Management Control Systems and International Entrepreneurship in Small, Young Firms from Resource-Based Theory, Contingence, and Effectuation Approach Perspectives
Bibliographic record
Abstract
This study analyses how entrepreneurs adapt or change international control management and organisation structures in response to their resources and capabilities and the context of the situation, from the resource-based theory (RBT) and contingency and effectuation framework approaches, taking the dynamism from knowledge-intensive services (KIS) into consideration. A multiple case study has been performed, based on semi-structured interviews with nine founders (entrepreneurs) of less-than 5-year-old international businesses who are actively involved in the management. All the interviews have been recorded, coded, and analysed through factsheets. The findings suggest that there is a relation between entrepreneurship and the characteristics of the entrepreneur; the character of owners or founders is key to embarking on this kind of business challenge. Furthermore, the age and nature of the manager—entrepreneur or non-entrepreneur—influence the business direction. This research analyses the role of the founder, owner, and/or management depending on the resources, capabilities, and uncertain contexts of the small, young firms. The age of the organisation’s and the degree of professionalism of the management’s impact on the management style and the use of control mechanisms are scarcely analysed yet, which could improve the relationships in MCS to achieve local and global control needs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| 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".