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Record W2809333739 · doi:10.1080/21568316.2018.1481453

Is There a Strategic Interdependence Between the USA and Canada in the Tourism Sector? An Analysis Using Game Theory

2018· article· en· W2809333739 on OpenAlexaboutno aff
Jean Max Tavares, Xuan Tran

Bibliographic record

VenueTourism Planning & Development · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismOrder (exchange)DestinationsCompetition (biology)EconomicsGame theoryProduct (mathematics)Gross domestic productError correction modelEconometricsEconomyRegional scienceMacroeconomicsGeographyCointegrationMicroeconomicsMathematicsFinance

Abstract

fetched live from OpenAlex

Although many tourist regions compete among themselves, there is a scenario of strategic interdependence between them that has not usually been considered in the literature. In this way, this present article has used Game Theory in order to analyse the competition / cooperation between two tourist destinations – namely, between Canada and the USA. In methodological terms, the study has used the Vector Autoregressive model; the Vector Error Correction model; and Granger Analyses in order to forecast the short-term and long-term impacts of tourism receipts between the USA and Canada. The article has used databases from 2007 – 2016 concerning their Gross Domestic Product (GDP). The tourism receipts were obtained from Statistics Canada and UNWTO. The findings have indicated that (1) there was no Nash equilibrium of a GDP payoff for the USA and Canada; (2) The USA has a dominant strategy when developing tourism, but Canada does not.

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)0.004
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 score0.160
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.357
Teacher spread0.273 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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