MétaCan
Menu
Back to cohort
Record W4392652265 · doi:10.1080/14616688.2024.2325932

Tourism destination development: the tourism area life cycle model

2024· article· en· W4392652265 on OpenAlexaboutno aff
Richard Butler

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.

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)0.001
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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

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
GenreReview

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

Citations57
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTourism GeographiesSame topicDiverse Aspects of Tourism ResearchFrench-language works237,207