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Record W4395071625 · doi:10.3390/jrfm17050178

Sustaining Family Businesses through Business Incubation: An Africa-Focused Review

2024· article· en· W4395071625 on OpenAlexvenueno aff
Chux Gervase Iwu, Nobandla Malawu, Elona N Ndlovu, Tendai Makwara, Lucky Sibanda

Bibliographic record

VenueJournal of risk and financial management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsIncubationBusinessFamily businessMarketingPsychology

Abstract

fetched live from OpenAlex

The influence of business incubation systems on family businesses in African economies has not been thoroughly investigated despite the potential contribution of family businesses to Africa’s economic expansion and the attainment of development goals outlined in the Africa Development Agenda 2063 and the Sustainable Development Goals. Therefore, this study investigates the potential benefits that family businesses in Africa can derive from engaging in business incubation. This study utilised an integrative literature review methodology to investigate the research question. Twenty-three peer-reviewed articles were systematically selected from the Scopus, Web of Science, and Google Scholar databases using the following combination of phrases: “family business” and either “business incubation” or “business incubator”. The findings suggest ways to create a mutually beneficial relationship between family businesses and business incubators to improve long-term sustainability, promote collaboration, facilitate knowledge transfer, and foster an entrepreneurial ecosystem. It also recognises challenges, such as cultural alignment in family businesses. Business incubators in Africa can improve the sustainability of family businesses, such as during the succession, by offering support, resources, and guidance. The South African experience is a role model for the rest of the continent, in this regard. Future research should broaden the sources beyond the three databases utilised, including non-peer-reviewed sources such as grey literature, and extend the focus beyond developing economies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.005
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.240
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2024
Admission routes1
Has abstractyes

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