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Record W3022300272 · doi:10.5539/ibr.v13n5p79

The Impact of Workplace Spirituality on Employee Performance: Evidence from Abu Dhabi University

2020· article· en· W3022300272 on OpenAlexvenueno aff
Ahmed Ebrahim Mousa

Bibliographic record

VenueInternational Business Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Spirituality and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsWorkplace spiritualityAbu dhabiSpiritualityPsychologySet (abstract data type)Variance (accounting)Sense of communityEmployee engagementPublic relationsSociologySocial psychologyApplied psychologyBusinessPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The aim of this paper is to argue that workplace spirituality may have an impact on enhancing the performance of employees. Hence, it focuses on the ways through which workplace spirituality can boost performance. The paper proposes a theoretical model regarding the links between five elements of workplace spirituality (team’s sense of community, alignment between organizational and individual values, sense of contribution to the community, sense of enjoyment at work and opportunities for the inner life) and employee performance. The theoretic model is then tested empirically using a spiritual modelling partial least squares analysis of a survey data set of 145 observations, collected from members of the Abu Dhabi University community. The presence of workplace spirituality in an organisational environment is considerably connected to employee performance. An interesting observation made from this study is that there is a significant variance in employee performance as a function of an employee position.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.249
GPT teacher head0.445
Teacher spread0.196 · 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 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

Citations23
Published2020
Admission routes1
Has abstractyes

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