , 2000, Inf. Manag..

[20]  A. Parasuraman,et al.  A conceptual framework for understanding e-service quality : implications for future research and managerial practice , 2000 .

[21]  V. Zeithaml.  Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence: , 1988 .

[22]  R. Peterson,et al.  Taking the pulse of Internet pharmacies. , 2001, Marketing health services.

[23]  V. Zeithaml.  Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence , 1988 .

[24]  M. Gilly,et al.  .comQ: Dimensionalizing, Measuring, and Predicting Quality of the E-tail Experience , 2002 .

[25]  T. L. Saaty.  Exploring the interface between hierarchies, multiple objectives and fuzzy sets , 1978 .

[26]  Francisco Herrera,et al.  Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations , 1998, Fuzzy Sets Syst..

[27]  Naveen Donthu,et al.  Developing a Scale to Measure the Perceived Quality of An Internet Shopping Site ( SITEQUAL ) , 2005 .

[28]  Mary Jo Bitner,et al.  The Service Encounter: Diagnosing Favorable and Unfavorable Incidents: , 1990 .