Perspectives on Smart Villages from a Bibliometric Approach

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.


Introduction
A Smart village (SV) is a model of community management in which the digitization of activities can support not only the geological ecosystem, but also has an impact on the economic and social system [1]. Digitization is considered possible only if a reliable communications network and infrastructure are established in rural areas. Human resources and education have been, and are, the most important resources for the success of the initiatives considered, being the driving force for SVs [2]. Gender equity improvement in information technology knowledge is essential for protecting a sustainable community and improving livelihoods [3]. At the same time, the climatic risks and livelihoods of small farmers in vulnerable regions, where they often face the loss of an entire crop, are causing a population migration (mostly men), creating a depopulation situation in rural areas. SVs attract the To achieve this, we combined two bibliometric methods: keyword co-occurrence and bibliographic linking by identifying groups of topics and publications related to SVs. Bibliometric methods were supplemented by a systematic literature review to understand the content of the identified clusters [1,11].
The co-occurrence analysis of the keywords allowed us to identify the main directions of research on SVs, as follows: "The size of SVs" [11] and "Access to the SV", the latter proved to be a subject which attracted the attention of applicants much more quickly, and with special attention. The bibliographic overlap of the documents was combined with a careful review of the literature, which allowed us to understand the current knowledge of the field and to identify thematic clusters that will lead to future research directions [3].
We identified six groups: "Energy Dimension in SVs", "Access to Energy Infrastructure in SVs", "The SV as an Engineer for Renewable Energy Consumer Behavior", "Access to Digital Infrastructure", "Governance and Planning in SVs" and "Perspectives for SVs".
We appreciate that these constructions show SVs as a way to solve problems in local communities, promoting sustainable consumption and production.
In the following, we present the methodology of data analysis, sampling, and research methods. Finally, the results of the analyses, discussions, and perspectives of the concept are presented.

Materials and Methods
Scopus and WoS are two important sources of bibliometric data for this type of analysis. For the research, we used the most complete database, Scopus processing being done with the help of VOSviwer [17]. The studied topic, the SV, is one of major interest, represented in our study from 2011 to date in 2022, which was has also been the most intense period in the development of SVs. Our contribution was highlighted in the following steps ( Figure 1): liometric methods were supplemented by a systematic literature review to understand the content of the identified clusters [1,11].
The co-occurrence analysis of the keywords allowed us to identify the main directions of research on SVs, as follows: "The size of SVs" [11] and "Access to the SV", the latter proved to be a subject which attracted the attention of applicants much more quickly, and with special attention. The bibliographic overlap of the documents was combined with a careful review of the literature, which allowed us to understand the current knowledge of the field and to identify thematic clusters that will lead to future research directions [3].
We identified six groups: "Energy Dimension in SVs", "Access to Energy Infrastructure in SVs", "The SV as an Engineer for Renewable Energy Consumer Behavior", "Access to Digital Infrastructure", "Governance and Planning in SVs" and "Perspectives for SVs".
We appreciate that these constructions show SVs as a way to solve problems in local communities, promoting sustainable consumption and production.
In the following, we present the methodology of data analysis, sampling, and research methods. Finally, the results of the analyses, discussions, and perspectives of the concept are presented.

Materials and Methods
Scopus and WoS are two important sources of bibliometric data for this type of analysis. For the research, we used the most complete database, Scopus processing being done with the help of VOSviwer [17]. The studied topic, the SV, is one of major interest, represented in our study from 2011 to date in 2022, which was has also been the most intense period in the development of SVs. Our contribution was highlighted in the following steps ( Figure 1): 1. The term "Smart Village" was collected in the title, abstract, and keywords of articles in May 2022. This search generated 926 documents published on Scopus in the period 2011 to May 2022.
2. Articles published in the English language were selected according to VOSviewer requirements [18]. The database searches were limited to research articles only, excluding conferences, reviews, and editorials, since they may include pre-preliminary research results. Books and book chapters were also excluded for the same reasons. Thus, after all listed exclusions, there were 390 publications in Scopus.  2. Articles published in the English language were selected according to VOSviewer requirements [18]. The database searches were limited to research articles only, excluding conferences, reviews, and editorials, since they may include pre-preliminary research results. Books and book chapters were also excluded for the same reasons. Thus, after all listed exclusions, there were 390 publications in Scopus.
