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Record W2112109670 · doi:10.5430/ijba.v4n3p22

Emergence of Movie Stream Challenges Traditional DVD Movie Rental—An Empirical Study with a User Focus

2013· article· en· W2112109670 on OpenAlexaffvenue
Chiang‐nan Chao, Saibei Zhao

Bibliographic record

VenueInternational Journal of Business Administration · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsRentingEntertainmentAdvertisingFilm industryThe InternetComputer scienceQuality (philosophy)Service (business)Focus (optics)MultimediaBusinessMovie theaterMarketingWorld Wide WebArtEngineering

Abstract

fetched live from OpenAlex

Traditional movie DVD rental model has been challenged by a new business model of movie stream. Movie stream possesses convincing advantages over the traditional DVD rental. E-commerce shows a trend in the movie industry that consumers can stream comparable quality movies and TV shows directly from the Internet instead of waiting for the DVDs in the mail. Thanks to global technology advancement, movie stream has already prevailed. This study focuses on consumers’ preferences of decision making variables for streaming movie from the Internet and the traditional DVD movie rental. The results indicate that consumers are shifting from DVD movie rental to movie stream, while home entertainment industry needs to improve both in technology and customer service. The consumers favor movie streaming and make it better competing with other ways of watching movie. The quality of movie stream and renting DVD disks may be less important for movie viewers. Movie industry should make movie stream easy to watch.

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)0.014
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.058
GPT teacher head0.271
Teacher spread0.213 · 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

Citations8
Published2013
Admission routes2
Has abstractyes

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