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Record W4407266505 · doi:10.1016/j.crsust.2025.100282

Current and future research in environmental sustainability: Synthesise of the role, responsibilities, and opportunities for the business sector

2025· article· en· W4407266505 on OpenAlexaff
Lára Jóhannsdóttir, Þröstur Olaf Sigurjónsson, Stefan Wendt, Mauricio Latapí, Ali Kharrazi

Bibliographic record

VenueCurrent Research in Environmental Sustainability · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsMount Royal University
Fundersnot available
KeywordsSustainabilityBusinessEnvironmental resource managementEnvironmental planningEconomicsEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Environmental sustainability is a timely and important topic to investigate given the increasingly complex challenges requiring businesses to reevaluate their business models in relationships with the natural environment, including their roles and responsibilities, and how opportunities in addressing these challenges may be utilized. This special issue enhances contemporary and future research by soliciting a wide variety of themes from ten papers falling under the scope of an ecological and climate focus of environmental sustainability relevant to the roles, responsibilities, and opportunities for the business sector, while also considering the links between environmental and social aspects. The articles included in the special issue provide an overview of five topics. These are 1) sub-national greenhouse gas accounting approaches, 2) corporate governance, policies, and practices, 3) sustainable finance, 4) consumer viewpoints and expectations, and 5) bioeconomy. Moreover, the crosscutting themes discussed suggest an inter- and transdisciplinary nature of environmental sustainability. In this introductory article to the special issue, the ten articles bring forth national and institutional levels, the sub-national level, and the organizational level. To conclude, future research avenues are vast based on suggestions presented in the ten papers the special issue covers. However, this introductory article also brings up topics suggested in the initial call for papers but were not covered in the papers included in the special issue, thus still relevant for future studies. • This special issue comprises ten papers by 57 authors coming from 15 countries. • The papers in this special issue studied various sectors and offer practical implications. • Six theoretical approaches are used in the published papers. • There is still vast room for future studies in the field of 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 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)0.016
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.016
Science and technology studies0.0020.004
Scholarly communication0.0160.018
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0150.003

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 head0.058
GPT teacher head0.328
Teacher spread0.270 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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