The Effects of ICT/e-Government on Migrant Workers' Remittance Inflows in Bangladesh: An Empirical Study
Bibliographic record
Abstract
This research article has explored and examined the effects of ICT/e-Government measures and some other significant socioeconomic factors on migrant workers’ remittance inflows in Bangladesh; Sustainable development approach is very much related to the economic growth that can be achieved by higher remittance inflows and related factors such as ICT/e-Government measures. So far, the effects of Information and Communication Technology (ICT) and e-Government measures on remittance inflows have not been explored adequately in the case of Bangladesh. The literature review shows the effects of ICT/e-Government along with the unemployment rate, the inflation rate, institutional quality, the number of recruiting agencies, the number of banks and financial institutions, financial development, remittance transaction cost, cash incentives as well as the currency exchange rate on the remittance inflows of Bangladesh. The article has been examined using a mixed methods (MM) approach. Secondary data from the World Bank and other institutions were collected for regression analyses using model equations and SPSS. Additionally, a total of 12 people involved in 12 different organizations were interviewed for collecting qualitative data for the thematic analysis; the analysis was conducted using NVIVO. After testing the hypotheses and after triangulation of quantitative and qualitative studies, it has been found that the use of ICT/e-Government measures and some other factors have significant positive effects on the remittance inflows of Bangladesh. Nonetheless, the effects of the number of recruiting agencies and remittance transaction cost on the remittance inflows did not resonate with the research hypotheses. Research findings show that the National ICT Policy and Overseas Employment Policy may also play roles in remittance inflows.
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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 | 0.002 |
| 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) | 0.005 | 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".