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Record W2980112286

PROCESSO DE DECISÃO DE COMPRA DOS CONSUMIDORES DE SERVIÇOS DE TV POR INTERNET: UM ESTUDO COMPARATIVO DO CASO NETFLIX NO BRASIL E ESTADOS UNIDOS

2019· article· pt· W2980112286 on OpenAlex
Fernanda Meneses de Oliveira, Luíz Marcelo Antonialli

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

VenueRevista Reuna · 2019
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsLambton College
Fundersnot available
KeywordsHumanitiesBusinessPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Este trabalho teve como objetivo compreender o comportamento dos consumidores em relacao aos servicos streaming oferecidos pela Netflix no Brasil e nos Estados Unidos, utilizando o modelo do processo de decisao de compra proposto por Blackwell, Miniard e Engel (2011). Para alcancar os objetivos estabelecidos, foi realizada uma pesquisa qualitativa de carater descritivo, com base em fontes bibliograficas, dados secundarios e analise de 61 entrevistas em profundidade com assinantes da Netflix, sendo 38 entrevistados no Brasil e 23 nos Estados Unidos. Para a analise das entrevistas optou-se pela tecnica de analise de conteudo por categoria e comparativa entre os respondentes dos dois paises. Os resultados obtidos mostraram que, comparativamente o comportamento dos consumidores dos Estados Unidos e do Brasil, percebe-se que existem diferencas que ocorreram principalmente na etapa do consumo, no que se refere a maneira com que os usuarios utilizam o servico e em relacao a disponibilizacao de titulos diferenciada. As estrategias de marketing utilizadas pela Netflix para concorrer no mercado de entretenimento de TV, filmes e series se concentram na maneira como o conteudo e disponibilizado, no preco e na praticidade oferecida.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.056
GPT teacher head0.355
Teacher spread0.300 · 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