MétaCan
Menu
Back to cohort
Record W2105739509 · doi:10.5539/ibr.v8n1p197

The Relationship between Corporate Social Responsibility toward the Employees and Hotel Industry Performance in Jordan

2014· article· en· W2105739509 on OpenAlexvenueno aff
Marzouq Ayed Al Qeed

Bibliographic record

VenueInternational Business Research · 2014
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilityLikert scaleBusinessProductivityMarketingHotel industrySocial responsibilityDescriptive statisticsDistribution (mathematics)AccountingPublic relationsTourismPsychologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Corporate Social Responsibility (CSR) has a positive relationship with businesses performance especially with services companies like Hotels, Hospitals and Universities. The growing concentration to Corporate Social Responsibility is based on its capability to authority company performance. The Corporate Social Responsibility movement is distribution over the world and in the current years a large number of methods and frameworks have been developed, the majority being developed in the West. The present research focuses on the relationship between Corporate Social responsibility and Jordanian Industry Hotels performance. Methodology: A questionnaire was distributed to 100 employees in a hotels of Marriott and Movenpick where operated in Jordan Amman, Aqaba over a month in 2014, with results from Likert scales analyzed using descriptive analysis, means and SDs to tabulate and analyzed. Results: Analysis of 83 suitable responses among the hotels employees found a significant relationship between CSR and hotels performance at the two Hypotheses. Recommendations: Improve employee overall wages packages for employees which is based on productivity rewards. And ensure there is an equally opportunities between the employees in terms of Training.

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)0.002
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 score0.040
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.165
GPT teacher head0.363
Teacher spread0.198 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicOrganizational and Employee PerformanceFrench-language works237,207