Research on the Construction and Measurement of Digital Governance Level System of County Rural Areas in China—Empirical Analysis Based on Entropy Weight TOPSIS Model

Abstract

Rural digital governance is an inevitable requirement to improve the efficiency of rural governance, and is also an important means to realize the modernization of rural governance. In the context of the digital rural development strategy, the index measurement system of the rural digital governance level is built around the five key governance areas of “digital economy, digital ecology, digital culture, digital people’s livelihood, and digital government affairs”. The entropy weight TOPSIS model is used to measure and evaluate the level of rural digital governance in 31 provinces in China in 2021. The results show that there is a large gap in the level of digital governance in China’s counties and villages, and the level of each region presents a decreasing spatial distribution from “east-middle-west”. In terms of digital economy, the eastern region has a high score and good development, while the central and western regions have poor development. In terms of digital ecology, only the eastern region is higher than the national average; In terms of digital culture, only the central region is higher than the national average; In terms of digital livelihood and digital government, the central and eastern regions are slightly higher than the national average; The top three provinces in overall scores are Zhejiang, Guangdong, and Jiangsu.

1. Introduction

With the advent of the information age and the digital age, the application of digital technologies such as cloud computing, big data, and the Internet of Things has made our lives more convenient, subverted traditional social life, and constantly promoted the digital transformation of society, which has also brought a huge impact on the economic life of rural areas [1]. More and more countries are focusing on the impact of digital technologies on rural development. India took the lead in launching the “Digital India Plan” in 2015, integrating digital infrastructure construction, digital government affairs, and telemedicine services into the process of building digital villages [2]. In 2016, Japan proposed the “Agricultural technology project of intelligent machinery + intelligent AI” to apply digital technology to disaster prevention and reduction [3]. In 2017, the European Commission launched the EU Smart Countryside Initiative, which aims to use digital technologies to narrow the urban-rural gap and solve the problems of rural life, implementing the digital countryside [4]. During the COVID-19 epidemic, Brazil promoted the digital development of mobile electronic payments agriculture and rural areas in Brazil through initiatives such as “WI-FI Brazil” and national connectivity, and promoted the digitalization of rural areas. In 2019, China put forward the “Digital Countryside Strategy” to make a series of deployments for the modernization of rural governance, and 22 provinces including Zhejiang, Guangdong, and Jiangsu have issued relevant policy documents on the construction of digital villages. From a global perspective, although the construction of digital villages in various countries has achieved phased results, it is facing unprecedented difficulties in fully building digital villages and achieving full coverage of digital villages. For example, the infrastructure construction of the digital countryside [5], insufficient technological innovation [6], uncoordinated regional development [7], and lack of close integration between theory and practice [8]. Therefore, for the current crucial digital village construction, we must seize the major historical opportunities brought by digital technology, focus on solving the problems existing in the construction of digital villages, and promote the digital transformation of rural areas.

In the process of building a digital village, the digital governance of the village is an indispensable element. The level of rural digital governance is an indicator of the degree of digital rural construction. From the literature review, it is found that most countries carry out more research on rural digital construction, but less on rural digital governance. As for digital governance, the United States, Europe, and other countries mainly focus on the public sector, smart cities, and digital platforms, and rarely involve rural digital governance [9]. Rural digital governance is a major topic in the modernization of rural social governance in China, and it is also a hot issue in the current academic circle.

In the report of the 20th National Congress, the strategic goal of “comprehensively promoting rural revitalization, adhering to the priority development of agriculture and rural areas, and accelerating the construction of an agricultural power” was proposed. In 2019, the General Office of the CPC Central Committee issued the Outline of the Digital Countryside Development Strategy, proposing to fully build digital villages and realize rural revitalization. The modernization of rural governance is an important embodiment of comprehensively promoting rural revitalization and realizing the modernization of the national governance system and governance capacity. The No. 1 Central Document in 2022 proposes to increase efforts to improve rural governance; Rural digital governance is an important part of promoting the digital countryside. To this end, rural grassroots governments should mainly focus on improving the level of digital governance and play a role in various governance fields. The establishment of a measurement system for the level of rural digital governance is a key measure to understand the progress and stage of the development of the current level of digital governance, promote the comprehensive construction of digital villages, and realize the modernization of rural governance.

Digital governance plays an important role in improving the digital level of education, health care, and culture in rural areas, promoting the process of rural digital governance, integrating information resources, eliminating information barriers, and improving the convenience of the people. The relevant policies issued by the state have promoted the construction of the digital countryside to a new level, and the construction of digital infrastructure has also covered China’s county and rural areas, providing a foundation for rural modernization. As the most basic unit in the governance system, rural governance occupies an important position and plays an important role in the national system.

In this context, all counties in the country have begun and gradually strengthened the implementation of digital governance, including data governance, digital public services, digital government, etc. Digital governance of county villages is an important part of promoting digital villages. Then, what is the specific level of the implementation of digital governance of county villages? What is the level of digital governance in county villages? How to improve the level of county rural figures? To answer these questions, we need to first answer how to understand digital governance, how to construct the measurement index system regarding the digital governance level of county and rural areas, and how to assign weight to these measurement indicators. In light of this, based on the understanding of the concept of digital governance, the review of relevant literature, the guidance of relevant theories, and the consideration of the actual implementation of digital governance, this paper builds an indicator system for measuring the level of digital governance in counties and villages, and then measures the level of digital governance in counties and villages in 31 provinces across the country, and proposes some countermeasures for improving digital governance in counties and villages.

The rest of this paper is organized as follows: Section 2 summarizes the relevant literature. Section 3 establishes the index system of rural digital governance level. Section 4 measures and analyses the digital governance level of county rural areas. Section 5 summarizes the research results and puts forward policy recommendations, as well as the existing shortcomings.

