1. Introduction
With the rapid development of digital technologies such as big data, the internet of things, and artificial intelligence, human society has entered the digital era. All kinds of digital scenes are filled with the production and lives of modern people. Digital transformation has become a basic trend in the development of human society. As an important unit of the modernization of national governance systems and governance capacity, digital transformation is an inevitable choice by which to realize the modernization and high-quality development of grassroots governance. Strengthening grassroots digital governance is conducive to improving the level of refinement, informationization, and modernization of grassroots governance, as well as improving the effectiveness of grassroots governance. In the Chinese government system, grassroots (JI CENG) refer to urban communities (social units with streets as geographical boundaries) and rural village communities (social units with China’s rural collective economy as the main body). Therefore, the research object of this paper is “China’s grassroots digital governance”. The research questions include two aspects: What is the current situation of China’s grassroots digital governance research and practice? How can the theoretical research and governance practice of China’s grassroots digital governance be promoted?
In recent years, the Chinese government has attached great importance to building a digital China and has actively implemented a national big data strategy, which has created strong momentum for grassroots digital governance. Community-level governments have undertaken a series of useful explorations, and accumulated some governance experience. Scholars have conducted systematic studies on these useful explorations. Wenbin Wang et al. (2022) introduced an integrated governance model formed by the reorganization of the grassroots governance structure, and the overall planning of grassroots governance resources in S Town, Hangzhou [
1]. Bo Peng et al. (2022) introduced typical cases of “whistling and reporting” in Beijing and “five powers decentralization” in Shanghai, which empowered and improved the overall governance capacity of the grassroots government [
2].Tao Li et al. (2022) summarized the typical experience of grassroots health digital governance in T city [
3]. Xiaoxing Huang et al. (2022) discussed the relationship between grassroots governance structure and government digital governance by taking the grid management and its special actions in T district of Z City as an example [
4]. Bo Peng et al. (2022) took the “one-code universal” digital governance of A town as an innovation case to study the governance mechanism empowered by grassroots governance technology [
5]. Yibo Xu et al. (2022) took the reading promotion work of Ningbo library as an example, and discussed the mission, challenges, and countermeasures of public libraries in the promotion of “national reading” [
6]. Jinghua Tang (2022) considered the operation logic and promotion strategy of digital rural governance, based on the investigation of the “LongYoutong” platform [
7]. Shaohua Hong et al. (2022) took “Jinjia” as an example to explore the experience of digital platforms participating in the construction of smart communities [
8]. Zhangliang Xin et al. (2021) took Beijing’s “12345” government hotline as an example to study agile governance at the grassroots level in megacities driven by government hotline reform [
9]. Haisheng Chen (2021) discussed the path of promoting the modernization of credit governance with wisdom based on the experience of Zhejiang Province in the digitalization of credit construction [
10].
In addition to the views of the above scholars, according to the basic digitization research literature collected by CNKI, the literature with the most citations includes the following papers: “Internet + Grassroots Governance”: The digital realization path of grassroots overall governance [
11]; Research on the digital transformation of grassroots Social Governance—Based on the analysis of practical experience in M City in the east of China [
12]; Research on the construction of grassroots community digital emergency management System [
13]; “Internet + grassroots Governance”: Promoting holistic governance with digital means [
14]; Exploring the necessity and path of digitization of grassroots Party building [
15]; Governance dilemma, digital empowerment and institutional Supply—Realistic logic of the digital transformation of grassroots governance [
16]; The tension between clarity and ambiguity and its Adjustment—Centered on the digital transformation of urban grassroots governance [
17]; Digital governance of urban grassroots society [
18]; Practical discussion on the digitization of paper archives in grassroots archives room [
19]; Problems faced by digitization of grassroots archives management and their countermeasures [
20]; Discussion on the digitization approach of grassroots library [
21]; Urgency, challenge and breakthrough point of digitization transformation of grassroots governance [
22]; Reflection and Innovation on the digital transformation of grassroots Social Governance [
23]; Exploration on the digital reform of grassroots finance—A case study of A City in Zhejiang Province [
24]; A survey on the use of digital telemedicine equipment in grassroots medical institutions in Guizhou Province [
25]; A study on the information disclosure mode of grassroots government in digital Transformation from the perspective of rural revitalization [
26]; Influence of Digital Transformation of Grassroots Social Governance on digital vulnerable Groups and countermeasures [
27]; Using digitalization to cover fuzzy affairs: Technology enabling mechanism of grassroots governance [
28]; Solving collaborative problems of grassroots governance: the path of the integration of digital platforms [
2]; Investigation and analysis of the digital construction of grassroots hospitals in Guizhou Province [
29]; Solving collaborative problems of grassroots governance: The layout and path of digital platform [
30]; The current situation and optimization strategy of the digital transformation of grassroots social governance [
31]; A study on the policy guidance of the digital transformation of grassroots government services—A case study of the Longhua District Administration Service Center of Haikou City [
32]; and The Overall transformation of the digital transformation of grassroots governance: Ecology, Logic and Strategy [
1]. In addition to domestic scholars, foreign scholars also pay attention to basic digitization issues, including Lee H et al. (2022) [
33], Cingolani L et al. (2022) [
34], Burinskien Yan A et al. (2022) [
35], Popescu M et al. (2022) [
36], and Clark S et al. (2022) [
37].
