In the current global context, where rural sustainability and economic diversification of agricultural regions are becoming increasingly important, rural tourism and agritourism are emerging as key strategies for sustainable development. This study aims to conduct a scientometric analysis of research trends in rural tourism and agritourism during the pandemic and post-pandemic periods (2020–2024) by identifying dominant themes, relevant scientific contributors, and emerging directions related to sustainability and post-COVID-19 transformations. To carry out this analysis, 1915 papers indexed in the Web of Science Core Collection database were selected. Using VOSviewer software, co-citation networks, keyword co-occurrence, and international collaboration were generated and analyzed to identify thematic clusters and main research directions. The results highlight an increasing scientific interest in sustainable tourism models that integrate digitization, circular economy principles, and authentic rural experiences. The most frequently identified terms include ‘rural tourism’, ‘agritourism’, ‘sustainability’, and ‘COVID-19’, reflecting the field’s adaptation to recent global challenges. This study identifies major contributors (China, Italy, Spain, USA, Romania), key institutions, and gaps in the literature. Additionally, future research directions and practical implications are proposed for policymakers, rural entrepreneurs, and tourism promotion organizations.

This study aimed to explore the perceptions of tourists regarding traveling for recreational or leisure purposes in times of health crisis. All areas of activity have been affected by the pandemic caused by the SARS-CoV-2 coronavirus (associated with a disease called COVID-19), and all countries are experiencing health crises. The tourism industry, together with its associated fields, experienced a decline during this period that is still difficult to assess. This study examined intentions to travel in the current conditions imposed by the health crisis. Various measures have been recommended or imposed by governments to control the spread of COVID-19. Travel has been significantly influenced by such measures. However, people have various travel needs, from shopping to work and leisure to exploration. The data were collected through an online questionnaire survey addressed to the active population in Romania. The application of this questionnaire coincided with the third wave of SARS-CoV-2 infections in Romania. The conditions related to the degree of incidence of infections in the respondents’ areas and also the connection between the expression of the intention to travel and the protection conditions in the destination areas were analyzed. The entire study was based on office research, statistical analysis, case study methods, and analysis of empirical data obtained through the survey of the active population in Romania. The results explain the travel tendencies of Romanians in the following period. Fear of infection and perceived risk have significantly influenced travel behaviors, but intentions to travel for recreational or leisure purposes have been maintained. The results of this study could be useful in planning and rethinking the activities of the tourism industry in the coming period.

The research aims at studying and predicting the migration process in Romania over the last 20 years and at identifying the impact of the COVID-19 pandemic. The study analyzes several models for estimating migration through linear regression, but also a VAR (Vector autoregression) analysis, as the variables can influence each other. Vector autoregression (VAR) is also used to model multivariate time series, and it can analyze the dynamics of a migration process. Therefore, the best model for forecasting the migration process in Romania is Model 1 of linear regression. This phenomenon generates many positive and negative economic, demographic and political effects. The migration process has become particularly important for Romania in the last 20 years, and its socio-economic, political and cultural effects affect the Romanian state. That is why flexible policies are needed in order to be coherent, to have as main purpose keeping specialists in the country in certain basic economic fields, as well to implement measures to determine the return of specialists and students who have left to study abroad.

This paper explores an important problem in tourism demand analysis, namely, the inherent uncertainty involved in projecting tourism demand. Tourism demand continues to be severely affected by unforeseen events associated with the current global health crisis, which has led to an examination of ways to predict the devastating effects of the COVID-19 pandemic on tourism. Tourism flow forecasting relating to arrivals is of particular importance for tourism and the entire hospitality industry, because it is an indicator of future demand. Thus, it provides fundamental information that can be applied in the planning and development of future strategies. Accurate forecasts of seasonal tourist flows can help decision-makers increase the efficiency of their strategic planning and reduce the risk of decision-making failure. Due to the growing interest in more advanced forecasting methods, we applied the ARMA model method to analyze the evolution of monthly arrival series for Romania in the period from January 2010 to September 2021, in order to ascertain the best statistical forecasting model for arrivals. We conducted this research to find the best method of forecasting tourist demand, and we compared two forecasting models: AR(1)MA(1) and AR(1)MA(2). Our study results show that the superior model for the prediction of tourist demand is AR(1)MA(1).

This study explores an important issue in tourism, namely, the competitiveness of tourism. In the present paper, we aim at analyzing the relationship between tourism and national prosperity. The term competitiveness is a research topic intensively addressed in various fields, and it can answer current research questions related to a constantly changing tourism industry. Thus, the possibility of knowing how competitive this particularly important sector is for the five emerging countries considered in the study, namely, the Czech Republic, Hungary, Poland, Romania, and Slovakia, allows public authorities and entrepreneurs to estimate the revenues that can generate the field of hospitality. Also, based on these results, a series of national strategies specific to the tourism industry can be founded to lead to the increase of its competitiveness. We used cross-country multiple regression analysis to determine variables that are particularly important for the competitiveness of the hospitality industry, a fact for which the study has a theoretical and practical applicability. The study offers the possibility to anticipate the values of this index (TTCI), thus enabling government and industry bodies to take the necessary steps to increase specific competitiveness in the international market.

Our study analyzes the essential role of social innovation in reducing social exclusion and unemployment while improving citizens’ well-being through targeted public policies that enhance GDP allocations to social protection. Using Eurostat data and European Innovation Scoreboard (EIS) from 2019 to 2020, a comparative econometric analysis of all 27 EU member states, focused particularly on Romania, examines the interdependence between social innovation, social protection expenditures, social exclusion, and unemployment rates. Regression and ANOVA models confirm a significant positive relationship between social innovation and social protection spending. However, Romania’s overall share of social protection in GDP remains well below the EU average, despite higher relative spending on health, pensions, and family support, reflecting structural limitations and a slower diffusion of innovative practices. As an exploratory effort, the study acknowledges possible distortions caused by the pandemic, which temporarily increased expenditures and altered long-term trends. Broader macroeconomic factors such as inflation, demographics, and technology were not included but may refine future analyses. The findings provide both theoretical and practical insights, suggesting that enhancing social innovation through public policy can strengthen social cohesion, improve quality of life, and support the sustainable development of national protection systems.