One step closer to the field: visual methods in marketing and consumer research
Bibliographic record
Abstract
Purpose – The purpose of this study is to examine the use of visual research methods in the area of recent marketing and consumer research. Design/methodology/approach – Content analysis was used to investigate visual method in articles from Journal of Consumer Research; Journal of Marketing; Journal of Marketing Research; Journal of Marketing Management; Consumption, Markets, and Culture and Qualitative Market Research. Abstract, key words and methodology sections of all articles published in these six journals from 2002 to 2012 were scanned to identify which of them applied visual methods in their studies. The selected articles were then closely analyzed to discover how visual research methods were used and in what manner did they contribute to the marketing and consumer behavior discipline. Findings – This study found that a growing number of marketing and consumer researchers utilized visual methods to achieve their research goals in various approaches such as cultural inventories, projective techniques and social artifacts. Visual method is useful when research deals with children who are not fully developed and able to comprehend text messages and also advantageous when investigating informants’ metaphorical thoughts about a subject or the content of their mind. Originality/value – This paper examined how visual methods have assisted marketing and consumer researchers in achieving their goals and suggests when and how researchers can utilize the visual methods for future research.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.077 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".