Multiple Group Structural Equation Modeling Development for Factor Analysis that affects Information

Technology Service Management of Higher Educational Academic

Institutions

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

Content

1. Introduction2. Theory and Methodology3. Methodology4. Results5. References

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.

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

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

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)

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.

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

METHODOLOGY• Data sets for the research– The data set of experimental group was 290

data sets.

METHODOLOGY

Factor Indicator of Factor

1 Service Transition (ST)Service Operation (SO)Continual Service Improvement (CSI)

2 Service Strategy (SS)Service Design (SD)Service Transition (ST)

Table 1: Results of main factors and indicators

METHODOLOGYStructural Equation ModelingTable 2: The statistic’s compatibility of SEM

Model DefaultChi-square ( ) 1.546

GFI 0.710

AGFI 0.667

RMSEA 0.094

Hoelter’s 91

2

METHODOLOGY• SEM standardized type

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

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.

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.

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.

Thank you

Q/A