MétaCan
Menu
Back to cohort
Record W4200258104 · doi:10.1108/yc-08-2021-1374

Determinants of Millennial behaviour towards current and future use of video streaming services

2021· article· en· W4200258104 on OpenAlexaff
Philip R. Walsh, Ranjita M. Singh

Bibliographic record

VenueYoung Consumers Insight and Ideas for Responsible Marketers · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsService providerSalience (neuroscience)MarketingOriginalityValue (mathematics)PopulationAppealService (business)Sample (material)Maturity (psychological)Product (mathematics)BusinessPsychologyComputer scienceSocial psychologyCreativitySociology

Abstract

fetched live from OpenAlex

Purpose This study aims to investigate the evolution of factors that influence the current and future use of video streaming applications by Millennial consumers. Design/methodology/approach Combining technology acceptance, perceived values and user identity theory this study used factor analysis and multiple regression to examine data from a survey of 292 university undergraduates. Findings Millennial’s current and future use of video streaming services remains driven more by social and emotional values and their effect on identity salience with their choice of content. Ease of use, convenience and monetary value remains less of an influence currently but may become more important in the future with the continued maturity of the industry. Practical implications The results of this study suggest that video streaming service providers should be developing business models that recognize the increasing importance of emotional appeal and self-identity of their service offerings as the industry matures and competition increases. Originality/value The research is novel in addressing future video streaming service provision by examining changes in young consumer behaviour over time within a similar sample population and considering the growth and technological advancement of video streaming services. The results are significant in addressing the gap that exists in understanding whether perceived values for technology adoption of the same product or service by millennials change over time and the implications that have for product and service providers.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.390
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.301
Teacher spread0.280 · 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.

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

Citations25
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueYoung Consumers Insight and Ideas for Responsible MarketersSame topicDigital Marketing and Social MediaFrench-language works237,207