Assessing the Impact of HRM Practices on Employee Absenteeism with Reference to Remote Employees

The study aims to explore the effect of three key HRM practices—Consistency, Distinctiveness, and Consensus—on reducing absenteeism in the workplace. It seeks to understand how these practices influence employees’ attendance and whether they can significantly lower absenteeism rates. The responses were collected from 604 participants using a structured questionnaire. The sample primarily consisted of individuals aged 25-44 from the IT, Marketing, and Finance departments, with most respondents occupying mid-level positions. Data were analyzed using SPSS for descriptive statistics and structural equation modelling with partial least squares (PLS-SEM) to examine the relationships between the factors and test the hypotheses. The study indicates a substantial impact of HRM practices on reducing absenteeism rates. structural equation modeling (SEM) confirms significant positive relationships between Consistency, Distinctiveness and Consensus with reduced absenteeism. Reliability and validity assessments demonstrate high reliability and strong validity for all constructs. The findings suggest that consistent, distinctive, and consensual HRM practices significantly reduce absenteeism among employees.

Authors

Institutions

Publication Details

Journal
International Review of Management and Marketing
Published
2025-10-13
DOI
https://doi.org/10.32479/irmm.19548
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the Impact of HRM Practices on Employee Absenteeism with Reference to Remote Employees

Manish Verma, Ashish Ranjan Sinha
International Review of Management and Marketing
Occupational Health and Safety Research
article

Assessing the Impact of HRM Practices on Employee Absenteeism with Reference to Remote Employees

Manish Verma, Ashish Ranjan Sinha
article en

Abstract

The study aims to explore the effect of three key HRM practices—Consistency, Distinctiveness, and Consensus—on reducing absenteeism in the workplace. It seeks to understand how these practices influence employees’ attendance and whether they can significantly lower absenteeism rates. The responses were collected from 604 participants using a structured questionnaire. The sample primarily consisted of individuals aged 25-44 from the IT, Marketing, and Finance departments, with most respondents occupying mid-level positions. Data were analyzed using SPSS for descriptive statistics and structural equation modelling with partial least squares (PLS-SEM) to examine the relationships between the factors and test the hypotheses. The study indicates a substantial impact of HRM practices on reducing absenteeism rates. structural equation modeling (SEM) confirms significant positive relationships between Consistency, Distinctiveness and Consensus with reduced absenteeism. Reliability and validity assessments demonstrate high reliability and strong validity for all constructs. The findings suggest that consistent, distinctive, and consensual HRM practices significantly reduce absenteeism among employees.

International Review of Management and MarketingVol. 15(6)
National Institute of Technology Patna (IN)
Openalex Percentile: Top 59%
Occupational Health and Safety Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Assessing the Impact of HRM Practices on Employee Absenteeism with Reference to Remote Employees — Manish Verma, Ashish Ranjan Sinha · International Review of Management and Marketing (2025) | TGRS Research Map | TGRS