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Record W2979767173 · doi:10.5430/ijfr.v10n6p283

The Effect of Total Quality Management on University Performance in Jordan

2019· article· en· W2979767173 on OpenAlexvenueno aff
Khaled Alzeaideen

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTotal quality managementSustainabilityBusinessOperations managementPsychologyMarketingEngineering

Abstract

fetched live from OpenAlex

Total Quality Management (TQM) a functioning idea to accomplish incessant performance improvement-is the word of mouth of the 1990s, attracting deep interest among organizations and educational institutions in many countries. Numerous policy-makers truly believe that TQM can improve the performance of their organizations but they did not test it to make sure the effect of TQM. Hence, the purpose of this study is to examine the effect of TQM on university performance in Jordan. This relationship obtains a substantial scholarly attention and several researches have been conducted in the western countries, but none has been conducted in Jordan in the recent year using this variable in a model. A structured survey was conducted and selected 10 public and 10 private universities in Jordan via cluster random sampling. The hypotheses were tested using SEM-AMOS package 22.0 based on resource based theory. Based on the statistical results, TQM has statistically significant effect on university performance in Jordan. Consequently, the findings evoked that there is a dire need to focus on TQM for boosting university performance and its sustainability in Jordan.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.324
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2019
Admission routes1
Has abstractyes

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