Factor Retention Decisions in Exploratory Factor Analysis Results: A Study Type of Knowledge Management Process at Malaysian University Libraries

Abstract

Structural equation modeling (SEM) is a versatile statistical modeling tool which uses in the social sciences research. Recently, in Library and Information Science (LIS) environment, structural equation modeling has gained popularity across many disciplines, due to its generality and flexibility. Its estimation techniques, modeling capabilities and breadth of application are expanding rapidly. This paper reported a structural equation modeling through an Exploratory Factor Analysis (EFA) result, which involves 300 lead users at six selected Malaysian university libraries through survey. The decision of how many factors to retain is a critical component of exploratory factor analysis. Evidence is presented that parallel analysis is one of the most accurate factor retention methods. SPSS 20 was utilized to analyze the factor analysis data. In this regards, the results of EFA could provide empirical evidence of each hypotheses construct. It is hoped that the EFA results could be used to level Confirmatory Factor Analysis (CFA) to perform full Structural Equation Modeling.