Although there is abundant literature regarding theoretical research into grassroots digitization, there is still a large gap compared with the theoretical demands of grassroots digitization practice. Therefore, with the deepening of digitization at the basic level and some practical dilemmas encountered, the theoretical research still needs to be continuously optimized and perfected. In summary, there is abundant research with respect to theoretical analysis framework interpretation, governance practice evaluation, and optimization of grassroots digitization at present, but there is still a lack of comprehensive sorting and systematic discussion on macro-grassroots digital change research, which needs to be studied and strengthened. Therefore, in this paper, we analyze the development and paths of grassroots digital governance in China; this has important theoretical and practical significance, which is another purpose of this paper.
Compared with traditional paper carriers of information, digital information carriers based on high capacity can better ensure that information maintains its characteristics, and can reduce loss in terms of time and space transformation and changes; that is to say, “digital” carriers have more natural sustainability. In the digital era, digital technology is the link between reality and the future by which to maintain social and economic development, and it has become the basic technology and platform by which to maintain sustainable social, and economic development. In the current situation of and increasing global volatility, digital empowerment has become the basic starting point from which to promote sustainable social and economic development. Digitally empowering the economy is conducive to promoting the sustainable development of digital industries and economies, and digitally empowering culture is conducive to promoting the construction and development of digital communities and societies. With respect to digital empowerment, grassroots digital empowerment has become the most critical and urgent link to strengthen. Based on this, in this paper we review the research on grassroots digital governance in China in recent years, from the theoretical perspective of digital empowerment and digital sustainability, and consider and discuss the paths of grassroots governance in China. Such research, not only from the perspective of theoretical construction, but also from the perspective of practical guidance, has significance with respect to research on digital empowerment and digital sustainability both at home and abroad.
We use CiteSpace and NVivo 12 Plus software for literature analysis to determine the current situation of China’s grassroots digital governance from the aspect of theoretical innovation, then consult the relevant literature and carry out practical analysis based on China’s grassroots political situation, and finally draw conclusions and propose optimization countermeasures. The structure of this paper is roughly divided into three parts, namely, literature metrology visualization analysis, practical analysis, and conclusions and countermeasures.
3. Visual Analysis
3.1. Post-Analysis
Publication analysis is the process of decomposing and analyzing the quantity, trend, and composition of the published literature in a research field from different dimensions. By analyzing the number of published papers in a research field, this can help researchers determine the overall number of published papers in the research field and the annual number of published papers, and predict the trends of published papers. Based on the previous data retrieval, a trend chart of 196 papers was drawn according to the time nodes (see
Figure 2). As can be seen from
Figure 1, in terms of the earliest publication time and overall number of publications, the high-level grassroots digital literature published in China began in 2000. From the trend of overall documents, the number of digital documents at the grassroots level in China is on the rise. From the perspective of the number of articles published annually, the average annual number of articles published in China is 8.52, which is relatively few compared with the reality of grassroots digital governance. Therefore, on the whole, Chinese basic digital research has been paid increasing attention; the research prospects are broad, and the research content and subjects need to be further enriched.