3. For a more relevant sample of articles on the subject of SVs, the 390 scientific articles were analyzed and verified, resulting in a final sample of 368 research articles. In the excluded publications, the term "Smart Village" appeared in abstracts or keywords, but the subject of the paper was not specifically related to SV [11,19].
Quantitative analysis of the previous studies, provided us with a bibliographic diversity (starting from the title, first name, last name, keyword, and year of publication). Using statistical methods, we analyzed a variety of scientific articles to focus on the current state of development techniques and models within the analyzed period. Bibliometrics is a well-established method which includes the analysis of aspects related to publication, and together with the specific statistical methods for such an analysis, the development of global databases can be achieved through subsequent indexing. Before these databases, researchers collected publications manually for the analysis of citations and other bibliometric methods. Different methods are used in the process of bibliometric analysis [20], either by analyzing the citations which show the frequency with which the papers are cited in other documents, or the bibliographic link which shows whether several papers have similar bibliographic references. The co-author's analysis shows the frequency with which a group of authors has a certain intensity of scientific collaborations. An analysis of citations shows the frequency of citations of some authors compared to others in the field. An analysis of how often keywords are used is then used to map a particular domain.
In conducting this study with the help of VOSviewer software, we followed the coappearance of keywords and bibliographic linkages; because the research field of SVs recent, it becomes interesting to map future research directions. VOSviewer was used because it is commonly used for exploring and viewing maps created by bibliometric data. The technique of tracking the co-occurrence of keywords and bibliographic linking can be used to show the intensity of the network, and also to show how well the network is merged.
Keyword co-occurrence is considered a method of analysis which shows how often keywords appear simultaneously, and the level of closeness of the basic concepts [20]. The method shows the degree of study for the content of documents, compared to the appearance of keywords. Scientific articles can show the level of concentration of concepts and the connections between them.
Co-occurrence of keywords using VOSviewer allowed us to identify keywords by criteria (by title, author, indexed, or all combined) and to distribute them as groups within the network [11]. The analysis is influenced by the quality of the database, the methods and tools used, and the quality of the keywords. Table 1 shows the parameters that were used to analyze the co-occurrence of keywords in the SV research field. Bibliographic linking occurs if two documents cite the same document. The bibliographic link analyzes the overlap in the document references. When the same references appear in two articles, we know that there is a certain bibliographic link. When a large number of common references appear in a group of articles, a strong bibliographic link is recognized between them [20]. Co-citation differs from bibliographic coupling as a method because it presents the latest articles, even with zero citations. Thus, the bibliographic link analyzes even the most recent research articles [4,11]. Table 2 presents the criteria used in the bibliographic coupling analysis of SVs. The systematic review of literature is a traditional method used in fundamental research which studies the topics, methods, constructions, and research frameworks through rigorous review. A systematic review of literature can help to understand the current state and the topicality of the field, and can also identify the limits of research and research perspectives. Using bibliometric methods followed by a literature review is a combined approach which gained ground after 2015, based on VOSviewer software, and today it is applied in different fields of research in sociology and economics. In our research, we started with the bibliometric analysis, especially in the analysis of the co-occurrence of keywords, looking for the main topics in the field of SV research, and identifying clusters of documents. Subsequent revisions of articles in the literature allowed us to analyze the clusters (on documents) identified by the bibliographic link. In-depth research was carried out on the clusters, understanding their content and discussing the results of the bibliometric analysis [11].
For each of the 30 countries, the total strength of the bibliographic links with other countries was calculated. The countries with the highest total link strength were selected. The articles identified by the bibliographic link by country are shown in Tables S1-S6 of the Supplementary Materials, with the most cited articles shown by country and cluster typologies. Figure 2 shows the evolution of the data analysis process using VOSviewer.
