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Record W4407269663 · doi:10.1016/j.econmod.2025.107029

Is implicit cooperation reasonable for the economy? Corporate environmentalism under Kantian behavior

2025· article· en· W4407269663 on OpenAlexaff
Hiroshi Kurata, Ngo Van Long

Bibliographic record

VenueEconomic Modelling · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsMcGill University
FundersJapan Society for the Promotion of Science
KeywordsEnvironmentalismEconomicsNeoclassical economicsKeynesian economicsLawPolitical science

Abstract

fetched live from OpenAlex

We investigate the effects on the market when firms adopt Kantian behavior, inherently fostering implicit cooperation in the context of corporate environmentalism. We focus on oligopolistic firms’ environmental technology investments and compare investment levels under the Kantian equilibrium with those under the Nash equilibrium and socially optimal levels. When firms are concerned about the environmental impact of others, their environmental investment under the Kantian equilibrium exceeds that under the Nash equilibrium. Furthermore, Nash equilibrium investment is consistently below the social optimum, while Kantian equilibrium investment can either match or approach the socially optimal level. The Kantian equilibrium investment may exceed the socially optimal level if a firm have substantial environmental concerns.

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)0.003
metaresearch head score (Gemma)0.009
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
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 head0.081
GPT teacher head0.326
Teacher spread0.245 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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