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Record W2922366338 · doi:10.5539/mas.v13n4p1

The Impact of Corporate Social Responsibility on Organizational Performance in Telecommunication Sector in Jordan

2019· article· en· W2922366338 on OpenAlexvenueno aff
Bana Al-ma’ani, Shaker Al-Qudah, Husam Shrouf

Bibliographic record

VenueModern Applied Science · 2019
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilityLikert scaleBusinessOrganizational performanceMarketingAccountingTelecommunicationsPublic relationsComputer science

Abstract

fetched live from OpenAlex

The study has aimed to investigate the impact of corporate social responsibility on organizational performance. The data from three telecommunication companies were collected through questionnaires, based on the Likert scale. The data has been collected from 500 employees of telecommunication companies. Statistical tools were used to analyze the data. The results showed that internal CSR positively affects both non-financial and financial performance. In addition, external CSR proved to positively affect non-financial performance. The effect of external CSR on financial performance was negative, but not significant. The current study provides insights into the value of corporate social responsibility key on organizational performance in telecommunication companies. Additionally, most of the respondents considered CSR as a key factor influencing the Organizational Performance of companies. This approach is expected to support telecommunication company’s managers in the developing world to evaluate their current performance, estimate the desired state based on the results.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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