appear in two articles, we know that there is a certain bibliographic link. When a large number of common references appear in a group of articles, a strong bibliographic link is recognized between them [20]. Co-citation differs from bibliographic coupling as a method because it presents the latest articles, even with zero citations. Thus, the bibliographic link analyzes even the most recent research articles [4,11]. Table 2 presents the criteria used in the bibliographic coupling analysis of SVs. The systematic review of literature is a traditional method used in fundamental research which studies the topics, methods, constructions, and research frameworks through rigorous review. A systematic review of literature can help to understand the current state and the topicality of the field, and can also identify the limits of research and research perspectives. Using bibliometric methods followed by a literature review is a combined approach which gained ground after 2015, based on VOSviewer software, and today it is applied in different fields of research in sociology and economics. In our research, we started with the bibliometric analysis, especially in the analysis of the co-occurrence of keywords, looking for the main topics in the field of SV research, and identifying clusters of documents. Subsequent revisions of articles in the literature allowed us to analyze the clusters (on documents) identified by the bibliographic link. In-depth research was carried out on the clusters, understanding their content and discussing the results of the bibliometric analysis [11].
For each of the 30 countries, the total strength of the bibliographic links with other countries was calculated. The countries with the highest total link strength were selected. The articles identified by the bibliographic link by country are shown in Tables S1-S6 of the Supplementary Materials, with the most cited articles shown by country and cluster typologies. Figure 2 shows the evolution of the data analysis process using VOSviewer.

Data Characteristics
The constructed centralizations resulted in several of the 926 research articles on SVs, published 2011-2021, being indexed in Scopus [11]. The topics of the articles were very varied, represented in fields such as "Social Sciences" (123 papers), "Agricultural and Biological Sciences" (80), and "Environmental Science" (63). The research territory presented in the papers covered 85 countries, but the main country for SV research was India (113 papers out of 368) [11].
The sample was limited [11] to the rank of journals from the last decade, because published research in the field of SVs grew rapidly after 2019. The Figure 3 shows the evolution of the publication of selected articles in rapid growth over the last ten years. varied, represented in fields such as "Social Sciences" (123 papers), "Agricultural and Biological Sciences" (80), and "Environmental Science" (63). The research territory presented in the papers covered 85 countries, but the main country for SV research was India (113 papers out of 368) [11].
The sample was limited [11] to the rank of journals from the last decade, because published research in the field of SVs grew rapidly after 2019. The Figure 3 shows the evolution of the publication of selected articles in rapid growth over the last ten years. Research on SVs was published in journals such as Sustainability (Switzerland), Agriculture (Switzerland), Land Use Policy, Social Sciences, and Ecological Economics. The research methods used were interview-based surveys, and the systematic analysis of documents for the case study was conducted using a focus group [15,21].
For further analysis using VOSviewer, 242 articles were exported from Scopus in CSV excel format (available online in additional materials) [11].
Thus, if we analyze the density of keywords used in SV analysis, (network links/possible links), we see high results around the red cluster (keyword "smart grid"), followed by the blue cluster (keyword "rural areas") and the "human" green cluster.  Research on SVs was published in journals such as Sustainability (Switzerland), Agriculture (Switzerland), Land Use Policy, Social Sciences, and Ecological Economics. The research methods used were interview-based surveys, and the systematic analysis of documents for the case study was conducted using a focus group [15,21].
For further analysis using VOSviewer, 242 articles were exported from Scopus in CSV excel format (available online in additional materials) [11].
Thus, if we analyze the density of keywords used in SV analysis, (network links/possible links), we see high results around the red cluster (keyword "smart grid"), followed by the blue cluster (keyword "rural areas") and the "human" green cluster.
We marked the first cluster (red) formed by the simultaneous appearance of the keywords "Energy dimension in SV" in close connection with SV and electric power transmission network, as well as energy efficiency and various ways to develop SVs. SV is described by keywords such as "rural electrification", "photovoltaic system", and "solar power" [22]. SV management is associated with keywords such as "energy management", "investments", "energy resources", and "hybrid systems". The keywords for the development of the areas referred to the main product [11] of the SV and their characteristics, such as "commerce", "cost analysis", "cost-benefit analysis", "demand", "design" and "electricity". In this cluster, SV appears among the alternative energy systems which are characterized by keywords such as "energy conservation", "energy efficiency", "energy management" and "hybrid system". The red cluster also refers to the development of the states; the main regions studied in this cluster are Kenya, Switzerland, and Europe. SV research includes urban as well as rural areas, with a predominance of urban studies [23].