2. Literature Review

After the outline of the Digital Countryside development strategy (hereinafter referred to as the Outline) was issued, the construction of the digital countryside is an important strategic content of the current rural modernization construction in China. At present, domestic scholars mainly interpret the Outline and carry out research on the construction of the digital countryside around its content. Zhao Xingyu et al. [10] believe that the digital countryside can promote the modernization and transformation of rural areas and improve the penetration rate of digital technology, which is an effective path to boost rural revitalization. By observing counties such as Jiangsu Province, Li Yijie et al. [11] revealed that digital rural construction is the path of choice for rural revitalization from three aspects: theoretical mechanism, practical path, and policy inspiration. Liu Yanhong et al. [12] believe that the future should focus on the structure and efficiency of financial expenditure in the construction of the digital countryside, and it is necessary to build a sustainable digital countryside.

The digital rural development strategy will inevitably put forward new requirements for the modernization of rural governance. Liu Junxiang et al. [13] analyzed the experience of digital governance in Zhejiang, Hubei, and Guizhou, and believed that rural digital governance could drive rural revitalization from the aspects of the government system, infrastructure construction, and economic, social, and people’s livelihood. Zhang Zhaosu [14] conducted a case study on the digital governance platform of Huzhou City and believed that the panoramic governance of the digital countryside could achieve precise governance. Wu Xiaolong [15] believes that digital governance is a process of constant change and analyzes the scenario analysis of digital governance in five dimensions, including economy, ecology, culture, people’s livelihood, and governance, with the overall framework of “how to carry out, and how to implement”. Cui Yuanpei [16] et al. analyzed the innovative logic of rural digital governance during the 14th Five-Year Plan period and proposed to accelerate the orientation of digital governance through eliminating digital divide, technology guidance, and multi-subject alliance.

Due to the late start and narrow coverage of digital governance in rural areas, this paper mainly discusses the constraints of digital governance in rural areas. Ding Bo [17] found the problems of digital formalism, estranged relationship, and invisible work in the process of rural digital governance by constructing the analytical framework of “institution-technology-life”, and proposed that the path of digital governance could be optimized from the three aspects of rules, organization, and people. Huang Xinhua et al. [18] analyzed the governance dilemmas existing in digital governance from the aspects of social structure change, development transformation, and risk. Zhao Xiaofeng [19] et al. believe that the current rural digital governance will fall into multiple dilemmas in practice, such as the disconnection between supply and demand, digital dependence, technology flooding, and lack of governance rationality and sensibility. Li Xiaoxia et al. [20] believe that the operational mechanism of rural digital governance, urban-rural connection, and industrialization docking are the key bottlenecks hindering governance.

In terms of the construction of rural digital governance indicators, Yang Yulei [21] studied the readiness of rural digital governance in Anhui province by taking infrastructure, digital subjects, scientific and technological innovation, and government environment as the evaluation framework. Zhu Honggen et al. [22] measured the level of rural digital development in 30 provinces in China by constructing index systems such as digital capital investment, digital industry development, digital information foundation, and digital service level. Zhang Hong et al. [23] constructed indicators from five aspects: digital macro environment, infrastructure support, information environment, government environment, and application environment, and measured the development readiness of the digital countryside. Wu, X. [15] constructed indicators for the development of the digital countryside from six aspects, including environment, economy, and scientific and technological innovation, by collating policy documents.

Through the above literature review and combing, scholars have deepened their study on the implementation of the path of digital village construction; In the aspect of digital governance, it is mainly studied by case analysis and empirical research. As rural digital governance started late, research mainly focused on the constraints of rural digital governance; In terms of index construction, scholars mostly evaluate the development of digital villages, and the fields involved in the evaluation indicators have different focuses. The existing measurement system for the level of rural digital governance applies a more traditional research paradigm, and there are no high requirements on the selection and empowerment methods of indicators. In view of the above problems, this paper analyzes the policy texts on rural digital governance and draws on the experience of scholars on the indicator system of governance level to build a measurement system of rural digital governance level, which provides a reference for the measurement of rural digital governance level and improves governance efficiency.

3. Construction of Index System of Rural Digital Governance Level

3.1. Selection of Indicators of Rural Digital Governance Level

The fundamental starting point and purpose of constructing the measurement system of rural digital governance level is to provide scientific and effective theoretical guidance and improve the level of rural digital governance on the premise of truly reflecting the current situation of rural digital governance. The indicators selected in this paper are firstly based on policy text analysis and literature review, national policy documents on rural digital governance are consulted, the attributes and characteristics of indicators are analyzed in combination with literature research, and preliminary classification of indicators is carried out. Then, through the correlation analysis of the use of relevant indicators in the policy text, the cross-comparison analysis is carried out according to the core elements of the digital rural development strategy outline, and then the specific indicators are obtained. Finally, by consulting experts in related fields, the preliminary indicators are evaluated and analyzed, and the index system is adjusted and modified according to the expert opinions.

3.2. Index System Design and Construction

The index basis of this paper is mainly combined with the relevant indicators of the Outline of Digital Rural Development Strategy, China Digital Rural Development Report (2020), and Digital Rural Construction Guide 1.0, and draws on the experience of scholars on the indicator system of governance level. Based on the above basis, combined with the latest implementation measures of rural digital governance issued by various provinces and cities in China, it is concluded that digital governance is essentially a “Digital + N” situational application [24]. Centering on the five key governance areas of “digital economy, digital ecology, digital culture, digital people’s livelihood, and digital government”, the index measurement system of rural digital governance level is built.

