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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Paper ID:IJSREM67013

AN EMPIRICAL STUDY ON RESUME SCREENING AND RECRUITMENT EFFECTIVENESS AT ABSERVETECH CONSULTANCY PVT. LTD.

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM67013

Volume:

10 |

8 |

Aug 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM67013

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.

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Authors

MVM

Ms. Vincy Mary.J

Department of Management Studies

Vels Institute of Science, Technology and Advanced Studies (Vistas), Pallavaram, Chennai, India.

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DK

Dr.R.Senthil Kumar

Department of Management Studies

Vels Institute of Science, Technology and Advanced Studies (Vistas), Pallavaram, Chennai, India.

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Abstract

Recruitment is a critical human resource activity because the quality of employees entering an organization influences productivity, service quality and long-term growth. This study examines resume screening and recruitment practices at Abservetech Consultancy Pvt. Ltd., with particular attention to fairness, transparency, standardized screening criteria, job-related qualifications, human resource practices and technology-supported recruitment. A descriptive research design and quantitative approach were adopted. Primary data were collected from 50 respondents comprising HR managers, recruiters, talent acquisition specialists, employees and students connected with recruitment activities. Convenience sampling was used and responses were obtained through a structured five-point Likert-scale questionnaire. The data were analyzed using frequency and percentage analysis, Cronbach’s Alpha reliability testing and Chi-Square tests. The recruitment and resume-screening scale showed excellent reliability (α=0.921), the HRM practices scale also showed excellent reliability (α=0.911), and the resume-screening criteria scale showed acceptable reliability (α=0.764). Respondents emphasized transparent recruitment, timely communication, merit-based assessment, unbiased screening and standardized criteria. The Chi-Square tests reported no statistically significant association between gender and perceptions of fair recruitment, or between work experience and perceptions of the importance of relevant experience in resume screening. The study concludes that technology can improve recruitment efficiency, but it should be implemented together with standardized procedures, ethical safeguards and human oversight.

KEYWORDS

Resume Screening Recruitment Applicant Tracking System Artificial Intelligence Human Resource Management Recruitment Effectiveness

Cite This Article

Ms. Vincy Mary.J, Dr.R.Senthil Kumar, "AN EMPIRICAL STUDY ON RESUME SCREENING AND RECRUITMENT EFFECTIVENESS AT ABSERVETECH CONSULTANCY PVT. LTD.," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 8, pp. 1-5, Aug 2026. https://doi.org/10.55041/IJSREM67013

Full Article/Conclusion

The study demonstrates that effective resume screening is closely associated with fairness, transparency, standardization and job-related evaluation. Respondents value objective screening based on qualifications and competencies. The reliability results support the internal consistency of the measurement scales, while the Chi-Square tests indicate no significant association for the two demographic relationships examined. Overall, Abservetech can strengthen recruitment effectiveness by combining technology-supported screening with standardized procedures, equal opportunity, ethical safeguards and human judgement.

References

[1]  Alsharif, A., et al., “Artificial intelligence-supported recruitment systems and hiring efficiency,” Journal of Human Resource Technology, vol. 12, no. 2, pp. 88–103, 2024. [2]  Fofanah, A., “Algorithmic friction in automated resume screening systems,” International Journal of Artificial Intelligence in Human Resources, vol. 5, no. 1, pp. 72–86, 2026. [3]  González-Morales, O., S. Martín-López, and O. Góngora-Larequi, “Artificial intelligence in recruitment and personnel selection: A systematic literature review,” Human Resource Management Review, vol. 36, no. 1, Art. no. 100945, 2026. [4]    Gupta, R., and P. Sharma, “Resume screening practices in recruitment consulting firms in India,” Indian Journal of Human Resource Management, vol. 29, no. 2, pp. 145–160, 2022. [5]   Kaur, H., and R. Singh, “Recruiters’ perspectives on automated resume screening,” International Journal of Human Resource Studies, vol. 12, no. 3, pp. 75–89, 2022. [6]  Kumar, S., and V. Reddy, “Impact of applicant tracking systems on recruitment effectiveness,” Journal of Human Capital Development, vol. 15, no. 2, pp. 110–124, 2023. [7]  Mishra, A., and S. Verma, “AI-based resume screening in talent acquisition: Opportunities and challenges,” International Journal of Management and Technology, vol. 18, no. 1, pp. 41–55, 2023. [8]   Nawaz, N., and A. M. Gomes, “E-recruitment techniques and resume screening strategies in modern organizations,” Journal of Organizational Effectiveness, vol. 8, no. 4, pp. 289–304, 2021. [9]     Parry, E., and S. Strohmeier, “Digital transformation in recruitment and selection,” Employee Relations: The International Journal, vol. 43, no. 6, pp. 1355–1372, 2021. [10]  Rajwar, R., and P. Malik, “Artificial intelligence applications in recruitment and selection: A systematic review,” International Journal of Human Resource Management, vol. 37, no. 2, pp. 201–220, 2026. [11]    Santiago-Torner, M., “Artificial intelligence in personnel selection: A scoping review,” Personnel Review, vol. 55, no. 1, pp. 1–22, 2026. [12]  Shree Priya, R., and M. Divyaranjani, “Applicant tracking systems and automated resume screening: Impact on hiring effectiveness,” Asian Journal of Management Research, vol. 17, no. 1, pp. 56–69, 2026. [13]  Van Esch, P., and J. S. Black, “Artificial intelligence in recruitment and selection: A review of adoption and implications,” Human Resource Management Review, vol. 30, no. 4, Art. no. 100708, 2020. [14]  Wilson, J., et al., “The impact of AI recommendations on human resume screening decisions,” Computers in Human Behavior, vol. 156, Art. no. 108258, 2026. [15]  Xu, Y., K. Yamamoto, and A. Morishima, “Automated resume screening using large language models: A privacy-preserving framework,” Expert Systems with Applications, vol. 270, Art. no. 126612, 2026.

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Publication Date

8/30/2026

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Double-Blind Peer Review

Review Rounds: 2

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