The main goal of this study is to assess the moderating role of digital leadership capabilities (DLC) in improving the overall performance of telecom companies through their organisational knowledge capabilities. The author builds a conceptual model with six hypotheses and tests them with data collected through an electronic questionnaire. The data is analysed using WarpPLS 8.0 software as an application of the structural equation modelling technique. The sample size included 528 participants. The study revealed that individual knowledge capability (IKC) does not significantly affect organisational performance (PR). Also, the results reveal that managerial knowledge capability (MKC) and organisational collaborative capability (OCC) have a positive but weak impact on the performance of telecom companies (PR). However, it was clear that individual knowledge capability (IKC) and organisational collaborative capability (OCC) do not affect organisational performance (PR) through the moderator, digital leadership capabilities (DLC). On the other hand, it was also evident that managerial knowledge capabilities (MKC) significantly negatively affect the performance of telecom companies (PR) through the moderator role of digital leadership capabilities (DLC). The author recommends that telecom companies adopt knowledge-based practices to ensure enduring high performance. He also suggests creating a knowledge management department to foster a culture of creativity and cooperation across departments, which is essential to establishing a work environment that promotes continuous learning and development. Findings may help telecom sector CEOs boost the company’s performance value. The research highlights the importance of fostering appropriate knowledge pillars and building digital leaders to shift telecom companies to a new successful stage. These findings offer tangible benefits that can be directly applied in the telecom industry, making the research highly relevant and valuable.

Since the external environment on a global level is very unstable, recovering from various unexpected shocks becomes a challenging question for all countries. Thus, for each country it is necessary to understand its weaknesses and threats. Further, the preparation for any level of uncertainty in various fields must be imperative. Even for the most unpredictable shocks such as pandemic, cyberthreat, or even war. The aim of the article is to evaluate the state resilience of the Baltic States by creating the national resilience index. A state’s resilience is based on four pillars: economic, social, good governance, and defence. The methodology is based the SAW method, data has been collected from NATO and Eurostat databases. As the result of the study, resilience index has been estimated for each year from 2015 to 2022. Results revealed vulnerability and problematic areas of each country.

This study investigates how digital transformation influences visitor satisfaction at 12 World Heritage Sites (WHS) across eight coastal provinces in Eastern and Southern China. Utilizing 402 valid survey responses, it explores the impact of demographic factors—education, age, and income—on visitors’ perceptions of digital services, particularly focusing on usability, quality, and overall experience. The findings reveal that younger, higher-income, and STEM-educated visitors express significantly higher satisfaction with digital services, while older, lower-income visitors report lower levels of engagement and satisfaction. This research highlights the need for tailored digital strategies that cater to diverse demographic groups, ensuring the balance between technological innovation and the preservation of cultural authenticity at heritage sites. The originality of this study lies in its focus on non-Western contexts, particularly China’s rapidly developing coastal regions, which have been largely overlooked in the global discourse on digital tourism. By applying established theoretical frameworks—such as the Technology Acceptance Model (TAM) and Expectation-Confirmation Theory (ECT)—to a non-Western setting, this research fills a crucial gap in the literature. The insights provided offer actionable recommendations for heritage site managers to enhance visitor engagement, adapt digital services to demographic variations, and promote sustainable tourism development.

Finding the right technique to optimize a complex problem is not an easy task. There are hundreds of methods, especially in the field of metaheuristics suitable for solving NP-hard problems. Most metaheuristic research is characterized by developing a new algorithm for a task, modifying or improving an existing technique. The overall rate of reuse of metaheuristics is small. Many problems in the field of logistics are complex and NP-hard, so metaheuristics can adequately solve them. The purpose of this paper is to promote more frequent reuse of algorithms in the field of logistics. For this, a framework is presented, where tasks are analyzed and categorized in a new way in terms of variables or based on the type of task. A lot of emphasis is placed on whether the nature of a task is discrete or continuous. Metaheuristics are also analyzed from a new approach: the focus of the study is that, based on literature, an algorithm has already effectively solved mostly discrete or continuous problems. An algorithm is not modified and adapted to a problem, but methods that provide a possible good solution for a task type are collected. A kind of reverse optimization is presented, which can help the reuse and industrial application of metaheuristics. The paper also contributes to providing proof of the difficulties in the applicability of metaheuristics. The revealed research difficulties can help improve the quality of the field and, by initiating many additional research questions, it can improve the real application of metaheuristic algorithms to specific problems. The paper helps with decision support in logistics in the selection of applied optimization methods. We tested the effectiveness of the selection method on a specific task, and it was proven that the functional structure can help the decision when choosing the appropriate algorithm.

The livelihood of ethnic minority households in Vietnam is mainly in the fields of agriculture and forestry. The percentage of ethnic minorities who have jobs in industry, construction, and services is still limited. Moreover, due to harsh climate conditions, limited resources, poor market access, low education level, lack of investment capital for production, and inadequate policies, job opportunities in the off-farm and non-farm activities are very limited among ethnic minority areas. This paper assessed the contribution of livelihood diversification activities to poverty reduction of ethnic minority households in Son La Province of Vietnam. The analysis was based on the data using three stages sampling procedure of 240 ethnic minority households in Son La Province. The finding showed that the livelihood diversification activities had positively significant contribution to poverty reduction of ethnic minority households in Son La Province. In addition, the factors positively affecting the livelihood choices of ethnic minority households in Son La Province of Vietnam are education level, labor size, access to credit, membership of associations, support policies, vocational training, and district. Thus, improving ethnic minority householder’s knowledge through formal educational and training, expanding availability of accessible infrastructure, and enhancing participation of social/political associations were recommended as possible policy interventions to diversify livelihood activities so as to mitigate the level of poverty in the study area.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.