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Record W2801404169 · doi:10.1108/tr-07-2017-0115

Video game–induced tourism: a new frontier for destination marketers

2018· article· en· W2801404169 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

VenueTourism Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTourismCreedDestinationsVideo gameAdvertisingFrontierMarketingOriginalityValue (mathematics)BusinessComputer scienceSociologyMultimediaPolitical science

Abstract

fetched live from OpenAlex

Purpose This paper aims to expand the media-related tourism literature in a new domain of application by highlighting a connection between the world of video games and tourism. Design/methodology/approach Through deductive content analysis, this study looks at 137 online comments posted on popular gaming and travel websites that connect two popular video games (Assassin’s Creed II and Assassin’s Creed Unity) and travel motivation. Findings Results establish that video games share similar travel motivation elements with film and should be considered as a driver of tourism. It argues that destinations should consider video games as a platform for motivating tourists before they consider investing in virtual reality. It outlines opportunities for destinations interested in video game-induced tourism and calls for more research and case studies that link video games with destinations. Originality/value This is, to the authors’ knowledge, the first paper to investigate this connection. As such, it outlines untapped opportunities for destinations interested in video game-induced tourism and opens up a new line of research within media-related tourism literature.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.068
GPT teacher head0.391
Teacher spread0.322 · 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