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Record W2172042202 · doi:10.1177/0047287513497839

Developing a Tourism Innovation Typology

2013· article· en· W2172042202 on OpenAlexaff
Ed Brooker, Marion Joppe

Bibliographic record

VenueJournal of Travel Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of GuelphSheridan College
Fundersnot available
KeywordsTypologyTourismLiminalityInnovatorMarketingNorm (philosophy)BusinessSociologyPolitical scienceEntrepreneurship

Abstract

fetched live from OpenAlex

Innovation has become a buzzword, regularly cited to convey any improvement made, regardless of the extent of newness. Tourism innovation has historically been viewed as either incremental or radical, a binary developed within manufacturing. However, given that incremental improvements are the norm in the tourism sector and that radical innovation is an abnormality, the binary is not representative of tourism innovation. We suggest a three-level typology, based on field research in Europe and Australia, and informed by Rogers’s innovation diffusion model; the concept of liminality and its role in the search for tacit knowledge through weak network ties; and the need to ask ultimate (why) rather than proximate (what, how) questions. Since the term innovation is overused, we introduce three alternate concepts: the “artist,” who is comparable to the innovator; the “artisan,” who represents early innovation adopters; and the “painter,” who epitomizes the early and late majority.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.007
Science and technology studies0.0030.006
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.225
GPT teacher head0.479
Teacher spread0.254 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations108
Published2013
Admission routes1
Has abstractyes

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