We are going through a period in which the concept of the smart village (SV) is a novelty for the management of a community, and the new smart economy of the village is based on the power of community support. Appropriately, the development of a SV is related to a family’s participation in the motivation and access to education, the increase in knowledge of information technology, information and communications technology (ICT) literacy, and also in the creation of facilities for research and development (R&D). The partnership between the public administration, the private sector, and the community heads will lead to a smart economy within the village. At the same time, the intervention of the food system to support climate change can be supported by intelligent agriculture. The SV has a strong social significance; research in the field can be multidisciplinary, including human nutrition, climate change, and community education. This paper aims to X-ray the research areas of the SV from a multidisciplinary sense, in support of the partnership with the community, and to identify the main directions of strategic development. In total, 368 pieces of research on SVs from the last ten years were analyzed through bibliometric analysis using VOSviewer software, doubled by the co-occurrence of keywords and the bibliometric combination of documents, followed by a systematic review of the literature. The research undertaken was intended to contribute to the development of research for SVs, with the analysis of identified clusters. The results obtained will have a special contribution at the SV level through strategic and research proposals and suggest that the most important strategic and research directions for SVs focus on community education, its satiety, as well as several environmental and social changes generated by SVs.

This paper shows the skills and competences (technical, behavioural and contextual) affecting regional and rural development in Romania. The methodology used is based on the model of Working with People (WWP), which integrates elements of social learning and planningand Project management international models, which integrate competences that have an influence on regional development. WWP model is the result of experience in rural development planning from the research group GESPLAN at the Technical University of Madrid in several European contexts and emerging countries.The results show that the main skills and competences for regional development in Rumania are focused on three components: technical-entrepreneurial,social-ethical and political-contextual. Experience lessons in the first years of the Romanian National Rural Development Network (NRDN) demonstrate the right project management approach for Regional Development, exceeding the “technical” approach of the management and emphasizing the behaviour of individuals and the contexts where they work. This new way of thinking opens up new fields of research in regional development projects planning, evaluation and management. These three dimensions are necessary for effective management and implementation of projects and programs under conditions of regional development

European Union (EU) policy encourages the development of a blue economy (BE) by unlocking the full economic potential of oceans, seas, lakes, rivers and other water resources, especially in member countries in which it represents a low contribution to the national economy (under 1%). However, climate change represents a main barrier to fully realizing a BE. Enabling conditions that will support the sustainable development of a BE and increase its climate resiliency must be promoted. Romania has high potential to contribute to the development of the EU BE due to its geographic characteristics, namely the presence of the Danube Delta-Black Sea macrosystem, which is part of the Romanian Lower Danube Euroregion (RLDE). Aquatic living resources represent a sector which can significantly contribute to the growth of the BE in the RLDE, a situation which imposes restrictions for both halting biodiversity loss and maintaining the proper conditions to maximize the benefits of the existing macrosystem. It is known that climate change causes water quality problems, accentuates water level fluctuations and loss of biodiversity and induces the destruction of habitats, which eventually leads to fish stock depletion. This paper aims to develop an analytical framework based on multiple linear predictive and forecast models that offers cost-efficient tools for the monitoring and control of water quality, fish stock dynamics and biodiversity in order to strengthen the resilience and adaptive capacity of the BE of the RLDE in the context of climate change. The following water-dependent variables were considered: total nitrogen (TN); total phosphorus (TP); dissolved oxygen (DO); pH; water temperature (wt); and water level, all of which were measured based on a series of 26 physicochemical indicators associated with 4 sampling areas within the RLDE (Brăila, Galați, Tulcea and Sulina counties). Predictive models based on fish species catches associated with the Galati County Danube River Basin segment and the “Danube Delta” Biosphere Reserve Administration territory were included in the analytical framework to establish an efficient tool for monitoring fish stock dynamics and structures as well as identify methods of controlling fish biodiversity in the RLDE to enhance the sustainable development and resilience of the already-existing BE and its expansion (blue growth) in the context of aquatic environment climate variation. The study area reflects the integrated approach of the emerging BE, focused on the ocean, seas, lakes and rivers according to the United Nations Agenda. The results emphasized the vulnerability of the RLDE to climate change, a situation revealed by the water level, air temperature and water quality parameter trend lines and forecast models. Considering the sampling design applied within the RLDE, it can be stated that the Tulcea county Danube sector was less affected by climate change compared with the Galați county sector as confirmed by water TN and TP forecast analysis, which revealed higher increasing trends in Galați compared with Tulcea. The fish stock biodiversity was proven to be affected by global warming within the RLDE, since peaceful species had a higher upward trend compared with predatory species. Water level and air temperature forecasting analysis proved to be an important tool for climate change monitoring in the study area. The resulting analytical framework confirmed that time series methods could be used together with machine learning prediction methods to highlight their synergetic abilities for monitoring and predicting the impact of climate change on the marine living resources of the BE sector within the RLDE. The forecasting models developed in the present study were meant to be used as methods of revealing future information, making it possible for decision makers to adopt proper management solutions to prevent or limit the negative impacts of climate change on the BE. Through the identified independent variables, prediction models offer a solution for managing the dependent variables and the possibility of performing less cost-demanding aquatic environment monitoring activities.

