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Enregistrement W186352918

Training women to win: women and enterprise development in the UK

2009· article· en· W186352918 sur OpenAlexaboutno aff
Spinder Dhaliwal

Notice bibliographique

RevueView · 2009
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueEntrepreneurship Studies and Influences
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDynamismEntrepreneurshipSustainabilityBusinessWomen entrepreneursPublic relationsMarketingEconomic growthSmall businessPolitical scienceEconomicsFinance
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

ABSTRACT Within the SME sector, women are responsible for about one third of all start-up businesses in the UK. They are vital to the economy and future growth of the SME sector. Their dynamism and enterprise enriches the sector. Despite the positive contribution and untapped potential of women in business, it appears that women may need help in seeing themselves as entrepreneurs and as leaders, and in enhancing their personal skills and the viability, growth potential, and sustainability of their businesses. The key question is: Do they get the help they need? If not, why not, and what, if anything, needs to change? This article sets out to look at these issues. It seeks to identify current good practice in terms of available support and to produce and pilot recommendations that will improve current business support and training provision for women. For academics, this article adds to the growing literature on female entrepreneurship. For business support professionals and policy makers, this article provides recommendations for use when supporting future initiatives and produces recommendations highlighting the possible direction of future provision. INTRODUCTION The number of women business owners is growing around the world; 1 in 11 women worldwide is now an entrepreneur (GEM, 2004). In the UK, women comprise 27% of selfemployed and own-account workers, compared with 34% in Austria, 28.7% in Belgium, 33.4% in Canada, 32.3% in Finland, and 39.8% in Portugal. In the U.S., around 30% of businesses are wholly or majority owned by women; in the UK, this number is 14%. Men are twice as likely to be entrepreneurs in the UK as women are. The British government has expressed a desire to have more women in business and has set targets to achieve this. The 2007 Global Entrepreneurship Monitor showed a growth in total entrepreneurial activity in the UK; however, women are still around half as likely to be involved in business start-up activity as men. In 2005, 3.74% of the female adult population were involved in independent start-up activity, compared to 6.17% of the male population (Minniti, Bygrave, & Autio, 2006). This article sets out to investigate training and business support provision for women, to see whether it has been effective, and to assess the impact of targeted women's enterprise support. This is based on an original report, Training Women to Win (Dhaliwal, Combly, Cundell, Lock, & Thomas, 2006), at the University of Surrey. The findings here will be applicable to women business owners in other countries, developing and developed, who can draw on the lessons and experiences of UK women in business. The structure of the paper is straightforward. The next section is a literature review drawing out the main issues pertinent to this article, followed by the methodology, report on findings, and conclusions and recommendations. LITERATURE REVIEW Early studies on female entrepreneurs concentrated on descriptive accounts of the characteristics and motivations of women in business and their experiences of business ownership, particularly at start up. More sophisticated studies include themes on gender differences regarding management of the business, particularly with regard to finance, business networks, and performance (Carter & Anderson, 2001; Carter, Anderson, & Shaw, 2001). Several studies have compared the performance of men and women in business. Findings for the Caribbean (Finnegan, 2003) and for Asian women (Dhaliwal, 1998) found that women are less likely to be members of associations than men. There are some issues that affect many women setting up their own businesses in specific ways, and some women find it difficult to achieve their full business potential in an environment that has been designed for a different model of entrepreneur (Carter & Shaw, 2006). Mirchandani (1999) challenges these comparative studies, as they do not illuminate how and why entrepreneurship came to be defined and understood vis-avis the behavior of only men. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil0,080

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0110,007
Communication savante0,0100,006
Science ouverte0,0010,009
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,0170,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,029
Tête enseignante GPT0,244
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2009
Routes d'admission1
Résumé présentoui

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