Implementing regional sustainable development strategies: Exploring structure and outcomes in cross-sector collaborations
Notice bibliographique
Résumé
Social problems are often too large for any one organization to solve, so are increasingly addressed through multi-organizational, cross-sector collaborations which formulate and implement collaborative strategies. This PhD dissertation examines the implementation of collaborative regional sustainable development strategies (CRSDSs), which are bound by a local region and involve numerous partners, including businesses, universities, governments and NGOs. Formulating these strategies has become increasingly popular, so there is a real need for relevant theory. Generally, when multiple organizations formulate a CRSDS, a new interorganizational structure is created as part of the implementation. Structure can broadly be characterized in terms of partners, forms (e.g., committees, etc.) and processes (e.g., decision-making, monitoring, etc.). This study consists of two parts: a census of the structures being used for the 27 CRSDS in Canada; and in-depth case studies of four of these. This research contributes to both theory and practice. Theoretically, it brings the literature on collaborative strategic management together with the practical challenge of regional sustainable development, illustrating three possible levels at which implementation can occur: a regional partnership; issue-based joint projects involving a sub-set of partner organizations and, possibly, additional organizations from outside the partnership; and individual partner organizations. The research identifies four archetypal structures for implementation of CRSDSs: 1) Implementing through Joint Projects; 2) Implementing through Partner Organizations; 3) Implementing through a Focal Organization; and 4) Informal Implementation. The study also proposes five types of outcomes against which the implementation of CRSDSs can be evaluated plan, organizational, process, action and personal. Analysis of the case studies identifies seven organizational outcomes stemming from CRSDSs gained knowledge, built relationships, accessed marketing opportunities, accessed business opportunities, experienced increased resource demands, made progress toward sustainability goals, and made internal structural changes and explores the relationship between these and the four archetypes. Finally, a closer examination of plan outcomes for two substantive issues, greenhouse gas reductions and air quality improvements, suggests specific structural features which enable the achievement of these. In terms of practical contributions, the advantages, disadvantages and tradeoffs of the archetypes are discussed, so this research helps those organizations undertaking CRSDSs to consider their implementation options.
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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 | 0,000 | 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».