This research explores the impact of employee green behavior on green transformational leadership (GTL) and green human resource management (GHRM), and their subsequent effects on sustainable performance within organizations. Utilizing a sample of 482 environmental quality promotion departments across Thailand, the study employs stratified random sampling to ensure representative data collection. Analysis was conducted using SPSS software, applying Ordinary Least Squares (OLS) regression to test the hypothesized relationships between the variables. The findings reveal a positive and significant influence of employee green behavior on both GTL and GHRM. Additionally, both GTL and GHRM are found to positively correlate with sustainable performance, indicating that enhanced leadership and management practices in the environmental domain can lead to better sustainability outcomes. This research utilizes the Ability-Motivation-Opportunity (AMO) theory as its theoretical framework, illustrating how organizations can leverage strategic HRM practices to promote environmental consciousness and action among employees, thereby enhancing their long-term sustainability success. Implications of this study underscore the importance of integrating green practices into leadership and HRM strategies, advocating for targeted training programs and energy conservation measures to boost environmental awareness and performance in the workplace. This contributes to the literature on sustainable performance by providing empirical evidence of the pathways through which green HRM and transformational leadership foster a sustainable organizational environment.

Lean (also referred to as the Toyota Production System, TPS) is considered to be a radical alternative to the traditional method of mass production and batching principles for maximising operational efficiency, quality, speed and cost. Many hospitals inspired from lean manufacturing to develop their process. They had many improvements in their process. Hospitals reduced their patient waiting times, defects, wastes related to inventory, staff movement and patient transportation by implementing. This study utilizes scientometric and bibliometric tools to analyze visually the literature published in the field of medical lean manufacturing from 2009 to 2023. The relevant articles published from 2009 to 2023 were retrieved from the Web of Science Core Collection, VOSviewer and R software were used for bibliometric analysis and visualization. The number of publications related to the research has been increasing year by year before 2021, and then showed a downward trend, including 418 articles from 64 countries and regions, 743 institutions, 198 journals, and 1766 authors. The United States, Italy, and England are the main publishing countries in this research field. The journal “International Journal of Lean Six Sigma” published the most papers (n = 21) about lean manufacturing in medicine, the author with the most publications is Teeling SP, and the most influential author is Improta G. The top three keywords are “Healthcare”, “Quality improvement” and “Management”. This study provides a comprehensive bibliometric analysis of lean manufacturing in medicine, which can help researchers understand the current research hotspots in this field, explore potential research directions, and identify future development trends.

The Huaiyang Canal, a significant section of the Grand Canal, boasts representative tourist attractions. This study analysis of online reviews from Ctrip and Mahive using R language, Gephi, ROST CM, and SPSS has provided insights into tourists’ perceptions of the Huaiyang Canal’s image. Key findings include: (1) Dominant landscape images encompass gardens, canals, and buildings, emphasizing the historical and cultural assets. Both cultural and natural landscapes equally captivate tourists. (2) The canal’s tourism image perception follows a “garden-history-canal” hierarchy with the canal as the central space and history expanding its tourism features. (3) The perceptions can be categorized into historical and cultural landscapes, man-made projects, and attraction perception. Despite varying tourist numbers in Huaian and Yangzhou, scenic spot experiences are similar. The overall perception of tourists is largely positive, but some express concerns about service attitudes and travel time planning.

The article highlights Malaysia’s multicultural history, the advancement of Internet technology, and the worldwide appeal of Chinese food, all of which serve as a good basis for the project. This study focuses on Malaysian Chinese takeout systems. The research’s primary goals include developing new business options for the Chinese food sector, as well as enhancing customer happiness and efficiency of takeout systems. As a result, the project intended to create a Web-based system for managing several tasks associated with meal ordering by users. For the system development, an Object-Oriented System Development (OOSD) methodology was used, mostly with the Java programming language. Model-View-Control (MVC) framework was employed throughout development to improve system administration. Redis and HTTP session technologies were included for user login to increase system security. For database operations, MyBatis and MyBatis Plus were also employed to enhance ease and security. The system adheres to design principles and leverages technologies like ElementUI and jQuery to further fulfill this criterion to provide a user-friendly interface. The results of this study demonstrate significant improvements in the overall efficiency of the takeout process, leading to enhanced user experiences and greater customer satisfaction. In addition to streamlining operations, the system opens new avenues for the Malaysian Chinese food industry to capitalize on the growing demand for online food ordering. This research provides a solid foundation for future innovations in takeout systems and serves as a reference point for enhancing the Chinese gastronomy sector in a rapidly digitizing world.

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.

Bibliometric analysis is a commonly used tool to assess scientific collaborations within the researchers, community, institution, regions and countries. The analysis of publication records can provide a wealth of information about scientific collaboration, including the number of publications, the impact of the publications, and the areas of research where collaborations are most common. By providing detailed information on the patterns and trends in scientific collaboration, these tools can help to inform policy decisions and promote the development of effective strategies to support and enhance scientific collaborations between countries. This study aimed to analyze and visualize the scientific collaboration between Japan and Russia, using bibliometric analysis of collaborative publications from the Web of Science (WoS) database. The analysis utilized the bibliometrix package within the R statistical program. The analysis covered a period of two decades, from 2000 to 2021. The results showed a slight decrease in co-authored publications, with an annual growth rate of −1.26%. The keywords and thematic trends analysis confirmed that physics is the most co-authored field between the two countries. The study also analyzed the collaboration network and research funding sources. Overall, the study provides valuable insights into the current state of scientific collaboration between Japan and Russia. The study also highlights the importance of research funding sources in promoting and sustaining scientific cooperation between countries. The analysis suggests that more efforts in government funding are needed to increase collaboration between the two countries in various fields.