The need for forest products, agricultural expansion, and dependency on biomass for the household energy source has largely influenced Ethiopia’s forest resources. Consequently, the country lost its forest resources to less than 6% until the millennium. In this study, quantitative and qualitative historical data analysis was employed to understand the socioeconomic benefits of large dam construction to Ethiopia and downstream countries. Moreover, remotely sensed data was also used to analyze the trends of vegetation cover change in the Nile catchment since the commencement of the dam; focusing on areas where there are high settlement and urban areas. It was identified that Ethiopia has one of the lowest electricity consumption per capita in Africa; about 91% of the source of household energy supply depends on fuelwood today and more than 55.7% of the population does not have access to electricity. The normalized difference vegetation index result shows an increment of vegetation area in the Nile catchment and a reduction of no vegetation area from 2011–2021 by 37.1%; which is directly related to the protection of the dam catchment for its sustainability in the last decade. The hydroelectric dam construction has prospects of multi-benefit to Ethiopia and downstream countries either through the direct benefit of hydropower energy production, related socioeconomic values, and reducing risks of destructive flood from Ethiopian highlands. Generally, it explains the reason why to not say ‘No’ to the reservoir as it is an ever more vital tool for fulfilling growing energy demand and supporting ecological stability.

The COVID-19 epidemic has given rise to a new situation that requires the qualification and training of teachers to operate in educational crises. Amidst the pandemic, online training has emerged as the predominant approach for delivering teacher training. The COVID-19 pandemic has created potential opportunities and challenges for online training, which may have a long-lasting impact on online training procedures in the post-pandemic era. This study aims to determine the primary potential and constraints of online training as seen by instructors. The Technology Acceptance Model (TAM) identified online training opportunities and challenges by examining the to-be-applied behavioral intention variables that influence trainees. These variables include individual, system, social, and organizational factors. The study has applied the Phenomenological technique to address the research issues, using the Semi-structured interview tool to get a comprehensive knowledge of the online training phenomena amongst the pandemic. A total of seven participants were selected from a list of general education teachers at the Central Education Office of the Education Department in Bisha Governorate. These people were deliberately selected because of their high frequency of completing training sessions throughout the epidemic. A series of interviews was conducted with these participants. The findings indicated that the primary prospects included both equal opportunities and digital culture within the individual factors, enrollment in training programs and variation in training programs across organizational characteristics, the use of digital material and electronic archiving within the system variables, engaging in the exchange of personal experiences, providing constructive criticism, and fostering favorable communication within the realm of social factors. However, the primary obstacles included deficiencies in digital competencies, compatibility of trainees’ attributes, and dearth of desire as per individual factors, the temporal arrangement of training programs, as well as the lack of prior preparation and preparedness within the realm of organizational factors. Other challenges included the absence of trainer assessment, limited diversity of training exercises, and technological obstacles within the system factors, and ultimately the absence of engagement with the instructor, and lack of engagement with peers are within the social variable.

In the contemporary landscape characterized by technological advancements and a progressive economic environment, the utilization of currency has undergone a paradigm shift. Despite the growing prevalence of digital currency, its adoption among the Vietnamese population faces several challenges, including limited financial literacy, concerns over security, and resistance to change from traditional cash-based transactions. This research aims to identify these challenges and propose solutions to encourage the widespread use of digital currency in Vietnam. This research adopts a quantitative approach, utilizing Likert scale questionnaires, with a dataset of 330 records. The interrelationships among variables are analyzed using partial least squares structural equation modeling (PLS-SEM). The analysis results substantiate the viability of the research model, confirming the hypotheses. The findings demonstrate a positive relationship and the significance impact of factors such as perceived usefulness (PU), perceived ease of use (PEOU), perceived trust (PT), social influence (SI), openness to innovation (OI), and financial knowledge (FK) to intention to use digital currency (IUDC). Thereby aiming to inform policymakers, industry stakeholders, and the wider community, fostering a deeper understanding of consumer behavior and providing solutions to enhance the adoption of digital currency in the evolving landscape of digital finance.

This investigation extends into the intricate fabric of customer-based corporate reputation within the banking industry, applying advanced analytics to decipher the nuances of customer perceptions. By integrating structural equation modeling, particularly through SmartPLS4, we thoroughly examine the interrelations of perceived quality, competence, likeability, and trust, and how they culminate in customer satisfaction and loyalty. Our comprehensive dataset is drawn from a varied demographic of banking consumers, ensuring a holistic view of the sector’s reputation dynamics. The research reveals the profound influence of these constructs on customer decision-making, with likeability emerging as a critical driver of satisfaction and allegiance to the bank. We also rigorously test our model’s internal consistency and convergent validity, establishing its reliability and robustness. While the direct involvement of Business Intelligence (BI) tools in the research design may not be overtly articulated, the analytical techniques and data-driven approach at the core of our methodology are synonymous with BI’s capabilities. The insights garnered from our analysis have direct implications for data-driven decision-making in banking. They inform strategies that could include enhancing service personalization, refining reputation management, and improving customer retention efforts. We acknowledge the need to more explicitly detail the role of BI within the research process. BI’s latent presence is inherent in the analytical processes employed to interpret complex data and generate actionable insights, which are crucial for crafting targeted marketing strategies. In summary, our research not only contributes to academic discourse on marketing and customer perception but also implicitly demonstrates the value that BI methodologies bring to understanding and influencing consumer behavior in the banking sector. It is this blend of analytics and marketing intelligence that equips banks with the strategic leverage necessary to thrive in today’s competitive financial landscape.

We present an interdisciplinary exploration of technostress in knowledge-intensive organizations, including both business and healthcare settings, and its impact on a healthy working life. Technostress, a contemporary form of stress induced by information and communication technology, is associated with reduced job satisfaction, diminished organizational commitment, and adverse patient care outcomes. This article aims to construct an innovative framework, called The Integrated Technostress Resilience Framework, designed to mitigate technostress and promote continuous learning within dynamic organizational contexts. In this perspective article we incorporate a socio-technical systems approach to emphasize the complex interplay between technological and social factors in organizational settings. The proposed framework is expected to provide valuable insights into the role of transparency in digital technology utilization, with the aim of mitigating technostress. Furthermore, it seeks to extend information systems theory, particularly the Technology Acceptance Model, by offering a more nuanced understanding of technology adoption and use. Our conclusion includes considerations for the design and implementation of information systems aimed at fostering resilience and adaptability in organizations undergoing rapid technological change.