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Record W2379073127 · doi:10.14400/jdpm.2011.9.4.069

Relationship between Motivations and Performances on the Internet Use: A Multinational Comparative Study-University Students in Canada, the U.S., and S. Korea

2011· article· en· W2379073127 on OpenAlexaboutno aff
Yong-Jean John

Bibliographic record

VenueJournal of Digital Convergence · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetMultinational corporationPerceptionPsychologyMarketingAdvertisingSocial psychologyBusinessComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

With a concentration on online university student behavior in highly-wired countries of Canada, the US, and South Korea, this study is aimed at identifying and comparing students' perception to the Internet use, willingness to use, and performance from its use. The cross-national comparison unveiled that students in each country did not have a compatible pattern of relationship among perception, intention, and performance. This study also examines the impact of levels of Internet use motivations on users' attitude, intentions to use, and performance. The results of the study help understand the factors affecting the Internet use in three countries and identify the differences in willingness to use and performance from cultural heterogeneity. Implications of the study, limitations, and further research directions are also discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.525
Threshold uncertainty score0.944

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.263
GPT teacher head0.356
Teacher spread0.094 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2011
Admission routes1
Has abstractyes

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Same venueJournal of Digital ConvergenceSame topicTechnology Adoption and User BehaviourFrench-language works237,207