Notice bibliographique
Résumé
Purpose Regulatory and institutional changes, restructuring and/or privatization of the erstwhile vertically integrated electricity networks have been adopted by all Sub‐Saharan African (SSA) countries in their pursuit of rural and urban electrification, poverty reduction and economic growth. But advances with the reforms remain limited and the results are at best debatable. The purpose of this paper is to examine the reasons for the unsuccessful implementation of deregulation in Sub‐Sahara electricity markets. Design/methodology/approach The paper examines the experiences with deregulation of the electricity industries in developed and developing economies and surmises on the factors that have contributed to the success of reforms in some industrialized countries and identifies the factors that have contributed to the failure of reforms in SSA. The “evidence‐based economics” (EBE) methodology is used to analyze the existing models of regulation and their differences particularly as they are practiced in SSA and developed economies. A gap analysis is realized by highlighting the differences between best practices and the existing level of knowledge. Two case studies are analyzed and the collection of information is assessed in a way that is useful for the development and implementation of the most appropriate models of regulation for SSA. Findings The paper finds that the current trend to the regionalization of the electricity markets in SSA and the creation of regional power pools make possible the creation of a genuine regional electricity market which would provide new opportunities for the adoption and adaptation of more advanced models of regulation (2‐G and/or 3‐G) similar to the ones currently employed by some developed economies in Europe and North America. To do so, regulators in SSA need to adopt a more dynamic approach to regulation. Research limitations/implications Given the comparative approach of this paper, it is not possible to prove that SSA countries will succeed in their electricity reforms by adopting the 2‐G and 3‐G regulatory models. Nonetheless, if they do follow the dynamic approach to regulation, as suggested in the paper, their chances to succeed are much better. Practical implications The analysis of this paper has major implications for governments, regulators, shareholders, customers and employees of the electricity industry. A better understanding of the reasons for the failure of previous reforms and the identification of major advantages and disadvantages of the electricity markets in SSA provide new opportunities and challenges. The success of the application of the 3‐G model may increase the competitiveness of the electricity industry and productive capacity of Sub‐Saharan countries. Social implications Electricity is an essential input in any industrial and commercial process. Its availability reduces costs, enhances productivity and creates jobs in other sectors. The social well‐being of Sub‐Saharan countries would increase by adopting the 3‐G model suggested in this paper. Originality/value To the best of the author's knowledge, there are no recent studies dealing with the same issues particularly for Sub‐Sahara Africa. This paper fulfils the gap that exists in the literature.
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 | 0,000 | 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 ».