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 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 | 0.001 |
| 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".