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Record W3111473873 · doi:10.5267/j.ac.2020.11.007

The effect of total quality management on the financial performance by moderating organizational culture

2020· article· en· W3111473873 on OpenAlexvenueno aff
Sanaa Maswadeh, Rania Al Zumot

Bibliographic record

VenueAccounting · 2020
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessStock exchangeOrganizational cultureEmpowermentMarketingOrganizational performanceModerationReturn on assetsPopulationBusiness administrationAccountingFinanceManagementEconomicsPsychologyEconomic growth

Abstract

fetched live from OpenAlex

This study aims to learn the effect of the Total Quality Management dimensions, Top Management Support, Customer Focus, Process Management, Employees Participation, Employees' Empowerment, and Continuous Improvement, on financial performance by moderating organizational culture. The study population includes nine transport companies listed on the Amman Stock Exchange until the end of 2019. Alia Company and Royal Jordanian Airlines were excluded since its financial data formed extreme values when compared with the values of the rest of the companies. The study uses Multiple Linear Regression to test the hypotheses. The study found a statistically significant effect at the level of significance (α < 0.05) for both top management support, customer focus, employees’ participation and empowerment, by moderating the organizational culture on financial performance measured by return on asset for the Jordanian transport companies listed on the Amman Stock Exchange. In light of the statistical results, the study presented several recommendations, the most important of which was to increase the top management interest in cultivating a profound organizational culture towards learning, development, mastering performance and improving the quality of its services to attract customers, and distinguish the organization from other organizations, in a way that reflects positively on developing its financial performance.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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 designSimulation or modeling
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

Citations16
Published2020
Admission routes1
Has abstractyes

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