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This 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.

Conducted data analysis were statistical analysis of questionnaires (mean, SD, max, min), descriptive analysis (%), t-test, analysis of variance test, correlation analysis and regression analysis.

The 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.

This study will provide insight into the effects of spouse, supervisor and number of children on both job and life satisfaction.

The purpose of this paper is to investigate the benefit of critical success factors (CSFs) clustering in different phases of make-to-order (MTO) projects and develop standards for management.

This study is based on a questionnaire survey. First of all, collecting data by structured interviews, relying on a questionnaire and second from leader contractors who are active in the engineering and steel industry (in Iran). So, the requirements and objective of the research are presented to the top management of MTO projects to gain their support in data collection. Then 20 CSFs were identified by the literature review so a questionnaire survey was prepared for the CSFs assessment and interview with the experts. Finally analyzing the importance and performance of CSFs in project phases and cluster them in different project phases with self-organizing map as one of the artificial neural network (ANN) approaches due to high predictive accuracy. Review the research result with the top management of MTO project and examine the results obtained from neural networks and validation indices.

Cluster analysis shows that the implementation phase is the most important stage in MTO organizations and the other phases like feasibility and start-up, design and planning, delivery and end-phase should be also considered as effective phases in determining the level of organization performance. Different industries with additional data at different periodic times will verify the result. Furthermore, testing the other ANN model will improve risk analysis and could shift this classification approach to a regression type.

The main limitation of the research is related to the sample. Research findings are limited to the time of data collection so validity is limited to the mentioned time. Different industries with additional data will verify the result. Furthermore, testing different ANN models such as K-MEANS, non-negative matrix factorization (NMF) analyses will improve risk analysis and could meet different classification results to find gaps.

In this paper, CSF and project phase dimensions are viewed together which is necessary to meet better results for simplifying social and economic benefits. Merge the new findings and latest technologies could prepare the best results and enable managers to create a better framework or implement key factors for minimizing waste.

This paper moves the definition of MTO organizations beyond measuring cost, complexity and financial variables by clustering CSFs in different phases of projects. So, the results enable managers to use this concept in their daily production to minimize waste and could be implemented to efficiently choose factors.