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The Impact of Multinational Auto Manufacturers on the Market Structural of Chinese Saloon Car Industry

2009· article· en· W2121709620 on OpenAlexvenueno aff
Minchun Han, Fan Qi, Xiu-lin Yuan

Bibliographic record

VenueCanadian social science · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationOligopolyCompetition (biology)Index (typography)BusinessBusiness administrationEconomyEconomicsMarket economyComputer science

Abstract

fetched live from OpenAlex

The paper studies the structural characteristics of Chinese Saloon Car market of 1993-2002 by three market structural indexes: rate of market concentration, HHI index and logarithm variance of manufacturer scale. We prove that the Saloon Car market that once was largely occupied by several monopolies has gradually developed into a multivariate competitive market. Although the multinational auto manufacturers still have a strong control of national auto market, the violent reaction of oligopoly with the continuing opening of the market is emerging. After WTO accession, the recombining situations of Chinese auto industry, which are participated by multinational auto manufacturers, have been fixed on the whole, but it is not the result of sufficient market competition. The Chinese auto market will still face danger of being shuffled after the transitional period of WTO. It is possible to create a more stable and mature market structure only after Chinese Saloon Car industry carries through a reconstruction which based on a more fairness and orderly competition. Keywords: Multinational Enterprise, Market Structure, Rate of Market Concentration, Saloon Car Industry Resume: Ce texte etudie les caracteristiques structurales du marche chinois de berline entre 1993 et 2002 a l’aide de trios index structuraux : vitesse de concentration du marche , index HHI , et la variance logarithmique de l’echelle de fabricant . On constate que le marche de berline , occupe aurapavant largement par plusieurs monopoles , est devenu graduellement un marche concurrentiel multivariant . Bien que les fabricants multinationaux d’automobile aient encore un controle fort sur le marche national de voiture , la reaction forte d’oligopole avec l’ouverture continuelle du marche est en train de s’emerger . Apres l’accession a l’OMC , la fusion de l’industrie chinoise d’automobile , participee par les fabricants multinationaux d’automobile a ete determinee dans l’ensemble , mais ce n’est pas le resultat de la concurrence du marche . Le marche chinois d’automobile fera face a la recomposition apres la periode de transition de l’OMC . Il est possible de creer une structure plus stable et mur du marche apres la traversee de reconstruction de l’industrie chinoise de berline . Cette reconstruction doit se baser sur la concurrence plus juste et plus ordonnee . Mots-cles: enterprise multinationale , structure du marche , vitesse de concentration du marche , industrie de berline

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)0.000
metaresearch head score (Gemma)0.002
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.242
Teacher spread0.219 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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