From materialism to hedonistic shopping values and compulsive buying: A mediation model examining gender differences
Bibliographic record
Abstract
Abstract Although prior research has extensively focused on explaining the direct mechanisms of the materialism‐compulsive buying relationship or stressed selected indirect variables such as consumers' social status, money attitudes, well‐being, emotions and identity, little research has examined how materialism impacts compulsive buying via hedonistic shopping values in a former communist economy that has transitioned to a democratic economy. Thus, we examined the materialism‐compulsive buying relationship in term of a mediational model that includes the theoretical construct of hedonistic shopping values. Additionally, the model's postulated relationships are explained from the perspective of gender differences, through the agency of moderated effects. Data for study were obtained from the Polish Household Survey resulting in a nationally representative sample (N = 1245). Results imply that materialism is related to compulsive buying, but the strongest effect occurs indirectly via hedonistic shopping values. Compulsive buyers appear to shop obsessively not only out of their materialistic orientations, but also out of hedonic joy, pleasure, and the 'emotional euphoria' they obtain during shopping. An in‐depth examination between female and male consumers revealed group differences such that the tendency to compulsively buy, which assumed a joint influence of materialism and hedonistic shopping values, is stronger in women than men. Results of this study are discussed in terms of gender and cross‐cultural differences and their theoretical and practical importance to understanding compulsive buying.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.000 |
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.
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".