Evaluation of Techno-Initiative Capital Support Program in Building Entrepreneurial Ecosystem within the Scope of Social Marketing
Bibliographic record
Abstract
The aim of this study it to investigate and find out the contributions of Techno-Initiative Capital Support (TICS) grant which was provided by the Ministry of Science, Industry and Technology for early-stage entrepreneurs to building entrepreneurial ecosystem in Turkey. Within this framework, voluntary behaviour change which the Ministry of Science, Industry and Technology tried to create in young entrepreneurs who received the grant was tackled through social marketing approach. TICS grant program was planned as a way of solution by the Ministry as the public authority in order to provide benefit to the society without expecting any material profit in return. Therefore, the grant program of the Ministry was evaluated within the scope of social marketing by the researchers since the program encouraged and mobilized early-stage young entrepreneurs to develop technology-based business ideas so that entrepreneurial ecosystem could be built in the country. In this study, purposive sampling technique was used and interviews were carried out with four entrepreneurs who received grant from the Ministry’s TICS program before and started their own companies in Gazi University Technopark. Qualitative research method was applied in the study, interviews were recorded and collected data were analysed by using a qualitative data analysis program, NVivo10. Entrepreneurs who received the grant stated that grants given to them within the scope of TICS program for their technology-based business ideas contributed to building entrepreneurial ecosystem in Turkey. Within this scope, it is seen that contributions were clustered under three themes as development of societal welfare, emergence of entrepreneurship awareness and power formation to create innovation. Furthermore, all the young entrepreneurs who obtained the grant stated that TICS caused change in their behaviours, thus they and the target audience of the program “developed technology-based business ideas” as an expected result of the program. Findings of the study confirm that in order to have an innovation-based economy, TICS reacted to the building an entrepreneurial ecosystem which is necessary for the benefit of the society with the driving force of the social marketing.
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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 | 0.006 | 0.007 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".