Today's competition is among supply chains rather than enterprises as independent actors. Additionally, the success of the actors within the SC network, through the improvement of the global performance, depends on how well they handle the growing environmental problems. For this reason, much attention is given to the greening concept. This paper aims to investigate the Green Human Resource Management (GHRM) impact on Green Supply chain Management (GSCM) in a strategic sector, namely the pharmaceutical sector. Our interest to deal with this issue was aroused by the fact that there are no studies exploring the causality relationships in the pharmaceutical sector in Saudi Arabia. Based on deductive methodology, a questionnaire has been developed. A research sample included 109 pharmaceutical companies operating in KSA. The results highlight a significant impact of GHRM on GSCM practices. In other words, training and performance appraisal, recruitment, and eco-behavior-based rewards influence GSCM practices positively. Based on the results, the study provides new theoretical insights and practical suggestions.

There are many researches on project selection field, but few of them have considered environmental criteria in their studies. Moreover, there are many articles in evaluating risk but there is no article that considers value at risk concept to evaluate the amount of risk in multi project selection. We propose a multi objective mathematical model to address a situation in which several projects are candidate to be invested completely or partially. Three objective functions are considered in this paper. The first objective maximizes sum of the net present value of pure cash flow obtained from selected projects. In this objective, we consider the factor of time and its impact on value of money. In addition, we use the concept of value at risk (VAR) as the present value for the first time in project selection problems. Although green projects are more interesting, there are few articles, which address environmental issues. Hence, we consider the objective, which are related to environmental issues as the final criterion. Multi-Objective Differential Evolution algorithm (MODE) algorithm is applied to solve a problem, which is known as robust and efficient algorithm. Then computational results are compared with solutions obtained by NSGA-II algorithm which is well-known algorithm in this field with respect to seven comparison metrics.