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Record W3205877229 · doi:10.52633/jemi.v1i1.41

Determining the Role of Conflict Management Strategies on Organizational Performance: A Mediating Role of Employees' Job Satisfaction

2019· article· en· W3205877229 on OpenAlexaff
Syeda Azra Batool, Fiza Hayat

Bibliographic record

VenueJournal of Entrepreneurship Management and Innovation · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsCasualJob satisfactionConflict managementPsychologyManagement stylesJob performanceApplied psychologyKnowledge managementBusinessSocial psychologyPublic relationsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Conflict Management is one of the essential elements in casual and professional life for enhancing an individual's performance and to bring better results in intense organizational pressures. Although studies which explore the effect of these on job satisfaction are very few and therefore there is a need to check the impact of these form of strategies on job satisfaction. Although according to the studies each and every style of conflict management does not relate to job satisfaction and therefore the major need to associate this style with organizational performance. Thus, a quantitative study has been conducted in the commercial banking sector of Pakistan through a closed-ended questionnaire. Analysis was carried out through the help of statistical data analysis software SMART-PLS and the results of the study indicated that each and every style of conflict management does not result in job satisfaction, nor in the betterment of organizational performance. The results imply that a more rigorous approach and innovative strategies in conflict management should be devised and followed by the managers to address the conflicting issues.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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