Electric cars are manufactured to address environmental problems, reduce dependence on fossil fuels, and nullify climate change. Their production aligns with sustainability objectives by encouraging cleaner transportation options, promoting energy efficiency, and contributing to a transition towards eco-friendly mobility in an answer to global environmental challenges. In Jordan, similar to any international market, car dealers and traders import electric cars. However, the prevailing perceptions and attitudes of Jordanian consumers need strong consideration. Nevertheless, there is still uncertainty and a need for more trust in electric vehicles among Jordanian consumers. Therefore, this research aims to ascertain whether electric cars have a lasting positive perception among Jordanians through an inductive research approach. Employing thematic qualitative analysis, this research is supported by the diffusion of innovation theory. Notably, the research findings provided robust insights, further leading to reinforcing the idea about the pervasive attitudes of Jordanian consumers. Thus, this research concludes that there still needs to be more confidence regarding electric vehicles among most consumers in Jordan. Furthermore, this research offers practical and theoretical contributions to Jordan’s policymakers and electric vehicle companies.

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

QR code transforms the way retailers offer their shopping experiences in the current context. In response, various retailers adopted innovative approaches such as QR code-based applications to attract their consumers. A QR code-based virtual supermarket refers to a space where goods or services are traded in a virtual space using a smart app-based QR code. To fully understand the opportunities of this type of supermarket applying QR-code technology, initial research is required to assess consumers’ use intention. This study has examined the antecedents of the adoption of QR code-based virtual supermarket among Vietnam consumers using the expanded Technology Acceptance Model (TAM) and explored the moderating effect of perceived risk on the relationship between attitude and consumers’ intention to use QR code-based virtual supermarket. A questionnaire was used to collect data from a sample of 335 consumers in Vietnam. The findings revealed that the antecedents are effective in predicting consumers’ attitudes and intentions toward QR code-based virtual supermarket adoption. The results showed the negative moderation effects of perceived risk for the effect of attitude on consumers intention. In addition, practical implications are supported for the application of new shopping technology and are likely to stimulate further research in the area of virtual supermarket shopping.

Ukrainian Human Resource (HR) practices have multiple difficulties from economic changes combined with digital transformation and workforce instability brought on by the war in 2022. The study examines Ukrainian HR practices between 2015 and 2024, focusing on the digitalization of HR systems, talent development, staff engagement, and hiring strategies. It considers the effects of organizational size and industry type. The study combined interviews with 30 HR professionals and surveyed 150 organizations from different industry groups and sizes. Our data required both quantitative statistical tests and manual content breakdown with codes. Research has shown significant differences between Information Technology (IT) and farming firms, as 89% of IT businesses have integrated artificial intelligence (AI)-powered HR tools. In comparison, only 15% of agricultural companies have adopted them. Small and medium-sized enterprises (SMEs) showed less commitment to digital transformation and European Union (EU) requirements than large enterprises, which adopted these systems at rates of 75% and 88%, respectively. Western Ukraine first established mental health initiatives during the crisis, and Eastern Ukraine moved toward decentralized administration. Digitalization assistance for small businesses, along with EU and local human resources frameworks, should form the basis of our suggestions. This research calls for flexible people management methods to boost the Ukrainian workspace’s ability to recover from shocks.

The women’s sector in the academe is one of the most affected profiles during the COVID-19 pandemic which directly ravages their livelihood and other economic activities. Thus, this research project investigated the economic situations of 30 private and public-school teachers who were displaced from their occupations or were forcibly deprived of income-generating activities. In-depth interviews as research instruments were employed in the study to extract responses on how the educators creatively apply adaptive economic strategies and how government should aid them during a global crisis. The research findings showed that the pandemic has affected the economic activities of the respondents including the loss of their livelihood and other economic sidelines. They responded to these economic effects through adaptive strategies using diversifying and analyzing trends, using digital technology resources, data-driven, acquiring new alternative skills, pricing strategy, and becoming an expert. Results dictated that government could support affected women by initiating training options, homepreneurship support, encouraging independent income-earners, financial management and tax breaks, and industry compatibility endorsement. This study is important to map out the specific economic effects of the pandemic and aid them with initiatives by providing them with concrete economic tools and programs.

Maps of forest stand condition—the current phase of the forest-forming process—will be useful for foresters in their forest management in addition to the forest planning and cartographic materials. The mapping methodology was applied in the test area of the Bolshemurtinsky forest district of the Krasnoyarsk region, which is typical for the southern taiga forests of East Siberia. Source data for mapping was obtained on the basis of descriptions of the forest subcompartments on the GIS attribute table of the forest district. Forest stand confinement to the terrain relief indicators was identified on the basis of the SRTM 55-01 digital terrain model data. Spatial analysis has been performed using the ArcGIS Spatial Analyst module. Mapping capability has been shown not only for the year of forest inventory but also for the earlier period of time. To determine the predominant species and the age of the 100-year-old forest stand, a scheme was proposed in which the conceivable options are typified depending on the succession trend, the forest stand age prior to disturbance, and the period of reforestation. Map fragments of the test area as of 2006—the year of forest inventory—and as of 1906—the year of the intensive colonization beginning in southern Siberia—are demonstrated. Maps of forest condition in the test area represent successions that are typical in the southern taiga forests of Siberia: post-harvest, pyrogenic, and biogenic. The methodology of forest condition mapping is universal.