The use of meta-analysis in validating the DeLone and McLean information systems success model

The measurement of systems success is important to any research on information systems. A research study typically uses several dependent measures as surrogates for systems success. These dependent measures are generally treated as outcome variables which, as a group, vary as a function of certain independent variables. Recently, a process perspective has been advocated to measure system success. This process perspective recognizes that some of the dependent measures, along with independent variables, also have an impact on outcome variables. A comprehensive success model has been developed by DeLone and McLean (1992) to group success measures cited in the literature into three categories: quality, use, and impact. This model further predicts that quality affects use, which in turn affects impact. This paper explores the plausibility of using meta-analysis to validate this success model. Advantages of using meta-analysis over other research methodologies in validating process models are examined. Potential problems with meta-analysis in validating this particular success model are discussed. A research plan that utilizes past empirical studies to validate this success model is described