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Record W2770795352 · doi:10.5430/ijba.v8n7p49

Toward Effect of Digital Advertisement on Mobile Users in Middle East

2017· article· en· W2770795352 on OpenAlexvenueno aff
Ismail Salamah, Heng Ma

Bibliographic record

VenueInternational Journal of Business Administration · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsAdvertisingSample (material)Mobile phoneService (business)BusinessShort Message ServiceThe InternetMiddle EastInternet privacyInternet usersComputer scienceMarketingPsychologyGeographyWorld Wide WebTelecommunications

Abstract

fetched live from OpenAlex

Nowadays smart-phones are the part of daily life for around the worlds but when user is using the smart-phone service over internet to collect the information or to use other services, there are lots of advertisement pops up on the screen that effect the users in many ways. The purpose of this study was to find out the effectiveness of the mobile advertisement on the consumer behavior in Middle East and reaction over advertisement, that how different people would act or what would be their response upon receiving the mobile advertisement. However, the use of smart phone advertisements in Middle East has not reached the expectations due to several factors. To complete the task, data was collected through questionnaire and this questionnaire was distributed among 300 people that means the sample size was 300. To interpret and analyze the data, Correlation and regression analysis were used where the results showed that the consumers generally have negative attitude toward the mobile advertisement unless the advertisers had specifically taken the consent of the consumer. The relation is both positive and negative and could vary according to the conditions.

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)0.001
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 score0.101
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.136
GPT teacher head0.399
Teacher spread0.263 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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