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Record W2286244826 · doi:10.1177/0007650315615855

Institutional Forces Affecting Corporate Social Responsibility Behavior of the Chinese Food Industry

2015· article· en· W2286244826 on OpenAlexaff
Wei Zuo, Mark S. Schwartz, Yuju Wu

Bibliographic record

VenueBusiness & Society · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsYork University
FundersNational Natural Science Foundation of ChinaNational Research Foundation
KeywordsCorporate social responsibilityChinaNormativeAffect (linguistics)Isomorphism (crystallography)Institutional theoryBusinessPerspective (graphical)Social responsibilityMarketingPublic relationsPolitical scienceSociologyEconomicsManagementLaw

Abstract

fetched live from OpenAlex

Food safety problems in China, such as deadly tainted milk, have attracted growing attention from a corporate social responsibility (CSR) perspective. To examine the forces that potentially drive CSR behavior within the Chinese food industry, our study is organized as follows. First, a review is conducted on the unique history of CSR in China as well as some of the major Chinese food scandals that have taken place. The primary drivers of CSR in China that have been suggested in the literature are then summarized. Next, new institutional theory perspectives are drawn upon to analyze three forces that potentially affect the behavior of Chinese firms: (a) coercive isomorphism, (b) mimetic processes, and (c) normative pressures. Based on a questionnaire survey of 164 Chinese managers and employees, the CSR behavior of firms operating in the Chinese food industry is found to only be significantly affected by the institutional factor of normative pressures. The study concludes with its limitations as well as the implications of the findings.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.067
GPT teacher head0.287
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

Citations24
Published2015
Admission routes1
Has abstractyes

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