The Mediating Effect of Innovation on Entrepreneurial Competencies and Business Success in Malaysian SMEs
Bibliographic record
Abstract
The purpose of this paper is to explore the extent of entrepreneurial competencies and innovation on business success in SMEs in Malaysia. Specifically, this study tested the mediating role of product innovation and process innovation between the relationship of entrepreneurial competencies and business success. The statical sample population of this research includes 407 owner and manager involved in SMEs, both manufacturing and services & other sectors. For data collection, a standard questionnaire using seven-point Likert scale and 72 items was used to evaluate 12 entrepreneurial competencies (strategic competency, commitment competency, conceptual competency, opportunity competency, organising and leading competency, relationship competency, learning competency, personal competency, technical competency, familism competency, ethical competency & social responsibility competency), seven items for innovation (product & process innovation) and, ten items for business success (financial & non-financial). Four hypotheses were developed in this study. The SPSS version 21.0 and Structural equation model (SEM)-AMOS version 21.0 techniques were used. The findings indicate that there is a positive and significant relationship between the entrepreneurial competencies and innovation on business success in SMEs. Moreover, there is a positive and significant relationship between all dimension of competencies and business success. The product innovation and process innovation served as partial mediator between entrepreneurial competencies and business success. Limitations and implications for future studies are discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".