Do Innovative Work Behavior Mediate the Contribution of Spiritual and Social Capital to Small and Medium Enterprise Performance
Bibliographic record
Abstract
The essential element influencing the performance of microbusinesses is the existence of spiritual and social capital.Spiritual capital significantly contributes to attaining targeted profits and fostering innovative behavior.On the other hand, robust social capital strengthens an entrepreneur's ability to detect emerging trends promptly.This research explains the contribution of spiritual and social capital to business performance, emphasizing the importance of innovative behavior, especially green product innovation, in improving SME performance.This research is based on the debate on research results regarding impact of spiritual and social capital to the performance of micro-enterprises.Research indicates that intellectual capital and its components can influence performance either directly or indirectly.Innovative work behavior serves as one of the mediating factors in this relationship.This study employed a questionnairebased survey design with data collected through proportional random sampling.The hypothesis was tested using Partial Least Squares (PLS) analysis on data obtained from 205 microenterprises.The findings of this study indicate that spiritual and social capital significantly influence innovative work behavior.While spiritual capital does not contribute to the business performance of microbusinesses, social capital provides a significant contribution.In addition, green product innovations carried out by entrepreneurs have significant contribution to the performance of micro-businesses.Therefore, this study supports the statement that an entrepreneur needs to have intellectual resources (spiritual and social capital) before starting a business.This research also highlights the importance of adopting innovative work practices, particularly in relation to the concepts of "green economy" and "green growth."
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".