Notice bibliographique
Résumé
The creation of new firms is a tremendously important phenomenon. Each year hundreds of millions of people are engaged in business start-up efforts (Reynolds et al., 2005). A careful review of 87 analyses in 57 recent studies confirms earlier claims that new firms play very significant roles in employment creation, productivity growth and innovations (van Praag & Versloot, 2007). Yet, new venture creation is both under theorized and empirically under studied. Due to its emergent, elusive and nebulous nature and the fact that firms not yet in existence do not appear in any sampling frames, researchers have largely been confined to exploring the phenomenon of new venture creation via survivor-biased samples and retrospective case studies. These conditions are obvious impediments to credible, scholarly knowledge development. This is why the occurrence of an approach to the systematic, longitudinal study of representative samples of on-going new venture start-up processes is potentially an important breakthrough. The Panel Study of Entrepreneurial Dynamics (PSED) (Gartner, Shaver, Carter & Reynolds, 2004b; Reynolds, 2007) was the first full scale realization of such a study. It has established a new empirical approach that – with local variations – has been employed by several large scale parallel or subsequent studies in a range of countries including Australia, Canada, Latvia, the Netherlands, Norway, Sweden, and the US. The basic design of the research can be summarized as follows (Reynolds, in press): (an approximation of) a probability sample of on-going, early-stage business start-ups is obtained through screening phone interviews with a very large number (typically tens of thousands) of adult members of households, selected through random digit dialing. Answers to a screening questionnaire determine whether respondents are ‘nascent entrepreneurs’ (NE) or not; i.e., whether they are involved in on-going but not yet operational business start-up efforts in which they are going to be (part) owners. Qualified NEs – typically a single digit percentage – are directed to a comprehensive (20-60 minutes) interview about select aspects of the emerging venture, its owners, and their actions. Eligible cases are re-interviewed at regular intervals; typically every 6-12 months over 2 to 5 years in order to follow the process and assess outcomes. Due to their comprehensiveness (often comprising several hundred variables and multiple waves of data) it is not really possible within the space given here to provide an adequate description of contents and theoretical underpinnings of the studies. Although tables 2-4 (below) summarize some such information readers are referred to the PSED and PSED II handbooks and website, which provide comprehensive information of this kind for the publicly available US data sets (Gartner et al., 2004b; Reynolds & Curtin, 2009; www.psed.isr.umich.edu). The purpose of this review is twofold. First, we aim to assess what has been learnt so far on substantive matters from the published research using this type of empirical data. In this, we will focus on micro level issues where this line of research has made unique contributions and largely leave aside the macro issue of relative prevalence of NEs across time and space, which is equally or better dealt with through the Global Entrepreneurship Monitor (GEM) research (Bosma & Harding, 2007; Reynolds et al., 2005). Second, based on the strengths and weaknesses revealed by the research undertaken we aim to develop a set of suggestions regarding how the approach can be further developed and refined to make a greater contribution in the future.
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 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 | 0,004 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
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.
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 ».