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Enablers of Six Sigma: contextual framework and its empirical validation

Dubey, Rameshwar, Gunasekaran, Angappa, Childe, Stephen J., Fosso Wamba, Samuel, Papadopoulos, Thanos (2015) Enablers of Six Sigma: contextual framework and its empirical validation. Total Quality Management & Business Excellence, . pp. 1-27. ISSN 1478-3363. E-ISSN 1478-3371. (doi:10.1080/14783363.2015.1075877) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1080/14783363.2015.1075877

Abstract

The aim of the paper is to identify the enablers for the successful implementation of Six Sigma. None of the existing frameworks provides any clear understanding related to linkages between, and hierarchical relationships among, the constructs of Six Sigma implementation. Our study has both inductive and deductive elements. We identified enablers of Six Sigma implementation from existing research, and we developed a contextual framework using the interpretive structural modelling technique. We further studied enablers based on their driving power and dependence using MICMAC analysis to categorise the enablers into four clusters. In order to validate the ISM model statistically we developed and pre-tested a structured questionnaire before using it for a survey. Data were collected using a split survey method using a modified version of Dillman's total design method. We performed non-response bias before checking assumptions such as constant variance and normality. We further checked the reliability and construct validity using confirmatory factor analysis. We find that constructs and indicators of our theoretical framework meet the criteria, and find them to be a good fit based on confirmatory factor analysis. We draw conclusions based on statistical analyses and our study limitations, and suggest further research directions.

Item Type: Article
DOI/Identification number: 10.1080/14783363.2015.1075877
Uncontrolled keywords: Six Sigma, implementation, interpretive structural modelling, MICMAC, confirmatory factor analysis, theory building
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > Kent Business School
Depositing User: Kimberley Attard-Owen
Date Deposited: 10 Dec 2015 13:59 UTC
Last Modified: 29 May 2019 16:41 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/53041 (The current URI for this page, for reference purposes)
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