The correct is: We labelled the second co-occurring keyword group (green) as 'human' refers to keywords including "female", "adult", "middle age", "social stigma", and "mental health services". The third co-occurring keyword group (blue) is labelled as 'rural area and smart village' because SV also refers to internet accessibility, where digital space is described [24], the internet of things (IoT), and rural development. Men and health appear in this cluster as people who are involved in SVs. The fourth co-occurring keyword group (yellow) "agriculture and climate change" refers to keywords including "adaptation to climate change", "smart agriculture", and "questionnaire analysis". This group includes keywords such as "farmers", "food security", "technology adaptation" and "attitude towards water management". Farmers and greenhouses appear in this cluster as the main pawns involved in the SV. . Co-occurrence analysis in the SV study using keywords. The first (red) smart grid cooccurrence cluster; the second (green) co-occurrence group "human", the third (blue) co-occurrence group "rural area". (VOSviwer offers the possibility of an interpretation of the references by color, as in the figure above).
We marked the first cluster (red) formed by the simultaneous appearance of the keywords "Energy dimension in SV" in close connection with SV and electric power transmission network, as well as energy efficiency and various ways to develop SVs. SV is described by keywords such as "rural electrification", "photovoltaic system", and "solar power" [22]. SV management is associated with keywords such as "energy management", "investments", "energy resources", and "hybrid systems". The keywords for the development of the areas referred to the main product [11] of the SV and their characteristics, such as "commerce", "cost analysis", "cost-benefit analysis", "demand", "design" and "electricity". In this cluster, SV appears among the alternative energy systems which are characterized by keywords such as "energy conservation", "energy efficiency", "energy management" and "hybrid system". The red cluster also refers to the development of the states; the main regions studied in this cluster are Kenya, Switzerland, and Europe. SV research includes urban as well as rural areas, with a predominance of urban studies [23].
The correct is: We labelled the second co-occurring keyword group (green) as 'human' refers to keywords including "female", "adult", "middle age", "social stigma", and "mental health services". The third co-occurring keyword group (blue) is labelled as 'rural area and smart village' because SV also refers to internet accessibility, where digital space is described [24], the internet of things (IoT), and rural development. Men and health ap- . Co-occurrence analysis in the SV study using keywords. The first (red) smart grid cooccurrence cluster; the second (green) co-occurrence group "human", the third (blue) co-occurrence group "rural area". (VOSviwer offers the possibility of an interpretation of the references by color, as in the figure above). Figure 5 shows the overlapping view of the keyword co-occurrence network [11], but the color of the articles here reflects the average year of publication, from purple Thus, we can visualize the overlap in the network to be able to analyze its evolution and its clusters, and to identify future research directions. The analysis of Figure 5 allowed the novelty of the resulting groups (clusters) to be appreciated, by the fact that the average year of publication is 2019. Therefore, a shift in attention was noted from studying the SV as a rural management system or connection model, to the rural electrification of villages, knowledge, and mental health for human and climate change.
The research allowed us to form new groups of words based on studies in the period 2011-2022 in this network, because most of them are very recent, especially from 2019. The new keywords for the first group of "Smart grid" are "rural electrification", "renewable energies", "energy conservation", "microgrids", "electricity generation", "surveys". The new keywords for the second group of "rural areas" are "GIS", "potable water", and "India". These keywords may represent real models for SV research, such as education, and mobile application. main pawns involved in the SV. Figure 5 shows the overlapping view of the keyword co-occurrence network [11], but the color of the articles here reflects the average year of publication, from purple (2011-2018), blue (2018-2019), green (2019), yellow (2020-2022).
Thus, we can visualize the overlap in the network to be able to analyze its evolution and its clusters, and to identify future research directions. The analysis of Figure 5 allowed the novelty of the resulting groups (clusters) to be appreciated, by the fact that the average year of publication is 2019. Therefore, a shift in attention was noted from studying the SV as a rural management system or connection model, to the rural electrification of villages, knowledge, and mental health for human and climate change. The research allowed us to form new groups of words based on studies in the period 2011-2022 in this network, because most of them are very recent, especially from 2019. The new keywords for the first group of "Smart grid" are "rural electrification", "renewable energies", "energy conservation", "microgrids", "electricity generation", "surveys". The new keywords for the second group of "rural areas" are "GIS", "potable water", and "India". These keywords may represent real models for SV research, such as education, and mobile application.

