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Record W4406042978 · doi:10.1002/csr.3074

Exploring the link between corporate social responsibility and financial performance in social enterprises: The mediating role of productivity

2025· article· en· W4406042978 on OpenAlexaff
Mahinda Wejesiri, Chansoo Park, Peter Wänke, Yong Tan, Cory Searcy

Bibliographic record

VenueCorporate Social Responsibility and Environmental Management · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsToronto Metropolitan UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsBusinessCorporate social responsibilityProductivityLink (geometry)Industrial organizationFinanceMarketingAccountingPublic relationsEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Abstract A key discussion in the current management literature is how businesses react to and can contribute to solving societal challenges while meeting the needs of their shareholders and their broader set of stakeholders. Most extant research focuses on corporate social responsibility (CSR) issues in large for‐profit corporations, but social enterprises are also critical given their ability to promote financial inclusion and focus on stakeholders' needs. This study explores the mediating role of total factor productivity (TFP) in the relationship between CSR and financial performance within social enterprises, using a sample of microfinance institutions (MFIs) from Latin America. Our analysis demonstrates TFP's critical role in translating CSR initiatives into sustainable financial outcomes and enhancing both economic and social objectives. Thus, our results may provide insights to regulators, policymakers, and practitioners, allowing them to better understand best practices and actions that foster stakeholders' trust and expectations, with the potential outcome of improving MFIs overall sustainability goals. Our findings are robust due to the use of a variety of methodological approaches to address possible endogeneity problems and alternative specifications of financial performance.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.052
GPT teacher head0.239
Teacher spread0.187 · 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

Citations10
Published2025
Admission routes1
Has abstractyes

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