Notice bibliographique
Résumé
Purpose – The purpose of this paper is to investigate a second round of intensive green community entrepreneurship, a form of social entrepreneurship, by a set of environmental service organizations (ESOs) facing the loss of their largest revenue source (the ecoENERGY program), to see if it differed from responses to a similar funding cut five years earlier. In particular, the study compared green community entrepreneurship rates and types to those of the previous program (EnerGuide for Houses) cancellation and examined the perceived importance of various factors, including a social entrepreneurship training program offered by the national association. Design/methodology/approach – Interviews were held with executive directors who had led their organization through both periods of financial crisis. Information was collected on changes in revenue, staffing, residential energy evaluations conducted, service creation, and the perceived importance of organizational factors. The adaptation strategy undertaken by each ESO was classified as resilience, transition, or transformation focussed. Findings – First, green community entrepreneurship is accelerated when needs are heightened, such as when ESOs face funding cuts. Second, only some of the new services or activities launched were financially successful and remained viable over a five-year period. Third, green community entrepreneurship is an important initiative for ESOs to implement their adaptation strategy (resilient, transition, or transformation strategy). Fourth, a higher perceived difficulty of adaptation to funding cuts is associated with the launch of more new services by the ESO. Originality/value – The original contributions of the paper include the verification of repeated increases to the rate of entrepreneurship undertaken in response to sudden funding cuts, as compared to the rate of entrepreneurship during a stable funding period. This accelerated creation of new services can be directed to achieve various adaptation strategies from creating new services in the established area of energy expertise, to initiatives in new areas of sustainability services, such as water, food, or finance. The importance of collective innovation is highlighted with the use of both local and national networks.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».