Are consumers' financial needs and values common across cultures? Evidence from six countries
Bibliographic record
Abstract
Abstract Are consumers' financial needs, and financial values, the same or different across cultures? Two studies, with student (Study 1;n = 988) and non‐student (Study 2;n = 959) participants, explore the extent of equivalence, across six countries (Brazil,Russia,China,Taiwan,Tunisia andUS), in financial need belief, and financial value, measurement models. The financial need beliefs, derived from self‐determination theory (SDT) principles, include financial self‐efficacy, financial autonomy, financial community trust and support; the financial values include materialism and financial altruism. Both the financial need and financial value constructs evidence configural invariance (similar factor structure), and factor invariance among student but not non‐student samples. The financial need constructs evidence full, and the financial value constructs evidence partial, metric (factor loading) invariance. Factor covariance invariance obtains for the financial need beliefs constructs but not the financial value constructs. Finally, neither financial need nor financial value constructs evidence scalar (intercept) invariance. These results provide partial support for extendingSDT's hypothesis of universal human needs to the financial domain. In contrast, the financial value constructs of altruism and materialism are largely instable across cultures, suggesting that consumer views of giving, and the role of wealth in social status, differ between countries.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".