Intellectual Capital, Members' Participation and Cooperative Performance: The Mediating Role of Management Capabilities
Bibliographic record
Abstract
The purpose of this paper is to validate the mediating effect of management capability/capabilities (MC) on the relationships between intellectual capital (IC) and cooperative members’ participation (MP) and the cooperatives' financial and non-financial performance. The major aim is to examine the effect of MC in mediating the relationship between influential antecedents and cooperative performance - a topic that is relatively understudied in the literature. The study employs the survey technique to gather data from the respondents. Therefore, the questionnaire is designed to measure the indicators of the prescribed independent and dependent variables. The independent variables consist of MP and IC, which is further itemised into structural capital (SC), human capital (HC) and relational capital (RC), whilst the dependent variable consists of performance measured by financial and non-financial indicators. The questionnaires are distributed to 234 cooperatives that consist of palm oil smallholders cooperatives in Peninsular Malaysia. Among the targeted sample, 44% responded to the survey. The relationships between the characteristics of the Board of Directors and performance are validated through the partial least squares analysis. The findings indicate MC is a significant mediator in the relationships between IC and MP and cooperative performance. Furthermore, MC has been found to have a positive effect on the financial and non-financial performance of the cooperatives. IC and MP have indirect effects on cooperative performance. The ability to influence such a performance lies in the abilities of the management to optimise the benefits obtained from the SC, HC and RC and MP in the cooperative's activities.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".