Female foundership in startups : a cross-cultural analysis between canadian and german women in new venture creation
Notice bibliographique
Résumé
An increased amount of female founders within a country has a positive impact on the local economy. The leading economic nations Canada and Germany have been expanding their support options for female founders in recent years. However, Canada has more female founders of startups in absolute numbers than Germany, even though the country is less populated. This paper aspires to compare both countries and to find out if and to what extent venture creation of female entrepreneurs differs in both countries. A specific focus is set on startups. The theoretical basis for this is the Cognitive Venture Creation Model by Mitchell et al. which is further built on. This approach allows for a holistic analysis as it considers the Affinity of a country towards venture creation as well as the extent to which founders display Arrangement, Willingness and Ability Scripts. To answer the research question, qualitative interviews were conducted with three female founders of startups from Canada and three female founders from Germany. \nIn general, both countries share similarities and differences in all areas. Canada seems to have a higher Affinity for venture creation in terms of inclusivity and institutional help. Nevertheless, venture creation as a career path is considered unattractive in both countries and female founders are still a rarity. The use of Arrangement Scripts shows similarities and differences. The most prominent is the lack of networking motivation in Germany. Regarding Willingness Scripts, it is clear that all female founders resemble each other in terms of unplanned founding, high altruistic aspirations, and emotional connectedness to their business. The triggers that lead to venture creation however slightly differ in both countries. The Ability Scripts show that female founders in Canada are loyal to the industry they come from and show more visionary thinking. German founders seem to be less confident about their own skills. Founders in both countries however align in their ability to learn from past experiences and feedback as well as staying creative. Thus this paper provides insights into the similarities and differences of female foundership in both countries and allows implications for the German female startup ecosystem.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,011 | 0,004 |
| Communication savante | 0,005 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».