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Record W3216359420 · doi:10.5539/ibr.v15n1p26

Role of Database Marketing in Improving Quality of Service in Jordanian Private Hospitals

2021· article· en· W3216359420 on OpenAlexvenueno aff
Tareq N. Hashem

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessQuality (philosophy)MarketingSample (material)Service qualityService (business)PopulationPrivate practiceSignificant differenceDatabaseMedicineFamily medicineEnvironmental healthComputer science

Abstract

fetched live from OpenAlex

Current study aims to determine the role of database marketing in improving quality of service in Jordanian private hospitals. The study's population is consisted of marketing managers only or their deputies in the Jordanian private hospitals which contains (69) hospitals. Online questionnaire was distributed over a random sample amounting (59) managers, (51) questionnaires were collected, that is (86.44%) of the total sample. The study results indicated that Jordanian private hospitals use database marketing in improving quality of Service in Jordanian Private Hospitals. There is no difference in the role of database marketing in improving quality of service in Jordanian private hospitals according to the managers’ educational level. There is a difference in the role of database marketing in improving quality of service in Jordanian private hospitals according to the managers’ experience.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
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 head0.043
GPT teacher head0.349
Teacher spread0.307 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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