3.2. Analysis of Research Subjects and Cooperation Networks
The current progress with respect to grassroots digitalization research cannot be achieved without the unremitting efforts of relevant researchers and teams. Analysis of the structural characteristics of the authors and their cooperative networks can reflect the core authors and their cooperative relationships in this field. “Core authors” refers to scholars with higher academic levels, and more scientific research achievements in a certain field. The analysis of core authors is helpful to understand the research status, and progress in this field. According to Price’s law, the number of core authors can be calculated as follows:
MP represents the minimum number of papers published by the core authors, and
NPmax represents the cumulative number of papers published by the authors with the most papers in the research time interval. If the number of stable core authors accounts for 50% of the total number of papers, it is considered that the field has formed a core author group. The retrieval information of 196 papers was imported into CiteSpace for author visualization analysis, and it was found that Hongzhu Zhang published the largest number of papers—22 papers in total. According to the calculation formula, the MP value was 3.51; that is, authors of four or more papers can be regarded as core authors in the fields of domestic grassroots digital research. As shown in
Table 1, there are two core authors of grassroots digital research, Hongzhu Zhang and Bingyou Fan. In general, in terms of the number of publications, the field of grassroots digitalization is a research subject with Hongzhu Zhang and Bingyou Fan as the core, and the number of core authors’ publications is higher than that of other authors, with Hongzhu Zhang having a total of 22 publications, followed by Bingyou Fan with 20 articles. In addition, the two core authors began to study grassroots digitalization in 2000, indicating that the two core authors have paid continuous attention to grassroots digitalization for more than 20 years, and made a series of achievements. In terms of health research, Xianglan Ru, Keyong Ding, Qianju Wang, and Xin Zhang all began their research in 2013; Hexia Feng, Min Ma, Zhiming Han, Qingchen Yao, Guisheng Chen, Shaofen Ding, Xian Feng, and Xiaoxing Huang began research in 2020. After that time, authors in recent years began to pay close attention to the basic digital output of these authors, and obtained high-quality results. According to the statistics of the literature authors, the core authors published a total of 42 articles, accounting for about 15.12% of the total number of papers on grassroots digital research, which was lower than the standard of the core authors; therefore, this indicates that the core authors in the field of grassroots digitalization in China have not yet formed.
We used CiteSpace to create an author cooperation network map (
Figure 3), in which the tree-ring nodes represent the author, the node size represents the centrality, and the connection between nodes represents the existence of a cooperative relationship. Through analysis (
Figure 3), the number of network nodes N = 218, the number of connections E = 143, and the network density D = 0.006 are obtained. This indicates that the distribution is relatively scattered. In general, there are some cooperative relationships among authors, but the concentration is still low, and the cooperative relationships are relatively loose. To be specific, the authors in the field of grassroots digital research show the characteristics of “large dispersion” and “small aggregation”. Most of the authors are undertaking independent research, only a few of the authors have established cooperative relationships, and the cooperation networks have not yet been formed. Researchers participating in a study can not only give play to the common wisdom of the participants, but also ensure the research results are recognized by the participants. From this perspective, the more often authors of research in a particular field encounter each other, the more often a common consensus can be reached, and more systematic theories and methods can be formed in this field. Therefore, from this perspective, the research on grassroots digital governance in China is still in the initial stage of theoretical research, and there are not many theories and methods by which to reach a consensus.
In order to explore the cooperation of research institutions in the field of grassroots digital research, co-occurrence analysis was carried out on the signature institutions of the sample literature, and a cooperation network map of institutions was obtained (
Figure 4). The size of annual rings is proportional to the number of publications, and the connections between nodes and the line thickness represent the cooperation relationships between institutions and the frequency of cooperation, respectively. As shown in
Figure 4, the number of nodes in the cooperation network of domestic research institutions is N = 173, the number of connections is E = 69, and the network density is D = 0.0046. In other words, a total of 173 institutions and 69 connections were selected from the co-occurrence knowledge graph in the field of grassroots digital research in China. From the perspective of the number of institutional publications (as shown in
Table 2), there are obvious errors in the number of publications. The most publications are by the School of Culture and Tourism of Quzhou Vocational and Technical College, and the School of Physical Education of Soochow University, with 21 publications each. These are followed by the School of Government of Nanjing University, and Peking University, with 3 publications each. As can be seen from
Figure 3, the number of links is less than the number of nodes, and the density is relatively low; this indicates that there is a lack of close cooperation between institutions that have made important contributions to this field in China, and the degree of communication is relatively low. In future, all institutions should strengthen cooperation, exchange theoretical frontiers, and promote research and development.
3.3. Analysis of Research Hotspots
3.3.1. Keywords Co-Occurrence Analysis
Keywords are the words defined by the author to summarize the topic of the article; these represent the author’s highly summarized and refined academic thoughts, research themes, and research contents of a specific study. Therefore, keywords can also be used as a means by which to analyze the research topic. At the same time, by examining the frequency of keywords in a field, we can understand the research hotspots in this field, and judge the updating speed of the research content and the vigor of the research.
