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Record W2754391981

The Determinants of Regional Price Discrimination in the Telecommunication Industry: An Empirical Study of 31 Provinces and Municipalities in China

2016· article· en· W2754391981 on OpenAlexvenueno aff
Xiaohong He, Guipu Wang

Bibliographic record

VenueJournal of Comparative International Management · 2016
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaGovernment (linguistics)Affect (linguistics)BusinessTelecommunicationsRegional scienceEconomyEconomic geographyEconomicsGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Telecommunication prices are vastly different across regions in China. This paper aims to identify the determinants that affect regional pricing behavior of China telecom operators. Using regional telecommunication data of 31 provinces and autonomous regions in China (excluding Hong Kong and Macao) during 2002–2011, we identified several factors which affect the regional price differences. The findings provide insights on the working of China telecommunication industry and have implications for firms’ marketing strategies and government policies.

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)0.000
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 score0.237
Threshold uncertainty score0.133

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.065
GPT teacher head0.377
Teacher spread0.312 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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