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Record W4232741602 · doi:10.1504/ijmp.2017.084934

The relationship between TQM practices and role stressors

2017· article· en· W4232741602 on OpenAlexaff
Zahra Fallah Ebrahimi, Reza Hosseini Rad

Bibliographic record

VenueInternational Journal of Management Practice · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTotal quality managementStressorBusinessStructural equation modelingProcess managementQuality (philosophy)Conceptual modelEmpirical researchHuman resource managementConceptual frameworkOperations managementKnowledge managementMarketingPsychologyEngineeringSociologyComputer scienceLean manufacturing

Abstract

fetched live from OpenAlex

Small and Medium-sized Enterprises (SMEs) are comprised 90% of all enterprises in Iran. In this regards they have significant role in the development of the country's economy. The purpose of this paper is to develop a conceptual framework to investigate the impact of multidimensionality of total quality management practices on the role stressors. Numerous studies have been done by other researchers on the quality revolution and implemented various Total Quality Management (TQM) programs such as ISO 9000 series as a way to improve quality. This paper investigates the multidimensional relationships between eight TQM practices and role stressors. The empirical data was gathered from 410 Iranian manufacturing SMEs and analysed by using the Structural Equation Modelling (SEM) technique. The findings indicate important association among leadership, information analysis; supplier management, employee involvement, process management and human resources focus with role stressors but no significant relationship between customer focus and supplier management with role stressors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0040.008
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.080
GPT teacher head0.370
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designObservational
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

Citations9
Published2017
Admission routes1
Has abstractyes

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