Investigation of the Antecedents of Personal Saving Behavior: A Systematic Literature Review Using TCM-ADO Framework
Bibliographic record
Abstract
This paper reviews the current research landscape on Personal Saving Behavior, focusing on its antecedents and outcomes. Using bibliographic analysis of publication trends—highlighting productive authors, journals, countries, and keywords—the literature is synthesized. A framework-based systematic review is conducted to understand factors influencing saving behavior and its effects, employing the TCM framework to analyze theory, context, and methods across selected studies. Additionally, the ADO framework is used to discuss antecedents, decisions, and outcomes related to personal saving behavior. The review consolidates 112 articles from 2000 to 2025, grouping unique antecedents into nine categories. It also examines how specific antecedents positively or negatively impact saving decisions and outcomes. Finally, using the TCM and ADO frameworks, the study identifies research gaps and discusses future directions, especially from the perspectives of behavioral economics and critical incidents.
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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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".