Individuals’ Assessment of Corporate Social Performance, Person-Organization Values and Goals Fit, Job Satisfaction and Turnover Intentions
Bibliographic record
Abstract
Recent research in the domain of corporate social responsibility (CSR) has underlined the importance of moving away from an institutional perspective of CSR towards research at the micro-level. Such calls have insisted on the necessity of a developing a deeper, and more nuanced understanding of its impacts and mechanisms at the individual level. This paper addresses this issue by focusing on the nexus between how employees judge their companies’ actual CSR performance and how that judgement can affect individual, micro-level outcomes such as job satisfaction and turnover intentions. We study this by a consideration of how perceived fit between employees and their organization mediates the relationship between perceived corporate social performance (CSP) on the one hand, and job satisfaction and turnover intentions on the other. While there is a notion, commonly embraced in the literature, that corporate social performance can have beneficial effects on individual employee outcomes, there have not been many empirical studies looking into the mechanisms by which this occurs. Through a survey of 317 young employees from differing company sizes and sectors in Europe and Asia, we find that positive assessment of CSP does not have a direct influence on job satisfaction and turnover intention, but is mediated by person-organization fit. The latter, in turn, has a positive effect on job satisfaction and reduced turnover intention. The implications of these findings are that the achievement of efficient and effective performance in social and environmental terms reinforces the perception of employees that their values fit with those of the organization. This process then creates value in terms of increased job satisfaction and reduced employee turnover intentions. We note also that simply improving CSP objectively, without involving and raising awareness among employees, will not necessarily lead to improved perceptions of how the employee fits within the organization and the potential positive knock-on employee outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".