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Record W4292959169 · doi:10.5267/j.ijdns.2022.6.002

Digital marketing and public relations: A way to promote public relations value

2022· article· en· W4292959169 on OpenAlexvenueno aff
Mohammed T. Nuseir, Ahmad Ibrahim Aljumah, Ghaleb A. El Refae

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingPromotion (chess)BusinessRelation (database)Digital marketingBusiness marketingCompetitive advantagePublic relationsReturn on marketing investmentMarketing managementValue (mathematics)Political sciencePolitics

Abstract

fetched live from OpenAlex

The objective of this study is to determine the relationship of digital marketing as a wide emerging marketing tool, in developing public relation values for modern business in the globalized competitive era of mature markets. For this study, the cross-sectional data were collected by 450 respondents including the people as customers, and the managerial staff of the different well-reputed organizations in the United Arab Emirates (UAE). The findings of this study highlight that there is a clear and strong relationship between digital marketing in developing public relations values, and modern businesses need this technique to develop equity and provide a distinct message about the vision and mission of the organization in the target market. The significance of this study is it addresses the theoretical gap in the literature, and the practical gap in business practices by providing the insight to utilize digital marketing not only for the promotion of products and services but could be used to promote public relation values.

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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0050.010
Scholarly communication0.0150.013
Open science0.0000.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.002

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 head0.026
GPT teacher head0.264
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations65
Published2022
Admission routes1
Has abstractyes

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