In the analysis of a knowledge graph, the research topics and hotspots of a certain field can be obtained through the analysis of keywords. In the keyword co-occurrence network picture, constructed using CiteSpace software, each node represents a keyword, and the size of the node represents the frequency of keywords. We ran CiteSpace, set the node type as “keyword”, and set the time range from 2000 to 2022 in China. We imported the research data, obtained the keyword co-occurrence map (as shown in
Figure 5), and the keyword frequency and centrality schematic table (as shown in
Table 3) through the “keyword” function of CiteSpace. It can be seen from
Figure 5 that the map formed by CiteSpace has a total of N = 253 nodes, E = 297 lines, and the network density = 0.0093. As shown in
Table 3, the top keywords were digitalization (24), sportsman (19), digital governance (13), grassroots governance (11), rural governance (11), digital countryside (11), digital government (10), digital technology (10), rural revitalization (9), and grassroots government (6). This shows that research on grassroots digitalization in China mainly focuses on digitalization, digital governance, grassroots governance, rural governance, digital countryside, digital government, digital technology, rural revitalization, and grassroots government.
3.3.2. Keyword Cluster Analysis
According to the network structure and the clarity of clustering, CiteSpace measures the effect of mapping via two indexes: Q value and S value. The Q value (Modularity) denotes the module value, and its interval is [0,1]. Q > 0.3 means that the divided community structure is significant. The S-value is the weighted mean silhouette, which means the average contour value. S > 0.5 means the clustering is reasonable, and S > 0.7 means the clustering is efficient and convincing. As shown in
Figure 6, the Q value of the keyword clustering map is 0.8963, so its structure is significant; the S value is 0.974, which is not only greater than the reasonable average contour value of 0.5, but also greater than 0.7, indicating that the clustering analysis in this paper is efficient and convincing. As shown in
Figure 5, the top 5 clusters are “#0 digitization”, “#1 grassroots governance”, “#2 digital government”, “#3 digital technology”, and “#4 digital countryside”, “#5 digital governance”.
A keyword cluster summary table was drawn to further explore the number of keywords contained in each cluster, the closeness of the cluster itself, the average year of keyword distribution, and the main keywords contained in the cluster. As can be seen from
Table 4, the mean silhouette (S value) of each cluster is greater than 0.8, indicating that each cluster is efficient, and convincing. The highest number of nodes is in cluster 0 (digital), which has 25 nodes. Cluster 1 (grassroots governance), cluster 2 (digital government), and cluster 3 (digital technology) all have 17 nodes. Cluster 4 (digital countryside) has 16 nodes. Cluster 5 (digital governance) has 12 nodes. Each cluster lists the keywords extracted according to the weighting algorithm. The top five keywords in each cluster are ranked from left to right in order of their importance.
3.4. Research Frontier Analysis
3.4.1. Statistical Analysis of Emergent Words
“Emergent keywords” refers to keywords with a sudden increase in frequency in a certain period, which reflects the importance of a certain keyword in that period. Chen Chaomei defined a “research frontier” as a set of emergent dynamic concepts and potential research questions, which can accurately reflect the frontier fields of related disciplines. Emergent keywords are used to explore the emergent dynamic concepts and potential research issues in grassroots digital development research, explore the reasons behind them, reflect active or cutting-edge research nodes, and assist in predicting future research hotspots and trends. The basic principle of emergent word detection is that the word frequency of a certain keyword variable surges in a short period of time, and suddenly becomes a research hotspot, which can be understood as the “Baidu index” of academic circles. Since the emergent state of emergent words usually has time continuity, with a continuation period of 2 years or more, it can be used to assist in predicting future research hotspots and trends. At the same time, emergent word detection can be used to review which keywords have become hotspots in which time period.
In
Figure 7, “Begin” represents the first year of the keyword within the research time category, “End” represents the final year of the keyword, “Strength” represents the breakout intensity, blue blocks represent the unit year time slice, and red blocks represent the breakout period.
