Structural equation modeling in social science research

Abstract

Purpose The purpose of this paper is to describe and discuss a few principal and crucial steps of “antecedents” and “postcedents” in relation to structural equation modeling (SEM) in social science research. Design/methodology/approach This paper is based upon a conceptual and reflective discussion of SEM in social sciences research. Findings SEM is not science per se, but just a tool that is used to extract meaning from the previous steps of research processes in terms of a research phenomenon in focus. Research limitations/implications Based upon the steps of validity and reliability discussed in relation to predetermined measurement and structural models in SEM, application implications are provided. Practical implications Like many statistical tools, SEM can be misused to manipulate findings and fit of measurement and structural models. Researchers may become more interested in the tool than in the subject matter. Originality/value Using SEM does not elevate research to be science or make the researcher a scientist! An area of concern for further debate is whether the widespread and variable applications of SEM in social science (in particular, marketing) research are all science.

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