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Record W2182542257 · doi:10.5539/ijms.v7n6p1

Competition, Cooperation, and Pricing: How Mobile Operators Respond to the Challenge of Over-The-Top

2015· article· en· W2182542257 on OpenAlexvenueno aff
Xiaobing Xu, Rong Chen

Bibliographic record

VenueInternational Journal of Marketing Studies · 2015
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBusinessCompetition (biology)Service (business)Value (mathematics)Operator (biology)Mobile telephonyMarketingTelecommunicationsIndustrial organizationComputer scienceMobile radio

Abstract

fetched live from OpenAlex

<p>Considering the threats from OTT (Over-The-Top) services, this paper examines whether the mobile operator should charge OTT services access fees and how to. By using a dynamic-gaming process, we find that: 1) under non-cooperative strategy, the mobile operator would charge OTT a mobile Internet access fee, which is positively correlated to OTT platform’s future commercial value and the price of direct communication service, and negatively correlated to the indirect communication service price. 2) under cooperative strategy, the OTT service price that the joint venture charges end users is negatively correlated to OTT platform’s future commercial value. 3) despite choosing cooperative or non-cooperative strategy, the pricing of mobile operator’s direct communication service has a negative correlation with OTT platform’s future value and a positive correlation with the platform’s quality; while the pricing of the indirect communication service is positively correlated to platform’s future value and negatively correlated with the platform quality.</p>

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.023
GPT teacher head0.298
Teacher spread0.275 · 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 designNot applicable
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

Citations7
Published2015
Admission routes1
Has abstractyes

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