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The Russia-Ukraine war and other similar conflicts across the globe have heightened risks to the United States of America's (USA's) energy security. However, little is known about the severity of the effect of energy security risks on the USA's quest to attain net-zero emissions targets by 2050. To this end, we examine the effect of energy security risks on the load capacity factor (LCF) in the USA. Employing a time series dataset spinning from 1970 to 2018, the results of the Dynamic Autoregressive Distributed Lag (ARDL) simulations model suggest that energy security-related risk hampers the long-term net-zero emissions targets with its effect decreasing over time until it varnishes in about 5 years time. The results also show that foreign direct investment (FDI) inflows, renewable energy consumption, and green technology have long- and short-run positive effects on the LCF. Conversely, economic expansion and urbanization impede environmental quality by lowering the LCF both in the long run and short run. These findings are upheld by the outcomes of the multivariate quantile-on-quantile regression. Therefore, the study advocates for the consumption of renewable energy, investment in green technologies, and FDI inflows to mitigate energy security-related risks and attain the net-zero emissions targets by 2050 in the USA.

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Since bettering environmental conditions has acquired significant interest globally, discovering factors that may facilitate the establishment of environmental sustainability is currently of foremost importance. Hence, this study considers a sample of 33 members of the Organization for Economic Cooperation and Development and checks whether reducing exposure to different forms of country risks, in the presence of international trade and clean energy consumption, can reduce their respective carbon footprint levels. Utilizing annual data from 2000 to 2018 and employing methods that handle problems related to dependence across cross-sectional units and heterogeneity of slope coefficients, the findings endorse that (a) reducing financial and political risks abate carbon footprints, (b) economic risk exposure does not influence carbon footprints, (c) international trade exerts carbon footprint-boosting effects, and (d) undergoing unclean to clean energy transition curbs carbon footprints. Accordingly, the concerned governments should these findings into account while conceptualizing green environmental policies in the future.

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FDI inflows remain an important source of economic growth and technology transfer for developing countries. However, the proponents of the pollution haven hypothesis (PHH) argue that FDI inflows may result in the production of polluted goods in poor economies. The empirical testing of PHH reveals conflicting outcomes on the subject. This study argues that foreign firms' choice of specific technologies and hence the validity of PHH can be determined by host countries' level of education. For developing economies having low levels of schooling, FDI inflows will accompany polluted technologies. Nonetheless, when education levels exceed certain thresholds, FDI inflows may reduce CO2 emissions. For our empirical investigation, we rely upon a large panel of 108 developing countries during 2000-2016. Our estimated outcomes, based on the panel cointegration method and panel vector error correction methods (P-VECM), confirm these moderating effects of human capital in the FDI-CO2 emissions nexus. The empirical results also confirm the presence of the environmental Kuznets curve (EKC) for developing countries. These results have important policy implications for the sample economies.

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Medical errors have been identified as one of the greatest evils in the field of healthcare, causing millions of patient deaths around the globe each year, especially in developing and poor countries. Globally, the social, economic, and personal impact of medical errors leads to a multi-trillion USD loss. Undoubtedly, medical errors are serious public health concerns in modern times, which could be mitigated by taking corrective measures. Different factors contribute to an increase in medical errors, including employees' risk of burnout. Indeed, it was observed that hospital employees are more exposed to burnout situations compared to other fields. In this respect, managing hospital employees through transformational leadership (TL) may reduce the risk of burnout. However, surprisingly, studies on the relationship between TL and burnout are scarce in a healthcare system, indicating the existence of a critical knowledge gap. This study aims to fill this knowledge gap by investigating the role of TL in reducing the risk of burnout among hospital employees. At the same time, this study also tests the mediating effects of resilience and role clarity with the conditional indirect effect of intrinsic motivation in the above-proposed relationship. To test different hypotheses, a hypothetical model was developed for which we collected the data from different hospital employees (n = 398). Structural equation modeling (SEM) was considered for statistical validation of hypotheses confirming that TL significantly reduces burnout. The results further indicated that resilience and role clarity mediate this relationship significantly. Lastly, the conditional indirect effect of intrinsic motivation was also confirmed. Our results provide meaningful insights to the hospital administrators to combat burnout, a critical reason for medical errors in hospitals. Further, by incorporating the TL framework, a hospital may reduce the risk of burnout (and, hence, medical errors); on the one hand, such a leadership style also provides cost benefits (reduced medical errors improve cost efficiency). Other different theoretical and practical contributions are discussed in detail.

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