Looking for potential service quality gaps to improve customer satisfaction by using a new GA approach

References

• Abalo , J. , Varela , J. and Manzano , V. 2007 . Importance values for importance-performance analysis: A formula for spreading out values derived from preference rankings . Journal of Business Research , 60 ( 2 ) : 115 – 121 .
   Web of Science ®Google Scholar
• Ambrozic , T. and Turk , G. 2003 . Prediction of subsidence due to underground mining by artificial neural networks . Computers and Geosciences , 29 ( 5 ) : 627 – 637 .
   Web of Science ®Google Scholar
• Bagozzi , R. P. and Yi , T. 1988 . On the evaluation of structural equation model . Journal of Academy of Marketing Science , 16 ( 1 ) : 74 – 94 .
   Google Scholar
• Becerikli , Y. , Konar , A. F. and Samad , T. 2003 . Intelligent optimal control with dynamic neural networks . Neural Networks , 16 ( 2 ) : 251 – 259 .
   PubMed Web of Science ®Google Scholar
• Brandt , D. R. 1988 . How service marketers can identify value-enhancing service element . The Journal of Services Marketing , 2 ( 3 ) : 35 – 41 .
   Google Scholar
• Chang , J. , Chang , L. C. and Huang , H. L. 2005 . Real time recurrent neural network for stream flow forecasting . Hydrological Processes , 16 : 2577 – 2588 .
   Google Scholar
• Ghiassi , M. , Saidan , H. and Zimbra , D. K. 2005 . A dynamic artificial neural network model for forecasting time series events . International Journal of Forecasting , 21 : 341 – 362 .
   Web of Science ®Google Scholar
• Hair , J. F. , Black , B. , Babin , B. , Anderson , R. E. and Tatham , R. L. 2006 . Multivariate data analysis , Upper Saddle River, NJ : Pearson Education Inc .
   Google Scholar
• Han , M. and Xi , J. 2004 . Efficient clustering of radial basis perception neural network for pattern recognition . Pattern Recognition , 37 : 2059 – 2067 .
   Web of Science ®Google Scholar
• Holmlund , M. 2008 . Suggesting and comparing different scopes on quality management: Production, service, relationship, and network . Total Quality Management & Business Excellence , 18 ( 8 ) : 847 – 859 .
   Web of Science ®Google Scholar
• Hung , Y. H. , Huang , M. L. and Chen , K. S. 2003 . Service quality evaluation by service quality performance matrix . Total Quality Management , 14 ( 1 ) : 79 – 89 .
   Google Scholar
• Jost , A. 1993 . Neural networks: A logical progression in credit and marketing decision systems . Credit World , 81 ( 4 ) : 26 – 33 .
   Google Scholar
• Kaastra , I. and Boyd , M. 1996 . Designing a neural network for forecasting financial and economic time series . Neurocomputing , 10 ( 3 ) : 215 – 236 .
   Web of Science ®Google Scholar
• Kano , N. Life cycle and creation of attractive quality . 4th International QMOD Conference Quality Management and Organizational Development . Sweden. Linkopings Universitet .
   Google Scholar
• Kano , N. , Seraku , N. , Takahashi , F. and Tsuji , S. 1984 . Attractive quality and must-be quality . Journal of Japanese Society for Quality Control , 14 : 39 – 48 .
   Google Scholar
• Khaw , J. F.C. , Lim , B. S. and Lim , L. E.N. 1995 . Optimal design of neural network using the Taguchi method . Neurocomputing , 7 : 225 – 245 .
   Web of Science ®Google Scholar
• Lee , M. C. and Hwan , I. S. 2005 . Relationships among service quality, customer satisfaction and profitability in the Taiwanese banking industry . International Journal of Management , 22 ( 4 ) : 635 – 648 .
   Google Scholar
• Liang , M. and Palakal , M. J. 2002 . Airborne sonar target recognition using artificial neural network . Mathematical and Computer Modeling , 35 ( 3–4 ) : 429 – 440 .
   Google Scholar
• Lin , S. P. , Chan , Y H. and Tsai , M. C. 2009 . A transformation function corresponding to IPA and gap analysis for constructing a comprehensive resource distribution model . Total Quality Management & Business Excellence , 20 ( 8 ) : 829 – 846 .
   Web of Science ®Google Scholar
• Lin , Y. , Chen , W. and Tsutsumi , A. 2003 . Long-trem prediction of nonlinear hydrodynamics in bubble columns by using artificial neural networks . Chemical Engineering and Processing , 42 ( 8–9 ) : 611 – 620 .