• Digital economy index design. The field of digital economy focuses on digital infrastructure, digitalization of rural industry, and digital inclusive finance, which is an important prerequisite for the five key governance areas and a key factor for carrying out rural digital governance work. There are four indicators in the second-level indicator layer. Among them, digital infrastructure, as the foundation of the development of digital economy, can not only upgrade and transform obsolete facilities, but also bring new technologies to empower rural industries and effectively promote industrial transformation and high-quality development in rural areas [25]. The digital infrastructure index in the National County Digital Countryside Index (2020) released by Peking University is taken as a secondary index. By referring to the Evaluation of National County Digital Agriculture Rural Development Level (2020), the paper constructs a model with “Taobao Village” as the representative of agriculture-related e-commerce and takes the proportion of Taobao villages in all administrative villages and the delivery rate of live agricultural products as the secondary indicators to reflect the digitalization situation of rural industries. Digital finance is an important support for the effective operation of rural economy. Inclusive finance increases the coverage of financial services, optimizes the allocation of financial resources, effectively alleviates the financing constraints of rural low-income groups, and greatly improves people’s living standards [26]. The rural inclusive finance index in the Peking University Digital Inclusive Finance Index (2021) is used as a secondary index.
• Digital ecological index design. The field of digital ecology focuses on the combination of digital information or technology with agricultural and rural production, environment, and other aspects to build a digital ecological environment of harmonious coexistence between man and nature. To this end, it is necessary to start from the aspects of agricultural science and technology investment, environmental remediation, and production safety. Among them, according to the “14th Five-Year Plan” to promote the modernization of agriculture and rural areas, the construction of local financial agricultural science and technology expenditure as a secondary index layer, through the financial investment in agricultural science and technology, can understand the construction degree of digital ecology; Referring to the research of scholar Zhang Hong [23], the green development of digital agriculture and the agricultural and rural informatization production environment are selected as the second-level index layer. The digital production index in the national digital rural index is used to reflect the rural digital production environment.
• Digital culture index design. Digital culture focuses on how to promote excellent rural culture and tourism consultation through digital media. It reflects the “soft power” of rural development and is the key to the promotion and development of rural excellent culture. There are three indicators in this secondary index layer. The number of county-level financial media centers is taken as a secondary index to reflect rural network culture. The comprehensive strength of county tourism is taken as a secondary index to reflect the development of new rural business forms. The number of cultural stations in towns and villages is taken as a secondary index to reflect the spread of rural digital culture.
• Digital livelihood index design. The field of digital livelihood aims at the idea of being “people-centered”, mainly including rural education, medical care, and training and employment of professional farmers in the new era, and is an important internal cause to promote the high-quality development of rural public services. The second level of indicators is set up with six indicators. Among them, Internet + education has the advantage of empowering the development of rural basic education, which can improve the quality of rural basic education, and is also an effective path for precise poverty alleviation through education [27]. The proportion of rural education expenditure reflects the importance of rural education, and the coverage rate of rural distance education can reflect the actual situation of rural Internet + education. The new rural cooperative medical care and local financial medical expenditures reflect the specific situation of Internet + medical care; Rural productivity and employment are reflected by the employment situation of farmers (primary industry) and the number of training options for new professional farmers.
• Digital government index design. Digital government mainly promotes the sinking of government services to the rural grassroots by digital technology, mainly including Internet + government and comprehensive governance at the grassroots level, and three indicators are set in this secondary index layer. Among them, the proportion of villages and towns on the WeChat public service platform and the proportion of online disclosure of rural government information reflect the level of Internet + government affairs; The coverage rate of “Xueliang Project” administrative village reflects the level of comprehensive management at the grassroots level.

4. Measurement and Analysis of Digital Governance Level of County Rural Areas in China

4.1. Data Source and Processing

In order to ensure the accessibility, representativeness, and authenticity of indicator data, the data of 31 counties in the country involved in this paper come from the National County Digital Rural Index (2020), China Taobao Village Research Report (2021), Peking University Digital Financial Inclusion Index (2021), National Bureau of Statistics (2021), China Rural Statistical Yearbook (2021), National Report on the Development of New Professional Farmers, scholar Zhang Hong [14], statistical yearbooks of counties across the country, and mined, collected, and sorted relevant indicator data from the Internet through Python3, as shown in

Table 1. Indicators and sources at each level.

Primary Indicator Layer	Secondary Indicator Layer	Attribute	Indicator Source
Digital Economy	Digital Infrastructure Index	+	National Digital Rural Index (2020)
	The proportion of Taobao villages in all administrative villages	+	China’s Taobao Village Research Report (2021)
	Agricultural products live commodity delivery rate	+	Oteo Consulting (2021)
	Rural Financial Inclusion Digital Index	+	Peking University Digital Financial Inclusion Index (2021)
Digital ecology	Local fiscal expenditures for agriculture, forestry, and water conservancy affairs	+	National Bureau of Statistics (2021)
	Green development of digital agriculture	+	Zhang Hong (2021)
	Digital production index	+	National Digital Rural Index (2020)
	Agricultural and rural informatization production environment	+	Zhang Hong (2021)
Digital culture	Number of county-level financial media centers	+	Digital Village Development Action Plan (2021)
	County tourism comprehensive strength top 100	+	National County Tourism Research Report (2021)
	Number of township cultural stations	+	China Rural Statistical Yearbook (2021)
Digital livelihood	The proportion of rural education expenditure	+	China Rural Statistical Yearbook (2021)
	Rural distance education coverage	+	Digital Village Development Action Plan (2021)
	Number of new rural cooperative medical care	+	National Bureau of Statistics (2021)
	Local government medical expenditure	+	National Bureau of Statistics (2021)
	Rural Employment (primary industry)	+	China Rural Statistical Yearbook (2021)
	The number of new professional farmer training options	+	National Report on the Development of New Professional Farmers
Digital government	The proportion of villages and towns on WeChat public service platform	+	National Digital Rural Index (2021)
	The proportion of rural government information disclosed online	+	National Bureau of Agriculture and Rural Affairs of Cities and Counties (2021)
	“Xueliang Project” administrative village coverage	+	Digital Village Development Action Plan (2021)

. For some counties where data are missing and difficult to collect, the average value is used to improve.

4.2. Ethics

The data collected in this paper are all public data from authoritative official websites. After collecting relevant data, the author has cleaned, screened, and sorted them without any conflict of interest. The data presented in this study are available on request from the corresponding author.

