Developing new capability: middle managers’ role in corporate entrepreneurship
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the role of middle managers in the corporate entrepreneurship process that drives new capability development. Middle managers are highlighted as key entrepreneurial agents because of their special position in an organization. Design/methodology/approach The paper draws on existing capability development and corporate entrepreneurship literature and develops a conceptual model and research propositions that are illustrated through three examples from a Chinese private firm. Findings This paper contends the dual role of middle managers, both as change implementers to follow pre-set rules of an existing corporate entrepreneurship system and as change initiators to bring new rules to improve the existing system. Research limitations/implications The paper is conceptual in nature, advancing the understanding of middle managers’ role in corporate entrepreneurship. The paper provides directions for future empirical research. Practical implications The interactions between middle managers and other organizational agents are discussed in the propositions. This paper suggests the importance of empowering middle managers to facilitate changes in complex internal environments. Originality/value The paper provides a unique theoretical contribution by introducing the interface-based, multi-level conceptual model of corporate entrepreneurship toward new capability development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".