Climate change dynamics for global energy security and equity: Evidence from policy stringency drivers.

This study investigates the dynamic interplay between financial integration, political stability, infrastructure, and global integration in enhancing Energy Security (ES) and Energy Equity (EE) across 50 economies from 2006 to 2018. It addresses gaps in understanding how socio-economic, political, and technological factors collectively influence ES and EE during the global transition from fossil fuels to renewable energy sources. The research aims to reveal the complex relationships and potential trade-offs between energy sustainability, economic growth, and equitable energy distribution. Utilizing robust panel data methods including System GMM, Fixed Effects, and Random Effects, the study examines the impacts of various determinants on ES and EE. The dataset includes annual observations on global integration, financial integration, infrastructure quality, political stability, and other relevant metrics from diverse global sources. The findings reveal that increased financial integration significantly enhances ES by easing capital flow into energy infrastructure, which is crucial for stable energy supply chains. Political stability also positively affects ES, underscoring the importance of stable governance in sustaining energy policies. Conversely, rapid urban growth and inadequate social integration pose challenges to achieving EE, highlighting disparities in energy access worsened by urbanization. Technological advancements and digital connectivity appear as positive drivers for EE, enhancing the efficiency and distribution of energy resources. This study contributes to the literature by providing a detailed examination of how integration into global financial and political systems affects energy strategies at a national level. It offers valuable insights for policymakers on fostering environments conducive to sustainable energy development and fair energy access. The research underscores the importance of incorporating socio-economic and technological advancements in energy policy frameworks to achieve balanced growth and sustainability. Future research directions include exploring the causal relationships and long-term impacts of these factors on ES and EE, particularly in the context of evolving global energy policies and technological advancements.

In Search of Optimal Practice: A Retrospective Comparative Study of Single- Versus Dual-Venous Anastomosis in Microvascular Flaps.

Background In the current era of reconstructive surgery, microvascular free flap transfers are the most popular reconstructive procedures performed. The main reason for the failure of the flap and re-exploration is venous thrombosis. Traditionally, most surgeons prefer performing two-vein anastomoses. There is insufficient literature to support that dual-venous anastomosis is better than single-venous anastomosis. In this study, we compared the success rate of single-venous anastomosis with dual-venous anastomosis of different free flap reconstructions. Methodology The retrospective cohort study was conducted with a total of 101 patients. Eighty-three were in the one-vein group, and the remaining 18 were in the two-vein group. Outcomes were compared between the two groups regarding re-exploration and flap failure. Results The overall success rate of free flap reconstruction was 96%. Among the 101 free flaps, 16 flaps had signs of venous compromise and were re-explored. Out of the 16 flaps, 11 flaps (13.2%) were in the one-vein group, and 5 flaps (27.7%) were in the two-vein group. In the two-vein group, 100% of the flaps were salvaged, and in the one-vein group, only 63% of the flaps were salvaged after re-exploration. There was no statistically significant difference between the one-vein group and the two-vein group concerning re-exploration.  Conclusions The rate of re-exploration was lower in the one-vein group when compared to the two-vein group. However, this difference was not statistically significant. Hence, a single-vein anastomosis is sufficient for a successful microvascular free flap. However, the rate of flap salvage is better with two-vein anastomosis if there is venous congestion.

Carbon conundrums: Geopolitical clashes and market mayhem in the race for sustainability.

This research presents an in-depth investigation into the dynamic correlation between geopolitical conflicts and carbon markets utilizing the Time-Varying Parameter Vector Autoregression (TVP-VAR) technique. The analysis focuses on the interconnectedness between the Geopolitical Risk Index Daily (GPRD) and vital carbon pricing instruments, specifically the Intercontinental Exchange Endex European Union Allowance (ECEFDC), KraneShares California Carbon Allowance Strat ETF (KCCAK), Shanghai Environment and Energy Exchange China Emission Allowances Online Transactions (SAXCEA), and S&P Global Ex-Japan LargeMidCap Carbon Efficient Index (SPGJ). The daily fluctuations were traced from May 2021 to July 2023. The analysis is divided into short- and long-term connectedness, with particular emphasis on the impact of the Russia-Ukraine conflict on the GPRD's spillover on carbon markets. The short-term connectedness (1-5 days) between GPRD and ECEFDC shows variability, fluctuating between 10% and 40%. Conversely, long-term connectedness exhibited a significant increase during the conflict, peaking at approximately 34% by mid-2022. The analysis of the Total Dynamic Connectedness (TCI) between the GPRD and the KCCAK indicates comparable magnitudes, although with minor initial discrepancies. The short-term connectedness of GPRD and KCCAK decreases from its peak of approximately 10% to approximately 1%. Conversely, long-term connectedness varies between approximately 32% and 2% from May 2022 onwards. The long-term connectedness between GPRD and SAXCEA revealed variable patterns, peaking at around 18% at the beginning of the sample period and rapidly reducing to around 1% within two months. The analysis of the connectedness between GPRD and the SPG) identifies intense fluctuations in both TCI and long-term connectedness. After an initial increase and decrease, these patterns rebound and experience another increase. This research provides significant insights into the complex dynamics of geopolitical conflicts and carbon markets, particularly the impact of the Russia-Ukraine conflict on carbon market behavior.

