MétaCan
Menu
Back to cohort
Record W4283389560 · doi:10.1080/10696679.2022.2056487

Digital analytics approach to understanding short video advertising in digital marketing

2022· article· en· W4283389560 on OpenAlex
Prince Clement Addo, Samuel Kofi Akpatsa, Philip Nukpe, Andy Ohemeng Asare, Nora Bakabbey Kulbo

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Marketing Theory and Practice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsGeorge Brown College
Fundersnot available
KeywordsDigital marketingMarketingBusinessAdvertisingQuality (philosophy)Service qualityOnline advertisingAnalyticsCustomer satisfactionRelevance (law)Service (business)Web analyticsComputer scienceWeb pageThe InternetWorld Wide WebData science

Abstract

fetched live from OpenAlex

This study relied on datasets from global B2C and C2C to investigate the relationship between short video advertising (SV), customer satisfaction, price, quality signals, and sales in digital marketing. Using the web-scraping mining technique, the results from over twenty-three thousand online shops indicate that logistics service quality overrides the relevance of location in digital marketing. SV directly impacts sales and increases the shops’ dynamic scores, including quality of service and customer satisfaction. We identified actual online data to justify why SV adoption is essential in digital marketing and recommend logistic service quality and price fairness to improve sales in e-commerce.

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)0.213
metaresearch head score (Gemma)0.211
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.696
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2130.211
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.310
Teacher spread0.270 · 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