The mediating role of financial management skills: Examining the impact of e-government adoption and social support on financial resilience
Bibliographic record
Abstract
In today's rapidly changing economic landscape, financial resilience has become increasingly important especially for public sector organizations. This study investigates the impact of e-government adoption and social support on individuals' financial resilience in Indonesia, with a focus on the mediating role of financial management skills. A quantitative research methodology was employed, and 348 complete and suitable questionnaires from individuals in the financial department in local government in Indonesia were analyzed using SmartPLS 4.0 software. The results indicate a significant relationship between e-government adoption and financial management skills, suggesting that digitizing government services contributes to improved financial resilience. Additionally, social support was found to have a positive impact on financial management skills, supporting the notion that social networks provide resources and support for financial well-being. Financial management skills were also found to be significantly associated with financial resilience, indicating that individuals with strong financial management skills are better equipped to adapt to changing circumstances. While the mediating effect of financial management skills between e-government adoption and financial resilience was not significant, it was significant in the relationship between social support and financial resilience. These findings provide insights into the factors that enhance financial resilience in an increasingly digitized society and inform strategies to promote financial well-being in Indonesia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".