Explore the impact of collectivism on conflict management styles: a Turkish study
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the impact of collectivism on conflict management styles in Turkey and to help conflict management researchers and practitioners better understand conflict and conflict management in an international context. Design/methodology/approach Self‐administered questionnaires with the ROCI scale were used in this study. Data were collected by surveying 244 managerial employees from both public and private organizations. Factor analysis and regression analysis were then used to explore the relationships between conflict management styles and different aspects of collectivism. Differences in demographic factors were also discussed. Findings This study shows Turkish people are more likely to use collaborating style, instead of compromising or avoiding as expected from a collectivistic culture. Further, different aspects of collectivism have different effects on Turkish conflict management styles: the importance of competitive success leads to preferences for competing style; the value of working alone leads to less collaboration; the norms of subordination of personal needs to group interest are positively related to more collaborating and accommodating; and the beliefs of the effects of personal pursuit on group productivity are positively related to more compromising. Originality/value While Turkey has become more important in world markets, very few studies have been conducted to explore Turkish conflict management styles. This paper examines the ranking of preferences in conflict management methods in Turkey, as well as the impact of collectivism on different conflict management styles, which extends the understanding of cross‐cultural differences in conflict management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".