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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66739
Volume:
10 |
8 |
Aug 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Bank Management
Guru Nanak College (Autonomous), Chennai
PG Department of Commerce
Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), Chennai
PG & Research Department of Commerce
Guru Nanak College (Autonomous), Chennai
PG & Research Department of Commerce
Guru Nanak College (Autonomous), Chennai
Corporate Secretaryship
Chevalier T. Thomas Elizabeth College for Women, Chennai, Tamil Nadu
This study empirically examines how fraudulent activity and procedural difficulties on online recruitment platforms influence the employment opportunities of fresh graduates. A descriptive and analytical research design was adopted. Primary data were collected from 149 respondents comprising final-year students and recent graduates through a structured questionnaire administered using a five-point Likert scale, combining 82 responses gathered through Google Forms and 67 through offline questionnaires. Non-probability convenience sampling was employed. Data were analysed using percentage analysis, frequency distribution, Pearson correlation, and simple linear regression (SPSS). Both online job portal frauds (r = .405, p < .001) and application-process challenges (r = .445, p < .001) were found to have a statistically significant, positive association with respondents' employment-opportunity scores. Regression results indicate that job portal frauds explain 16.4% of the variance in employment opportunities (R² = .164, F(1, 147) = 28.807, p < .001), while application challenges explain 19.8% of the variance (R² = .198, F(1, 147) = 36.304, p < .001). The findings support the case for stronger employer-verification systems, simplified application interfaces, and structured awareness programmes to protect freshers and to preserve confidence in digital recruitment channels. While prior literature has separately examined recruitment-fraud detection techniques and the operational benefits of e-recruitment, empirical evidence linking both fraud perception and application friction to the employment prospects of fresh graduates remains scarce. This study addresses that gap using primary survey data and regression-based evidence..
KEYWORDS
This study provides empirical evidence that both fraud exposure and application-process friction are significantly associated with the job-search experience of fresh graduates using online recruitment platforms. While online portals continue to offer convenient and wide-reaching access to employment opportunities, the persistence of fraudulent postings and cumbersome application procedures represents a meaningful, quantifiable barrier that platform operators, employers, and policymakers should not treat as a peripheral concern. Strengthening employer-verification systems, simplifying application workflows, and expanding structured awareness programmes are practical, evidence-based interventions that could improve both the trustworthiness and the usability of online recruitment for fresh graduates. Future research using longitudinal designs and verified (rather than self-reported) employment outcomes would help clarify the causal pathways underlying the associations identified here.
1. Ahjaz, A. (2023). A study on the impact of online job portals on employee performance and recruitment efficiency. International Journal, 10(8). 2. Akram, N., Irfan, R., Al-Shamayleh, A. S., Kousar, A., Qaddos, A., Imran, M., & Akhunzada, A. (2024). Online recruitment fraud (ORF) detection using deep learning approaches. IEEE Access, 12, 109388–109408. 3. Alghamdi, B., & Alharby, F. (2019). An intelligent model for online recruitment fraud detection. Journal of Information Security, 10, 155–176. 4. Ansar, S., & Hussain, S. (2025). Effect of online job scams on trust and dependence on digital platforms. Journal of Political Stability Archive, 3(3), 1299–1310. 5. Ashritha, V., Yeshwanth, D., Mohammed, M., Kulkarni, R., & Krishna Jyothi, K. (2025). Fake job recruitment detection using machine learning approach. Available at SSRN 4836075. 6. Bhandarkar, S. (2022). Study on usefulness and problems of recruitment portals. 7. Bhushan, P. (2024). The digital transformation in recruitment: Exploring the effect and challenges of online recruitment. Available at SSRN 4885182. 8. Dutta, S., & Bandyopadhyay, S. K. (2020). Fake job recruitment detection using machine learning approach. International Journal of Engineering Trends and Technology, 68(4), 48–53. 9. Fernando, A. N., Singh, N., & Tourek, G. (2023). Hiring frictions and the promise of online job portals: Evidence from India. American Economic Review: Insights, 5(4), 546–562. 10. Gayathri, B. J., & Sweety, R. (2024). Perception of job seekers on recruitment through online job portals. International Journal for Multidisciplinary Research, 6(2).
Publication Date
8/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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