4.3. Evaluation Method

At present, the index weighting methods in multi-index comprehensive evaluation can be roughly divided into subjective weighting methods, objective weighting methods and subjective and objective combination weighting methods: The common subjective weighting methods include the Delphi method, analytic hierarchy process (AHP), chain scoring method, etc. Objective weighting methods include the multi-objective programming method, principal component analysis method, entropy weight method, etc. [28], among which the entropy weight method can effectively avoid the bias brought by subjective consciousness. The TOPSIS method is a commonly used intra-group comprehensive evaluation method, which can make full use of the information of the original data, and its results can accurately reflect the gap between evaluation schemes. Scholars combine the TOPSIS model with the entropy weight method, that is, the entropy weight TOPSIS model, and apply level measures in many fields [29,30,31].

The entropy method is a kind of objective weighting method. It uses entropy value to measure the degree of influence of various evaluation indicators on the pros and cons of schemes for the system, which avoids the influence of subjective factors from experts. The entropy method is used to determine the weight with good stability, and the result is relatively reasonable.

For this reason, the entropy weight TOPSIS model is used in this study to measure the level of digital rural governance at the county level in China, as shown in

Table 2. Weight table of rural digital governance level measurement based on the entropy weight TOPSIS model.

Primary Indicator Layer	Weight	Secondary Indicator Layer	Weight
Digital Economy	0.2618	Digital Infrastructure Index	0.0134
		The proportion of Taobao villages in all administrative villages	0.2061
		Agricultural products live commodity delivery rate	0.0441
		Rural Financial Inclusion Digital Index	0.0088
Digital ecology	0.1353	Local fiscal expenditures for agriculture, forestry, and water conservancy affairs	0.0271
		Green development of digital agriculture	0.0138
		Digital production index	0.0613
		Agricultural and rural informatization production environment	0.0385
Digital culture	0.3387	Number of county-level financial media centers	0.0523
		County tourism comprehensive strength top 100	0.1715
		Number of township cultural stations	0.0406
Digital livelihood	0.1490	The proportion of rural education expenditure	0.0190
		Rural distance education coverage	0.0240
		Number of new rural cooperative medical care	0.0343
		Local government medical expenditure	0.0413
		Rural Employment (primary industry)	0.0667
		The number of new professional farmer training options	0.0473
Digital government	0.1152	The proportion of villages and towns on WeChat public service platform	0.0094
		The proportion of rural government information disclosed online	0.0057
		“Xueliang Project” administrative village coverage	0.0749

.

• Index data standardization

Since each indicator is different in quantity, unit, and other aspects, it is necessary to standardize the collected indicator data. In this paper, the range transformation method is adopted to conduct dimensionless processing on the original data. After dimensionless processing, the index value is located in the interval [0, 1]. The larger the value of all indexes, the better. Indicators can be divided into positive indicators and negative indicators. The formula of range standardization method is as follows [32]:

$${\chi }_{ij}^{’}=\frac{{\chi }_{ij}-min{\chi }_j}{max{\chi }_j-min{\chi }_j}$$

(1)

2.

Index weighting

First, through the matrix

$$Z=({\gamma }_{ij}{)}_{m\times n}$$

(2)

Find the proportion of the index value of the i sample of the j index.

$${\eta }_{ij}=\frac{{\gamma }_{ij}}{{\displaystyle \sum _{i=1}^n{\gamma }_{ij}}}$$

(3)

where ${\eta }_{ij}$ is a standardized decision matrix, and ${\gamma }_{ij}$ is the value i = 1, 2, …, n; j = 1, 2, …, m of the J-th evaluation index of the ith evaluation object.

Secondly, calculate the entropy value of the J-th index ${\chi }_{ij}$.

$$k=\frac{1}{ln n}$$

(4)

$${\chi }_{ij}=-k{\displaystyle \sum _{i=1}^n{\eta }_{ij}ln\left({\eta }_{ij}\right)}$$

(5)

where ${\chi }_{ij}$ is the entropy value of the J-th index among the m evaluation indexes.

Finally, the weights of each index are calculated.

$${\upsilon }_j=\frac{(1-{\mathrm{e}}_j)}{{\displaystyle \sum _{j=1}^n(1-{\mathrm{e}}_j)}}$$

(6)

3.

To evaluate the governance level, the specific steps are as follows.

Step 1, construct the weighted normalized decision matrix

$$V={\left(V_{ij}\right)}_{m\times n}$$

(7)

$$V_{ij}={\beta }_j{X}_{ij}$$

(8)

where V_ij is a weighted decision matrix, and X_ij refers to the index weight of the J-th index.

Step 2, determine the positive ideal solution $V^{+}$ and negative ideal solution of the measure object $V^{-}$.

$$V_j^{+}=\left({minV}_{ij}|i=1,2,\cdots ,m\right)$$

(9)

$$V_j^{-}=\left({minV}_{ij}|i=1,2,\cdots ,m\right)$$

(10)

where $V^{+}$ is the normalized and weighted target ideal solution, and $V^{-}$ is the normalized and weighted target negative ideal solution.

Step 3, calculate the difference between each evaluation index and the optimal and worst vectors.

$$D_i^{+}=\sqrt{{\displaystyle \sum _{j=1}^m{\omega }_j{\left(Z_j^{+}{-Z}_{ij}\right)}^2}}$$

(11)

$$D_i^{-}=\sqrt{{\displaystyle \sum _{j=1}^m{\omega }_j{\left(Z_j^{-}{-Z}_{ij}\right)}^2}}$$

(12)

where $D_i^{+}$ is the Euclidean distance between the actual value of each evaluation object and the ideal solution, and $D_i^{-}$ is the Euclidean distance between the actual value of each evaluation object and the negative ideal solution.

Step 4: Measure how close the object is to the optimal scheme $C_i$.

The value range of $C_i$ is (0–1). The larger the value, the higher the level of rural digital governance in the county.

$$C_i=\frac{D_i^{-}}{D_i^{+}+D_i^{-}}$$

(13)

where $C_i$ is the relative approaching degree between the feasible solution and the ideal solution.

For the multi-level index evaluation model, it is necessary to generate the initial matrix of the upper level from the relative approaching degree C_i of the single level evaluation index, calculate the relative approaching degree of the upper-level indexes, and obtain the evaluation results of the upper level [33].

