Why Are There So Few Schumpeterian Entrepreneurs from China? Understanding the Factors That Influence Entrepreneurial Opportunity Evaluation from a Comparative Culture Perspective
Bibliographic record
Abstract
Opportunity evaluation is a very important part of entrepreneurial activity; however, entrepreneurs’ individual differences in evaluating opportunities have been neglected in prior research. To address this gap, we apply institutional theory and stereotype threat theory to explain how some institutional factors differentiate entrepreneurs’ opportunity evaluation process. More specifically, we explore how external institutional factors, such as political and social factors, along with personal institutional factors, such as family influences, affect the opportunity evaluation of entrepreneurs under various cultural backgrounds, specifically China and the United States. The Schumpeterian entrepreneur, in which radical innovation and the desire to significantly upend market equilibria, frames our discussion. This paper contributes to the theoretical understanding of the factors influencing entrepreneurial opportunity evaluation from a comparative culture perspective and to the comparative international entrepreneurship field by building a comparative evaluation framework that summarizes institutional factors influencing Chinese and American entrepreneurs’ opportunity evaluation. We propose that policy, social value, and belief as well as family will have significant impacts on entrepreneurs’opportunity evaluation. We further propose several cultural constructs such as individualism vs. collectivism, uncertainty avoidance, and Confucian work dynamism will moderate the relationship with institutional factors in influencing an entrepreneur’s opportunity evaluation process. We discuss our implications with attention given to how our comparative evaluation framework provides insights into why China and the United States differ in terms of developing Schumpeterian entrepreneurs. We then discuss the framework’s limitations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".