MétaCan
Menu
Back to cohort
Record W3106762638 · doi:10.3390/jrfm13120303

International Tourism Development in the Context of Increasing Globalization Risks: On the Example of Ukraine’s Integration into the Global Tourism Industry

2020· article· en· W3106762638 on OpenAlexvenueno aff
Yurii Kyrylov, Viktoriia Hranovska, Вікторія Бойко, Aleksy Кwilinski, Liudmyla Boiko

Bibliographic record

VenueJournal of risk and financial management · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicDiverse Scientific Research in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsTourismGlobalizationContext (archaeology)World economyBusinessDomestic tourismTourism geographyEconomyEconomicsEconomic growthPolitical scienceGeographyMarket economy

Abstract

fetched live from OpenAlex

Today, international tourism is one of the most affected sectors of the economy due to the global COVID-19 pandemic. The main purpose of this article is to analyze current trends and identify prospects for the international tourism development in the context of increasing globalization risks in the world, using the example of Ukraine’s integration into the global tourism industry, as Ukraine is located in the centre of Europe and belongs to a number of countries with developing economies, and has the potential to expand its tourism industry, which may be of interest to the international scientific community in terms of overcoming the bifurcation point of its economic development. Analyzing the tourism industry, as one of the most progressive sectors of the world economy, we used general scientific and special research methods (abstract-logical, statistical, systemic analysis and synthesis, abstract-theoretical, and correlation-regression analysis). The paper analyzes major indexes of international tourism development in the modern globalized world and details the risks emerging during the global COVID-19 pandemic. It examines the global dynamics of tourism flows, where France, Spain, and the USA are unquestionable leaders. The study considers foreign exchange earnings of international tourism and the industry contribution to the gross domestic product of countries being an essential component of national budgets. Based on the study conducted, there were developed reliable forecast models for the tourism industry development in the countries under research. These models will provide an opportunity to generate reliable forecasts, which will allow timely identification of potential threats and making effective decisions to address them. At the same time, the issues of managing information support of economic entities in the field of international tourism need to be further developed in order to reduce risks.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
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 head0.030
GPT teacher head0.265
Teacher spread0.236 · 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

Citations118
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of risk and financial managementSame topicDiverse Scientific Research in UkraineFrench-language works237,207