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Record W1596950671 · doi:10.1108/09547540610681077

Benchmarking wine tourism development

2006· article· en· W1596950671 on OpenAlex
Donald Getz, Graham Brown

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Wine Marketing · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBenchmarkingTourismWineBusinessDestinationsMarketingTourist destinationsProcess managementPolitical scienceFood science

Abstract

fetched live from OpenAlex

Abstract Purpose – This paper seeks to develop a framework for comparisons and benchmarking between wine tourism destinations. Design/methodology/approach – A regional case study was undertaken, including data from a survey of 23 wineries in Canada's Okanagan Valley, British Columbia. The survey provides the winery perspective on development of wine tourism, as well as opinions on what should be done to improve wine tourism. Findings – Wineries were found to be pursuing tourism developments, but kept little data on visitors and related spending. Their goals and opinions on what is needed in the region revealed that they are mostly oriented toward domestic, independent travelers. One hypothesis emerging from this case study is that the growth and increasing sophistication of wine tourism infrastructure, both at wineries and elsewhere in the region, is in large part a function of market potential. On the supply‐side, a critical mass can be facilitated through establishment of major, landmark wineries that are purpose‐built as tourist attractions. Practical implications – Using this profile of the Okanagan, implications are drawn for comparisons and benchmarking among wine tourism destinations, including a suggested process and measures. Research limitations/implications – The single case study limits generalizability to other destinations, and the achieved sample of wineries does not necessarily reflect the major corporate wineries in the Okanagan Valley. More systematic comparison of wine regions is recommended. Originality/value – This research makes an original contribution for applying the concept and method of benchmarking to wine tourism destinations. It is of value to the wine industry, destination marketers, and host community planners.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.146
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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