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Record W4392652265 · doi:10.1080/14616688.2024.2325932

Tourism destination development: the tourism area life cycle model

2024· article· en· W4392652265 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTourism Geographies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismBusinessTourism geographyMarketingEconomic geographyGeography

Abstract

fetched live from OpenAlex

The tourist area life cycle has been in existence for over four decades since its publication in The Canadian Geographer and was described as 'one of the most cited and contentious areas of tourism knowl-edge.(and)has gone on to become one of the best known theories of destination growth and change within the field of tourism studies' It was noted as one 'Of the most influential conceptual models for explaining tourist, development' .The model was developed primarily from the Product Life Cycle model used in business and management studies and modified to explain the process of development and change that took place in tourist destinations throughout the world.The model has received considerable attention over its life span, but has often been cited from second hand sources or misquoted on many occasions.Its appearance in a non-tourist journal has resulted in it often not appearing in various early literature surveys based on tourism-focused sources and for its first decade access to the original article was limited and difficult, as demonstrated by many requests to the author for copies of the article.Electronic access to journals and libraries have resolved this problem, but its considerable visibility (in excess of 56,000 reads on Research Gate) and use (close to 5000 citations) means that it has possibly entered the realm of tourism myths and become part of accepted dogma in the field of tourism development.This could present problems to those challenging the original concept and introducing alternative or contradictory ideas and propositions, and it is perhaps, appropriate to briefly review the history of the concept.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.301
Teacher spread0.270 · 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