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Record W3124718127

Entrepreneurial Growth Aspirations and Familiarity with Economic Development Organizations: Evidence from Canadian Firms

2018· article· en· W3124718127 on OpenAlexaffabout
Angelo Dossou-Yovo

Bibliographic record

VenueJagiellonian University Repository (Jagiellonian University) · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEntrepreneurshipBusinessProcess (computing)Business ecosystemMarketingResource (disambiguation)Knowledge managementFinance
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this paper is to investigate the relationship between the entrepreneurship ecosystem and the entrepreneur's willingness to grow. This study is particularly interested in exploring the relationship between entrepreneur's familiarity with the key economic development organizations in the entrepreneurship ecosystem and the willingness to grow. Several studies have investigated the growth process in small and medium sized enterprises (SMEs) since the case has been made that high growth SMEs contribute to economic growth through job creation. To date, these studies have identified multiple internal and external determinants including their effects on small business growth. There is evidence in the literature that characteristics of the entrepreneurs such as the willingness to grow and the entrepreneur's network are important factors in growth process. However, the relationship between growth process and the entrepreneur's networking behavior is yet to be fully understood. Drawing from the entrepreneurship ecosystem literature, the growth process literature and the resource dependence theory, this study uses the business confidence survey from 2011 to 2013, which targeted all businesses across all of Halifax Regional Municipality (HRM) in Nova Scotia, Canada, to explore the relationship between the entrepreneur willingness to grow and the propensity to network with key economic development organizations of the entrepreneurial ecosystem. The findings support the assumption that the proportion of businesses that are willing to grow (i.e. hire additional staff and enter new markets within the next twelve months) is higher for the group of businesses that are familiar with the key economic development organizations than for the group of businesses that are not familiar with them. However, the results are not homogeneous across all populations. Our findings also indicate that the higher the expectation to enter new markets over the next twelve months, the higher the odds to be familiar with the key economic development organizations. Our findings contribute to the literature around the association between networking and small business growth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.011
GPT teacher head0.162
Teacher spread0.151 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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