Work from home practices as corporate strategy- an integrative review.

The Covid 19 pandemic led to major changes at the individual, organisational and institutional levels of policy, productive functions, and organising. During Covid 19 morbidity, public institutions enforced social isolation, mandatory self-isolation, quarantines, and administrative regulatory lockdowns, which led to a movement away from the physical, material world and into an all-consuming digital universe. With growing interest in work-from-home (WFH) opportunities, this article provides an integrative review of 107 papers. It comprises the bibliometric analysis and manual review of the articles, on the basis of which we present an elaborative discussion and agenda for future research. According to the analysis, WFH looks a tad of a double-edged sword in that it may have major but unintended repercussions for institutions, and organizations as well as hidden, positive as well as negative consequences for individuals/employees. One of the significant insight from our analysis was the absence of HR function's strategic or operational input or oversight during corporate WFH strategies. We suggest several theoretical frameworks for further developing, theorizing, and empirically testing various aspects of WFH. Further, we recognise that WFH is becoming increasingly visible as a result of the pandemic scenario and significant technical advancements, which must be reflected in the research. Finally, because WFH represents a significant disruption in how organizations produce work and manage it, we propose employee and managerial consequences as future research agendas.

What do we learn from Nexus between trade diversification and structural change: informing the future about climate action and Sustainability.

Economic complexity is considered key a driver of social change, structural change, and economic development. Economic complexity is mostly used to capture issues apropos product diversification of exports, trade, technological innovation, human knowledge, and skills. The current study has conducted a detailed bibliometric review of economic complexity, export quality, and trade diversification. In doing so, the authors used the literature up to 2021 to unveil economic complexity's contextual information that witnessed structural change, social change, and trade indicators. The current study is the first integrative review to report the theoretical contribution, future research agendas, and thematic analysis of economic complexity, export quality, and export diversification. Our study, on the subject of economic complexity, export diversification, and import diversification in the period from 1966 to 2021, was carried out by systematically scanning 386 documents, and it is one of the pioneering studies in this field. In addition, economic diversity, development, and economic complexity; export diversification, import diversification, trade openness, and economic growth; energy, environmental Kuznets curve, and economic complexity; and sustainability and economic diversification are the four main research topics of the study. The findings are discussed apropos of economic complexity and exports, methodological aspects of economic complexity, and environmental issues nexus with economic complexity. The current study reports novel findings toward a path for achieving SDG-9 (industry and innovation) and SDG-13 (climate action). The biometric review enables researchers and policymakers to understand export quality, economic complexity, and the trade nexus and report future research directions for achieving sustainable growth in industries and innovation.

Forecasting carbon emissions future prices using the machine learning methods.

Due to the uncertainty surrounding the coupling and decoupling of natural gas, oil, and energy commodity futures prices, the current study seeks to investigate the interactions between energy commodity futures, oil price futures, and carbon emission futures from a forecasting perspective with implications for environmental sustainability. We employed daily data on natural gas futures prices, crude oil futures prices, carbon futures prices, and Dow Jones energy commodity futures prices from January 2018 to October 2021. For empirical analysis, we applied machine learning tools including traditional multiple linear regression (MLR), artificial neural network (ANN), support vector regression (SVR), and long short-term memory (LSTM). The machine learning analysis provides two key findings. First, the nonlinear frameworks outperform linear models in developing the relationships between future oil prices (crude oil and heating oil) and carbon emission futures prices. Second, the machine learning findings establish that when oil prices and natural gas prices display extreme movement, carbon emission futures prices react nonlinearly. Understanding the nonlinear dynamics of extreme movements can help policymakers design climate and environmental policies, as well as adjust natural gas and oil futures prices. We discuss important implications to sustainable development goals mainly SDG 7 and SDG 12.