The purpose of this study is to analyze issues related to the use of green technology and to provide a theoretical basis for how the application of green technology in agriculture can reduce inequality. Additionally, the study aims to explore policy alternatives based on the analysis of inequality reduction issues through farmer surveys. For this purpose, this study used survey data to analyze farmers’ perceptions, acceptance status, willingness to accept green technology, and perceptions of inequality. The quantitative analysis was performed to analyze the relationship between the acceptance of green technology and perceptions of inequality. The results confirmed that access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions are major factors. In particular, the higher the satisfaction with policies regarding the introduction of green technology, the lower the perception of inequality. Specifically, the acceptance of green technology showed a significant positive correlation with access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions, while perceptions of inequality showed a significant negative correlation with policy satisfaction. In conclusion, green technology in agriculture is vital for reducing climate change damage and inequality. However, targeted policy support for small-scale farmers is essential for successful adoption. This study provides policy implications related to the application of green technology in the agricultural sector, which can promote sustainable agricultural development.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.

With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.

This research reviews the environmental, social, and governance (ESG) performance of corporate social responsibility (CSR) and technology innovation development, and analyzes the impact of technology innovation on ESG performance and its influencing mechanism. In additional, the main purpose of this study is to gain an understanding the relationships of ESG performance, CSR and technology innovation in Art industry. We found that technology innovation impact CSR of art firm, and ESG performance with the moderating variable of technology innovation has a significant and positive impact on CSR. Likewise, the study is based on primary panel data collected from 161 consumer, product and service manufacturing companies through an electronic questionnaire (Google, Microsoft online survey) with five-point Likert measurement scale. The exploratory factor analysis is proposed to be carried out using IBM SPSS 27.0 and the confirmatory factor analysis (CFA analysis) is proposed to be carried out using SmartPLS.4.0 analysis software, and this study investigate the measurement factors and the reliability of the construct items and to validate the factorial structure of the research variables. Moreover, digital technology and CSR has the potential to contribute to this impact. Based on these findings, we propose relevant ESG performance recommendations to improve technology innovation and CSR. Our findings offer an excited knowing and learning of the impact of ESG performance, CSR and technology innovation in Chinese art industry. Furthermore, this study extends stakeholders theory and Schumpeter’s Innovation Theory by proving their utility in the perspective of CSR, ESG performance.

In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.

Primary reason for interpretation the paper was the creation of a starting position for setting up e-learning in the structures of the executive forces of the Slovak Republic, which absent in the current dynamic environment. Problems with education arose mainly in connection with the global problem of Europe, such as the influence of illegal migrants, and it was necessary to retrain a large number of police officers in a short time. We reflect on the combined model of LMS Moodle and proctored training through MS TEAMS and their active use in practice. We focused on the efficiency in the number of participants in individual trainings and costs per participant according to the field of training. We compared the processed data with the costs of the pilot introduction of analytical organizational unit providing e-learning and interpreted the positive results in the application of e-learning compared to conventional (face-to-face) educational activities. As a basic (reference) comparative indicator, the costs of educational activities of selected organizational unit of state institution represented by own educational organizations and the number of trained employees for the periods in question were chosen. To measure effectiveness, we set financial—cost KPIs. Our findings clearly demonstrated that it is possible to significantly optimize costs when changing the current form of ICT education to e-learning. The implementation of another educational activities form of education, e-learning, within public institutions, according to the results of the analysis, can simplify and at the same time make education processes more efficient in the context of individual subjects of the Ministry of the Interior of the Slovak Republic.