In agriculture, the production structure of farms can be highly diversified to reduce risk and uncertainty related to unsealing the products. To determine the optimal structure of crops, different methods which take into account the income and expenditure of crops per hectare are used. As a result, the area of each crop is identified, so that, in combining them to derive maximum profit level. In this paper, linear programming method is used for optimizing profit, investigating whether, after applying the econometric model, the profit increased or not. The results show that profit rose to 143% and costs reduced to 81%.

Moldova possesses the largest area of farmland as a share of its total land surface, an advantage which should encourage economic development strategies oriented towards the agriculture sector. Government subsidies and agriculture loans have been used as tools for developing the Moldavian agriculture. However, considering the challenges generated by both climate change (the drought from year 2012 that affected 80% of farmland) and a difficult political situation (restrictions imposed by the Russian Federation on the Republic of Moldova’s agri-food imports and exports between 2013 and 2014), the country’s agricultural system ranks very low when it comes to agricultural production efficiency. The present paper analyses the performances of the agricultural sector and its impact on the Moldavian economy over a nine-year period (between 2008 and 2016), by using a custom-developed analytical framework based on a dataset containing 21 relevant indicators. The analytical framework generates various perspectives that can be used to elaborate an economic sustainable development strategy of the Moldavian agriculture sector. The development of the analytical framework is based on the dynamics of agriculture subsidies, agricultural loans, the agricultural sector’s gross domestic product (GDP) and gross value added (GVA), as well as the dynamics of agricultural production and production value, also considering the main crops belonging to the Moldavian agriculture sector. The results are presented as sets of mathematical regression models that quantify the relationships found between the relevant agricultural parameters and their impact on the economics of the agricultural sector. It has been identified that the agriculture sector has a considerable impact on the Moldavian economy, a fact revealed by the significant model between the agriculture GVA and total GVA and GDP. A significant, negative correlation model was identified between agriculture subsidies and agriculture loans, although a small percentage of Moldavian agriculture farms were subsidized. Strong correlation models were also identified between wheat and maize production and total agriculture production, emphasizing the importance of these two crops for the Moldavian agricultural economy. Grape and maize production values also generated a correlation model, emphasizing the market interconnection between these crops It can be concluded that the increase in value of governmental agriculture subsidies, as well as expanding their addressability in order to maximize the access possibility for a higher number of agriculture farms, are essential for the Moldavian agriculture sector’s future development, since considering the limiting value of and accessibility to subsidies, a direct correlation model was identified between governmental agriculture subsidies and agriculture GVA.