Traditional and emerging interest networks supported by the advancement of digital and telecommunication technologies, the growing use of bioenergy and the ability to take advantage of knowledge beneficial for local populations and business development promote strategic breakthroughs of rural communities. The paper focuses on the problem of the smart village development with respect to a sustainable rural regional development. The aim of the research is to identify the preconditions for rural area progress and smart rural villages driving forces in Lithuania. The research object concerns the principles and driving forces of the development of smart villages. The research methods inter alia included analysis, systematization, and comparison of scientific literature, documents, and good practice examples. Analysis of the experiences of villages and local/international organizations and research into the best practices helped to identify the drivers and the key principles of the smart village development. The case study revealed that three out of five selected pilot rural areas of Lithuania have an innovative potential with some of the smart village principles adopted. The main constraints identified by the study were related to the lack of technological, digital or energy efficiency innovation and human resources in rural areas.

This article deals with the important issue concerning that small towns and villages play an important role in the development of many European regions, not only from the point of view of agricultural function, but also due to the preservation of identity and heritage as well as social relations and management of spatial structures. On the other hand, in small towns and villages, there are growing problems related to the migration of people to big cities, leaving farms and villages. Progressive unemployment is observed, especially in peripheral areas. The research question is: what are the similarities and differences of social and spatial relations between small towns and surrounding villages in the selected countries? The article aims to present the interface between social and spatial relationships in small towns and surrounding villages in the context of analyzing the potential of rural areas and models for their development. Authors compared the specificity of small towns and villages of selected regions of Poland, Lithuania, and Slovakia. The following methods were used in the research: analysis and synthesis of literature and documents (legal and strategic), descriptive method, secondary data analysis, comparative method, visual data representation, case study.

Research on household energy poverty is crucial for addressing basic human needs, highlighting the importance of conducting studies across different countries. This study examines energy poverty in the Visegrad Group countries using 2022 data from the EU Statistics on Income and Living Conditions survey, with the ‘inability to keep the home warm’ indicator as a measure. The study aims to identify socio-economic factors influencing energy poverty and examine how their impacts differ across the examined countries. Logistic regression, combined with machine learning techniques, was applied for this purpose. Furthermore, the study evaluates the classification results of logistic regression and three machine learning methods—CatBoost, Balanced Random Forests, and Extreme Gradient Boosting—on imbalanced data. It was found that, among the three machine learning methods used, Balanced Random Forests performed the weakest. Logistic regression, effective for our imbalanced data, complements the results and provides deeper insights into the socio-economic factors influencing energy poverty. The study found that Slovakia had the highest percentage of households vulnerable to energy poverty, while Czechia had the lowest. Income, household type, and the presence of disabled individuals were found to be important across all countries. However, other factors varied in their influence from one country to another, highlighting the need for country-specific analyses. Monitoring households’ exposure to energy poverty is a challenge for future social policy and the use of different methods provides an in-depth view of this complex issue.

Social infrastructure is largely related to various services for community, facilities and public spaces, relationships and networks among local community members. It is therefore obvious that social infrastructure could be viewed as an important factor for creating better opportunities for integration and participation in society, fostering functional capabilities of a community, acknowledging human rights, improving judgements related to overall life satisfaction. The links between social infrastructure services and focus on local community wellbeing in Lithuanian’s social science discourse has not been substantiated sufficiently yet. Consequently, this article aims at disclosing the importance of social infrastructure services in promotion of local community wellbeing. The research question of this article is formulated as follows: how social infrastructure services contribute and could promote wellbeing of local community. The methodological background is based on both theoretical and empirical findings pertaining to the topic. The research results have suggested that the need of local community for social infrastructure services should be evaluated more carefully in the context of wellbeing. These services have been found to play significant role in reaching a certain level of wellbeing in view of the place where people live, how they feel and how to evaluate the future of their living.

Scientists and policy makers more often point out that pro-environmental attitudes and behaviour are related to subjective well-being, but there is a lack of deep scientific insights, as well as possible measure analysis, which would promote pro-environmental behaviour but, at the same time, lead to higher subjective well-being. The aim of this study is to investigate the relationship between pro-environmental attitudes, concerns about climate change, and subjective well-being in Central and Eastern European countries. This study employs descriptive statistics and multiple regression analysis to identify subjective well-being predictors in the case of Central and Eastern European countries. This study uses data from European Social Survey (ESS) rounds 4–10, and includes questions on pro-environmental attitudes, climate change cognition, orientation towards materialistic values, and households’ total net income. The conducted research revealed that pro-environmental attitudes were related to higher levels of subjective well-being in different ESS rounds in many Central and Eastern European countries. In addition, there is some evidence that the relationship between pro-environmental attitudes and subjective well-being is weaker among individuals who are more oriented towards materialistic values. According to the results of this study, policy makers should develop policies that not only address environmental problems but also contribute to subjective well-being.

This article reveals the importance of different methods for assessment of social infrastructure (SI) development needs in rural areas. Rural social infrastructure is a significant element of rural territories interpreted in different ways: as social and economic system, basic services for local community, social bridge for integrating different social groups into the society, important factor for satisfaction of rural people’s needs and acknowledgement of their human rights. Besides the mentioned importance of SI to rural areas and rural community, the lack of exploration of methods for analysis of the needs for developing rural social infrastructure has been noticed in the scientific literature. The research aim is therefore to analyse the methods for assessment of needs of rural social infrastructure. The research question has been set accordingly: how different methods for need analysis could be applied to social infrastructure planning and development? The research results show that need analysis is generally linked to various methods, but for the SI planning, development and implementation specifically, there are certain methods, the application of which depends on specifics of rural areas (as territory) and features of local community.