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Investigation into the hierarchical nature of TQM variables using structural modelling

Johan Veltmeyer (School of Engineering, Griffith University, Gold Coast, Australia)
Sherif Mohamed (School of Engineering, Griffith University, Gold Coast, Australia)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 3 April 2017

528

Abstract

Purpose

The purpose of this paper is to provide the empirical evidence supporting the existence of a multi-level hierarchical TQM model showing the structural inter-relationships among a total of 16 TQM variables (i.e. drivers, enablers and outcomes).

Design/methodology/approach

The set of identified TQM variables is the product of an in-depth review of the literature, and a robust reiterative process of verification and validation. Inter-relationships among the TQM variables were subjected to the scrutiny of a panel of experts, and were used as a basis for developing a web-based survey to explore the existence as well as strength of the structural relationship between each and every pair of the identified variables using interpretive structural modelling and MICMAC (Impact Matrix Cross-Reference Multiplication Applied to a Classification).

Findings

TQM variables were classified and clustered based on their influence and dependence on each other. Variables such as commitment by top management and customer satisfaction appear to have a strong chance to affect change, whereas variables such suppliers and competitors are very dependent on, and sensitive to, the evolution of the influent variables.

Originality/value

The paper demonstrates a multi-level TQM model encompassing all identified TQM drivers, enablers, and outcomes. The paper not only addresses a gap in the relevant literature (reduces the evidence scarcity about the hierarchical nature of TQM variables), but also gives insights into the variables with most driving power needing greater management attention.

Keywords

Citation

Veltmeyer, J. and Mohamed, S. (2017), "Investigation into the hierarchical nature of TQM variables using structural modelling", International Journal of Quality & Reliability Management, Vol. 34 No. 4, pp. 462-477. https://doi.org/10.1108/IJQRM-04-2015-0052

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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