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The purpose of this research paper is to identify the sources of job stress and their impact on health of employees.

A total of 650 employees of power sector in Punjab (India) responded to the survey. Exploratory factor analysis and ANOVA were performed. Further, post hoc was conducted to find out which variable differs significantly.

The findings indicates that five parameters, namely workload, working environment, concentration, positivity and future perspective are the factors that are responsible to create stress in employees. There is great impact on health as “frequency of visit to a doctor” and “numbers of diseases” they have are high and “employee's time spared for exercise” is less.

Since the survey was conducted only in power sector, it is difficult to generalize the results. However, the findings from this study will provide the factors that cause job stress and how they impact on health of employees.

The result indicates the impact of job stress on health of employees in power sector. Current research suggests that job stressors should be treated timely to minimize the impact of job stress.

While previous research has focused on the effect of stress on health, the present study provides evidence of the relationship between the sources of job stress and health, particularly in power sector in Punjab. This study would be contributing to the existing literature in Indian context.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The authors of the study find that work stress in the Indian power sector has a negative impact on employee health. Employees experiencing higher levels of work stress have more diseases, visit the doctor more often and have less time to exercise.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Principally, this study aims to test a conceptual framework of the moderating influence of fear of COVID-19 on the following hypothesized relationships (1) quality of work life and bankers' commitment, (2) the mediating spillover effect of job satisfaction in the quality of work life (QWL) and affective commitment relationship.

A quantitative cross-sectional research design is adopted on 318 bankers chosen from four prominent Indian cities. The mediation model is tested through SPSS, PROCESS macro, and AMOS. Conditional process modeling is also administered to test the moderating effect of fear of COVID-19.

The results suggest that the positive effect of QWL on commitment is completely mediated through job satisfaction. Further, the fear induced by COVID-19 negatively moderated the positive direct relation of QWL with commitment and the positive mediating spillover effect of job satisfaction.

The present research is virtually the first to introduce fear of COVID-19 as a psychological construct, to test a moderated mediation model for implications to organizational behavior and human psychology theory and practice. In coalescence of the need satisfaction, spillover, and COR theories, the authors postulate that as spillover between the domains of an individual's life (work, social, financial, personal, and overall life satisfaction) occurs, such effect is calibrated (augmented or attenuated) by the degree of risk/threat/depletion of their resources in the quest for attaining higher valued resources (overall life satisfaction). The moderated mediation mechanism is suggested for replication in other avenues for greater generalizability.

The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.

This paper studies the efficiency of Indian coal-fired thermal power plants (CTPPs) in by-production of electricity and particulates also known as Suspended Particulate Matter (SPM).

A non-radial directional distance function is optimized using data envelopment analysis to enumerate the overall inefficiency of CTPPs and its components in recent times. Further, second-stage regression analysis is conducted to identify factors that affect the inefficiency of plants.

The low inefficiency score for electricity generation suggests that most CTPPs operate close to the good output frontier. A high degree of emissions inefficiency is a challenge for Indian CTPPs. Ever-rising coal use inefficiency is a hindrance to control SPM emissions. The second stage regression analysis concludes that factors like ownership and capacity utilization play vital roles in determining a plant’s inefficiency level. Privately owned CTPPs have performed better in terms of technical inefficiency and emission inefficiency than plants owned by Central and State governments.

To the best of the authors’ knowledge, this study is one of the few published works that benchmark the productive and environmental performance of Indian CTPPs.