Design of online survey system with an advanced IPA discrimination index for customer satisfaction assessment Presenter: Mai, Yi-Ting ( 麥毅廷, 臺體大運管系 ) Paper source: Electronic Commerce Research, vol. 14, No. 3 Contact Info.:

Total 26 pages22 Outline The purpose of survey Related works –Web-based computing –Importance - Performance Analysis (IPA) Web-based survey system with an advanced IPA discrimination index Performance analysis Conclusion

Total 26 pages33 The purpose of survey? Service trade, business, academic domain, etc. To provide the high quality service for customer To get feedback from customers/clients –How to prepare a questionnaire? –How to analyze results? –Considering user preference?

Total 26 pages44 Related works How to know service quality satisfaction from clients? –Questionnaire survey –Cloud, web, online questionnaire survey systems Convenience, survey anytime & anywhere Survey system with IPA model –Importance - Performance Analysis (IPA) –Survey including extra-functionality Creative, lower complicated and higher effective

Total 26 pages55 IPA Importance - Performance Analysis (IPA) –To measure the relation between the importance of the service quality and satisfaction IPA four steps: –To produce questionnaire with each service attribute –To give scores in “ Importance ” and “ Performance ” –Importance as y-axis, Performance as x-axis –I-P matrix is divided into four quadrants or sections

Total 26 pages66 IPA framework B. A.

Total 26 pages7 PZB model PZB (Parasuraman, Zeithaml & Berry, 1985) –service quality perceptions of user satisfaction Five dimensions: –Assurance –Empathy –Tangibles –Reliability –Responsiveness

Total 26 pages8 Web-based questionnaire Web-based questionnaire with IPA model –View with Likert Scale 5 point –Support Likert Scale 9 point Multiple choice –Online checking scheme No answer alert, pagination for large subjects

Total 26 pages99 Web-based questionnaire (cont.)

Total 26 pages10 IPA discrimination index The positive effective value of IPA area B. A.

Total 26 pages11 IPA discrimination index (cont.) Negative effect Positive effect

Total 26 pages12 IPA discrimination index (cont.)

Total 26 pages13 Result analysis information 257 valid questionnaires (278 questionnaires) 30 regular questions about user satisfaction ( for visited clients ) Special question item for survey checking

Total 26 pages14 Result analysis information (cont.) Web-based questionnaire – Multiple-option with single-survey High single-option (higher value of multiple choices) Low single-option (lower value of multiple choices)

Total 26 pages15 Result analysis I – survey types The three grading schemes –high single-option –low single-option –multiple-option Which one is the best? What is the appropriate tool for comparison?

Total 26 pages16 Reliability vs. Validity Case1Case2Case3 Neither Reliable nor Valid Reliable not Valid Both Reliable and Valid

Total 26 pages17 Reliability Reproducibility of a measurement

Total 26 pages18 Scale reliability analysis Internal consistency –correlations amongst multiple items in a factor –e.g., Cronbach’s Alpha (α) –<.6  not reliable –>=.6  OK

Total 26 pages19 Reliability of three grading schemes

Total 26 pages20 Mean Squared Error (MSE) As stated in our discussion on closeness, one potential measure for the goodness of an estimator is MSE.

Total 26 pages21 MSE of three grading schemes

Total 26 pages22 Multiple-optionHigh single-option Low single-option Comparison?? IPA matrix

Total 26 pages23 Quadrant analysis Quadrant Multiple- option High single- option Low single- option Quadrant A 1099 Quadrant B 475 Quadrant C Quadrant D 566

Total 26 pages24 IPA index An advanced IPA discrimination index

Total 26 pages25 Result analysis II – PZB model Five categories of PZB –How to compare? IPA matrix IPA index

Total 26 pages26 Conclusion “Web-based Survey system with an advanced IPA discrimination index” is a useful tool for assessment of the quality of service. The advanced IPA index is an efficient tool to enlarge the application scale of the original IPA model. The advanced IPA discrimination index can provide the quantitative comparisons information.