Journal article
An empirical investigation of the Baldrige framework using applicant scoring data
The International journal of quality & reliability management, Vol.35(8), pp.1599-1616
09/03/2018
DOI: 10.1108/IJQRM-12-2016-0215
Abstract
Purpose The purpose of this paper is to overcome evaluative limitations of previous studies to provide a more decisive test of the causal relationships implied in the Baldrige Criteria for Performance Excellence (CPE) using a unique data source.
Design/methodology/approach The authors employ partial least squares path modeling on blinded scoring data from Baldrige Award applicants. In addition, the authors conduct multi-group analysis to examine whether the hypothesized causal model is universal across different industry sectors.
Findings The path analysis provided strong support for the CPE framework in its entirety. However, analysis of sector-specific subsets of the data did not confirm all relationships, suggesting the possibility of industry-dependent performance excellence frameworks and raising new research questions to be explored.
Practical implications This research offers several pertinent implications for managers who seek to translate the theoretical CPE framework to actionable quality-improvement efforts.
Originality/value CPE operationalizes many total quality management (TQM) concepts and provides guidelines to TQM programs. This study validates the CPE framework using the most relevant data set to date - the applicant scoring data. The authors are also the first to investigate the cross-industry differences in the relationships between the CPE constructs.
Details
- Title: Subtitle
- An empirical investigation of the Baldrige framework using applicant scoring data
- Creators
- Feng Mai - Stevens Institute of TechnologyMatthew W. Ford - Northern Kentucky UniversityJames R. Evans - University of Cincinnati
- Resource Type
- Journal article
- Publication Details
- The International journal of quality & reliability management, Vol.35(8), pp.1599-1616
- Publisher
- Emerald Group Publishing
- DOI
- 10.1108/IJQRM-12-2016-0215
- ISSN
- 0265-671X
- eISSN
- 1758-6682
- Number of pages
- 18
- Language
- English
- Date published
- 09/03/2018
- Academic Unit
- Business Analytics
- Record Identifier
- 9984701832702771
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