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Enregistrement W1514994014

Diversification Strategy in Electric Utilities: Who Wins? Who Loses?

2008· article· en· W1514994014 sur OpenAlexaboutno aff
Karen A. Froelich, John Ramsey McLagan

Notice bibliographique

RevueAcademy of strategic management journal/Academy of Strategic Management journal · 2008
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueCooperative Studies and Economics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDiversification (marketing strategy)DeregulationElectric utilityIndustrial organizationBusinessProfit (economics)EconomicsPurchasingMarketingMarket economyMicroeconomicsEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

ABSTRACT Diversification is a prominent strategy for pursuing organizational growth, yet performance outcomes have been notoriously disappointing, especially for unrelated diversification via acquisition. While firms in most industries have thus constrained their diversification strategies, electric utility firms are increasingly pursuing diversification by purchasing businesses outside their fields of expertise to cope with bleak growth prospects and deregulation uncertainties. Considering that a utility company is generally a sole provider of essential service within a geographic territory, many stakeholders are justifiably concerned about increasing levels of electric utility diversification and potential performance outcomes. This exploratory study examines diversification within the electric utility industry in four upper-Midwestern states. All ten investor-owned utilities (IOUs) and five of the largest rural electric cooperatives (RECs) in each of the four states are included in the study. Annual report data are analyzed to identify each company's diversification strategy and performance outcomes. Results indicate that IOUs are more diversified than RECs, and intended strategies are not always realized. Reasons for the varied strategies and outcomes are explored, and the differential impact on specific stakeholder groups is examined. The study concludes with recommendations for diversification strategy in the electric utility industry, and suggestions for improving future research through data refinements. INTRODUCTION Utilities, particularly electric utilities, are presently operating in an environment characterized by an awkward combination of tight regulation and impending but uncertain change. The highly regulated electric service operations provide profit but restricted growth, while looming deregulation spawns defensive forays into new business arenas. Following industry calamities including the 2000-2001 California brownouts, the 2003 power blackouts in the Eastern U.S. and parts of Canada, and corporate scandals such as that of Enron, there is heightened concern about business practices and their potential impact on energy reliability and cost. Various stakeholders - regulators, community leaders, investors and consumers - are uneasy about corporate strategies, mergers and acquisitions, accounting practices, and possible bankruptcies. So while many utility companies appear to be supplying energy reliably and affordably, aggressive growth and increasing diversification is viewed warily by the diverse set of observers. Considering the generally poor track record of diversification in other industries, particularly unrelated diversification via acquisition that is prominent as utilities buy instant entry into new lines of business, skepticism about the long-term value of many diversification moves is well placed. Further, considering the role of utility companies in providing affordable essential services, questions arise about whether growth and profit should be primary obj ectives of these firms anyway. Is diversification a viable strategy for electric utility companies? Is the strategy broadly beneficial for stakeholders? Such basic questions warrant study in the electric utility industry. Accordingly, this exploratory study examines diversification in electric utilities. First we explain relevant features of the electric utility industry, and review diversification literature pertinent to this inquiry. Then we describe the study's methodology, including sample selection and data sources. Results of the study reveal that diversification is generally less extensive than expected, with publicly traded electric providers being more diversified than rural electric cooperatives. The varied performance outcomes are interpreted in light of current diversification theory and the utility industry context. The study concludes with recommendations for diversification strategy in the electric utility industry, and suggestions for advancing future research through data refinements. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,462
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,003
Science ouverte0,0020,001
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,097
Tête enseignante GPT0,275
Écart entre enseignants0,179 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2008
Routes d'admission1
Résumé présentoui

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