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Record W2802319925 · doi:10.1108/ebr-08-2016-0104

Developing new capability: middle managers’ role in corporate entrepreneurship

2018· article· en· W2802319925 on OpenAlexaff
Yuanyuan Wu, Zhenzhong Ma, Milo Shaoqing Wang

Bibliographic record

VenueEuropean Business Review · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of AlbertaUniversity of WindsorLakehead University
Fundersnot available
KeywordsEntrepreneurshipMiddle managementOriginalityBusinessProcess (computing)Conceptual modelConceptual frameworkKnowledge managementIntrapreneurshipDual (grammatical number)Empirical researchValue (mathematics)MarketingProcess managementSociologyComputer scienceQualitative research

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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.

Opus teacher head0.088
GPT teacher head0.251
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

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