1. Multiple Group Structural Equation Modeling Development for Factor Analysis that affects Information Technology Service Management of Higher Educational Academic Institutions

2. Researcher Sarun Nakthanom Instructor in Department of Information Technology, Faculty of Science and Technology, Bangkok Suvarnabhumi College, Bangkok, Thailand Namon Jeerungsuwan, Ph.D. Director of Ph.D. Program in Information and Communication Technology for Education, Faculty of Technical Education, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

3. Content 1.Introduction 2.Theory and Methodology 3.Methodology 4.Results 5.References

4. Introduction Higher education institutions have adopted information technology as a tool in management as below: –Service Management –Teaching and learning –Research To analyze have good information technology about its services. Information Technology Infrastructure Library or ITIL V.3 Foundation is an international standard in many countries have made to the guidelines.

5. Theory and Methodology Factor analysis Structural Equation Model Accuracy Evaluation Criterion Information Technology Infrastructure Library

6. Theory and Methodology Factor analysis is a technique used to extract the factors (component) from a group of indicators that are related to each factor. Where:F = factor, w = coefficient of variable x x = manifest variable e = margin of error

7. Theory and Methodology Structural Equation Model (SEM) is a technique used to analyze the relationship of factors from the survey From the statistics of (Model fit) 1) Chi-square (χ2) should be a non-significance (P>0.05) 2) Goodness of Fit Index (GFI>0.90) 3) Root Mean Square Error of Approximation (RMSEA<0.06) and 4) Hoelter's N, the value (Hoelter's. N>75)

8. Theory and Methodology Accuracy Evaluation Criterion MMRE have small values, the results should be precise or very close to the real data as formulated below.

9. Theory and Methodology Information Technology Infrastructure Library (ITIL) Service Strategy Service Design Service Transition Service Operation Continual Service Improvement - Financial Management - Service Portfolio Management - Demand Management - Service Catalogue Management - Service Level Management - Capacity Management - Availability Management - IT service Continuity Management - Information Security Management Supplier Management, Application Management - Data and Information Management Business Service Management - Change Management - Service asset and Configuration Management - Release and deployment Management - Knowledge Management - Stakeholder Management - Transition Planning - Support and Service Evaluation - Event Management - Incident Management - Request Management - Problem Management - Access management The 7-Step Improving Process

10. METHODOLOGY Data sets for the resear ch –The data set of experimental group was 290 data sets.

11. METHODOLOGY FactorIndicator of Factor 1Service Transition (ST) Service Operation (SO) Continual Service Improvement (CSI) 2Service Strategy (SS) Service Design (SD) Service Transition (ST) Table 1: Results of main factors and indicators

12. METHODOLOGY Structural Equation Modeling Table 2: The statistic’s compatibility of SEM Model Default Chi-square ( )1.546 GFI0.710 AGFI0.667 RMSEA0.094 Hoelter’s91

13. METHODOLOGY SEM standardized type

14. Table 2 and the new SEM are shown in Fig. 2

15. METHODOLOGY Product indicator approaches of structural equation modeling with constrained approach. The only measure left over from the results of the SEM according to Fig. 1 is F1 = {CSI5, CSI4, CSI3, CSI1, SO7, CSI7, CSI2, CSI6, SO6, SO3, SO5, SO2, SO1, SO4, ST6, ST4, ST7, ST5, ST3} F2 = {SD1, SS3, SD2 SS2, SS1, SD3, SD5,SD6, ST1, SD7, ST2, SD4 } to create SEM have the statistics of compatibility.

16. RESULTS The test group of 290 sets was assigned to find estimate the replacement value of missing data as follows: 1) the data imputation estimation methods using SEM, the result of MMRE was 25.23% 2) Thus, comparing estimates of data showed that using the SEM with the unconstrained approach and related indicators had high accuracy, while MMRE declined using the constrained approach with related indicators.

17. REFERENCES Prakancharoen, S.(2008). The estimated time to develop application software oriented network using structural equation modeling. Information Technology Journal. Year 4 Vol. 7. Bangkok: King Mongkut's University of Technology North Bangkok. Jan van Bon, Pieper,M., Veen,A., Verheijen,T. (2007). Best Practices: Introduction to ITIL,TSO Publications, Norwich,June. Taylor,S., Iqbal,M., Nieves,M. (2007) ITIL:Service Strategy,TSO publications.Norwith,UK. Taylor,S., Lioyd,V.,Rudd,C. (2007). ITIL:Service Design,TSO publications.Norwith,UK. Taylor,S., Lacy,S.,Macfarlane,I. (2007). ITIL:Service Transition,TSO publications.Norwith,UK. Taylor,S.,CannonD.,Wheeldon,D. (2007). ITIL:Service Strategy,TSO publications.Norwith,UK. Taylor,S.,CaseG.,Spalding,G. (2007). ITIL:Continual Service Improvement,TSO publications.Norwith,UK. Arbuckle, James L. (2006). Structural equation modeling -AMOS6.0 user guide,Chicago-IL SPSS Inc., USA David Garson. (2006) Structural equation modeling, Statistics solution inc, USA.

18. Thank you Q/A