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Record W4411490743 · doi:10.1057/s41267-025-00794-y

Beyond reductionism: rethinking MNEs’ role in environmental crises

2025· article· en· W4411490743 on OpenAlexaff
Liena Kano, Birgitte Grøgaard, Luciano Ciravegna, Gilbert Kofi Adarkwah

Bibliographic record

VenueJournal of International Business Studies · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsHEC MontréalUniversity of Calgary
Fundersnot available
KeywordsMultinational corporationEnvironmental governanceInternational businessBounded rationalityInstitutional theoryScholarshipEconomicsCorporate governanceInterdependenceSociologyEconomic systemPolitical scienceManagementLaw

Abstract

fetched live from OpenAlex

Abstract This counterpoint challenges the view advanced by Yu, Bansal, and Arjaliès (J Int Business Stud 54:1151–1169, 2023), who argue that multinational enterprises (MNEs), by virtue of their cross-border operations, are inherently detrimental to the environment. While Yu et al.’s call for responsible resource use is commendable, we contend that their framework oversimplifies the complex realities of international business (IB). Drawing on New Internalization Theory (NIT), we examine environmental crises through the lens of multilevel complexity—macro-level institutional interdependencies, firm-level heterogeneity, and individual-level cognitive and behavioral constraints. Our approach underscores the role of bounded rationality and bounded reliability across all relevant actors—not just MNE managers—in shaping environmental outcomes. We find that Yu et al.’s proposed strategies give limited attention to the institutional, industry, organizational, and governance conditions under which environmental value is created. By contrast, we apply comparative institutional analysis to investigate MNEs’ impact on the environment as compared to feasible, real-world alternatives. We argue that meaningful environmental progress hinges not on targeting MNEs, but on fostering multilateral coordination among public, private, and civil society actors, with MNEs being well positioned to lead such collaborations. We call for scholarship that avoids ideological overreach, embraces IB theory, and acknowledges MNEs as key agents in advancing environmental sustainability.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.586
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.275
Teacher spread0.253 · 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 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

Citations13
Published2025
Admission routes1
Has abstractyes

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