The TOPSIS method used in this paper is implemented to rank the distance from the evaluation object to the optimum solution and the worst solution [34]. To make better use of the original data, it has been extensively applied in multi-criterion evaluation [35] with no strict restriction on the sample content and the number of indexes of the data and good applicability. Moreover, TOPSIS can be used for evaluating different levels of the evaluation system to determine the problems existing in the evaluation object. To this end, the TOPSIS method is applicable to the horizontal measure of rural digital governance in this paper.

4.4. Analysis of the Measurement Results of Digital Governance Level in County Rural Areas in China

The comprehensive scores and sub-system scores of digital governance level measurement in China’s counties and villages in 2021 are shown in

Table 3. Measurement results of the digital governance level of counties and villages in China in 2021.

Regional	Digital Economy	Digital Ecology	Digital Culture	Digital Livelihood	Digital Government	Total Score	Rank
Eastern region	0.0769	0.0608	0.0406	0.0978	0.0506	0.3267	-
Peking	0.0417	0.0324	0.0026	0.0435	0.0387	0.1591	28
Tianjin	0.0289	0.0276	0.0021	0.0334	0.0532	0.1452	30
Jiangsu	0.0978	0.1114	0.0590	0.1140	0.0837	0.4659	3
Liaoning	0.0246	0.0284	0.0186	0.0793	0.0107	0.1616	27
Shanghai	0.0270	0.0364	0.0018	0.0376	0.0866	0.1894	19
Zhejiang	0.2358	0.1010	0.1939	0.0842	0.0899	0.7047	1
Kwangtung	0.1457	0.0849	0.0338	0.1787	0.0391	0.4822	2
Shandong	0.1013	0.0831	0.0313	0.1361	0.0457	0.3974	5
Hebei	0.0765	0.0811	0.0422	0.1165	0.0135	0.3297	8
Henan	0.0398	0.0691	0.0583	0.1683	0.0406	0.3761	6
Hainan	0.0273	0.0133	0.0025	0.0844	0.0553	0.1828	21
Central region	0.0334	0.0461	0.0565	0.1057	0.0489	0.2907	-
Shanxi	0.0255	0.0163	0.0287	0.0994	0.0307	0.2007	17
Ji Lin	0.0249	0.0381	0.0207	0.0443	0.0436	0.1716	24
Sichuan	0.0226	0.0577	0.1419	0.1518	0.0559	0.4300	4
Anhui	0.0232	0.0568	0.0384	0.1111	0.0616	0.2912	12
Jiangxi	0.0345	0.0425	0.0717	0.0887	0.0459	0.2833	14
Fujian	0.0846	0.0545	0.0466	0.0876	0.0593	0.3327	7
Hunan	0.0225	0.0538	0.0739	0.1189	0.0296	0.2986	11
Hubei	0.0294	0.0494	0.0304	0.1435	0.0647	0.3174	9
Western region	0.0229	0.0334	0.0275	0.0759	0.0179	0.1776	-
Inner Mongolia	0.0153	0.0402	0.0125	0.0744	0.0121	0.1545	29
Guangxi	0.0238	0.0394	0.0348	0.0794	0.0130	0.1905	18
Chongqing	0.0182	0.0393	0.0268	0.0720	0.0129	0.1692	25
Heilongjiang	0.0162	0.0468	0.0249	0.0856	0.0419	0.2154	16
Guizhou	0.0182	0.0339	0.0819	0.1044	0.0299	0.2684	15
Yunnan	0.0589	0.0394	0.0442	0.1603	0.0095	0.3124	10
Xizang.	0.0186	0.0137	0.0066	0.0274	0.0045	0.0708	33
Shaanxi	0.0270	0.0376	0.0247	0.0649	0.0312	0.1853	20
Gansu	0.0193	0.0288	0.0354	0.0854	0.0122	0.1810	22
Qinghai	0.0200	0.0164	0.0038	0.0313	0.0269	0.0985	32
Ningxia	0.0293	0.0263	0.0020	0.0483	0.0114	0.1172	31
Xinjiang	0.0101	0.0389	0.0321	0.0772	0.0094	0.1678	26
National average	0.0449	0.0467	0.0412	0.0933	0.0381	0.2643	-

Note: The regional division refers to the division standard of economic geography concept: The eastern region includes 11 provinces, including Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan; the central region includes 8 provinces: Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan; the western region includes 12 provinces: Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.

.

1.

Analysis of the comprehensive development trend of digital governance level in county rural areas in China

According to the analysis, there are 14 provinces and cities whose digital governance level is higher than the national average (0.2641), mainly distributed in the central and eastern regions, namely Zhejiang, Jiangsu, Guangdong, Jiangsu, Sichuan, Shandong, Henan, Fujian, Hebei, Hubei, Yunnan, Hunan, Anhui, Jiangxi, and Guizhou provinces. The overall score of digital governance level in the eastern region (0.3228) ranked first; The central region (0.2693) ranked second. Finally, the western region (0.1955) ranks the third, which has a certain correlation with geographical, environmental, economic, and other factors in different regions.

From the numerical situation of the total score, the total score of county rural digital governance in 31 provinces is generally not high, the overall distribution is 0.171601 to 0.430000, and the median value of the total score is 0.2007 of Shanxi Province. Among counties, the highest level of rural digital governance was in Zhejiang Province (0.7047), followed by Guangdong Province (0.4822) and Jiangsu Province (0.4659), and the lowest level was in Tibet Autonomous Region (0.0708). The total score of the first place was about 9.953 times that of the last place. In general, it can be seen that in the total score of the digital governance level of counties and villages, the gap between counties and villages is very wide. In addition, the top five provinces and counties in the total score are Zhejiang, Guangdong, Jiangsu, Sichuan, and Shandong, and the median of the top five is 0.4659, among which the fourth is Sichuan Province in the western region, and the other four provinces are eastern regions. The bottom five provinces and counties were Inner Mongolia, Tianjin, Ningxia, Qinghai, and Tibet, and the median of the bottom five was 0.1172. The median value of the total score in the top five is about four times that of the median value in the bottom five, indicating once again that the difference between provinces and counties in the total score is significant.

