The implication of knowledge management in innovation process in Small and medium-size enterprises
Bibliographic record
Abstract
Purpose. The paper presents results of study which is focused on importance of knowledge in innovation process. Innovation represents a complicated mechanism. Innovation is important point for most of companies which want to be able to compete. Methodology. The paper is based on primary research due questionnaire research. The research was hold in the fourth quarter of the year 2013 in the Czech Republic and the results were analysed during the year 2014. The study involved two phases. First, it was secondary research based on relevant scientific literature from national and international sources. Second, was held a primary research. The research was attended by 321 respondents. Various studies prove that there is a relationship between education and successful innovation. It was established that people with higher education are more creative in respect of new innovations. However, it is also important that the innovations are successful. The questionnaire survey was evaluated by statistical methods. Various statistical tests have been used within the statistical analysis. The tests were performed by the statistical program IBM SPS Statistics 20. Results. Various studies prove that there is a relationship between education and successful innovation. It was established that people with higher education are more creative in respect of new innovations. However, it is also important that the innovations are successful. According to the results of the research in this study it is possible to see a direct relationship between theoretical knowledge management and successful innovation process. People who have theoretical knowledge in innovation management are not only able to generate innovations but they are also able to make the innovations profitable and successful. The theoretical contribution. The main aim of this paper is to set up complex of methodological steps to provide successful innovation process. This research also extends theoretical background of knowledge management. Practical implications . The primary research was held in the Czech small and medium companies and result are primarily intended for Czech companies. On the other hand results could be a good inspiration for companies from other countries. For better implication to abroad companies is appropriate to make the similar results in other countries. Due defined methodological steps, managers could make more successful the innovation process in their companies. Keywords: knowledge, knowledge management, small and medium enterprises, education Paper type : Research paper
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".