A Study on Quality of Work Life of Employees in LPG Bottling Plant

Abstract

Goal: Quality of Work Life (QWL) draws more attention in the present context, and it is a multidimensional construct. The oil and gas industries have realized the significance of employees' QWL to retain and attract a talented workforce in the competitive job market. This study examines the status of QWL of employees in the LPG Bottling Industry.Design / Methodology / Approach: A measuring scale was designed and validated to evaluate the employees QWL working in the LPG bottling plant. The data for the study was gathered from 435 employees working in four LPG bottling industries. Using Exploratory Factor Analysis (EFA), predominant components of QWL are identified. With the Confirmatory Factor Analysis (CFA), the designed scale is validated. With percentage analysis and chi-square analysis, the data was analyzed, and meaningful inferences were drawn.Results: EFA and CFA resulted in four components of QWL with 19 items representing superior model fit. The model fit indices reported from the model namely Chi-Square value = 399.020; CMIN = 2.978, AGFI = 0.900; CFI = 0.937; GFI = 0.915; IFI = 0.938; NFI = 0.909; TLI = 0.920 and RMSEA = 0.068 are in the acceptable range. 51.5% of the respondents expressed to be satisfied with present condition of QWL. The research outcome revealed that among demographical characteristics, nature of activities significantly impacts on the status of QWL of employees. Limitations of the investigation:The data was collected from 435 employees working in four industries because of time constraints.Practical implications: This research's outcome will help the policymakers of LPG Bottling industries to implement QWL interventions for improving the work-life of employees.Originality / Value: The present paper is one among the few studies carried out in the oil and gas sector as minimal research has been done in this area.

The Human Resource Management Practices for the Implementation of TQM in Indian Manufacturing Industries

“…To assess the proposed model, several model fitness indices are verified. In this proposed research model, the results from the data analysis process are: Chi-square/df (CMIN)= 2.94 (<3); RMSEA = 0.079 (<0.08); CFI = 0.901 (>=0.9), TLI = 0.900 (>=0.9), IFI = 0.902 (>0.9), p = 0.000; therefore, the structural model reveals a sufficient model fit to collected data according to Hair et al, 2006 andNanjundeswaraswamy et al,(2022).The tested SEM model is represented in figure 3. From this analysis, it is explored that the probability of getting a critical ratio as large as 10.31 in absolute value is less than 0.001.…”