Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously, of the population’s exposure to pollution. This paper considers some realistic assumptions for the first time, including location-routing problem, time window-based green vehicle routing problem, vehicles scheduling, vehicles failure, split delivery, population risk, and load-dependent fuel consumption to manage both infectious and non-infectious medical waste. We apply a fuzzy goal programming approach for solving the proposed bi-objective model, and the efficiency of the proposed model and solution approach is assessed using data related to 13 nodes of medical waste production in a location west of Tehran.
Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the heterogeneous population are among the practical assumptions in the proposed approach. Real-world data is used to demonstrate the efficiency and effectiveness of the mathematical programming approach proposed in this study.
Typically, the lack of effective stakeholder participation in a project-especially in the initial planning and implementation stages-has a negative impact on the expected performance of the project. These negative consequences require attempts to encourage their effective participation. Nevertheless, there are some challenges ahead, such as conflict of interest among the stakeholders. For more accurate identification of the interests, objectives, and performance of the stakeholders, this paper proposes an accurate and organized model for the analysis of results from the stakeholder impact index. We implemented the proposed model to determine the existing barriers to renewable energy development in Iran, specifically the wind and solar energy sectors. For data collection, we used the opinions of the experts and other people involved in these industries. Data analysis showed that the current implantation conditions of the solar and wind energy sectors were similar from the stakeholders' perspectives as not bad but poor. The required position of each stakeholder to lift the barriers and develop these industries was identified and their current positions from the desirable conditions were assessed. Finally, some recommendations were presented to improve the stakeholders' conditions and eliminate the barriers.
Enterprise risk management (ERM) has emerged as a more integrated risk management (IRM) framework in recent years. Many studies have been conducted in recent years to determine the effects of ERM implementation on other parts of an organization. The purpose of this research was to explore the relationship between ERM implementation and organizational performance. The research sample consisted of Iranian banks that either had a license from the central bank of Iran (CBI) or were active in the stock market. A novel measure of ERM implementation was employed in this study. Furthermore, the return on equity (ROE) and Tobin's Q ratio were used as two measures of organizational performance. The results showed that there was a positive and significant relationship between ERM implementation and Tobin's Q ratio, whereas such a significant relationship was not observed between ERM implementation and ROE. The study findings suggested that the adoption of an ERM strategy influences the long-term performance of a firm, not its short-term performance.
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