As can be seen from the above figure, the keywords with high outburst intensity are “sportsman (6.66)”, “rural revitalization (2.86)”, “targeted poverty alleviation (2.53)”, “digital technology (2.47)”, “rural governance (2.34)”, “archives department (2.32)”, etc. This indicates that these keywords are frontier topics to which researchers pay more attention in their corresponding time periods. From the perspective of an increase over a particular time span, longer-duration keywords are “sportsman (17 years)”, “information resources (12 years)”, “archives department (7 years)”, “archives (7 years)”, “digital governance (3 years)”, and “grassroots governance (3 years)”. This shows that these keywords are a focus of attention for scholars over a long period of time, and in some cases are a hot topic. According to the time ranking, frontier keywords are constantly changing with the passage of time, and the overall evolution shows stages. Therefore, we divided the research frontiers in the field of grassroots digitalization according to the time stage, and selected keywords with high intensity of emergence in those periods for analysis. The period from 2000 to 2010 represented the early stage, and the frontier keywords with high intensity of emergence were “sportsman (6.66 years)”, “information resources (1.06)”, “archives department (2.32)”, “grassroots files (1.32)”, “archives center (1.13)”, and “paper-archives (1.24)”. In the middle period 2011–2020, the frontier keywords with high emergent intensity were “targeted poverty alleviation (2.53)”, “archives management (1.07)”, “digital governance (1.88)”, and “mechanics (1.21)”. In the period 2021–2022, the frontier keywords with high emergent intensity were “rural revitalization (2.86)”, “digital technology (2.47)”, “community governance (1.47)”, “government hotline (0.99)”, “government service (0.99)”, and “public culture (0.99)”. Over the next few years, rural revitalization, digital technology, rural governance, digital governance, digital government, grassroots governance, community governance, grassroots government, government hotlines, government services, and public culture will be the hot topics of grassroots digital research in China.
3.4.2. Time Zone Analysis
Research hotspots are dynamic, and vary in each time period. On the basis of the keyword co-occurrence map, the time slice was set to 1 year, and other settings remained unchanged. The original map was obtained through the CiteSpace software, and the map was further refined by adjusting the parameters. A time-zone map of grassroots digital research hotspots from 2000 to 2022 was obtained, as shown in
Figure 8.
As shown in the above diagram, nodes represent keywords. The keywords in one year indicate collecting data for the first time in that year, due to the time slice of one year, so that only they can be determined as the keywords in that year. After that year, keywords appearing again will be in the position of the first occurrence in the frequency accumulation, appearing several times. The circle will become larger accordingly, so the large circle on the “digital” node does not mean a high frequency of occurrence in the current year, but a high total frequency of this keyword in the collected data. The line represents the connection between the keywords. If the keywords appear in one paper at the same time, a line will appear between the two keywords, and the two years will also be related. If the two keywords appear in multiple papers at the same time, the line will be bold.
Overall, a basic digital domain has formed at a certain scale, and the focus of basic digital research—from early in the construction of information resources and digital archive management at the grassroots level—is the main content of e-government phase-shifting, characterized by the integrity of digital governance at the grassroots level of the digital government stage. Work in relation to the sharing of electronic governance is the main characteristic of the phase transformation. At present, the focus is moving towards a new stage of “digital-wise governance” characterized by digital empowerment, and technological empowerment. Hot topics in the study of basic digital migration will deepen over time, and overall governance, collaborative governance, dissecting, the e-government hotline, the urban community, and community governance will gradually become hot research topics. The overall research direction will develop a strong osmosis aspect of theory with practice, and, along with China, researchers will pay increasing attention to grassroots governance and the development of a digital economy. The current research hotspots are likely to continue for a period of time.
3.4.3. Timeline Analysis
The CiteSpace software was used to draw the timeline map of keywords in the field of grassroots digital, and the duration and evolution trends of research hotspots were obtained, as shown in
Figure 9. The keyword evolution map is arranged chronologically from left to right, and the size of each circular node in the graph is proportional to the occurrence frequency of the corresponding keywords. CiteSpace was used to analyze the evolution of hotspot research topics in the selected literature. The time parameter was set as 2000–2022, with other parameters as follows: year per slice = 1, g-index (k = 25), node type = keyword. The results are shown in
Figure 9. A total of 253 nodes and 297 lines were generated in the obtained map, and Q = 0.8963, indicating that the structure of the division was significant.
As shown in
Figure 9, the prominence of keywords in this timeline goes through two stages; namely, a large-span stage with large fluctuations, and a large-span stage with fewer changes and then more changes. This indicates that the development of grassroots digitalization research has experienced three stages: steady rise, relatively steady development, and rapid development. Therefore, researchers have experienced certain fluctuations in the research process of grassroots digitalization. In the figure, the keyword digitization node is the largest, which indicates that this word is a hot research topic in this field, and also shows the importance of digitization for the development of grassroots digitization research. The nature of this keyword also determines that it is studied by scholars as a central keyword. It is located at the front of the timeline, indicating that this field began to be explored based on this keyword, and then related research on grassroots digitalization research was associated with this keyword. This is because at the beginning of this century, with the development of network and information technology, digitalization and informatization have gradually had a transformative impact on the market and services. Some grassroots governance fields with strong information attributes, such as libraries and archives management departments, have become a common trend at home and abroad. Therefore, digitalization has become a hot topic in grassroots research. The right side of the map is the keyword cluster tag, and is divided into digital, grassroots governance, digital government, digital technology, digital countryside, digital governance, and other clusters in the evolution process.
