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Record W2045307949 · doi:10.17722/ijme.v3i1.124

Measuring the Effectiveness of Online Advertising: The Tunisian Context

2014· article· en· W2045307949 on OpenAlexvenueno aff
Ali Haj Khalifa

Bibliographic record

VenueInternational Journal of Management Excellence · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsInteractivityAdvertisingComputer scienceOnline advertisingThe InternetContext (archaeology)BannerCLARITYEmpirical researchMemorizationMarketingWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

The development of the Internet tool was accompanied by a business turnaround which has deep effects on the rules of marketing and particularly company-customers relationships. The graphical interface that the Web can create between the company and its customers promotes its use as a medium of marketing communication. The advantages of e-communication are endless for companies, including timeliness, cost and interactivity. However, users are daily confronted with large masses of information which may affect the issue of effectiveness of this communication form. Therefore, it is necessary to know whether the information transmitted is accessed and if it achieves the objectives associated with it. In other words, to what extent the internet communication is effective. In this research, efficiency is studied through two indicators: the advertising memorization and the click on the pop-up advertising. The empirical study was conducted on a sample of 200 Internet users. The statistical analysis used is descriptive analysis and logistic regression. The main empirical results show that memory is largely affected by the location in the screen, size and animated banner advertising. As for the "click", it’s related to the colors used in the banner, size and clarity of the message.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.286
Teacher spread0.267 · 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 designOther design
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

Citations1
Published2014
Admission routes1
Has abstractyes

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