In order to further explore the spatial distribution of county-level rural digital governance, this paper calculates the median total score of each region in the three regions and compares the level of county-level rural digital governance based on this. It can be clearly seen from Figure 1 that the scores of the eastern region in terms of the digital governance level of counties and villages are higher than the median values of the central and western regions and the whole country. The central region scored higher than the western region and the national median; The West is slightly below the national median. This indicates that the eastern region and the central region perform relatively well in the implementation of county rural digital governance, while the western region needs to strengthen the implementation of county rural digital governance.

2.

Spatial difference analysis of digital governance level in China’s counties and villages

In order to more intuitively present the differences in digital governance levels of provinces and counties across the country, the comprehensive scores of provinces and counties were divided into five groups using the natural break point method [23], namely, low digital governance level, low digital governance level, medium digital governance level, high digital governance level, and high digital governance level, as shown in

Table 4. Digital governance level division of counties.

Area Type	Counties	Level
S ≥ 0.430001	Zhejiang, Jiangsu, Guangdong	Higher
0.215401 ≤ S < 0.430000	Sichuan, Shandong, Henan, Fujian, Hebei, Hubei, Yunnan, Hunan, Anhui, Jiangxi, Guizhou, Heilongjiang	High
0.171601 ≤ S < 0.215400	Shanxi, Guangxi, Shanghai, Shaanxi, Hainan, Gansu, Jilin	Medium
0.117201 ≤ S < 0.171600	Chongqing, Xinjiang, Liaoning, Beijing, Inner Mongolia, Tianjin	Low
S < 0.117200	Ningxia, Qinghai, Tibet	Lower

.

According to the division of digital governance level of provinces and counties, the ArcMap10.8 software is used to visualize the spatial differences of rural digital governance level of 31 provinces and counties in China, as shown in Figure 2. It is found that there is a large gap in the level of rural digital governance in various counties in China, and the regional level presents a decreasing spatial distribution from “east-middle-west” in turn, as shown in Figure 1. There are three counties with a significant effect on the level of rural digital governance, distributed in the east; There are 12 counties with a high level of rural digital governance, which are concentrated in the eastern and central regions. There are seven counties with a medium level of rural digital governance, which are concentrated in the south. Nearly 30% of the country’s regions are at a low level of digital governance. Due to the early development of digital infrastructure, preferential policies, pilot work, and the economic development of provincial capitals, the eastern region attaches importance to the development of digital economy and digital government, and the comprehensive level of rural digital governance is more prominent. On the basis of attaching importance to digital government affairs, the central region focuses on the development of digital people’s livelihood, with rural medical care and education as the starting point. Due to the influence of hard factors such as geography and environment, the western region is lower than the national average in digital economy, ecology, people’s livelihood, and government affairs. Therefore, solving the problems faced by rural digital governance in western China is the key to realize the modernization of rural governance.

3.

Analysis of the sub-systems of digital governance in China’s county rural areas

First-level indicators are the core dimension for measuring the digital governance level of county and rural areas. By comparing the median of five first-level indicators of digital economy, digital ecology, digital culture, and digital government at the level of digital people’s livelihood in 31 provinces and counties, one can determine in which dimension the implementation level of digital governance level of county and rural areas in 31 provinces is making rapid progress, as well as in which dimension the construction is deficient.

 1.

The score of 31 provinces and counties at each indicator level

According to Figure 3, it can be seen that the 31 provinces and counties have the highest scores in the first-level index dimension of digital livelihood, the first-level index scores of digital ecology and digital government are similar, followed by the first-level index of digital culture, and finally the lowest score is achieved for the first-level index of digital economy. Through the analysis of the median scores of 31 provinces in five first-level indicators, it can be shown that in the implementation of digital governance in counties and villages, on the whole, all provinces and counties have relatively good performance in digital livelihood, relatively flat performance in digital ecology, digital government, and digital culture, while there are obvious shortcomings in digital economy.

 2.

The scores of the three regions at each level of the indicators

As can be seen from Figure 4, the digital economy, digital ecology, and digital government in the eastern region are higher than the corresponding median values in the central and western regions as well as the whole country. In terms of digital culture and digital livelihood, the central region is higher than the eastern region, the western region, and the corresponding national median value. The western region is higher than the national median value only in the aspect of digital culture, basically equal to the national median value in the aspect of digital livelihood, and lower than the national median value in other aspects. Overall, the eastern region performed better than the other two regions in the five first-level indicators, followed by the central region and the western region, while the total score of the western region was slightly below the national median value.

1. The level of digital economy mainly focuses on exploring how to drive farmers’ poverty alleviation and income increase through “digital production”, high-quality agricultural development, and digital financial inclusion. The average value and median value of 31 provinces and counties in the digital economy level are 0.0447 and 0.0270, respectively. It can be seen from Figure 5 that the scores of 31 provinces and counties in this dimension are mostly distributed in the range of 0.0100–0.0238. Among them, Zhejiang Province ranked first with a score of 0.2358; Guangdong and Shandong ranked second and third, respectively, with scores above 0.1000. In addition, the top five provinces and counties are Zhejiang, Guangdong, Shandong, Jiangsu, and Fujian, with a median value of 0.1013; The next five provinces and counties are Guizhou, Chongqing, Heilongjiang, Inner Mongolia, and Xinjiang. It can be seen that all provinces except Heilongjiang belong to the western region, with a median value of 0.0161. The median value of the top five is about 6.266 times that of the bottom five. This shows that there is a clear gap in the level of digital economy between provinces and counties. Digital economy is the necessary basis for the normal development of digital governance, so the provinces and counties with low ranking, especially those in the western region, should pay attention to and strengthen the construction of the level of digital economy. Such developments as the upgrading of obsolete facilities can also bring new technologies to empower rural industries, and effectively promote the industrial transformation and high-quality development of rural areas. Given that the level of digital economy plays a fundamental and important role in the implementation of digital governance, the eastern and central regions still need to continue to strengthen the construction of this aspect, so as to provide a sustainable digital governance environment for the implementation of digital governance.

