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Record W2152296210 · doi:10.1017/jmo.2015.37

Effects of learning orientation and global mindset on virtual team members’ willingness to cooperate in: The mediating role of self-efficacy

2015· article· en· W2152296210 on OpenAlexaff
Thi Bich Hanh Tran, Chang Hoon Oh, Suk Bong Choi

Bibliographic record

VenueJournal of Management & Organization · 2015
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMindsetPsychologySample (material)Knowledge managementOrientation (vector space)Virtual teamTest (biology)Social psychologyBusinessComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This study investigates the effects of learning orientation and global mindset on virtual team member’s willingness to cooperate. It also explores the mediating role of self-efficacy in these relationships. To test the hypothesized relationships, the study used a sample of 224 employees from five global companies in South Korea. The results show that while global mindset is directly and positively related to virtual team members’ willingness to cooperate, learning orientation is not. Self-efficacy serves as a mediator in these relationships. The study concludes with a discussion of the theoretical contributions and managerial implications for improving virtual team members’ cooperative behavior.

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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.260
Teacher spread0.254 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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