The integration of chatbots in the financial sector has significantly improved customer service processes, providing efficient solutions for query management and problem resolution. These automated systems have proven to be valuable tools in enhancing operational efficiency and customer satisfaction in financial institutions. This study aims to conduct a systematic literature review on the impact of chatbots in customer service within the financial sector. A review of 61 relevant publications from 2018 to 2024 was conducted. Articles were selected from databases such as Scopus, IEEE Xplore, ARDI, Web of Science, and ProQuest. The findings highlight that efficiency and customer satisfaction are central to the perception of service quality, aligning with the automation of the user experience. The bibliometric analysis reveals a predominance of publications from countries such as India, Germany, and Australia, underscoring the academic and practical relevance of the topic. Additionally, essential thematic terms such as “artificial intelligence” and “advanced automation” were identified, reflecting technological evolution in this field. This study provides significant insights for future theoretical, practical, and managerial developments, offering a framework to optimize chatbot implementation in highly regulated environments.

This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—ScienceDirect, Web of Science, IEEE Xplore, and Scopus—were systematically searched using predetermined inclusion/exclusion criteria. This screening process resulted in 50 studies which were further classified into groups: AI Technologies (19 studies), Machine Learning (11), Deep Learning (8), Chatbots/ChatGPT/WeChat (4), and Other (8). The results were analyzed taxonomically to provide a structured framework for understanding the diverse applications of AI in mobile learning and education. This review summarizes current research and organizes it into a taxonomy that reveals trends and techniques in using AI to support mobile learning, particularly for indigenous groups in Malaysia.

Objective: This study aimed to examine the psychometric properties of the 21-item Depression, Anxiety, and Stress Scale (DASS-21) in a sample of Moroccan students. Method: A total of 208 Moroccan students participated in this study. The dimensionality of the DASS-21 scale was assessed using exploratory factor analysis. Construct validity was assessed using the Stress Perception (PSS-10), State Anxiety (SAI), and Depression (CESD-10) scales. Results: Correlation analyses between Depression, Anxiety, and Stress subscales showed significant results. The exploratory factor analysis results confirmed the DASS’s three-dimensional structure. Furthermore, correlation analyses revealed positive correlations between the DASS-18 sub-dimensions and the three scales for Stress (PSS-10), Anxiety (SAI), and Depression (CESD-10). Conclusion: In line with previous work, the results of this study suggest that the DASS-18 reflect adequate psychometric properties, making it an appropriate tool for use in the university context.

The study explores improving opportunities of forecasting accuracy from the traditional method through advanced forecasting techniques. This enables companies to optimize inventory management, production planning, and reducing the travelling time thorough vehicle route optimization. The article introduced a holistic framework by deploying advanced demand forecasting techniques i.e., AutoRegressive Integrated Moving Average (ARIMA) and Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) models, and the Vehicle Routing Problem with Time Windows (VRPTW) approach. The actual milk demand data came from the company and two forecasting models, ARIMA and RNN-LSTM, have been deployed using Python Jupyter notebook and compared them in terms of various precision measures. VRPTW established not only the optimal routes for a fleet of six vehicles but also tactical scheduling which contributes to a streamlined and agile raw milk collection process, ensuring a harmonious and resource-efficient operation. The proposed approach succeeded on dropping about 16% of total travel time and capable of making predictions with approximately 2% increased accuracy than before.

Generational differences shape technological preferences and fundamentally influence workplace motivation and interactions. Our research aims to examine in detail how different generations assess the importance of workplace communication and leadership styles and how these diverse preferences impact workplace motivation and commitment. In our analysis, we studied the behavioral patterns of four generations—Baby Boomers, Generations X, Y, and Z—through anonymous online questionnaires supplemented by in-depth interviews conducted with a leader and a Generation Z employee. To verify our hypotheses, we employed statistical methods, including the Chi-Square test, Spearman’s rank correlation, and cross-tabulation analysis. Our results clearly demonstrated that different generations evaluate the importance of applied leadership and communication styles differently. While Generations Y and Z highly value flexible, supportive leadership styles, older generations, such as the Baby Boomers prefer more traditional, structured approaches. The study confirmed that aligning leadership and communication styles is crucial, as it significantly impacts the workplace atmosphere and employee performance. Our research findings hold both theoretical and practical significance. This research highlights how understanding generational preferences in leadership and communication styles can enhance workplace cohesion and efficiency. The results provide specific guidance for leaders and HR professionals to create a supportive and adaptable environment that effectively meets the needs of diverse generations.

