A Study on the Hybrid Start-up Intention by Using the Model of Goal-Directed Behavior (MGB)
Bibliographic record
Abstract
Background/Objectives: The hybrid start-up is when a worker keeps his or her job and at the same time starts a business. This study is intended to analyze the impact of factors on the hybrid start-up desire and the hybrid start-up intention by applying the Model of Goal-directed Behavior (MGB).Methods/Statistical analysis: After establishing a research model that combines the hybrid start-up with the MGB, a survey was conducted on office workers for one month from December 2019. Of the collected samples, 101 copies suitable for the study were subjected to a statistical analysis such as evaluation of the measurement model and the structural model by using PLS-SEM with SmartPLS 3.0.Findings: The results of empirical analysis showed that attitude, positive anticipated emotion and negative anticipated emotion among the five factors presented in the MGB had a statistically positive effect on the hybrid start-up desire. However, subjective norm and perceived behavioral control didn’t have a statistically significant effect on the hybrid start-up desire. Like other models of goal-directed behavior, the hybrid start-up desire was found to be the most important in the hybrid start-up intention. And, it was also found that there was a mediation effect between the above three factors (attitude, positive anticipated emotion, negative anticipated emotion) and the intention of starting a business. In this study, it suggests that a start-up consulting should be made to take into account the objective aspects in the future, given that the hybrid start-up desire and intention are increased by subjective attitudes and anticipated emotions while not ready for start-up. And considering that most office workers are not ready to start their own businesses and want to consult on their own businesses, there is a need to expand the hybrid start-up consulting.Improvements/Applications: Future researches need to study the effectiveness of a start-up consulting through whether there is any change in the behavioral model before and after a start-up consulting. Research on hybrid start-ups will help improve government policies and systems that encourage office workers to start their own hybrid businesses.
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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 | 0.004 | 0.006 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".