MétaCan
Menu
Back to cohort
Record W3081674597 · doi:10.1561/1400000061

Research on Corporate Sustainability: Review and Directions for Future Research

2020· article· en· W3081674597 on OpenAlexaff
Jody Grewal, George Serafeim

Bibliographic record

VenueFoundations and Trends® in Accounting · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCorporate sustainabilitySustainabilityBusinessPolitical scienceEngineering ethicsSociologyCorporate social responsibilityPublic relationsEngineeringEcology

Abstract

fetched live from OpenAlex

We review the literature on corporate sustainability and provide directions for future research. Our review focuses on three actions: measuring, managing and communicating corporate sustainability performance. Measurement is the least developed of the three and represents promising opportunities for research. Compelling evidence now exists on the role of management control systems, investor pressure and mandated disclosure in improving corporate sustainability outcomes. Research has moved beyond weighing the importance of all sustainability issues equally, with recent studies drawing distinctions between the financial materiality of different sustainability issues. Collectively, this new line of inquiry suggests that improving performance on material sustainability metrics is related to improved financial performance, helping to resolve four decades of inconclusive evidence on the relation between sustainability and financial outcomes. Finally, we review research on how disclosure mediums, accounting standards, information monitors and intermediaries shape the communication of sustainability performance. We conclude with a call for research on how to measure performance in the 21st century when corporate purpose extends beyond shareholder value maximization.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.206
GPT teacher head0.431
Teacher spread0.225 · 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

Citations207
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueFoundations and Trends® in AccountingSame topicCorporate Social Responsibility ReportingFrench-language works237,207