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Record W2382202114

ANALYSES ON MARKET COMPETITION STATE OF CHINESE INBOUND TOURISM IN NEW CENTURY

2005· article· en· W2382202114 on OpenAlex
Sun Gen-nian

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEconomic Geography · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsChinaTourismCompetition (biology)BeijingBusinessEconomyState (computer science)GeographyEconomic geographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

In market economy system, the establishment of regional tourism developing strategy must be based on the exact market analysis and grasp. In this paper, according to the two indexes combination of market occupancy rate and growth rate, a mathematical model of tourism market competition state is put forward, using this model, a regional tourism markets is compartmentalized into four types, such as bright star market, cash-cow market, infant market and thin-dog market. This model provided a new method for analyzing the regional tourism market in the drawing of regional tourism developing strategy. As an example of the study, the paper partitions customer recourses markets and objective markets of China inbound tourism in the end of last century in quantity, the result shows: the customer recourses markets focus on three regions, which are west of Europe, north of America, southeast of Asia. In the intercontinental markets, Russia and America are the first grade, England, Germany, Canada and Australia are the second, Italy, Holland, New Zealand and Spain are the third. In the inner-continent markets, Japan and Korea are the first one, Malaysia, Philippines, Singapore and Mongolia are the second, and the third are Thailand, Indonesia, India and Vietnam. In china, the inbound tourism development of each province is unbalance, the eastern is high and the western is low, the inbound tourists are mainly distributed at 12 hot provinces. In the eastern region, Guangdong is the first grade, Beijing, Shanghai Fujian and Jiangsu are the second, Zhejiang, Shandong and Liaoning are the third. In the middle part district, Guangxi is the first grade, Heilongjiang, Hubei, Hunan and Inner Mongolia are the second. In the western region, Yunnan and Shaanxi are the first grade, Szechwan and Chongqing are the second one. With analyzing the status of each markets, the research provides the new according for market exploit strategy of China inbound tourism in the beginning of new century. The partition of tourism market competition state is comparatively, and it is dynamic in time and space, this work is only a principium exploration and there is some questions await research going to deep.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.332
Teacher spread0.313 · 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