3.5. Analysis of Highly Cited Literature
3.5.1. Research Topic Analysis
Papers in a certain research field are not isolated, but gradually form a citation space network that is interconnected, connecting the past and the future and cross-integrating disciplines through normative citation behavior among scholars. In view of this, according to the limited citation frequency method, we sorted 196 papers retrieved from the CNKI database using the same method, and selected papers with no fewer than 35 citations for high-citation analysis, as shown in
Table 5. By analyzing the research topics of highly cited literature in the research field, the main topics of the classical literature in the research field, and the main content categories of the knowledge base can be determined.
The full texts of 10 highly cited papers were imported into NVivo 12 Plus to obtain the topics, numbers of nodes, summaries of their reference points (see
Table 6), and nodes of the “grassroots digitization” research. As shown in
Table 6, “Governance (406)”, “Digital (380)”, “Information (281)”, “Resources (274)”, “Services (255)”, “Data (255)”, “Construction (222)”, “Government (221)”, “Technology (214)”, “Digitalization (203)”, “social (201)”, “culture (197)”, “organization (188)”, “enterprise (174)”, “grassroots (170)”, “rural (166)”, “development (149)”, “work (142)”, “management (140)”, and “platform (134)” are the themes of highly cited literature. This shows that the authoritative research on domestic grassroots digitization focuses on three aspects: government governance, digital governance, and grassroots governance. Among these, government governance and technological governance are the main topics on which scholars focus, which means that the research on domestic grassroots digitization has involved extensive research and discussion on the technical issues of realizing grassroots digitization. Research focusing on grassroots governance needs to be strengthened.
3.5.2. Emotional State Analysis of Research Literature
Through the analysis of highly cited literature and automatic code-recognition emotion analysis by NVivo software, a statistical table of coding points of the research literature compiled according to emotion was obtained. According to the statistics in
Table 7, there are 305 code nodes in total that are “very negative”. “More negative” has 257 coding nodes; “Relatively positive” has 718 coding nodes; and “Very forward” has 17 code nodes. As can be seen from
Table 7, the literature numbers corresponding to the maximum values of very negative and very positive values are C08 and C01, indicating that the academic community holds a strong negative emotional attitude towards data governance, and a strong positive emotional attitude towards platform-driven digital governance. It can be seen that the “neutral” attitude occupies an absolute advantage, and the “positive” and “mixed” attitudes also occupy a large area. Therefore, according to the results of
Table 7, the current attitude of Chinese scholars towards grassroots digital governance is still in a complex state. However, this tends to show that the existing relevant policies have achieved certain results, but still have a large space and prospects for development.
3.6. Analysis of Research Content
Content analysis, as a structured method for analyzing textual materials, transforms natural information in unstructured texts into structured information forms that can be used for quantitative analysis through a series of transformation paradigms. The multi-dimensional content analysis of reliable and authentic text materials is conducive to the multi-dimensional structured interpretation of text materials, and can be used to find the deep logic and laws hidden behind the text. In this paper, NVivo 12 Plus qualitative analysis software was used to analyze the content of the literature from the past three years (including 2020), and the original collected literature was further manually screened; a total of 118 valid papers were screened. Firstly, the PDF full texts of 118 papers were imported into Nvivo. Secondly, 118 articles were imported into the case project list as 118 cases. Thirdly, a folder named “grassroots digitalization” was created in the case node classification folder, and three attribute categories of “governance domain”, “dDi Wangs”, and “governance logic” were established under this folder. The text contents of the 118 papers were classified and sorted into three dimensions: governance domain, driving factors, and governance logic. The classification cases of the three dimensions were constructed in the case node classification, and the actual situation of each dimension was analyzed by constructing node matrix coding.
The composition and analysis of the coding in all dimensions are as follows (see
Figure 10).
First, literature under different governance domains. Through the coding analysis of the literature content, the direct or indirect expression of the literature in this aspect was summarized. The primary governance fields involved included community, village, society, health, archives, targeted poverty alleviation, digital formalism, technology empowerment, culture, library, Party building, etc. The above aspects were used as the attribute values of the case node classification analyzed by NVivo software.
