This study explores how Jordanian telecom companies can balance Internet of Things (IoT) driven automation with maintaining genuine consumer-brand connections. It seeks strategies that blend IoT automation with personalized engagement to foster lasting consumer loyalty. Employing qualitative research via semi-structured interviews with IT and customer service managers from Jordanian telecom companies. IoT-driven automation in Jordan’s telecom sector revolutionizes consumer-brand relationships by enabling data-driven personalization. It emphasizes the importance of IoT proficiency, transformed marketing strategies, and the need to balance personalization with consumer privacy. Interviews stress the significance of maintaining authentic human connections amidst automation. Strategies for Jordanian telecom firms include integrating IoT data into CRM systems, employing omnichannel marketing, balancing automation with human interaction, adopting a consumer-centric approach, mitigating security risks, and leveraging IoT insights for adaptive services. These approaches prioritize consumer trust, personalized engagement, and agile service adaptation to meet dynamic consumer preferences. This research provides actionable strategies for telecom firms on effective IoT integration, emphasizing the need to maintain genuine consumer relationships alongside technological advancements. It highlights IoT’s transformative potential while ensuring lasting consumer loyalty and business success. Future research avenues could explore longitudinal studies and the interplay between AI and IoT in telecom services.

During his 22-year rule, Turkey’s populist leader Erdoğan not only ensured his control of mainstream media ownership, but he also aligned the language and style of these media with his own populist politics. This investigation presents a unique perspective by highlighting the AKP’s establishment of a network of loyal media outlets and business individuals through crony capitalism while also demonstrating that the party garnered loyalty from religious foundations, and the urban poor due to the aid and financial support provided by AKP municipalities. The primary objective of this research is to offer a distinct scholarly contribution by analyzing the influence of crony capitalism and welfare policies within the context of populist politics. This study employed a methodology centered around network graphs designed to reveal connections between the AKP, various media outlets, and associations and foundations, thereby highlighting the AKP’s association with key actors involved in the establishment of a neoliberal-conservative hegemony.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

This paper aims to explore how developing countries like Indonesia have an approach to managing talent to enhance career development using an application system. The application of talent management in the career development of civil servants in Indonesia includes planning, implementing, monitoring, and evaluating career development. Talent management is essential for the government sector and can help improve employee quality, organizational performance, and the achievement of human potential. This research aims to examine the application of talent management in organizations and develop a state civil apparatus information system (SI-ASN) to support the career development process of civil servants. The research methods used include library research and field research, including interviews with competent officials in West Java Province as primary data. The qualitative data was collected in 2022–2023. The results of this study show that the application of talent management for civil servants in Indonesia is considered appropriate, as it directs employees to positions that are in line with their qualifications, competencies and performance. However, it requires an improvement in the methods used, particularly for competency tests, which may be conducted with new methods that are more efficient in terms of budget and time. The study concluded that the application of talent management in the career development of civil servants in Indonesia has a positive impact on the quality of leaders and organizations because it ensures that the appointed leaders are the most competent ones in the field and shows the importance of talent management in succession planning and the career development of civil servants.

Implementing green retrofitting can save 50–90% of energy use in buildings built worldwide. Government policies in several developed countries have begun to increase the implementation of green retrofitting buildings in those countries, which must rise by up to 2.5% of the lifespan of buildings by 2030. By 2050, it is hoped that more than 85% of all buildings will have been retrofitted. The high costs of implementing green retrofitting amounting to 20% of the total initial construction costs, as well as the uncertainty of costs due to cost overruns are one of the main problems in achieving the implementation target in 2050. Therefore, increasing the accuracy of the costs of implementing green retrofitting is the best solution to overcome this. This research is limited to analyzing the factors that influence increasing the accuracy of green retrofitting costs based on WBS, BIM, and Information Systems. The results show that there are 10 factors affecting the cost accuracy of retrofitting or customizing high-rise office buildings, namely Energy Use Efficiency, Water Use Efficiency, Use of Environmentally Friendly Materials, Maintenance of Green Building Performance during the Use Period, Initial Survey, Project Information Documents, Cost Estimation Process, Resources, Legal, and Quantity Extraction applied. These factors are shown to increase the accuracy of green retrofitting costs.