Bibliographic Coupling Analysis Combined with Systematic Literature Review
The bibliographic link of the articles was published by country so that the field of SV research could be approached from a different angle compared to previous analyses. This

Bibliographic Coupling Analysis Combined with Systematic Literature Review
The bibliographic link of the articles was published by country so that the field of SV research could be approached from a different angle compared to previous analyses. This helps with the identification of the proximity of publications to certain centers of interest (countries) which can focus in on a certain perspective. The bibliographic network of documents is presented in Figure 6.
With a small number of citations (not excluding the latest publications), as well as a minimum of 5 articles per country (as recommended by VOSviewer), this network consists of 30 countries and comprises six groups and 276 links between documents. With 11,884 possible connections, the density of the network is 43.05%, which reflects a low network interconnection.
We followed the overlap made in the map (Figure 7) which showed the development of the network on a timeline (2011-2022). Table 3 and Figure 8 summarize the results of the bibliographic link analysis of the documents completed by the systematic review of the specialized literature for the identified clusters.
In the additional materials, tables present the most cited and most influential journals for each cluster built using the contents of these articles. Therefore, we propose names for each network (cluster) with their explanations below: helps with the identification of the proximity of publications to certain centers of interest (countries) which can focus in on a certain perspective. The bibliographic network of documents is presented in Figure 6. With a small number of citations (not excluding the latest publications), as well as a minimum of 5 articles per country (as recommended by VOSviewer), this network consists of 30 countries and comprises six groups and 276 links between documents. With 11,884 possible connections, the density of the network is 43.05%, which reflects a low network interconnection.
We followed the overlap made in the map (Figure 7) which showed the development of the network on a timeline (2011-2022).  With a small number of citations (not excluding the latest publications), as well as a minimum of 5 articles per country (as recommended by VOSviewer), this network consists of 30 countries and comprises six groups and 276 links between documents. With 11,884 possible connections, the density of the network is 43.05%, which reflects a low network interconnection.
We followed the overlap made in the map (Figure 7) which showed the development of the network on a timeline (2011-2022).   The most stable cluster One of the youngest clusters, with growing interest in the cluster's scope Figure 8. Network view of the bibliographic linkage of the documents in the 6 resulting clusters. Cluster 1 (red) "The energy dimension in the SV", Cluster 2 (green) "Access to energy infrastructure in the SV", Cluster 3 (blue) "The behavior of renewable energy consumers", Cluster 4 (yellow) "Access to digital infrastructure in the SV", Cluster 5 (purple) "Governance and planning in SVs", Cluster 6 (turquoise) "Access to renewable energy for SVs".
In the additional materials, tables present the most cited and most influential journals for each cluster built using the contents of these articles. Therefore, we propose names for each network (cluster) with their explanations below: Figure 8. Network view of the bibliographic linkage of the documents in the 6 resulting clusters. Cluster 1 (red) "The energy dimension in the SV", Cluster 2 (green) "Access to energy infrastructure in the SV", Cluster 3 (blue) "The behavior of renewable energy consumers", Cluster 4 (yellow) "Access to digital infrastructure in the SV", Cluster 5 (purple) "Governance and planning in SVs", Cluster 6 (turquoise) "Access to renewable energy for SVs". Cluster 1 (red): "Energy dimension in the SV" is representative of the number of citations and the highest content. The overlapping map in Figure 7 shows its current development, the articles in the cluster being published during the period 2017-2020.
Among the most influential theoretical works, attention is drawn to the awareness of citizens regarding "smart" applications and solutions and their ability to use them.
Research results [25], have shown that users who are aware and skilled in using applications are concerned about the usefulness, security, accessibility, and efficiency of those services. In turn, this theoretical work analyzes the potential of AI which can provide support in the process of achieving energy sustainability. Empirical work examines AI monitoring within the context of shaping the power consumption of electrical appliances. New contributions of AI are also being debated in greening agriculture.
In addition, the empirical works [26] from this group present a new global model for smart, green ecological villages in tropical countries. An ecovillage [27] based on renewable energy using the concept of an "integrated biomass solar city" [28] will optimize the use of biomass resources in Malaysia at a very low cost compared to electricity costs.
