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Record W4200371284 · doi:10.1108/yc-06-2021-1347

Do pop-up ads in online videogames influence children’s inspired-to behavior?

2021· article· en· W4200371284 on OpenAlexaff
Amir Zaib Abbasi, Umair Rehman, Ding Hooi Ting, Muhammad Ali Quraishi

Bibliographic record

VenueYoung Consumers Insight and Ideas for Responsible Marketers · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsAdvertisingValue (mathematics)Affect (linguistics)EntertainmentOriginalityPsychologyIncentiveSocial psychologyBusinessComputer scienceCreativityPolitical scienceCommunicationEconomics

Abstract

fetched live from OpenAlex

Purpose Advertising through the videogame has become one of the most effective and prevalent channels of advertisement, especially via pop-up ads – appearing on the screen that interrupts children’s gaming activity. Despite its importance, the effectiveness of pop-up ads and its advertising value in online videogames (O-VGs) to predict children’s inspired-to behavior remains scant. This study aims to investigate the underlying factors that explain the relationship between the four dimensions of pop-up ads and perceived advertising value, which further predicts children’s inspired-to behavior. Design/methodology/approach Data from 196 parents who observed their children while playing O-VGs, were analyzed using Smart-PLS. As the respondents are parents, the authors took extra precautions to ensure that the findings are valid. Findings Results showed that perceived irritation and incentives of pop-up ads do not affect children’s advertising value, whereas perceived informativeness and entertainment of pop-up ads positively impact perceived advertising value among children. Besides, children’s perceived advertising value of pop-up ads in O-VGs predict their inspired-to behavior. Originality/value This study contributes to children’s inspired-to behavior via empirically studying the perceived advertising value as a potential deriving source of inspiration. Finally, the study provides information for developers/advertisers about why and under what circumstances children perceived advertising value affect inspired-to behavior.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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.

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

Citations13
Published2021
Admission routes1
Has abstractyes

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Same venueYoung Consumers Insight and Ideas for Responsible MarketersSame topicChild Development and Digital TechnologyFrench-language works237,207