Organizational Trust and Social Exchange: What If Taking Good Care of Employees Were Profitable?
Bibliographic record
Abstract
Several studies show a decrease in employees’ trust toward their organization; in parallel, organizations want to develop a long-term employment relationship to remain competitive in a context of employee shortage (Robinson and Rousseau, 1994). How can organizations develop a high level of organizational trust among their employees? In this article, we propose to integrate organizational trust - defined as “the willingness of the employee to be vulnerable to the actions of the organization” (Mayer, Davis and Schoorman, 1995) - into a chain of relationships between HRM practices, perceived organizational support (POS) and two attitudes that reflect a long-term link with the organization: affective commitment and intention to quit. Our hypotheses suggest that organizational trust will partially mediate the link between POS and employees’ attitudes (i.e., affective commitment and intention to quit). As many past studies found a direct link between POS, affective commitment and intention to quit (Eisenberger et al., 1986, 1997, 2001; Rhoades, Eisenberger and Armeli, 2001; Shore and Tetrick, 1991; Shore and Wayne, 1993; Wayne, Shore and Liden, 1997), we expect that the mediation will be partial. A direct and negative link is also expected between affective commitment and intention to quit. Finally, the chain of relationships identifies two examples of HRM practices - skills development practices and communication practices - as potential antecedents of organizational trust (Lamsa and Pucetaite, 2006) and POS (Allen, Shore and Griffeth, 2003). HRM practices generate a perception of support favourable to trust, because those practices illustrate the attention the organization gives to employees. The chain of relationships is tested with a three-wave longitudinal design that is more appropriate for the study of causal relations between variables than a cross-sectional design. We used AMOS 4.01 software to test two alternative models: the first model does not include organizational trust in path analyses; the second model includes this variable in the structural equation model. Results show that the second model has better fit indexes than the first model (Chi 2 = 170.79; RMSEA = 0.05; CFI = 0.97; GFI = 0.93). We validate that organizational trust partially mediates the relationship between POS and affective commitment, and fully mediates the relationship between POS and intention to quit. The last part of the article aims to discuss results. We focus the discussion on three major contributions: (1) the integration into one unique model of several research fields that were tested only separately in the past; (2) the mediating role of trust in this chain of relationships; (3) the use of a longitudinal design that provides guaranties about the direction of tested relationships. Despite these strengths, our research has several limitations; specifically, we did not control risks of common variance for the answers given in the same questionnaire.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".