Managerial Factors and Management Conflict in Venture Capital Financing in Malaysia
Bibliographic record
Abstract
The warm venture cooperation built between venture capitalists and entrepreneurs may still be interrupted by the management's conflicts occurred due to various managerial factors. As a result, this study investigates the management conflict in venture capital investments. A cross-sectional study of questionnaire survey research design was conducted in this respect. Questionnaire data was generated from 35 Malaysian venture capital companies located in Kuala Lumpur and Selangor. The questionnaires were distributed through the mailing procedure. Overall, the findings indicate that the managerial factors significantly influence the management conflict. Further results show that managerial factors which consist of Deal Origination and Screening (DOS), Evaluating Venture Proposal (EVP), Contracting and Deal Structuring (CDS), Monitoring and Post Investment Activities (MPI) and Risk Management (RM) significantly influence the formation of management conflict in venture cooperation. Based on the findings, it is inferred that managerial factors does influence the occurrence of management conflict in venture cooperation. Thus, the study recommends that Malaysian venture capitalists give consideration to the managerial factors in reducing or curbing the possibility of conflict to occur.
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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 | 0.002 | 0.009 |
| 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) | 0.001 | 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".