Analyzing Financial Behavior in Undergraduate Students in Economics, Administration and Accounting Sciences
Bibliographic record
Abstract
This study examines the financial behavior of university students in Economics, Business Administration, and Accounting in Tegucigalpa, Honduras, using the FB–13 instrument. Exploratory and confirmatory factor analyses validate a three-dimensional structure: (1) financial planning and control, (2) savings and financial preparation, and (3) fulfillment of obligations, with high internal consistency (α = 0.915), supporting its psychometric robustness in Latin American academic contexts. Based on a sample of 714 students with diversity in gender, age, work experience, and parental status, the analyses confirmed that the FB–13 model best fits a three-factor structure. Significant correlations were identified between financial behavior and experiential variables such as age, work experience, and parenthood, while traditional sociodemographic attributes such as gender, residence, marital status, employment, and educational level showed limited associations. These findings suggest that personal experiences have a greater influence on the configuration of financial practices than conventional demographic categories. The study acknowledges limitations related to cross-sectional design, non-probabilistic sampling, and self-reported data, yet these do not diminish its contributions. By validating the FB–13 in Honduras, the research offers comparative evidence and promotes cultural diversity in financial behavior literature. Future research should move toward longitudinal and qualitative studies that explore the role of family dynamics, work contexts, and personal aspirations in responsible financial behaviors.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".