Technopreneurship-Based Competitiveness and Innovation at Small Business in Gorontalo City
Bibliographic record
Abstract
Business today has been globalized. This has made business even more competitive. Companies, regardless of their size, have to improve their competitiveness. Sustainable competitiveness is the core need for innovation. This study aims at exploring the correlation between IT-based innovation or technopreneurship and business competitiveness. This was a quantitative study with survey method. The respondents in this study were small business owners in handicraft and creative content production in Gorontalo city. The data were collected by online form and after three month collecting data, data were collected were 163 respondents. Product, process and organizational innovation and business competitiveness instruments use instruments from previous research. All instruments use a Likert scale with points 1 to 5 which indicate a scale of disagreement to agreement from the respondents. The data were analyzed using PLS-SEM. The Results show that information technology-based product innovation, IT based process innovation, and IT organizational innovation significantly and positively influence the growth of business competitiveness. Product innovation of business owners in Gorontalo city, Indonesia is actively producing new products. Also, innovation is not only limited to product innovation but also production process innovation, which uses information technology. Utilization of technopreneurship is significantly able to increase business competitiveness, especially for small businesses in Gorontalo city. Utilization of innovation in information technology assumed to strongly develop business competitiveness. The business competitiveness of small businesses in the high-tech field is influenced by products, processes and organizational innovation. SMEs must be able to create products, or product segments, and services that exceed the performance limitations of traditional products by utilizing everything possible through digital models.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".