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Record W2514562221

Diversification by the largest US contractors

2011· article· en· W2514562221 on OpenAlexvenueno aff
KimHyung-Jin, F ReinschmidtKenneth

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsDiversification (marketing strategy)BusinessRevenueIndustrial organizationPortfolioEmpirical researchFinanceMarketing
DOInot available

Abstract

fetched live from OpenAlex

Market diversification may be a corporate strategy for risk management, for firm growth, or both. The purpose of diversification, either reduction of market risks or growth of revenues and profits, affects a contractor's selection of market sectors to enter. Diversification into different sectors affects the contractor's portfolio of business and its financial perform- ance. The current study performs an empirical analysis of contractors' diversification using US construction industry data published by Engineering News-Record (ENR). The study identifies (1) cross-correlations between market sectors; (2) the possible reasons for diversification by contractors; (3) diversification patterns by the contractors; and (4) differences in per- formance among the contractors classified by diversification strategy. These empirical findings may be of assistance to con- tractors in the development of their own diversification strategies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.054
GPT teacher head0.244
Teacher spread0.190 · 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 designNot applicable
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

Citations13
Published2011
Admission routes1
Has abstractyes

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