Impact of Employee Welfare Measures on Workforce Well-Being in SBI: Insights from the Public Banking Sector
Authors
Dr. D. Appala Raju
Assistant Professor AKNUCE, Adikavi Nannaya University, Rajamundry (IN)
Dr. P. Sree Devi
Assistant Professor JNTUGV, Vizianagaram (IN)
Article Information
DOI: 10.51583/IJLTEMAS.2025.1411000003
Subject Category: Human Resource Management
Volume/Issue: 14/11 | Page No: 28-40
Publication Timeline
Submitted: 2025-11-29
Published: 2025-12-02
Abstract
Abstract: The physicochemical properties of the premium motor Spirit (PMS) and Automotive Gas Oil (AGO) were determined to ascertain with each other and their compliance with American Society for Testing Materials (ASTM) standards and the Nigerian Midstream and Downstream petroleum Regulatory Authority (NMDPRA). The properties studied for NNPC and Zone 4 oil depots results obtained were respectively as follows: density 0.7445, 0.7425, Research octane number 91.8, 93.1, ethanol content was absent for both petroleum depots samples, distillation test at the initial boiling point is 34, 30, at the final boiling point were 181, 181 for both NNPC and zone 4 depots samples, benzene content were 1.0, 0.9, Sulfur content test 0.0275, 0.0215 and Reid Vapour pressure 49.5, 49.0, the study revealed that the PMS quality was within the ASTM and NMDPRA requirements for both NNPC and zone 4 depots and has positive effect on motor engines. AGO samples from two different depots (NNPC and Hudson) was analyzed. The parameters analyzed and the results obtained as follows; density test 0.8530 and 0.8404, flash point 69, 70, distillation at the initial boiling point 127, 80 for NNPC and Hudson oil depots, diesel Index 38.2, 42.8, cetane number 37.9, 46.2, kinematic viscosity 3.324, 3.144, sulfur content 0.0740, 0.0475, Acidity were all within the ASTM and NMDPRA specifications for PMS for both NNPC and Hudson depots. Hudson depot cetane number analyzed was in compliance with the regulatory authority standards while NNPC depot cetane number, and carbon residue were off specifications. There was deviation in the diesel index number and carbon residue, distillation test for both NNPC and Hudson oil depots for AGO samples will have adverse effect on motor engine. Based on the research studied, the AGO might have been poorly refined or adulterated and could constitute problems to automobile engines if utilized. It is imperative that regular quality tests be conducted randomly to check depots petroleum products compliance with the required standards.
Keywords
Welfare schemes, Socio-culture, work life balance, Employee well-being
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References
1. Kumar, G. S. A., and Kumar, K. A. (2018)., "A Study on Labour Welfare Measures in Singareni Collieries Company Limited", International Journal of Engineering Technology Science and Research, 5(3), 1376-1382. [Google Scholar] [Crossref]
2. SVaradaraj, A., and Charumathi, D. (2019)., "Impact of Welfare Measures on the Quality of Employees Performance with Special reference to Construction Industry", International Journal of Management Science and Business Administration, 5(2), 30-36 [Google Scholar] [Crossref]
3. Kumari, K. P., and Kannan, R. (2018)., "A Study on Statutory Labour Welfare Measures in Garment Industry", International Journal for Research Trends and Innovation, 3(2), 45-48. [Google Scholar] [Crossref]
4. Yamane, Taro. 1967. Statistics: An Introductory Analysis, 2nd Ed., New York: Harper and Row. [Google Scholar] [Crossref]
5. Shaik Rahamath Bee.2017. Intellectual Capital Management in Institutions of Higher Learning in Select Universities of Andhra Pradesh, an unpublished thesis. [Google Scholar] [Crossref]
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