Self-concept orientation and organizational identification: a mediated relationship
Bibliographic record
Abstract
Purpose The purpose of this paper is to test a mediated model of the relationship between self-concept orientation (individualist and collectivist) and organizational identification (OrgID, Cooper and Thatcher, 2010), with proposed mediators including the need for organizational identification (nOID, Glynn, 1998) as well as self-presentation concerns of social adjustment (SA) and value expression (VE, Highhouse et al., 2007). Design/methodology/approach Data were collected from 509 participants in seven countries. Direct and mediation effects were tested using structural equation modeling (AMOS 25.0). Findings Individualist self-concept orientation was positively related to VE and collectivist self-concept orientation was positively related to nOID, VE and SA. VE mediated the relationship between both self-concept orientations and OrgID. In addition, nOID mediated the relationship for collectivist self-concept orientation. Practical implications This study identifies underlying psychological needs as mediators of the relationship of self-concept orientation to OrgID. Understanding these linkages enables employers to develop practices that resonate with the self-concept orientations and associated psychological needs of their employees, thereby enhancing OrgID. Originality/value This study provides a significant contribution to the OrgID literature by proposing and testing for relationships between self-concept orientations and OrgID as mediated by underlying psychological needs. The results provide support for the mediated model as well as many of Cooper and Thatcher’s (2010) theoretical propositions, with notable exceptions.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".