The works in this group (Table S1) show that the energy dimension in SVs integrates solutions from artificial intelligence [19,24] in a context defined by energy sustainability [22], and the optimization of energy consumption, for the creation of so-called intelligent ecological communities.
Cluster 2 (green): "Access to energy infrastructure in the SV" is the oldest cluster in the network, given the most cited works.
Seven papers in this group (Table S2) are empirical in the field of energy management and the optimization of supply and demand in rural areas, aimed at evaluating the effects of technology on rural consumers in ecological, equitable, and social terms. It is estimated that hybrid microgrids will play an important role in expanding access to electricity in rural areas [29]. Another paper examines intelligent energy management in renewable systems that require artificial intelligence to implement procedures to reduce energy costs [30]. Another paper considers that the SV solution is an intelligent energy management system with a role in regulating supply and demand with low distribution costs.
Other research considers that the reduction of urban-rural gaps can be achieved with the help of remote community electrification projects [31]. Energy distributed from off-grid renewable sources can provide energy to remote communities using smart grids. An energy management system was modeled for direct current microgrids in rural villages and was evaluated by computer demonstration simulations.
Another paper describes a multi-objective optimization solution in which the hierarchical digital control of the microgrid is integrated into the micro-cogeneration powered by solar energy [32]. The control solution includes an integrated algorithm for economic and environmental optimization, with competitive costs, and customized according to the needs of small, isolated settlements in villages outside of the network. This cost-conscious optimization algorithm was tested in a rural microgrid by using parametric computer simulation models of a hybrid residential solar cogeneration system.
Representative works from this group (Table S2) show that access to different energy sources in SVs [24,26] integrates solutions in the area of artificial intelligence defined by hybrid electric microgrids, and at the same time [27,28], networks (for several villages) which optimize the distribution of electricity according to the needs of communities very far from the National Network [29].
Cluster 3 (blue): "The behavior of renewable energy consumers" is the youngest cluster on the map (Table S3 and Figure 7), with seven papers in this group. At the same time, it is the third-largest in the network: it has grown rapidly since 2019.
Among the most cited articles in the group, a conceptual paper considers the SV as an economical and optimized design for electricity generation using the hybrid biomass energy source in agriculture. Data collected from consumers showed the need for crop irrigation and use in residential areas. Empirical work justifies biomass performance and shows that the system is technically and economically viable, based on current net costs and energy costs [33]. Another echo of the researchers shows that solar systems for homes and photovoltaic solar power systems for villages can play an important role in the supply of electricity in the peripheral areas of the network [34].
Another research team encourages home consumers (90) to connect to the micro-hydro mini-grid of a GridShares system as a SV solution to prevent supply interruptions during the high consumption periods caused by meal preparation. Following the installation of the GridShares solution, outages dropped by over 92% [10].
Another research [35] analyzes the behavior of locals without electricity and describes how a smart mini-network could serve the purpose of helping the development of the village in terms of the implementation of new renewable energy technologies.
Representative works from this group (Table S3) show the needs and interests of energy consumers in SVs [10,32], and integrates a broad education program in the use of various intelligent solutions [30,31] to optimize energy consumption from different sources.
Cluster 4 (yellow): "Access to digital infrastructure", similar to group 3, this cluster is very young in the field, slightly smaller in size than cluster 3. The map (Figure 7) shows the growing interest in the field application of the cluster. An empirical paper in Poland [5,36] shows that SVs can be a means of achieving sustainability and resilience in rural areas. The study concludes that the concept of the SV can be useful in facilitating the sustainable development of rural areas by strengthening the mobility between rural and urban areas nearby.
Another group of researchers [10,36], with the highest number of citations in this group, considers that the use of the internet in the SV is vital in combating rural decline. They associate poor internet access with rural decline in Poland. Thus, the chance for rural revitalization could lie in the continuous spread of communication and information technologies in the affected areas.
Other researchers associate SVs [17] with the quality of the IT infrastructure and the ability to use it. In Scotland, for example, policy supports bottom-up communities, building on the capacity of communities to self-organize and deliver a range of developments that support well-being and resilience, and the research explores some of the challenges that arise from this.
