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Record W2131358438 · doi:10.18438/b8tp50

Perceived Convenience, Compatibility, and Media Richness Contribute Significantly to Dedicated E-book Reader Acceptance

2012· article· en· W2131358438 on OpenAlexvenueno aff
Theresa Arndt

Bibliographic record

VenueEvidence Based Library and Information Practice · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityCompatibility (geochemistry)PsychologyComputer scienceEngineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

Objective – Investigates the effects of perceived convenience, compatibility and media richness on users’ attitudes toward dedicated e-book readers.
 
 Design – Convenience sample survey.
 
 Setting – Taiwanese university.
 
 Subjects – A total of 288 students at the senior secondary (5%), four-year university (78%), and graduate student (17%) levels. Male-female participation was approximately equal.
 
 Methods – Students completed a 23-item survey on dedicated e-book readers, with 
 questions on perceived usefulness, perceived ease of use, intention to use, convenience, compatibility, and media richness. Data was analyzed using the partial least squares statistical technique.
 
 Main Results – Users state an increased intention to use dedicated e-book readers if they perceive the technology to be compatible with what they desire in a “book,” if the device delivers rich media content, and if the device is convenient. Compatibility was found to significantly affect perceived ease of use, and was found to be the strongest influence on intent to use a dedicated e-book reader. Compatibility, media richness and convenience also increased the perceived usefulness of dedicated e-book readers.
 
 Conclusion – Users will prefer dedicated e-book readers that are compatible with their preferences in a “book,” that deliver media-rich content, and that they find convenient. The study has implications for the design and development of e-book reading devices.

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)0.003
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.179
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.348
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

Citations1
Published2012
Admission routes1
Has abstractyes

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