Structural equation modelling in marketing and business research: Critical issues and practical recommendations

Abstract

Purpose

Structural equation modelling (SEM) is a method that is very frequently applied by marketing and business researchers to assess empirically new theoretical proposals articulated by means of complex models. It is, therefore, a logical thought that the quality of the new advances in marketing and business theory depends, in part, on how well SEM is applied. This study aims to conduct an extensive review and empirical analysis of a broad variety of classic and recent controversies and issues related with the use of SEM, in order to identify problematic questions and prescribe a compendium of solutions for its suitable application.

Design/methodology/approach

The main analyses were conducted on a sample of 191 SEM‐based papers and 472 applications, i.e. all the SEM‐based studies published in four leading marketing journals during the period 1995‐2007.

Findings

Despite the maturity of SEM, its application in marketing research still has notable room for improvement. This is a general conclusion based on numerous problems detected and discussed here.

Practical implications

The study provides plausible solutions to the problems identified, a useful guide that is easy to follow and to apply adequately to present SEM issues in marketing and business studies.

Research limitations/implications

The sample of SEM‐based papers and applications is limited to four publication outlets. A wider set or/and other journals different to those analyzed here may be preferred.

Originality/value

This is a valuable and timely study of the application of SEM in marketing and business research, and is also useful as a guiding framework for good practice. Likewise, as the problems discussed here presumably occur in other areas of social science, this paper should be welcome beyond the borders of the business disciplines.

Citation

Martínez‐López, F.J., Gázquez‐Abad, J.C. and Sousa, C.M.P. (2013), "Structural equation modelling in marketing and business research: Critical issues and practical recommendations", European Journal of Marketing, Vol. 47 No. 1/2, pp. 115-152. https://doi.org/10.1108/03090561311285484