Intellectual capital and financial performance in social cooperative enterprises
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide empirical evidence of the relationship between intellectual capital (IC) and economic performance, with focus on social cooperative enterprises (SCEs) that work in non-profit sectors. Design/methodology/approach A survey was developed and administered in Italy. A final sample of 151 SCEs participated in the study. Data were collected on IC measures, social enterprise activities and economic and mission-based performance outcomes. Findings Two hypotheses that proposed a positive association between IC sub-components (i.e. human capital, structural capital and relational capital) and the economic and mission-based performance of SCEs were tested. Findings highlight that human capital contributes to explain economic performance which is positively affected by the presence of graduate employees and value added per employee. However, economic performance is negatively affected by the yearly training per employee. In addition, human and relational capital contribute to explain mission-based performance which is positively affected by yearly training, the value added per employee and the quality of relationships with customers. However, mission-based performance is negatively affected by the relationships’ quality with the reference territorial community. Therefore, relational capital would seem to affect only mission-based performance, and human capital influences both dimensions of corporate performance. Structural capital does not affect social cooperatives’ performance. Practical implications Some of the results in this study are particular to this research setting. It is therefore important for senior leaders of SCEs to take the results of general IC literature with a grain of salt. Whereas most of the academic literature generally supports the positive relationship of all IC sub-components (i.e. human, structural and relational capital) with performance outcomes, this is not the case in this particular study. Originality/value This is the first empirical study that has examined the linkages between IC sub-components and performance outcomes in SCEs in Italy.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".