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Record W2940094691 · doi:10.5267/j.msl.2019.3.016

Linking employee engagement towards individual work performance through human resource management practice: From high potential employee’s perspectives

2019· article· en· W2940094691 on OpenAlexvenueno aff
Siti Amirah Othman, Nik Hasnaa Nik Mahmood

Bibliographic record

VenueManagement Science Letters · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsEmployee engagementHuman resource managementBusinessWork (physics)Work engagementHuman resourcesEmployee resource groupsKnowledge managementEmployee researchPsychologyPublic relationsComputer scienceManagementPolitical scienceEconomicsEngineering

Abstract

fetched live from OpenAlex

Most previous studies of employee engagement and performance have been rooted in either Social Cognitive Career Theory (SCCT) or the Social Exchange Theory (SET), giving often inconclusive outcomes. In fact, there are only a few researchers in social science focusing on the level of high potential employee's engagement towards individual work performance through human resource management practices. The purpose of this study is to investigate the relationship between employee engagement and individual work performance with mediation role of human resource management (HRM) practices for selected manufacturing organizations in Malaysia. Two hundred and fifty-two usable questionnaires are collected to empirically test the hypotheses using IBM SPSS software and Smart Partial Least Square (SmartPLS) version 3. The results suggest that high potential employee engagement positively and significantly influence on individuals' work performance. Additionally, human resource management practices play significant role in mediating the relationship between employee engagement and individual work performance among high potential employees. Therefore, these results should provide insight towards managing high potential employees, especially in the manufacturing sector.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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; both teacher heads agree on what is shown here.

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

Citations31
Published2019
Admission routes1
Has abstractyes

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