Bibliographic record
Abstract
Background:\nThe present study is the first study of Danish consumers on compulsive buying. It draws on a\nrepresentative sample of 1,015 Danish consumers (aged between 15 and 84 years) and extends prior\nresearch undertaken in other countries (such as Germany, Austria, Switzerland, France, Canada, the\nUS). It is the first study to shed light on the situation in a Scandinavian context and is designed to\nallow for a comparison with the situation in other countries.\nResults:\nThe prevalence of compulsive buying tendencies in Denmark are: 9.75% of the respondents show\ncompensatory buying behavior and 5.81% show compulsive buying tendencies. These percentages\nare similar to those found in Germany and slightly lower than in Austria. They are also within the\nrange of preferences in other countries.\nRegarding socio‐demographics, age and sex play a decisive role while marital status, education and\nincome cannot be associated with compulsive buying. If there is such a thing like “a typical\nshopaholic”, it would be a women aged between 25 and 44 years, disregarding whether she is a\nsingle or not, has a low or high education and income. The internet offers shopping opportunities\nthat lure both, potential shopaholics and compensatory buyers more than inconspicuous buyers.\nCompensatory and compulsive buyers have far more customer cards than others.\nConclusion:\nTo sum up, this study identifies diverse factors that are related to compulsive buying behavior. To\nfind out what cause is and what effect, more qualitative research as well as experimental studies are\nneeded. Additionally, more intercultural comparisons could lead to insights into the effects of the\nsocial and cultural consumption environment, i.e., the role of norms, values, policies, and the mass\nmedia on buying behavior. This type of research has, to date, not been undertaken in any\nScandinavian country. A first step is the comparison of Danish, Austrian and German data which is\ncurrently undertaken. The results of the present study together with future analyses could feed into\nstrengthening consumer education and informing debt counseling and consumer advice. It is also\nrelevant data for credit card companies and retail.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.108 | 0.016 |
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".