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Record W1514994014

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

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

Bibliographic record

VenueAcademy of strategic management journal/Academy of Strategic Management journal · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsDiversification (marketing strategy)DeregulationElectric utilityIndustrial organizationBusinessProfit (economics)EconomicsPurchasingMarketingMarket economyMicroeconomicsEngineering
DOInot available

Abstract

fetched live from 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. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.275
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2008
Admission routes1
Has abstractyes

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