In the Czech Republic [37] the promotion of digital technologies for remote work in rural areas and the use of ICT for participation and governance are discussed. It is suggested that more attention should be paid to increasing the digital literacy of the rural population rather than access to digital infrastructure.
Cluster 4 accumulated studies (Table S4) which show the needs and interests of energy consumers in SVs [13,33] and emphasize the integration of extensive education programs along with the use of various [36,38] smart solutions to optimize energy consumption from different sources [34,35].
Cluster 5 (purple): "Governance and planning in the SV" is the fifth largest group in the network. This cluster is also the second most cited cluster (after the green cluster) in the network.
The cluster is a new one, forming after 2015, in which more than half of the most cited articles appeared after 2019. In the purple cluster, the empirical works propose programs and tools of competitiveness, with the potential to attract areas considered marginal and at risk of demographic collapse.
A research paper with a significant number of citations discussed SVs through the application of technology and IoT [39], with the efforts of local governance standardization to improve the overall quality of life of their inhabitants.
Other research from China [40], with the highest number of citations in this group (38), considers that the relationship between the three key factors (state, market, and society) is pursued by issues such as the lack of transparent planning processes leading to inefficient collective decision-making. Smart local government in SVs is responsible for social sustainability, by involving marginalized migrants and other marginalized social groups, and establishing a fair relationship between the three key factors in the regeneration process. In their view, the SV is a relationship between smart governance and social sustainability for migrant communities.
Other research [41] considers that a smart tourist destination needs an innovative solution at the level of sustainable local governance based on 3 pillars: socio-cultural, environmental, and economic to spread the cultural heritage of these tourist destinations to their visitors. This is one of the most requested approaches by specialists: an innovative progressive web application co-created for visitors.
Cluster 5, accumulated studies (Table S5) which summarize the importance of digital infrastructure [39,41], because the tools and smart solutions [42,43] applied by local government have the mission to transform rural areas into smart destinations [44] and to disseminate cultural heritage with all hyper-connected users.
Cluster 6 (turquoise): "Access to renewable energy for SVs" is the sixth and smallest cluster in the network. The overlay map shows the novelty of the cluster and its appearance after 2018.
A study [45] with the highest number of citations in this group (39) presents a perspective for SVs as a technical-economic solution for biomass gasification in mini-grids outside the community grid in rural Uttar Pradesh, India. Another research [46] with 13 citations proposes a hybrid system for SVs which combines fossil and renewable resources to obtain energy in the village. The research proposes a diesel generator and a concentrated solar energy system to meet the daily and seasonal energy demands of the village. Another study [47] discusses households that prefer relatively larger generation capacities for multiple purposes, while micro-enterprises prefer smaller ones, mainly for night lighting. One perspective for SVs would be a way to promote solar systems for housing, by differentiating between marketing approaches for households and micro-enterprises [48].
The above analysis is based on clusters built on the most cited papers. We argue that the potential for SVs allow for a new policy, entrepreneurship, and environmental guidelines in a unified approach.
The results, provided by the construction of these clusters, are promising and could be continued [49]. It has been shown that ensuring universal access to energy will be achieved with the achievement of sustainable development objectives at the level of a community. It confirms the usefulness of the smart village concept as a way to finance innovations in the area of affordable solutions from different energy sources for all rural areas [36].

Limitations and Perspectives and of the Study
The purpose of the present research was to reach deeper levels of information to better understand the emergence of SVs, as well as the experiences, attitudes and behaviors of some communities [39] which have adopted the concept of the SV. The chosen research technique-bibliometrics-had the advantage in that it dealt with a complex subject, the results of the selected research were not influenced by others, and the respect of the received information was taken in to account.
A limitation of the research was a qualitative one; the involvement and contribution of the team contributed to the analysis, synthesis of information, and the presentation of research results in the field of the SVs [50].
Knowledge of the literature in the chosen field of research is an essential starting point from which advanced results can be obtained, with important subsequent contributions [20]. Our study showed that the bibliometric method provided aggregate syntheses of the literature, which allows future researchers to structure their work.
Considering the non-probability sampling, a certain number of research articles were requested, the main limitation of the research consisted in the impossibility of generalizing the conclusions of the study at the level of all communities [33] that can adopt the whole SV concept.
