How are telecommunications infrastructure, institutions and poverty related in a war-torn economy such as Afghanistan? Afghanistan has been plagued by poor governance, low usage of telecommunications, and extreme poverty levels which can be termed triple-challenges. High levels of political instability affected telecommunications investment and adversely affected the adoption and diffusion of modern technology. This study examines the asymmetric effect of telecommunications and governance (institutions) on poverty reduction over the period 1989–2019 using a nonlinear autoregressive distributed lag (NARDL) model. In the short run, we establish that information and communication technology, private domestic credit, governance, and educational access for males and females are essential tools that can be used for poverty reduction. In the long run, we also establish that Afghanistan can reduce poverty levels through the use of information and communication technology, governance, and educational access for both males and females. The following policy recommendations were suggested: research and development, robust policy formulation on governance and ICT, development of the ICT sector, and improved governance. These are critical in reducing the high poverty levels as well as solving the institutional challenges faced by Afghanistan.

The telecommunications sector is crucial in a country’s economy. The advancements in information and communication technology have had a significant impact on this sector, particularly in the electronic transactions domain. The utilization of electronic transactions in the telecommunications sector can yield substantial benefits, including increasing non-tax state revenue and economic development in Indonesia. The Covid-19 pandemic has served as a catalyst for the sharp rise in internet usage and telecommunications services, such as work-from-home, distance learning, online shopping or payments, industrial digitization, telemedicine, and others. Consequently, digital transformation has accelerated, necessitating the equitable distribution of Information and Communication Technology (ICT) in Indonesia. The utilization of electronic transactions has directly contributed to the increase in state revenue from non-tax sector, particularly in the telecommunications sector. This can be observed through the continuous growth of non-tax revenue achieved by the Ministry of Communication and Informatics, surpassing the set targets each year in terms of realized value. The objective of this research is to analyze the effectiveness, challenges, and impacts of electronic transactions in increasing non-tax state revenue, in order to generate policy recommendations in Indonesia. This study uses a normative juridical method, analyzing positive legal provisions. Data sources were obtained from three types of legal materials, and data collection was conducted both online and offline. The research results indicate that the utilization of electronic transactions can increase non-tax state revenue in the telecommunications sector through various forms such as telecommunications bill payments, e-commerce transactions, sales of prepaid credit and data packages, telecommunications devices, digital services, content delivery, and transaction monitoring and oversight.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.

The sustainable development of the global economy and society necessitates the integration of environmental and socially responsible management, known as ESG (environmental, social, and corporate governance). Despite growing recognition of ESG’s importance, the strategic management of ESG factors in Kazakhstan’s telecommunications industry remains underexplored. This study bridges this gap by analyzing Kazakh telecom’s ESG strategies from 2019 to 2021 through a cross-sectional design and semi-structured interviews with 12 industry experts. Utilizing the National Rating Agency (NRA) methodology, the research evaluates environmental, social, and governance variables. Key findings reveal that Kazakh telecom excels in “Climate Change” and “Human Capital Management” but needs significant improvements in “Environmental Impact” and “Society.” The study offers specific recommendations such as enhancing corporate volunteering, responsible marketing, service quality, and integrating sustainable practices. The primary contributions of this research include actionable insights for improving ESG strategies in telecommunications companies and advocating for more systematic and standardized ESG assessment approaches. This study expands the understanding of how ESG principles can enhance competitiveness and sustainable development in the telecommunications industry, providing valuable guidance for industry practitioners and policymakers. It offers insights into effective ESG implementation practices and highlights critical areas requiring attention to drive sustainable development in telecommunications.

Nowadays, customer service in telecommunications companies is often characterized by long waiting times and impersonal responses, leading to customer dissatisfaction, increased complaints, and higher operational costs. This study aims to optimize the customer service process through the implementation of a Generative AI Voicebot, developed using the SCRUMBAN methodology, which comprises seven phases: Objectives, To-Do Tasks, Analysis, Development, Testing, Deployment, and Completion. An experimental design was used with an experimental group and a control group, selecting a representative sample of 30 customer service processes for each evaluated indicator. The results showed a 34.72% reduction in the average time to resolve issues, a 33.12% decrease in service cancellation rates, and a 97% increase in customer satisfaction. The implications of this research suggest that the use of Generative AI In Voicebots can transform support strategies in service companies. In conclusion, the implementation of the Generative AI Voicebot has proven effective in significantly reducing resolution time and markedly increasing customer satisfaction. Future research is recommended to further explore the SCRUMBAN methodology and extend the use of Generative AI Voicebots in various business contexts.

Competition in the telecommunications market has significant benefits and impacts in various fields of society such as education, health and the economy. Therefore, it is key not only to monitor the behavior of the concentration of the telecommunications market but also to forecast it to guarantee an adequate level of competition. This work aims to forecast the Linda index of the telecommunications market based on an ARIMA time series model. To achieve this, we obtain data on traffic, revenue, and access from companies in the telecommunications market over a decade and use them to construct the Linda index. The Linda index allows us to measure the possible existence of oligopoly and the inequality between different market shares. The data is modeled through an ARIMA time series to finally predict the future values of the Linda index. The results show that the Colombian telecommunications market has a slight concentration that can affect the level of competition.