PurposeThis study was designed to investigate the impacts of work-family role conflict on job and life satisfaction among three major professionals: doctors, engineers and university teachers. Data were collected through a face to face survey on 60 doctors, 60 engineers and 60 university teachers of different public and private institutes of Bangladesh.Design/methodology/approachConducted data analysis were statistical analysis of questionnaires (mean, SD, max, min), descriptive analysis (%), t-test, analysis of variance test, correlation analysis and regression analysis.FindingsThe results demonstrate that the university teachers had experienced more work-family conflict (WFC) on job satisfaction and family-work conflict (FWC) on job and life satisfaction than doctors and engineers; however, engineers experienced more WFC in the case of life satisfaction. The study also implied that control variables such as gender identification, reported number of children, marital status, education level and adhered religion had significant impact (p < 0.05) on WFC, FWC, job satisfaction and life satisfaction.Originality/valueThis study will provide insight into the effects of spouse, supervisor and number of children on both job and life satisfaction.

Newly, the rates of energy and material consumption to augment industrial production are substantially high, thus the environmentally sustainable industrial development has emerged as the main issue of either developed or developing countries. A novel approach to supply chain management is proposed to maintain economic growth along with environmentally friendly concerns for the design of the supply chain network. In this paper, a new green supply chain design approach has been suggested to maintain the financial virtue accompanying the environmental factors that required to be mitigated the negative effect of rapid industrial development on the environment. This approach has been suggested a multi-objective mathematical model minimizing the total costs and CO2 emissions for establishing an environmentally sustainable closed-loop supply chain. Two optimization methods are used namely Epsilon Constraint Method, and Genetic Algorithm Optimization Method. The results of the two mentioned methods have been compared and illustrated their effectiveness. The outcome of the analysis is approved to verify the accuracy of the proposed model to deal with financial and environmental issues concurrently.

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