Transitioning to a green economy is a global concern, considered a pathway to sustainable development. This paper aims to investigate the effect of the transition into a green economy on Vietnam’s sustainable development and its two economic and environmental dimensions, with consideration of several essential issues including renewable energy, technological innovation, natural resource rents (oils, forest, and minerals), foreign direct investment, and trade. This paper utilizes data from 1996 to 2020 and then applies the autoregressive distributed lag (ARDL) method for analysis. The results conclude that renewable energy is a driving key to reducing environmental degradation, but it hampers economic growth, while the contrast occurs with technology. Our results emphasize the dependence on non-renewable energy, whereas the innovation of technology does not show a green orientation in Vietnam. Furthermore, there is a lack of sustainability in the effect of natural resource rents, foreign direct investment, and trade. Overall, the transition into a green economy in Vietnam does not illustrate the sustainable orientation. The findings of this research provide empirical evidence to clarify the relationship between this transition and its driving factor, with sustainable development and the two economic environment dimensions. In addition, this study will bring worthwhile implications for the policymakers and scholars on whether the transition to a green economy fulfills the orientation towards sustainability, then enhancing the economy's efficiency to achieve green growth, following the pathway to sustainable development.

Enterprise Resource Planning (ERP) system utilization and Environmental, Governance, Social (ESG) practice incorporation have jointly wielded significant influence on various aspects of accounting operations. On the other side, leveraging the robust information infrastructure, Taiwanese firms have widely implemented ERP systems and have been aligning with international ESG initiatives in recent years. The objective of this study is to investigate the impact of ERP utilization and ESG practices on real and accrual earnings management among firms listed in Taiwan over an 19-year span from 2003 to 2021. The results of this study suggest duration of ERP implementation has a negative impact on accruals earnings management, but has a positively influence on real management. The results underscore the significant influence of ERP utilization duration on the different aspects of corporate earnings management activity. Additionally, our investigation illustrates a negative association between the corporate assimilation of ESG practices and both real and accrual earnings management. This reveals that enterprises committed to implementing ESG practices highlight long-term substantive operations over the short term periodic performance of financial statements.

The transportation sector is currently experiencing a significant transformation due to the influence of digital technologies, which are revolutionizing travel, goods transportation, and interactions with transportation systems. This study delves into the possibilities and obstacles presented by digital transformation in the realm of sustainable transportation. Moreover, it identifies the most effective methods for implementing digital transformation in this sector. Furthermore, our analysis sheds light on the potential impacts of digital transformation on sustainable development and environmental performance indicators within transportation systems. We discover that digital transformation can contribute to reduced greenhouse gas emissions, improved air quality, and increased resource efficiency, among other benefits. Nevertheless, we emphasize the potential risks and uncertainties associated with digital transformation, including concerns regarding data privacy, security, and ethics. Collectively, our research provides valuable insights into the opportunities and challenges presented by digital transformation in sustainable transportation. It also identifies best practices for successfully implementing digital transformation in this sector. The implications of our findings are significant for policymakers, businesses, and other stakeholders who aspire to drive the future of sustainable transportation through digital transformation.

The increasing epileptic electricity supply, mainly in the residential areas of Nigerian cities, has been linked to the incorrect knowledge of the numerous socio-economic and physical indices that influence household electricity usage. Most of the seemingly identified explanatory factors were done at macro level which does not give a clear estimate of this electricity demand. The thrust of the study is to analyse empirically the household electricity determinants in Nigerian cities with a view to evolving a more informed and sustainable energy policy decision. Multistage area cluster sampling method was adopted in the study where 769 copies of structured questionnaire were distributed to electricity users of prepaid meters in five major Nigerian cities. The research hypothesis was tested using the multiple linear regression statistical tool. The result revealed that nine variables which include age (r = 0.05, p-value: 0.05), household income (r = 0.00, p-value: 0.05), number of hours that people stay outside the house (r = 0.043, p-value: 0.05), number of teenagers at home, (r = 0.006, p-value: 0.01) number of electrical appliances (r = 0.016, p-value: 0.01), type of house (r = 0.012, p-value: 0.01), hours that the electrical appliances are used (r = 0.043, p-value: 0.05), weather condition, (r = 0.011, p-value: 0.05) and the location of the building (r = 0.045, p-value: 0.05) were significant in determining the household electricity consumption. Policies based on the findings will give energy and urban planners an empirical basis for accurate and robust forecasting of the determinants that influence household electricity consumption in Nigeria that is devoid of any speculation or unfounded predictions.

This paper aims to explore how to build a sustainable peace and development model for China’s peacekeeping efforts through the application of data-driven methods from UN Global Pulse. UN Global Pulse is a United Nations agency dedicated to using big data and artificial intelligence technologies to address global challenges. In this paper, we will introduce the working principles of UN Global Pulse and its application in the fields of peacekeeping and development. Then, we will discuss the current situation of China’s participation in peacekeeping operations and how data-driven methods can help China play a greater role in peacekeeping tasks. Finally, we will propose a sustainable peace and development model that combines data-driven methods with the advantages of China’s peacekeeping efforts to achieve long-term peace and development goals.