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Record W4377238953 · doi:10.3390/businesses3020019

Effects of Corporate Social Responsibility on Online Recruitment Processes in the Vietnamese Food and Beverage Industry

2023· article· en· W4377238953 on OpenAlexaff
Kudrat Khuda, Hong Chau Linh Nguyen, Dieu Hack‐Polay

Bibliographic record

VenueBusinesses · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployer Branding and e-HRM
Canadian institutionsCrandall University
Fundersnot available
KeywordsCorporate social responsibilityVietnameseBusinessContext (archaeology)PerceptionMarketingHuman resourcesUnemploymentHuman resource managementPublic relationsEconomic growthPolitical scienceManagementEconomicsPsychology

Abstract

fetched live from OpenAlex

This paper examines the effect of CSR perceptions on online recruitment practices and outcomes in the Vietnamese food and beverage sector. Semi-structured interviews were conducted with seventeen participants, including CEOs, HR (human resource) staff and store managers. The results show that CSR perception varies and is exemplified through employee-related activities, ethical products, environment, philanthropy, and international standards. The study is novel in establishing that, despite high unemployment in developing economies, CSR communication in online recruitment sites impacts job applicants’ choice of company. While the strategic potency of CSR has been established, this study brings to light its critical significance for human resources processes, particularly online recruitment, in an emerging economy context. The study has considerable implications for practitioners and researchers, suggesting the necessity to strategically manage the interface between CSR and online recruitment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.107
GPT teacher head0.297
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes1
Has abstractyes

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