Second, the literature under different dimensions of driving factors. Through the literature content analysis, it was found that problems, tasks, technologies, and policies are the main driving forms of grassroots digital governance. Therefore, they were listed as attribute values under this dimension.
Thirdly, the literature situation under different governance logic dimensions was studied. According to the retrieved literature, the governance logic of grassroots digital governance in China includes technology governance logic, theory governance logic, practice governance logic, innovation governance logic, and hybrid governance logic. Therefore, in this paper we provide a special discussion and analysis regarding the logic of governance by technology, governance by reason, governance by practice, and hybrid governance logic. Governance logic was applied as the attribute value in the case node classification.
In order to ensure the integrity of the case classification, “other” was added as the supplementary attribute value in the three dimensions.
By carefully reading the content and coding information of the literature, a three-dimensional analysis model was constructed from the three dimensions of governance domain, driving factors, and governance logic, and then a qualitative analysis of the research results was carried out.
3.6.1. Literature Research and Analysis under the Dimension of Governance Domain-Driving Factors
As shown in
Figure 11, in terms of the governance domain, cases involving basic digital fields of governance, according to matching the numbers of nodes from high to low, are as follows: countryside (30), else (29), society (8), community (11), sanitation (7), archives (6), targeted poverty alleviation (4), formalism of digitization (3), technology empowerment (3), culture (2), library (2), the Party building (2), journalism (1), burden alleviation (1), technology implementation (1), sports (1), education technology (1), accountant (1), policy release (1), government affairs center (1), finance (1), and credit (1). Countryside and community are the top two areas of governance, and the number of cases are 30 and 11, respectively. Countryside and community are the foundations of grassroots governance units. As important areas of grassroots governance, countryside and community are also the major issue areas of grassroots digital governance. From the perspective of the categories involved in the field of governance, China’s grassroots digital governance has involved science, education, culture, health, and other aspects, indicating that with the transformation and development of China’s economy and society, all walks of life are undergoing digital transformation, and expect to achieve high-quality development in terms of digital transformation. In terms of the intersection of governance areas and drivers, one driving factor of the attribute value is the maximum number of cases that are “problem driving”; this term explains that the basic digital governance in China is still in the adaptive control process. At this stage, there is a lack of mature management experience and theoretical guidance in the system, and the governance structure, systems, and operations remain to be perfected. Areas of governance and driving factors of overlapping cases are denoted by “else”. Cross-problem-driven cases have the highest numbers of case nodes, the overlapping indicating that, at present, many scholars are not studying a specific field of integrated digital governance, but are examining the macro-structure, systems, and mechanisms, which require in-depth analysis of basic digital abstract problems.
3.6.2. Literature Analysis under the Governance Domain–Governance Logic Dimension
As shown in
Figure 12, according to the number of matched case nodes, the basic digital governance logic is in the order of hybrid governance logic (70), practical governance logic (16), technological governance logic (15), rational governance logic (11), innovative governance logic (4), and else (1). Among these, hybrid governance logic has the highest number of matching case nodes. Technical instructions embedded in grassroots governance not only create technical problems, but also create the superposition of multiple attributes of complex activities such as social, cultural, and process activities in the field of technology. There is different governance in terms of the interaction of various elements, so we must examine basic digital-governance-related issues. It is not only necessary from a single-logic perspective to determine the method of governance, but on the basis of recognizing the high uncertainty and complexity of the risks to society, a variety of perspectives and methods should be used, so countermeasures and suggestions can be put forward with more depth and breadth. With respect to areas of governance and the control logic of overlapping cases, the “countryside” governance field case-node-matching number is much higher than for other areas of governance. One of the basic types of rural grassroots governance in China is digital fragmentation, creating digital islands and concentrated digital governance problems, such as digital formalism; these are points of difficulty with respect to China’s basic digital governance.
3.6.3. Driving Factors—Analysis of the Literature under the Governance Logic Dimension
As shown in
Figure 13, in terms of driving factors, in addition to problem-driven factors, technology-driven (29), policy-driven (13), and task-driven (8) factors are the top driving factors. We must follow the instructions of the Party’s governance body with respect to the whole digital transformation and digital development strategy under the guidance of China, to create superior tasks driven by a series of activities, and take measures to process these tasks. In terms of logical governance, in addition to mixed logic, application logic, and technical incurable logic, reason and logic matching the node numbers are higher than the logic and other matching case numbers of nodes. Along with China’s basic digital pilot management mode of constant exploration, these nodes have sprung up around many typical cases, and the typical experiences have been summarized. In the process of summarizing typical practical experience, some technical optimization explorations and theoretical interpretations have been carried out, but innovative governance needs to be further strengthened. In terms of the intersection of drivers and governance logic, problem-driven cross-hybrid governance logic matches 36 nodes; this involves the analysis of the maximum number of dimensions of the matching case, explaining basic digital governance involving many areas. The problems faced are complicated, and require using technology and a variety of logic tools. It will be helpful to put forward targeted policy recommendations.
