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Record W2034892059 · doi:10.4018/jabim.2013010107

Does Stakeholder Perception of Firm’s Corporate Social Responsibility Affect Firm Performance?

2013· article· en· W2034892059 on OpenAlexaff
Siva Prasad Ravi

Bibliographic record

VenueInternational Journal of Asian Business and Information Management · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsCorporate social responsibilityBusinessStakeholderCorporationPerceptionRevenueAffect (linguistics)Competitive advantageProfit (economics)MarketingCompetition (biology)Stakeholder theoryPublic relationsIndustrial organizationAccountingMicroeconomicsEconomicsFinancePsychology

Abstract

fetched live from OpenAlex

In the present-day business landscape characterised by global competition, demanding customers and depleting natural resources, Corporate Social Responsibility (CSR) has become an important strategy for corporations for creating competitive advantage. CSR involves a corporation’s commitment to align performance (revenue growth and profit) motives with fulfillment of social, ethical, community and environmental obligations. Researchers have found a positive correlation between stakeholder perceptions of firm’s CSR performance and financial performance, assuming other factors as constant. This paper, based on analysis of Wal-Mart’s performance from 2001 to 2011, found, seemingly significant negative perceptions of CSR activities of corporations result in lower performance. Once formed, changing negative perceptions is often difficult and the effort involves considerable amount of resources with questionable outcomes. This study has come to the conclusion that being a good ‘Corporate Citizen’ and creating positive stakeholder perceptions is a better strategic approach for firm’s continuing success.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.009
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 head0.028
GPT teacher head0.248
Teacher spread0.220 · 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 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

Citations3
Published2013
Admission routes1
Has abstractyes

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