Exploring Income and Employment Outcomes in Digital Training Programs: A Gender Perspective

Clicks: 7
ID: 334214
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #508 of 1,064 articles by views in Annals of Human and Social Sciences

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,064 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
This study intends to investigate the fact that whether digital training generates equal or relatively equal financial benefit in the form of post training incomes or not. This paper helps to substantiate this notion for policy makers to therefore, look into deeper side of the story that can explain this biasedness. Although the investment in training digital skills has been immense, the disparities in how males and females participate in the job market as well as their earnings have remained an immense problem in the rapidly growing digital economy of Pakistan. This paper executes the administrative and survey data of PSDF to run a Quantitative Analysis. This research approach engaged 253 participants who have undergone at least one type of digital training offered by PSDF platform in the past two years that is 2024 and 2025. The paper takes gender as the independent variable while earnings and employment are the dependent variables. In order to substantiate the significant differences in income and employment, a Multivariate Analysis of Variance (MANOVA) is used and then the effect of gender is also determining each of the dependent variables separately also. According to the MANOVA test results, the joint influence of gender on post-training employment and salary is statistically significant at a 10% level. According to univariate analysis, the significant difference caused by gender is due to salary and not employment. Employment status is not influenced by gender, although post-training salary is statistically affected by gender. This means that men and women receive different salaries for similar training in digital platforms. The lesson is that what the government and companies should do is tighten their belts: implement more strict pay-equity legislation, penalize the firms, and initiate campaigns of cultural change in case they desire actual gender parity. Altogether, the study provides tangible evidence that may be valuable to redesign the workforce development strategies in the new digital economies and rethink them.
Reference Key
imported_1793226749_6ae277fdbc2eb Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal Annals of Human and Social Sciences
Year 2026
DOI
10.35484/ahss.2026(7-II)05
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.