Despite the surge of publication of chatbots in the recent years in the field of education, we have little to know how this area has been researched so far, and the metrics of this type of research is still not known. To address such gap, this article offers a descriptive bibliometric study of chatbot research in education, aiming at presenting bibliometric analysis on articles on chatbots in education that were published in journals indexed in the Web of Science (WOS) database specifically Social Science Citation Index (SSCI) and Science Citation Index Expanded (SCIE) between 2016 and 2023. Descriptive bibliometric analysis was used to examine the data gathered from the chosen publications. including the annual number of articles and citations, the most productive author, countries with the highest publication output, productive affiliations, funding organizations, and publication sources. The bulk of the articles on chatbots in education, according to our dataset, were published between 2016 and 2023. The United States of America tops the list of countries regarding research productivity. The United Kingdom and China were ranked as most second and third productive countries, in terms of publication outputs. “Luke Kutszik Fryer emerged as the most productive author in this research domain in terms of the number of publications.” The University of Hong Kong had the highest number of publications among affiliations, indicating their significant contribution to the field. Additionally, the journal “Computers in Human Behavior” stood out with the highest number of publications per year, highlighting its relevance in publishing research on chatbots in education. This research offers valuable insights and a roadmap for prospective researchers, pinpointing critical areas where success can be attained in the study of chatbots in education.

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.

This research aims to examine the role of learning leadership on teacher performance in elementary schools, analyze the influence of digital literacy on teacher performance, analyze the role of emotional intelligence on teacher performance and analyze the role of intellectual intelligence on teacher performance. In this digital era, digital literacy plays an important role in education. The application of digital literacy in education is still not optimal and there is no previous research that discusses the variables of instructional leadership, teacher performance, digital literacy, emotional intelligence and intellectual intelligence. The research method used is quantitative, the population of this research is all teachers who have used e-learning methods, and the analysis of this research uses structural equation modelling (SEM), the respondents for this research are 675 Indonesian teachers. The sampling method is simple random sampling. Research data was obtained from distributing online questionnaires designed using a 5-point Likert scale, namely scale 1 is strongly disagree, scale 2 is disagree, scale 3 is neutral, scale 4 is agree and scale 5 is strongly agree. Data processing uses SmartPLS 3.0 software tools. The SEM test stages in this research are the outer model test, namely convergent validity, discriminant validity and composite reliability, and then the inner model test, namely hypothesis testing. The results of the analysis using SEM are that the Instructional leadership variable has a positive and significant relationship to teacher performance, the Digital literacy variable has a positive and significant relationship to teacher performance, the Emotional intelligence variable has a positive and significant relationship to teacher performance and Intellectual intelligence has a positive and significant relationship to teacher performance. The novelty of this research is the discovery of a model of the relationship between instructional leadership variables, digital literacy variables, emotional intelligence variables, and intellectual intelligence variables on teacher performance which did not exist in previous research studies. This research has a novelty, namely a model analyzed using SEM-PLS in the digital era. The principal must be able to determine and set learning objectives in his school, in his implementation the principal always involves teachers in developing and implementing learning goals and objectives and the principal also refers to the curriculum set by the government in developing learning. The dimensions of instructional leadership are defining school goals, managing learning programs, and creating a positive learning climate. In other words, the principal has implemented Instructional Leadership with indicators of setting learning goals, indicators of being a resource for staff, indicators of creating a school culture and climate that is conducive to learning, indicators of communicating the school’s vision and mission to staff, indicators of conditioning staff to achieve their goals.

The purpose of this study is to investigate the relationship between the use of business intelligence applications in accounting, particularly in invoice handling, and the resultant disruption and technical challenges. Traditionally a manual process, accounting has fundamentally changed with the incorporation of BI technology that automates processes and allows for sophisticated data analysis. This study addresses the lack of understanding about the strategic implications and nuances of implementation. Data was collected from 467 accounting stakeholder surveys and analyzed quantitatively using correlational analysis. Multiple regression was utilized to investigate the effect of BI adoption, technical sophistication on operational and organizational performance enhancements. The results show a weak association between the use of BI tools and operational enhancements, indicating that the time for processing invoices has decreased. Challenges due to information privacy and bias were significant and negative on both operational and organizational performance. This study suggests that a successful implementation of a BI technology requires an integrated plan that focuses on strategic management, organizational learning, and sound policies This paper informs practitioners of how accounting is being transformed in the digital age, motivating accountants and policy makers to better understand accounting as it evolves with technology and for businesses to invest in concomitant advances.

The low-carbon economy is the major objective of China’s economy, and its goal is to achieve sustainable economic development. The study enriches the literature on the relationship between digital Chinese yuan (E-CNY), low-carbon economy, AI trust concerns, and security intrusion. The rapid growth of Artificial Intelligence (AI) offered more ways to achieve a low-carbon economy. The digital Chinese yuan (E-CNY), based on the AI technique, has shown its nature and valid low-carbon characteristics in pilot cities of China, it will assume important responsibilities and become the key link. However, trust concerns about AI techniques result in a limitation of the scope and extent of E-CNY usage. The study conducts in-depth research from the perspective of AI trust concerns, explores the influence of E-CNY on the low-carbon economy, and discusses the moderating and mediating mechanisms of AI trust concerns in this process. The empirical data results showed that E-CNY positively affects China’s low-carbon economy, and AI trust concerns moderate the positive impact. When consumers with higher AI trust concerns use E-CNY, their feeling of security intrusion is also higher. It affects the growth of trading volume and scope of E-CNY usage. Still, it reduces the utility of China’s low-carbon economy. This study provides valuable management inspiration for China’s low-carbon economy.

Amidst the COVID-19 pandemic, the imperative of physical distancing has underscored the necessity for telemedicine solutions. Traditionally, telemedicine systems have operated synchronously, requiring scheduled appointments. This study introduces an innovative telemedicine system integrating Artificial Intelligence (AI) to enable asynchronous communication between physicians and patients, eliminating the need for appointments and providing round-the-clock access from any location. The AI-Telemedicine system was developed utilizing Google Sheets and Google Forms. Patients can receive dietary recommendations from the AI acting as the physician and submit self-reports through the system. Physicians have access to patients’ submitted reports and can adjust AI settings to tailor recommendations accordingly. The AI-Telemedicine system for patients requiring daily dietary recommendations has been successfully developed, meeting all nine system requirements. System privacy and security are ensured through user account access controls within Google Sheets. This AI-Telemedicine system facilitates seamless communication between physicians and patients in situations requiring physical distancing, eliminating the need for appointments. Patients have round-the-clock access to the system, with AI serving as a physician surrogate whenever necessary. This system serves as a potential model for future telemedicine solutions.