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Record W1547198708

Total Quality Management Implementation: The "Core" Strategy

2005· article· en· W1547198708 on OpenAlexaboutno aff
Chuck Ryan, Steven E. Moss

Bibliographic record

VenueAcademy of strategic management journal/Academy of Strategic Management journal · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsTotal quality managementQuality (philosophy)Quality managementProcess managementOperations managementEmpirical researchProcess (computing)Computer scienceBusinessMarketingEconomicsManagement systemMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT This research presents an empirical investigation of total quality management (TQM) implementation in small- to medium-sized manufacturing firms. The study introduces a new TQM implementation strategy: the Core approach and tests the efficacy of a five-element quality management model. Factor analysis, cluster analysis, and ANOVA are used to test relationships among implementation, resulting practices, and performance. Results suggest TQM implementation transcends industry type and is most successful when viewed as a holistic process rather than either selective or contingent. INTRODUCTION Most American and European businesses have deployed some type of quality initiative in their operations (Silvestro, 2001). Yet, many firms have seen little to no benefit from their quality management efforts. Research has attributed many of these disappointments to improper quality management program implementation (Belohav, 1993; Cole, Bacdayan, & White, 1993; Smith, Tranfield, Foster, & Whittle, 1994; Hackman & Wageman, 1995; Douglas & Judge, 2001; Yusof & Aspinwall, 2002). Indeed, recent work suggests that the high failure rate of quality management initiatives results from a mismatch between these processes and critical problems in their respective environments; in short, that quality management should be seen and properly executed as a contingent process (Melcher, Khouja, & Booth, 2002; Das, Handfield, Clalantone, & Ghosh, 2000; Claycomb, Droge, & Germain, 2002; Wang, 2004). While there is a growing body of literature studying the linkage between quality management practice and performance, most research is not empirically-based and centers on large manufacturing companies (Rahman, 2001). Furthermore, Ingle (2000) noted that little discussion has focused on total quality management (TQM) implementation methodologies and that further work in the area is called for. It is these gaps that this research will address by investigating the relationships among implementation practices and performance in small-to-medium manufacturing businesses. This research will show that, for these firms, quality management implementation transcends industry type and is most successful when viewed as a holistic process, as opposed to either a step-wise or contingent process. The next section of the paper features a review of the literature relevant to the current study. We follow with the operational definition of TQM upon which our research is based. Research methodology is then presented, followed by an analysis of the demographics of firms included in the study. Empirical results are then shown. A final discussion of results and implications is presented in the conclusion section. EXECUTION, CONTINGENCY THEORY, AND IMPLEMENTATION Powell (1995) hypothesized that TQM firms outperform those without quality management programs in a survey of CEOs and quality executives in the Northeastern U.S. Powell utilized financial performance as a dependent variable and evaluated it on the basis of profits, sales growth, and overall financial performance, reported subjectively by the senior manager responding to the survey. He found that certain behavioral aspects of TQM result in improved performance, and concluded that firms with a formal quality management program outperform those without a TQM program. Ahire (1996) studied the impact of TQM programs centering on the following question: Is TQM a long campaign, one taking several years before desired results are seen? He surveyed a total of 499 U.S. and Canadian plant managers and found that successful firms see measurable benefits of the quality management efforts in 2-3 years. In addition, he found that higher levels of top management commitment, customer focus, supplier relations, design quality, training, use of quality management tool s, and employee involvement were associated with better operational results. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.356
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2005
Admission routes1
Has abstractyes

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