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Record W2535754356 · doi:10.5539/ibr.v9n11p222

Impact of Moral & Material Incentives on Employee’s Performance; An Empirical Study in Private Hospitals at Capital Amman

2016· article· en· W2535754356 on OpenAlexvenueno aff
Hasan Salih Suliman Al-Qudah

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveBusinessEmpirical researchDescriptive statisticsCapital (architecture)Descriptive researchActuarial scienceMarketingEconomicsStatisticsGeography

Abstract

fetched live from OpenAlex

<p class="1main-text">The aim of this study is to identify the impact of moral & material incentives on employee’s performance as it will focus on some private hospitals operating at Amman capital of Jordan. The research use empirical analysis and distributed set of a questionnaire with a total of 291 out of which 20 were rejected due to various reasons including incompletely questionnaire, thus, 271 questionnaires was completed and shortlisted for statistical analysis , the study applied descriptive analytical method, and reached to following result, there is no difference application on moral and material incentives for employees to improve their performance when it comes to demographic variables like gender, age, educational qualifications. The study recommended a number of recommendations that private hospital has to develop policies and strategies to increase effectiveness incentives in addition to this, also the study recommend that the private hospitals in Amman should use incentives systems to meet with the needs of all employees.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.112
GPT teacher head0.466
Teacher spread0.354 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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