Another limitation of this research is that due to the different experiences of the communities in the implementation of certain operational programs, the comparison between the different communities was not based on balanced, structured information.
In this context, considering the complexity of SVs, the interpretation of the results of this qualitative research was carried out in correlation with the results obtained by the bibliometric method.
In the present research, the bibliometric study of SVs used a co-occurrence analysis of keywords and a bibliographic linking of documents followed by a systematic review of the literature. The bibliographic linking of the documents offered the opportunity to identify the intellectual offerings and the diversity of the field, using specific thematic groups (clusters), the evolution within the analyzed period, and the relationships of the most cited works from each cluster.
We identified six clusters; the first with the largest size and most rapid growth refered to the energy size in the SV (cluster 1, red). Most of the works in this cluster were new (after 2017) and promoted artificial intelligence in agriculture and in reducing the energy consumption of rural areas.
The red cluster contributed to the development of different types of renewable energy sources in the SV which, together with the green cluster, have developed rapidly ( Figure 7) and can contribute to the access of the population to them. The two clusters can represent the implementation of the European policy on SW, which can be an engine for environmental change.
The special number of articles in the red, blue, and yellow clusters, reflect the manifestation of academic interest, and show the greatest prospects for results and advanced research in the coming period. The behavior of renewable energy consumers in SVs, and access to such infrastructure, will include the SV as an engine for social transformation, which refers to partnership, cooperation and environmental responsibility, as well as a sustainable living environment. All of this will produce a certain capacity for the SV to solve the problems of the rural space through the energy autonomy of the local community, and by promoting the implementation of new renewable energy technologies.
The turquoise cluster aimed at a perspective for ways to promote solar systems for housing in SVs, by differentiating between marketing approaches for households and microenterprises. This cluster supports the sustainability of SVs, including organic farming and community ethics.
The turquoise and green clusters are interconnected, by focusing on the contribution of SVs to access and the development of energy infrastructure in the new smart communities. In this cluster, we can conclude that new policies, reforms, and institutions will be oriented towards SVs, by fulfilling the Sustainable Development Goals (SDGs).
Historically, SV research has moved from the green and purple clusters, which offer a perspective on the management of SVs, an alternative energy system based on direct social relationships, and contributes to a sustainable and ecological community, both economically and socially. The purple cluster also considers the SV as a green community with an emphasis on its relationship to digitalization and the IoT. In the purple cluster, the factors which support the development of SVs also refer to governance and rural planning, along with political, social, and ethical factors.
The research contributes to the development of the SV concept by cumulatively increasing the planning and promotion of green energy, digitalization and the IoT.
The research includes limitations related to the method of analysis presented at the beginning. The exclusion of books, conference papers, and other research topics could be presented. The fact that we chose only the Scopus database in our searches could exclude topics analyzed in other databases. The fact that we chose the VOSviewer software, and chose to exclude works in other languages other than English could also change the construction of the clusters that we analyzed.
This research opens up new research directions and provides new links into the depth of the SV using bibliometric analysis. However, there are some limitations encountered when carrying out a bibliometric analysis using the VOSviewer program. It allows the processing of data exported from the major article indexing platforms (Scopus and Web of Science), but does not allow the merging of two or more files for import. This is one reason why we limited our research to articles found just in Scopus and did not consider other scientific articles, books or expert reviews.

Conclusions
Our research has shown that the research topic [11] is still extremely limited (only 368 research papers published by March 2021 met our selection criteria), but it shows an increase in the interest shown by researchers in the following period ( Figure 3). The annual number of SV publications has increased almost fifteenfold in the last decade.
Our analysis shows that the SV is a multidisciplinary field because it attracts the attention of researchers in various disciplines, including medicine, marketing, and environmental studies (to name a few). Based on the SV phenomenon, issues such as digitalization, IoT, household behavior, SMEs, rural and environmental development, and significant current and future phenomena for the study of transparent and multidisciplinary SVs can be addressed.

Supplementary Materials:
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su141710723/s1, Tables S1-S6. The tables synthetically represent the selection of bibliometric references based on which the cluster analysis was carried out. Funding: This research did not receive any specific grants from the public, commercial, or non-profit funding agencies.