Capital budgeting decision making, national culture and bounded rationality. A regional comparative study of Canadian and Mexican entrepreneurs
Bibliographic record
Abstract
This study is located in the rather young area of international entrepreneurship research. Despite the vast literature in Western countries exploring the nexuses on entrepreneurship-national culture and entrepreneurship-decision making, we know very little about how bounded rationality and national culture affect the entrepreneur’s capital budgeting decision making in emerging economies. Past research on small business and capital budgeting shows a predominance of quantitative approaches to identify which capital budgeting techniques were used and why they are used. Through qualitative interviews with 20 Mexican and 20 Canadian participants, this study looks at how Mexican and Canadian entrepreneurs approach capital budgeting decisions in small businesses in the food sector industry. This study confirms that capital budgeting decisions are taken under conditions of bounded rationality, but also suggests that context affects how bounded rationality is used. For instance, Mexican entrepreneurs rely more on “gut feeling”, while Canadian entrepreneurs tend to combine intuition with business plans. The differences observed for both national samples are further discussed through a Hofstedian and a GLOBE lens. I argue that national culture affects how capital budgeting decisions are made throughout the decision making process (planning, identifying, evaluating, selecting and authorizing) and also that national culture plays a role for who influences the entrepreneurs’ decisions. By contextualizing capital budgeting decisions and using a constructivist logic of discovery, this study provides insights into entrepreneurs’ capital budgeting decision making in small businesses and suggests that national cultural differences play a valuable part in understanding this important aspect of entrepreneurial activity. This thesis also adds to our understanding of entrepreneurs in emerging economies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".