5. Prospects
To sum up, the work and contributions of this paper mainly include four aspects: First, using CiteSpace and NVivo software, measurement and visualization research on the representative literature of grassroots digitization research in China was carried out, which has methodological guiding significance for similar research by other scholars. Second, we conducted normative and systematic research on the characteristics, theme, focus, time line, and emotional orientation of China’s grassroots digitization research, which has value for the theoretical cognition of China’s grassroots digitization research. Third, the conclusions of this paper are useful contributions to the theory and practice of China’s grassroots digitization, and are conducive to promoting the research and practice of China’s grassroots digitization in a deeper, richer, and more systematic way. Fourth, grassroots digitization research and practice is a global topic. The research paradigm and conclusions of this paper are a useful reference for foreign digitization research and practice.
At present, China’s grassroots digital governance is in the transition period of exploration. This article represents an initial analysis. Many issues have not been discussed in depth, especially the lack of necessary discussion on digital governance in China’s rural governance and rural revitalization, which is the main shortcoming of our research; in future, we also need to strengthen the breadth and depth of theoretical research on grassroots digital governance, promote domestic and international theoretical reference and cooperation, and realize the quality of China’s grassroots digital governance ecology.
Based on the above views, aiming at the current situation of grassroots digital governance in China, we propose the following optimization suggestions for how to improve the effectiveness of grassroots digital governance in China.
5.1. Strengthen the Integrated Governance of Grassroots Digital Systems
Digitalization at the grassroots level involves all aspects of governance and rapid changes in the digital era. It presents unprecedented opportunities and challenges with respect to governance methods, which require comprehensive consideration and systematic management. The problems encountered in grassroots digital governance should be considered systematically as a whole, and the real causes of obstacles among governance elements should also be considered, so as to enable appropriate governance. To avoid fragmentation in basic digital governance, redundant construction, and fragmentation problems, governments at all levels should supervise systems at the grassroots level, strive to build overall correlations, enable an organic digital governance structure, improve the existing basic digital management platforms of interaction, and establish and perfect systems for basic digital standards and norms [
53].
5.2. Improve the Ability to Solve Digital Governance Problems
Digital empowerment of grassroots governance will inevitably create a series of new problems and challenges. For grassroots governance subjects, the most direct challenge is the digital governance ability, which directly determines the governance effectiveness. Grassroots digital governance does not involve completing task indicators, innovating, or building impressive platforms and equipment, but instead should involve using digital technology to solve problems encountered in grassroots governance, especially where traditional governance has been unable to address the difficulties. On the one hand, education and training of primary governance subjects should be strengthened to improve their awareness and ability to find and solve digital governance problems at the primary level. On the other hand, attention should be paid to basic digital management experience in order to provide basic digital governance in more effective practice cases. We should also strengthen the management of digital fault-tolerant error-correction mechanisms and create a basic digital atmosphere, guided by pros and cons, that will work well in the adaptive control of grassroots governance subjects’ subjective initiative and creativity [
54].
5.3. Progressive Transformation of Grassroots Digital Governance Should Be Promoted by Incremental Governance Logic
Transformation means the resetting of existing rules, and the destruction of many vested interests. There is still a long way to go to solve the long-standing contradictions in China’s grassroots governance structure. The position of grassroots governance subjects in the whole governance system determines their limited transformation activity. How to establish their own governance in heavy grassroots affairs is a common problem faced by grassroots governance subjects. Incremental governance logic is a more realistic choice by which to promote the gradual transformation of grassroots digital governance. On the one hand, the main body of grassroots governance should take the initiative to find the incremental issues that are changing rapidly in grassroots digital governance, and take the initiative to participate in the governance of the remaining affairs, so as to create a new space for grassroots digital governance. Grassroots governance bodies, on the other hand, should actively address the problem of governance responsibility. There is a need to interact with the existing market structure subject tasks, and promote good management practice. Good management will play its own role in incremental management coordination, balancing stock, and incremental problems involved in the relationship between stakeholders [
55].