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Record W1926856000 · doi:10.1353/jda.2015.0159

Is the boom in East Asian tourism happening at the expense of other destinations?: A cross-country analysis

2015· article· en· W1926856000 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue˜The œJournal of developing areas · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsTrent University
Fundersnot available
KeywordsTourismDestinationsChinaBoomEast AsiaGeographyEconomyDevelopment economicsEconomics

Abstract

fetched live from OpenAlex

Over the years, tourism has emerged as the world’s largest peacetime industry employing approximately 221 million people worldwide. According to the UNWTO, the tourist traffic rose to a record 1.087 billion arrivals in 2013 and this surge is expected to continue through 2030, in annual increments of 3.8 percent. Much of this unprecedented boom may be attributed to newly-affluent Asian nations such as Taiwan, South Korea and Malaysia as well as the huge populations of China, India and Indonesia - the first, second and fourth most populated countries in the world. Many analysts worry that the Asia Pacific region - a collection of dissimilar states squeezed between the Indian Ocean and the Pacific - could potentially be gaining market shares at the expense of their older rivals. We disagree with such a notion and will argue instead that the boom in East Asian tourist traffic is attributable to local factors primarily. Our examination of tourism data from the World Development Indicators database comprising a total of 92 countries covering a 16-year period (1995-2011), provides strong empirical support for our claim that the regional variation in tourism growth does not imply that some destinations are gaining at the expense of the rest. We examine changes in tourist arrivals among all relevant bilateral country pairs to test for a link between changes in tourist arrivals in Southeast Asian nations with Europe and North America. We do find that growth in tourist arrivals to countries of Southeast Asia has been particularly strong, but at the same time, tourism growth to Eastern Europe and to the Middle East has also been strong. This suggests that tourism is driven at least partly by economic growth of a destination, and it may also drive that growth. In examining changes in tourist arrivals by bilateral country pairs we find that for the vast majority of cases there is no support for the hypothesis that growth of tourism in one location comes at the expense of tourist arrivals to other countries. The tourism industry is dynamic and growing, and the success of new destinations does not come at the expense of traditional destinations. Rather countries seem to be establishing niches for themselves in terms of tourist offerings and as such may well be more complementary to each other than competitive. All countries—both developed and developing—may be able to stake a claim in the ever expanding global tourist trade.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.093
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.066
GPT teacher head0.369
Teacher spread0.302 · 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