2. The level of digital ecology is mainly about how to build a rural humanistic ecological environment of harmonious coexistence between man and nature through digital monitoring. Specific secondary indicators include local financial expenditure on agriculture, forestry and water affairs, digital agricultural green development, digital production index, and agricultural and rural information production environment. The average value and median value of the 31 provinces and counties in the digital ecological level are 0.0467 and 0.0394, respectively. It can be seen from Figure 6 that the scores of the 31 provinces in this dimension are mostly distributed in the range of 0.0238–0.0846. Among them, Jiangsu Province ranked first with a score of 0.1114, Zhejiang Province and Guangdong Province ranked second and third, respectively, and Zhejiang Province also scored more than 0.1000. In addition, the top five provinces and counties are Jiangsu, Zhejiang, Guangdong, Shandong, and Hebei, with a median value of 0.0849; The last five provinces and counties are Ningxia, Qinghai, Shanxi, Tibet, and Hainan, in that order. It can be seen that all provinces except Hainan belong to the western region, with a median value of 0.0163, and the median value of the top five is about 5.2 times that of the bottom five, indicating that there is an obvious gap in the level of digital ecology among provinces and counties. Digital ecology is an important link in the normal development of digital governance, so the provinces and counties with low ranking, especially those in the western region, should pay attention to and strengthen the construction of the digital ecology level, such as counties still need to increase financial expenditure on agriculture, forestry, and water affairs, organically integrate digital technology with agricultural manufacturing, machinery, and tools, and improve the quality and quantity of agricultural production. Given that the level of digital economy is an important condition for the implementation of digital governance, the eastern region and the central region still need to continue to strengthen the construction of this aspect, so as to provide a good digital ecological environment for the implementation of digital governance.

3. The level of digital culture in counties mainly focuses on how to empower rural culture through digital communication. The mean value and median value of digital literacy level of 31 provinces and counties in China are 0.0411 and 0.0313, respectively. It can be seen from Figure 7 that the scores of 31 provinces and counties in this dimension are mostly distributed in the range of 0.0238–0.0846. Among them, Zhejiang Province ranked first with a score of 0.1939, and Sichuan and Guizhou ranked second and third, respectively, with Sichuan scoring more than 0.1000. In addition, the top five provinces and counties are Zhejiang, Sichuan, Guizhou, Hunan, and Jiangxi, with a median value of 0.0819; The last five provinces and counties are successively Beijing, Hainan, Tianjin, Ningxia, and Shanghai, with a median value of 0.0021, and the median value of the top five is about 39 times that of the bottom five, which indicates that there is an obvious gap in the digital literacy level among provinces and counties. It should be noted that in addition to Ningxia, the last five provinces and counties belong to the western region, and the remaining four provinces and counties are from the eastern region, while in the top five provinces and counties, except Zhejiang Province, the remaining four provinces and counties are from the central region and the western region, which indicates that there is also a significant gap in the level of digital culture within the region. Digital culture is the “soul project” of the normal development of digital governance, so the provinces and counties with low scores should pay attention to and strengthen the construction of the digital culture level, such as the promotion and inheritance of rural culture more widely through digital technology and platforms, and effectively promoting the development of rural tourism. In view of the fact that the promotion of digital culture level is an important means to promote the common prosperity of rural areas and plays an important role in the implementation of digital governance, the eastern and western regions still need to continue to strengthen the construction of this aspect, so as to effectively play the comprehensive driving role of digital culture in rural economic and social development at the county level.

4. County digital livelihood mainly reflects how to use digital platforms to promote the high-quality development of rural public services, mainly including education, medical care, and other aspects. The average value and median value of the 31 provinces and counties in the country in the level of digital livelihood are 0.0936 and 0.0854, respectively. It can be seen from Figure 8 that the scores of the 31 provinces and counties in this dimension are mostly distributed in the range of 0.0417–0.1457. Among them, Guangdong Province ranked first with a score of 0.1787, and Henan and Yunnan ranked second and third, respectively, with scores above 0.1600. In addition, the top five provinces and counties are Guangdong, Henan, Yunnan, Sichuan, and Hubei, with a median value of 0.1603; The bottom five provinces and counties are Beijing, Shanghai, Tianjin, Qinghai, and Tibet, showing that the eastern region accounts for the majority, and there are no provinces and counties in the central region. The median value of the top five is 0.0334, and the median value of the top five is about 4.8 times of the median value of the bottom five. This shows that there is a clear gap in the level of digital livelihood between provinces and counties. Digital people’s livelihood is an important guarantee for the normal development of digital governance, which is related to all aspects of rural villagers’ lives. Therefore, provinces and counties with low scores, especially those in the western region, should attach importance to and strengthen the construction of digital people’s livelihood, such as maintaining investment in people’s livelihood and improving rural public services. In view of the fact that the level of digital livelihood is an important measure to promote the upgrading of rural digital governance, which can effectively improve the governance efficiency, the central and western regions still need to strengthen the construction of this aspect, so as to comprehensively improve the sense of gain, happiness, and security of farmers.

5. The key area of county digital government level is how to achieve sustainable development and digital transformation of rural society through technology embedding. The average and median values of the 31 provinces and counties in China in the level of digital government affairs are 0.0380 and 0.0387, respectively. It can be seen from Figure 9 that the scores of the 31 provinces and counties in this dimension are mostly distributed in the range of 0.0238–0.0846. Among them, Zhejiang Province ranked first with a score of 0.0899, while Shanghai and Jiangsu ranked second and third, respectively, with scores above 0.0800. In addition, the top five provinces and counties are Zhejiang, Shanghai, Jiangsu, Hubei, and Anhui, with a median value of 0.0837; The bottom five provinces and counties are Ningxia, Liaoning, Yunnan, Xinjiang, and Tibet, with a median value of 0.0095, and the median value of the top five is about 8.81 times that of the bottom five, indicating that there is an obvious gap in the level of digital government among provinces and counties. Digital government affairs are the extension of “Internet + government affairs services” to the countryside, making full use of information means to undertake a comprehensive and efficient job in government affairs services. Therefore, provinces and counties with low scores, especially those in the western region, should pay attention to and strengthen the construction of digital government affairs. For example, digital government will continue to play a positive role in policy communication, public opinion transmission, open village affairs, dispute mediation, etc., and fully protect the villagers’ right to supervision and participation.

