The influence of financial behavior in mediating financial satisfaction: Systematic literature review
Bibliographic record
Abstract
This research is motivated by the low level of financial welfare among lecturers, which is influenced by the complexity of economic factors, financial behavior, and the development of financial technology. In the context of Muslim society, variables play a very important role in shaping financial satisfaction, especially if mediated by healthy financial behavior. The approach used is Systematic Literature Review (SLR) with the PRISMA protocol, which includes a literature search on the Google Scholar database using the Publish or Perish tool and Bibliometric and VOSviewer analysis of publications during 2014–2024 as many as 127 articles. The four independent variables have a positive influence on financial satisfaction, either directly or indirectly through financial behavior, with sharia financial literacy and financial technology occupying the most dominant position. The integration of the four variables in a single model makes a theoretical contribution to the development of a conceptual framework that integrates cognitive, behavioral, technological, and religious value dimensions. In this paper, the variable of qona'ah attitude is used which is rarely used in the concept of financial satisfaction. This study is mainly in data sources that only include open access literature in the 2014–2024 timeframe, which has the potential to ignore important findings from paid articles or publications prior to that period. For further research, it is recommended to test this mediation model in cross-border and cultural populations, as well as the exploration of the integration of other psychological variables such as financial self-efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".