Assessing the Elements That Mediate the Impact of Innovation on Business Performance: Moderate Accreditation Ranking and Competitive Advantage
Bibliographic record
Abstract
Vocational higher education is higher education that prepares for employment with specific applied skills that are approximately equivalent to a bachelor's degree. Furthermore, vocational training is described as the provision of formal courses in higher education, such as technology colleges and diploma programs. The existence of vocational higher education is expected to reduce unemployment. The goal of the study is to investigate how competitive advantage and the accreditation standing of private Vocational Higher Education Institutions (VHEI) affect the effects of product and marketing innovation on company success. This research methodology uses quantitative methods, using the Structural Equation Model Smart PLS version 14.1 technique. The research population was 118 private VHEIs in West Java Province, Indonesia, and the respondents were 126 leaders and representatives of private VHEIs. According to the research, competitive advantage is significantly boosted by both product and marketing innovation. Product and marketing innovation, which is monitored by private VHEI certification ranking and mediated by competitive advantage, have a major beneficial impact on corporate success.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".