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Record W4293214651 · doi:10.5267/j.ijdns.2022.8.008

The impact of digital content of marketing mix on marketing performance: An experimental study at five-star hotels in Jordan

2022· article· en· W4293214651 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingBusinessContent marketingDigital marketingMarketing mixAdvertisingSocial mediaLoyalty business modelRelationship marketingMarketing managementMarketing strategyService qualityComputer scienceService (business)World Wide Web

Abstract

fetched live from OpenAlex

The study aimed to examine the impact of the marketing mix for digital content on the marketing performance of five-star hotels in Jordan. The dimensions of the marketing mix for digital content were (digital marketing database, social media platforms, digital pricing, and digital advertising), while the dimensions of marketing performance were (customer loyalty, customer satisfaction, and attracting new customers). The study population represented five-star hotel customers in Jordan, where an appropriate sample of (294) customers was used. The data of the study were analyzed using the Structural Equation Modeling (SEM) technique. The study concluded that all dimensions of the marketing mix for digital content had a positive impact on the marketing performance of five-star hotels in Jordan. Accordingly, the study recommended managers in these hotels pay more attention to promoting through digital means by publishing advertisements that include images and videos related to the quality of services available.

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.

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)0.005
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 score0.135
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0030.002
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 head0.040
GPT teacher head0.312
Teacher spread0.272 · 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