Factor Analysis in Measuring Information Systems Effectiveness

Abstract

In order to evaluate the value and usefulness of information systems that guide IS management actions and IS investments, DeLone and McLean established a universal definition of IS success that includes different perspectives of how information systems might be evaluated. The IS success taxonomy consists of six success categories (1) systems quality, (2) information quality, (3) service quality, (4) use, (5) user satisfaction, and (6) net benefit from which they created a multidimensional and interdependent measuring model that exemplifies the interdependencies between the different success categories to capture the complex nature of IS success. While the characteristics of information systems steadily increase in scope and complexity, it is imperious that academia and practice develop the means to evaluate the successfulness or effectiveness of a system and understand the factors and circumstances to build and maintain a successful system. The objective of conducting empirical research on systems success is to gain insight into the details of the complex systems processes and features which can be translated into prescriptive action plans for implementation. A focus of this article is to discuss how potential “user perceptions” influence on the information system effectiveness. The DeLone model is used as a base model for the systematic study of the features, factors and delivered benefits. The article employs the survey as an instrument to operationalize the model. The paper introduces the factor analysis technique to estimate the parameters of the proposed casual model. The factor analysis of the result reveals the underlying constructs that guide the decision making and planning processes for successful information systems implementations.