The effectiveness and efficiency of e-learning system in industry significantly depend on users’ acceptance and adoption. This is specifically determined by external and internal factors represented by subjective norms (SN) and experience (XP), both believed to affect users’ perceived usefulness (PU) and perceived ease of use (PEOU). Users’ acceptance of e-learning system is influenced by the immensity of region, often hampered by inadequate infrastructure support. Therefore, this study aimed to investigate behavioral intention to use e-learning in the Indonesian insurance industry by applying Technology Acceptance Model (TAM). To achieve this objective, Jabotabek and Non-Jabotabek regions were used as moderating variables in all related hypotheses. An online survey was conducted to obtain data from 800 respondents who were Indonesian insurance industry employees. Subsequently, Structural Equation Model (SEM) was used to evaluate the hypotheses, and Multi-Group Analysis (MGA) to examine the role of region. The results showed that out of the seven hypotheses tested, only one was rejected. Furthermore, XP had no significant effect on PU, and the most significant correlation was found between PEOU and PU. In each relationship path model, the role of region (Jabodetabek and Non Jabodetabek) had no significant differences. These results were expected to provide valuable insights into the components of e-learning acceptability for the development of a user-friendly system in the insurance industry.

The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.

This study investigates how corruption impacts sustainability in African countries. Using public databases, the research draws on the African Development Bank’s corruption indicators and the World Bank’s financial inclusion metrics. The findings reveal that as financial inclusion increases, particularly through the use of digital financial services, perceptions of corruption decrease. However, economic growth paradoxically correlates with an increased perception of corruption due to rising consumption demands. The study concludes that promoting financial literacy, along with robust governance, is essential for combating corruption and fostering sustainable development.

This study examines the impact of Human Resource Management (HRM) practices, specifically Compensation, Job Design, and Training, on employee outcomes, including Engagement, Efficiency, Customer Satisfaction, and Innovation within an organizational framework. Employing a quantitative research methodology, the study utilizes a cross-sectional survey design to collect data from employees within a public service organization, analyzing the relationships through structural equation modelling. Findings reveal significant positive relationships between HRM practices and employee performance metrics, highlighting the pivotal role of Employee Engagement as a mediator in enhancing organizational effectiveness. Specifically, Compensation and Job Design significantly influence Employee Engagement and Efficiency, while training is crucial for driving Innovation and Customer Satisfaction. The practical implications of this research underscore the necessity for organizations to adopt integrated and strategic HRM frameworks that foster employee engagement to drive performance outcomes. These insights are vital for HR practitioners and organizational leaders aiming to enhance workforce productivity and innovation. In conclusion, the study contributes valuable perspectives to the HRM literature, advocating for holistic HRM practices that optimize employee well-being and ensure organizational competitiveness. Future research is encouraged to explore these dynamics across various sectors and cultural contexts to validate the generalizability of the findings.

The target area of the survey is the rehabilitated flat area behind the capital cities of Vienna and Bratislava, which lies in the tourist area of Győr. Wetlands provide a backdrop for tourism products such as kite flying, cycling and walking. The city centre offers tourists an easy sightseeing tour behind the natural scenery of the Danube tributary (Szigetköz). Objective: The demographic characteristics of demand and preferences for active tourism product types and the extent of the scope of supply were analyzed. The present research also analyses the cycling routes in the region with regard to the EUROVELO 6 road network. The primary research was a quantitative (questionnaire) survey conducted between 10 September 2023 and 30 October 2023. The survey sample of 666 respondents is not representative and was selected by random sampling. The results of the research include an analysis of the demand for participation in cycling tourism and tour programs as activities requiring activity. The findings of the research provide a basis for demand-supply segmentation of sustainable active tourism product development based on physical experience according to demographic characteristics (e.g. age, education). The landscape of the wetland can be positioned for the bicycle tourists. Especially for the target group of people over 40 and for people with higher education. The scope of the guided tours, linked to the central offer, extends over an area of more than 50 km. Activating the target group helps the rehabilitated natural scenery to connect to sustainable tourism.

Institutional thinking, a concept that underscores the importance of internal perspectives and the enduring purposes of institutions, plays a critical role in maintaining societal stability and ethical governance. This paper explores the dual nature of institutional thinking, highlighting its positive aspects and inherent dangers. Through an examination of economic, political, and philosophical forces, the paper identifies modern challenges that undermine long-term commitments and ethical values within institutions. By drawing on historical and contemporary examples, including slavery, Nazism, and discriminatory practices, the discussion provides a comprehensive understanding of how institutional thinking can both promote human well-being and perpetuate systemic issues. The paper concludes by emphasizing the need to reaffirm institutional values, promote long-term thinking, and balance individual rights with collective responsibilities to harness the positive aspects of institutional thinking while mitigating its risks.