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Record W4312871579 · doi:10.22495/cgsrv6i4p1

Firm identity and image: Strategic intent and antecedents to sustainability reporting

2022· article· en· W4312871579 on OpenAlexaff
Ranjita M. Singh, Philip R. Walsh

Bibliographic record

VenueCorporate Governance and Sustainability Review · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSustainabilityCorporate social responsibilitySustainability reportingBusinessIdentity (music)Corporate sustainabilityInclusion (mineral)Corporate identityAccountingPublic relationsSustainability organizationsSocial responsibilityMarketingSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

A firm’s strategic intent is often communicated through its vision, mission, and values statements. By linking sustainability with strategic intent (Galpin, Whittington, & Bell, 2015), firms seek to portray to their stakeholders (Ali, Frynas, & Mahmood, 2017; Papoutsi & Sodhi, 2020) that sustainability is a core part of their long-term goal. But there is limited research about whether publicly avowed sustainability messaging matches firms actual conduct reflected in their sustainability reports (Amran, Lee, & Devi, 2014). Content analysis of the vision, mission, and values statements of firms comprising the S&P/TSX composite index in 2020, and regression modelling tested whether firms’ that communicate their corporate social responsibility intentions, sustainable image, and sustainable identity in their vision, mission, and values statements are also more likely to engage in sustainability reporting. We find that firms were more likely to report, and at greater levels, on their sustainable activities when they message their strategic corporate social responsibility (CSR) intent. However, including external stakeholders when messaging about their CSR intent has a greater effect than the inclusion of internal stakeholders suggesting these firms are keener to portray a sustainable image than creating a sustainable identity. This result has implications for the successful implementation of sustainability strategies by these firms

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)0.008
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.002
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 head0.055
GPT teacher head0.316
Teacher spread0.261 · 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 designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

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