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Record W2031702775 · doi:10.1155/2012/142910

Creating Values for Sustainability: Stakeholders Engagement, Incentive Alignment, and Value Currency

2012· article· en· W2031702775 on OpenAlexaff
Frank T. Lorne, Petra F. A. Dilling

Bibliographic record

VenueEconomics Research International · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsNew York Institute of Technology
Fundersnot available
KeywordsIncentiveCurrencyStakeholderValue (mathematics)Stakeholder theoryBusinessSustainabilityIndustrial organizationEconomicsShareholder valueShareholderMicroeconomicsCorporate governanceMonetary economicsFinanceManagement

Abstract

fetched live from OpenAlex

A shareholder theory of firm and a stakeholder theory of firm may differ in their respective evaluation method of firm performance. Both theories however recognize the importance of value creation as the economic role of firms as institutions. The New Institutional Economics (NIE) emphasizes incentives alignment, while also viewing stakeholder engagements as methods to expand the boundaries of firms. The difference in performance evaluation between the two approaches can be reduced if stakeholders, while formulating incentive alignment, also evaluate the mechanisms of establishing a common currency value. The concomitant development of stakeholder engagement, incentive alignment, and value currency creation is argued to be an evolutionary process with the efficiency implications of the two theories tending to converge.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.023
Scholarly communication0.0110.017
Open science0.0010.009
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.232
GPT teacher head0.382
Teacher spread0.150 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations23
Published2012
Admission routes1
Has abstractyes

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