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Record W3208723986 · doi:10.1016/j.ijans.2021.100377

The drive process model of entrepreneurship: A grounded theory of nurses’ perception of entrepreneurship in nursing

2021· article· en· W3208723986 on OpenAlexaff
Nneka Ubochi, Joseph Osuji, Vincent N Ubochi, Ngozi P. Ogbonnaya, Agnes N. Anarado, Peace Iheanacho

Bibliographic record

VenueInternational Journal of Africa Nursing Sciences · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsMount Royal University
Fundersnot available
KeywordsEntrepreneurshipGrounded theoryThematic analysisNursingPsychologyCreativityExploitQualitative researchSociologyPublic relationsMedicineBusinessSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Entrepreneurship is a concept involving developing and managing a business venture in order to gain profit by taking several risks in the cooperate world. Nurses enjoy the privilege as the singular group of professionals with the most far-reaching presence at all levels of the health care system. However, the nurse is yet to exploit the opportunity created by the lack in the health system. Nurses need to get the necessary drive to exploit the entrepreneurship opportunities available to them. The purpose of this study is to explore the perception of entrepreneurship among nurses and develop a mid-range theory that explains the meaning and practices of entrepreneurship among nurses. The constructivist grounded theory design was used. In-depth Interview was conducted on 20 purposively selected participants using the zig-zag method of data collection until data saturation. Open to axial coding paradigm was used for thematic analysis by the researchers and co-coders. Finding was returned to participants and literature for verification. Findings were captured in six themes (a). Nursing entrepreneurship is creating innovation in nursing driven by education and expertise, passion for creativity and positive creative climate (b) : Nursing entrepreneurship is philanthropy in nursing through innovation creation motivated by passion for caring, need for recognition and the desire to leave a legacy, (c) Nursing entrepreneurship is innovation creation in nursing driven by professionalizing in Nursing motivated by specialized training and retraining, practicing with autonomy, research and ethical code, (d) Nursing entrepreneurship is creating innovation in nursing for social gratification driven by the need for leadership, financial independence, status enhancement and time flexibility, (e) Nursing entrepreneurship is innovation creation to fulfill the need for business savvy driven by opportunity identification, health risk management and health marketing, (f) Nursing entrepreneurship is innovation creation in nursing for socio economic transformation driven by the desire for job creation and wealth generation. Drive for innovation creation emerged as the core category and based on the relationship with other themes, the drive process model of entrepreneurship in nursing is proposed. Nursing entrepreneurship is perceived as innovation creation in nursing driven by the need for professionalism, philanthropy, social gratification, business savvy, and economic transformation, for optimal positive impact and better client outcomes. Utilizing this model will lead to positive transformations in health care practice, and engineer a positive future for the nursing profession, and the health care system globally especially in sub-Saharan Africa where the health care indices is alarming.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.011
Scholarly communication0.0050.005
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.050
GPT teacher head0.395
Teacher spread0.345 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations20
Published2021
Admission routes1
Has abstractyes

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