The soundscape studied has gained increasingly frequent attention across multiple disciplines, especially in tourism and leisure domain. While it has already indicated a unique soundscape provides dynamic and memorable tourism experiences, a clearly mapped perspective across different segmentations of soundscapes, both natural and acoustically created, remains missing. Therefore, a comprehensive mapping and review of soundscape studies is imperative to understand its implications for potential inbound tourism research in future. This article aimed to explore potential soundscape studies by assessing trends and developments in recent decades (2013–2023). We applied a bibliometric approach, using a PRISMA framework and under NVivo 12 Plus, VOSViewer, and Biblioshiny-R-Studio software as analytical tools. Significant yield discoveries showed that tourism soundscape research is undergoing steady growth, as evidenced by quantity of publications and citation trends. Single and multi-country international collaborations characterized by soundscape outreach research playing an influential role were highlighted. We identified multiple research themes, such as anthropogenic noise and music heritage, and pointed out how we approached this research from two perspectives: environmental/natural and manufacturing/acoustics. In our review, several keywords and predominant themes were identified, which suggested soundscape studies have recently become an increasingly popular topic in tourism research. The broad spectrum of key themes, such a tourism, tourists, sustainability, areas, and development perspectives, are evidence points of significant diversity in these topics. Most importantly, our research offers significant theoretical and conceptual implications for future direction of soundscape studies. We identified three originality main focus domains in soundscape tourism research: urban and natural environments, technological advancements, and tourists’ perceptions and behaviors.

Fiscal decentralization is one of the policy implementations of regional autonomy, which authorizes local governments to manage their local finances independently. However, with the evolution of the times and the dynamics that are taking place, the application of fiscal decentralization worldwide is changing at each time of year. Therefore, it is necessary to investigate fiscal decentralization research temporarily over the course of four decades. The study aims to explain the development of research on fiscal decentralization over a period of four decades. This research integrates Scopus database to offer a thorough conceptual and structural overview of the field by integrating bibliometric approaches and content analysis. The research procedure begins with the determination of the scope of the research, the inclusion and exclusion criteria for the selection process, the collection of data on Publish or Perish (PoP), and the execution of bibliometric analysis on VosViewer. The research shows that the type of journal with the highest productivity has sub-topics of economy, public service, development, and environmental. The development of fiscal decentralization research has a positive upward trend and most of the top-ranked journals indicate that fiscal decentralization has links and influences with other variables. It is apparent that the most often keywords emerged and studied in the research on fiscal decentralization are related to efficiency, measure, role, degree, growth, and fiscal federalism. Meanwhile, the least frequent keywords are related to poverty and inequality, health outcome, environmental pollution, Latin America, South Africa, fiscal autonomy, corruption, OECD country, determinant, and public sector. These keywords are the future lines of research that may be used for future research on the topic of fiscal decentralization.

On the basis of the enlightenment of international engineering education accreditation for the reform and development of higher education in China, combined with the important measures of the national “double first-class” construction, new challenges have been proposed for innovative talent cultivation among engineering majors in the context of promoting national development. These challenges also promote the reform of science-oriented courses among engineering majors. As a core mandatory course for engineering majors, biochemistry plays a crucial role in the entire educational process at universities, serving as a bridge between basic and specialized courses. To address challenges such as limited course resources, insufficient development of students’ advanced thinking and innovation skills, and overly standardized assessment methods, the bioengineering major from Guilin University of Technology restructured the biochemistry course content. A blended teaching model termed “three integrations, three stages, one sharing”, was implemented. This effort has yielded significant results, providing a research foundation for constructing an innovative talent cultivation system that is oriented toward industry needs within modern industrial colleges. It also offers valuable insights into and reference points for the cultivation of engineering talents and curriculum reform in local universities.