Mapping wine business research in the<i>International Journal of Wine Business Research</i>: 2007-2017
Bibliographic record
Abstract
Purpose The purpose of this paper is to systematically review the body of work featured in the International Journal of Wine Business Research ( IJWBR ) since its transition from the International Journal of Wine Marketing ( IJWM ) in 2007, and to assess the collective evolution of the topical structure of published research against the Journal’s aims as described in the inaugural editorial. Design/methodology/approach A scientometric study using both network analysis and narrative methods was used to evaluate the research contents of the IJWBR . Findings Results lead to four conclusions. Overall, the research published in IJWBR has met the editorial aim of expanding beyond the marketing focus of IJWM . Second, the Journal has become increasingly international in its approach to research activities, both in terms of authorship and sites of study. Third, the methods used in the study of wine business have advanced from descriptive univariate to more complex or predictive multivariate approaches. Finally, despite all of these desired advances, research grounded in marketing and consumer behavior perspectives still predominates the Journal. Originality/value This is the first review of IJWBR to use a scientometric method; and this paper provides a description and assessment of progress made toward the publishing goals first envisioned for the Journal at its transition from IJWM to IJWBR .
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.009 | 0.002 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".