مطالب

The paper’s purpose was to investigate the obstacles the Zimbabwean government faces as it works towards meeting Sustainable Development Goal 3, which speaks of health and well-being for all. Various obstacles were observed, such as political and economic issues, personnel leaving for greener pastures, dilapidated infrastructure, and a lack of monitoring and evaluation systems that allow tracking of the goals. The author used a qualitative method and adopted a document review for data collection. Three major documents were used: The Ministry of Health and Child Care’s national policy (2021-2025), the World Health Organization 2023 report, and UNDP’s 2020 Zimbabwe’s SDG Progress report. The researcher scanned through the documents and highlighted areas where they discussed the SDG 3 challenges faced. The results confirmed that Zimbabwe is facing numerous challenges, including a fragmented procurement system and political and economic issues. The study's practical implications are that this document may remind policymakers that the Sustainable Development Goals, especially SDG 3, cannot be ignored, but effort is needed to ensure that all obstacles impeding the attainment of SDG 3 are addressed. Policymakers should provide a conducive environment that allows the ministries concerned to work towards the attainment of SDG 3. Healthy people are productive, and the focus will be on improving everyone's life, hence the need for SDG 3 to be fulfilled so no one is left behind. Significant progress is made when people are protected from illness, premature death is avoided, and the overall health of the population is improved. Issues such as inequalities and poverty are eradicated, and people enjoy prosperity and justice. The study is original and seeks to contribute to the body of knowledge regarding SDG 3, the challenges Zimbabwe is facing, and how they can be addressed to protect its citizens from diseases, improve prosperity, and enhance socio-economic factors.

According to statistics from the Ministry of Interior of Iran, more than 75% of the waste produced in the country is landfilled. Many of the programs proposed by waste management organizations and municipalities have not been effective due to the failure to consider the impacts of various economic and non-economic variables on waste generation. Therefore, this study aims to increase the effectiveness of proposed waste management programs for Tehran in line with sustainable development. An empirical modeling approach was used, utilizing 120 months of data (April 2011 to March 2021) to develop models for predicting different types of waste generation. Additionally, the statistical relationship between 32 macroeconomic variables, including industry and mining, agriculture, urban management, population, and climate, and five waste generation variables was examined at a 90% confidence level. The results indicate that 79% of the variations in the total waste generation tonnage, 73.4% of the variations in the mixed waste tonnage at the source, 80.3% of the variations in the separated dry waste tonnage at the source, and 81.4% of the variations in the construction and demolition waste tonnage in Tehran can be predicted using the models developed in this study. 

The main goal of this research was to design a green marketing model based on the emotional intelligence of Iran's oil industry managers. This research was conducted based on a mixed-methods approach, incorporating both qualitative and quantitative phases. In the first stage, the research was classified as qualitative with an exploratory approach, and in the second stage, it was descriptive-quantitative-survey research. In the qualitative phase, the purposeful and snowball sampling method was employed based on the saturation rule by conducting 18 interviews with managers of companies under the Ministry of Petroleum and university marketing professors. The data were analyzed using the Strauss and Corbin coding method and MaxQDA2020 software, and finally, the research paradigm model was presented. In the quantitative part, 384 managers and employees of Iran's oil industry were selected by stratified random sampling. The obtained model was validated using the partial least squares method and Smart PLS software. The research results indicated a positive and significant effect of causal conditions on the central phenomenon, as well as a positive and significant effect of background conditions, the central phenomenon, and intervention conditions on strategies. Also, strategies were found to have a positive and significant effect on the consequences of green marketing based on the emotional intelligence of managers.