   Web of Science ®Google Scholar
• Marchant , J. A. and Onyango , C. M. 2003 . Comparison of a bayesian classifier with a multilayer feedforward neural network using the example of plant/weed/soil discrimination . Computers and Electronics in Agriculture , 39 ( 1 ) : 3 – 22 .
   Web of Science ®Google Scholar
• Matzler , K. and Sauerwein , E. 2002 . The factor structure of customer satisfaction: An empirical test of the importance grid and the penalty-reward-contrast analysis . International Journal of Service Industry Management , 13 ( 4 ) : 314 – 332 .
   Google Scholar
• Matzler , K. and Hinterhuber , H. H. 1998 . How to make product development projects more successful by integrating Kano's model of customer satisfaction into quality function deployment . Technovation , 18 ( 1 ) : 25 – 37 .
   Web of Science ®Google Scholar
• Matzler , K. , Bailom , F. , Hinterhuber , H. H. , Renzl , B. and Pichler , J. 2004 . The asymmetric relationship between attribute-level performance and overall customer satisfaction: A reconsideration of the importance-performance analysis . Industrial Marketing Management , 33 : 271 – 277 .
   Web of Science ®Google Scholar
• Mukherjee , A. and Nath , P. 2005 . An empirical assessment of comparative approaches to service quality measurement . The Journal of Services Marketing , 19 ( 3 ) : 174 – 184 .
   Google Scholar
• Nunnally , J. C. 1978 . Psychometric theory , New York : McGraw-Hill .
   Google Scholar
• Pakdil , F. and Harwood , T. 2005 . Patient satisfaction in a preoperative assessment clinic: An analysis using SERVQUAL dimensions . Total Quality Management & Business Excellence , 16 ( 1 ) : 15 – 30 .
   Web of Science ®Google Scholar
• Parasuraman , A. , Zeithaml , V. A. and Berry , L. L. 1985 . A conceptual model of service quality and its implications for future research . Journal of Marketing , 49 : 41 – 50 .
   Web of Science ®Google Scholar
• Parasuraman , A. , Zeithaml , V. A. and Malhotra , A. 2005 . E-S-QUAL: A multiple-item scale for assessing electronic service quality . Journal of Service Research , 7 ( 3 ) : 213 – 234 .
   Web of Science ®Google Scholar
• Rohini , R. and Mahadevappa , B. 2006 . Service quality in Bangalore hospitals – an empirical study . Journal of Services Research , 6 ( 1 ) : 59 – 81 .
   Google Scholar
• Roses , L. K. , Hoppen , N. and Henrique , J. L. 2009 . Management of perceptions of information technology service quality . Journal of Business Research , 62 ( 9 ) : 876 – 882 .
   Web of Science ®Google Scholar
• Sahoo , B. , Ray , C. and Wade , H. F. 2005 . Pesticide prediction in ground water in North Carolina domestic wells using artificial neural networks . Ecological Modelling , 183 : 29 – 46 .
   Web of Science ®Google Scholar
• Tontini , G. and Silveira , A. 2007 . Identification of satisfaction attributes using competitive analysis of the improvement gap . International Journal of Operations & Production Management , 27 ( 5 ) : 482 – 500 .
   Web of Science ®Google Scholar
• Tsaur , S.-H. , Chiu , Y.-C. and Huang , C.-H. 2002 . Determinants of guest loyalty to international tourist hotels – a neural network approach . Tourism Management , 23 : 397 – 405 .
   Web of Science ®Google Scholar
• Wang , S. M. , Feng , C. M. and Hsieh , C. H. 2010 . Stakeholder perspective on urban transport system service quality . Total Quality Management & Business Excellence , 21 ( 11 ) : 1103 – 1119 .
   Web of Science ®Google Scholar
• Winch , G. , Usmani , A. and Edkins , A. 1998 . Towards total project quality: A gap analysis approach . Construction Management & Economics , 16 ( 2 ) : 193 – 207 .
   Google Scholar
• Yang , C. and Chang , F. J. 2005 . Modelling the combined open channel flow by artificial neural network . Hydrological Processes , 19 ( 18 ) : 3747 – 3762 .
   Web of Science ®Google Scholar
• Yieh , K. , Chiao , Y.-C. and Chiu , Y.-K. 2007 . Understanding the antecedents to customer loyalty by applying structural equation modeling . Total Quality Management & Business Excellence , 18 ( 3 ) : 267 – 284 .
   Web of Science ®Google Scholar