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Record W1485718541 · doi:10.1111/jems.12033

Incentives, Capital Budgeting, and Organizational Structure

2013· article· en· W1485718541 on OpenAlexaff
Adolfo de Motta, Jaime Ortega

Bibliographic record

VenueJournal of Economics & Management Strategy · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsMcGill University
FundersMinisterio de Ciencia e InnovaciónComunidad de Madrid
KeywordsIncentiveDiversification (marketing strategy)BusinessIndustrial organizationCompetition (biology)Capital callOrganizational structureMicroeconomicsEconomicsMarketingIndividual capitalFinancial capitalManagement

Abstract

fetched live from OpenAlex

Divisional managers compete for financial resources in what is often referred to as an internal capital market. They also have a common interest in maximizing corporate profits, as this determines the resources available to the firm as a whole. Both goals are powerful motivators but can at times conflict: while the amount of resources available to the firm depends on corporate performance, divisional funding depends upon the division's performance relative to the rest. We propose a model in which organizational form is endogenous, divisions compete for corporate resources, and managers have implicit incentives. We show that organizational design can help companies influence their divisional managers' potentially conflicting goals. Our analysis relates the firm's organizational structure to the source of incentives (external vs. internal), the nature of the incentives (competition vs. cooperation), the level of corporate diversification, the development of the capital market, and to industry and firm characteristics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.171
Teacher spread0.164 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2013
Admission routes1
Has abstractyes

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