Quantifying the relationship between latent variables after successful implementation of QM practices in MSMEs

Abstract

Purpose

The purpose of this paper is to explore the relationship between latent variables, i.e. human resource management (HRM) effectiveness, quality cost (QC), and firm performance (FP) for the successful implementation of quality management (QM) practices in micro, small and medium enterprises.

Design/methodology/approach

The data analysis is accomplished in three steps: in the first step, factor analysis was conducted to extract the latent variables representing key QM practices. In the second step, a descriptive analysis (cross-tabulation) was performed to examine the current situation and association between key QM variables and firm size. In the third step, to test the research hypotheses based on latent constructs, structural equation modelling (SEM) has been used.

Findings

The percent point score shows that there are substantial improvements in all organisational aspects after successful implementation of QM practices. The χ²-test revealed that only three domains namely employee participation, recruitment and retaining and supplier relationship are having a significant variation with respect to the firm size. The SEM results show that HRM effectiveness has a direct and positive relationship with FP, whereas QC has a negative association with HRM effectiveness and FP.

Originality/value

Managers will know which aspect they must consider seeing as an indicator of QM practice in their company(s). Out of the three identified latent constructs first will help to create an efficient human capital, whereas the second will help for addressing extra cost due to poor quality. Finally, the third latent variable will show the effectiveness of these two and will assist in evaluating firm’s performance.

Citation

Kharub, M. and Sharma, R.K. (2018), "Quantifying the relationship between latent variables after successful implementation of QM practices in MSMEs", International Journal of Quality & Reliability Management, Vol. 35 No. 4, pp. 875-896. https://doi.org/10.1108/IJQRM-12-2016-0221