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Record W2383253476

Management of Relationship Conflict:The Moderating Effects of Team Efficacy and Team Emotional Intelligence

2015· article· en· W2383253476 on OpenAlex
Wei Xu-hu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of systems management · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyModerationTeam effectivenessEmotional intelligenceSocial psychologyContingency theoryContingencyConflict managementPsychological safetyTeam compositionMeaning (existential)Applied psychologyKnowledge managementComputer science
DOInot available

Abstract

fetched live from OpenAlex

Relationship conflict is one of the inevitable phenomenon of the interactive processes in work teams,meaning that it is important to pay more attention to relationship conflict management.The present study integrates contingency theory,social cognitive theories and emotion theories to examine the effects of relationship conflict,team efficacy and team emotional intelligence on team performance.The results based on 68 teams show that relationship conflict is negatively related to team performance,whereas team efficacy and team emotional intelligence significantly improves team performance.Furthermore,team efficacy plays as an important moderator between relationship conflict and team performance,which means relationship conflict has a strong negative impact on team performance in low efficacy teams and the negative effect disappears in high efficacy teams.However,the moderating effect of team emotional intelligence on the relationship between relationship conflict and performance is not significant.

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.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.057
GPT teacher head0.318
Teacher spread0.261 · 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