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Record W3204933391 · doi:10.33423/jabe.v22i3.2860

Managers’ Personality Traits and Employee Job Performance in the Telecommunication Industry

2020· article· en· W3204933391 on OpenAlexvenueno aff
Joseph Kwadwo Tuffour, Irene Ockrah-Anyim

Bibliographic record

VenueJournal of Applied Business and Economics · 2020
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBig Five personality traitsPersonalityExtraversion and introversionTraitBusinessJob performancePsychologyMarketingSocial psychologyJob satisfactionComputer science

Abstract

fetched live from OpenAlex

The study examines the effect of managers’ personality traits on employee job performance in the telecommunication industry in Ghana. A cross-sectional survey design was adopted using structured questionnaires to collect primary data from a sample of 350 employees and managers in four selected telecommunication firms. Correlation and regression techniques are used. The study discovered that the dominant personality trait of leaders’ in the telecommunication industry in Ghana is open-minded with extraversion. Furthermore, there is a fairly strong significant positive relationship between each of the five leaders’ personality traits and employee job performance. After controlling for demographic characteristics, it was revealed from the analysis that the personality traits of leaders have significant effects on employee job performance. Years of experience and age collectively were very significant to job performance. The study recommends among other things that formalized leadership training programs should be instituted in the telecommunication industry in Ghana to train leaders and employees on leaders’ personality traits and its effect on employee 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.230

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 studies0.0000.000
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 head0.062
GPT teacher head0.281
Teacher spread0.220 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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