The role of financial risk-taking attitude in personal finances and consumer satisfaction: evidence from Australia
Bibliographic record
Abstract
Purpose Financial risk-taking attitude (FRT) plays an important role in consumers' financial decisions, thereby determining consumer well-being. Motivated by the recent research on consumer well-being, this paper explores the relationships between financial literacy, a propensity to plan (PTP), FRT, financial satisfaction and life satisfaction. Design/methodology/approach The authors use the Household, Income and Labour Dynamics in Australia (HILDA) survey to achieve the purpose of this paper. Furthermore, the authors use the variance-based partial least square structural equation modeling (PLS-SEM), also known as the PLS path modeling approach to test our proposed hypotheses empirically. Findings The study finds a strong partial mediation of FRT between financial literacy and financial satisfaction. Moreover, the analyses reveal that a high PTP combined with a high FRT results in achieving high financial satisfaction, which leads to improved life satisfaction. Practical implications The findings show the importance of creating financial plans in accordance with risk tolerance. While increasing financial literacy is relevant, the research suggests that tools that help consumers plan and invest in appropriate risky investments will lead to better outcomes. Originality/value Though scholarly acumen of consumer well-being is rapidly developing, little remains known regarding the collective roles of financial literacy, PTP and FRT. The study addresses this gap by showing that financial literacy, risk-taking attitudes and planning propensities are all interconnected and necessary ingredients to improve financial and life satisfaction.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".