5. Conclusions and Suggestion

5.1. Research Conclusion

By using the weighted county-level rural digital governance measurement index system and based on relevant data, the overall analysis of the county-level rural digital governance level score of 31 provinces, the cluster analysis of the county-level rural score, the score ranking of the three major regions, and the analysis of each first-level index are carried out. It is proved that the index system of county-level and rural digital governance with weights constructed in this paper has certain rationality and operability. In addition, the following findings were obtained.

First, on the whole, the score of county rural digital governance level in 31 provinces is generally not high, and only Zhejiang Province exceeds 0.7, which reflects that the level of county rural digital governance in China is still in its infancy at this stage.

Secondly, the paper analyzes the scores of rural digital governance in 31 provinces by natural breakpoint method, and divides 31 provinces and counties into five echelons. Among them, the scores of the first echelon of county rural digital governance are relatively leading, with Zhejiang, Guangdong, and Jiangsu provinces. The scores of rural digital governance in the second tier of counties are relatively excellent, including 12 provinces such as Sichuan, Shandong, and Henan. The scores of the third echelon of rural digital governance in counties are relatively average or moderate, which includes seven provinces and counties, including Shanxi and Guangxi. The fourth echelon includes six provinces and counties, including Chongqing, Xinjiang, and Liaoning. The scores of the fifth tier of rural digital governance are relatively at the level of urgent development, including Ningxia, Qinghai, and Tibet.

Third, through the comparative analysis of the three regions in five first-level indicators, it is found that the performance of the eastern region in digital economy, digital ecology, and digital government is better than that of the other two regions. The central region performs better than the eastern and western regions in terms of digital culture and digital people’s livelihood. The west is not performing well in any way.

5.2. Suggestions

By measuring the level of rural digital governance in 31 provinces and counties in 2021, this paper finds that there is a large gap in the level of rural digital governance in all counties in China, and the regional level presents a decreasing spatial distribution from “east-middle-west” in turn. Rural digital governance is the inevitable way to realize the modernization of rural governance. Each county should combine its own unique regional advantages, seize the dividend period of digital rural development, and comprehensively improve the level of digital governance. Therefore, countermeasures and suggestions for rural digital governance are proposed according to the following five aspects of measurement results.

(1) In terms of digital economy, digital economy as the “accelerator” of rural economic development, one is to improve the overall level of rural digital economy in the country, and digital economy can bring lasting dividends to rural economic development. First of all, all counties in the country should, based on their own development, increase government policy support, stimulate enterprise investment and construction scale, and upgrade their own regional brand characteristics by optimizing the current policies especially the counties in Tibet, Inner Mongolia, Heilongjiang, and other provinces which are ranked at the bottom should timely improve the relevant rural digital economy policy content and increase policy support. In addition, they should promote the integration of urban and rural areas, break the information barrier, accelerate the integration of urban and rural digital economy, realize the sharing of urban and rural technology, digital infrastructure, and other resources, and then form a new development pattern of urban and rural integration. Second, it is necessary to narrow the gap of rural digital economy in various provinces, focusing on the construction of digital infrastructure for the first time, building a solid foundation for industrial digitalization, and narrowing the differences between counties through industrial digitalization. Second, the eastern region should maintain the momentum of sustainable development of digital economy, create more “Fengqiao experience”, and give play to the “spillover effect” to do a good job of fixed-point and precise assistance to remote areas. At the same time, the policy should also increase efforts to tilt the construction of digital infrastructure in the western region.

(2) In terms of digital ecology, the eastern and central regions pay more attention to it. A good digital ecological environment is an important condition for realizing the goal of ecological basis. In terms of agricultural science and technology, counties still need to increase financial expenditure on agriculture, forestry, and water affairs, organically integrate digital technology with agricultural manufacturing, machinery, and tools, and improve the quality and quantity of agricultural production. In terms of smart green villages, county governments can actively promote the concept of green and sustainable development to farmers, guide farmers to achieve green and sustainable standards in agricultural production, processing, and other aspects, and improve their subjective initiative. At the same time, they should also increase the punishment for agricultural production activities that pollute and destroy the environment. In terms of digital production, as there are a large number of small-scale agricultural cooperatives and enterprises in some regions, these cooperatives and enterprises do not have the conditions for digital production. Therefore, the county government can appropriately support local leading agricultural enterprises and guide them to generate “spillover benefits” under the drive of leading agricultural enterprises, thus driving the green development of regional agriculture, improving the scale and digital degree of agricultural production, and then forming a sound green agricultural production chain.

(3) In terms of digital culture, it is found from the evaluation scores of digital culture in various regions that the emphasis on digital culture is not high, resulting in a low overall score of digital culture. We should strengthen the emphasis and development of rural digital culture. Excellent rural culture is the soul of the countryside. Through digital technology and platforms, rural culture can be carried forward and inherited more widely. In terms of the prosperity of rural network culture, the county-level government should take the lead in organizing and building more county-level financial media, strengthen the communication role of mainstream financial media, give full play to the local advantages of county-level financial media, spread excellent rural culture and folk stories to the public through financial media, and explore the establishment of local service models such as “financial media platform + government affairs + technology + culture”. In addition, it is necessary to vigorously develop new rural business forms, and each county should enrich tourism, take local characteristics of culture and industry as an attraction point, and create “one village, one product” and other characteristics of tourism. In terms of digital communication, we should continue to promote the construction of digital village pilot projects, carry out digital transformation of township cultural stations, village-level libraries, rural libraries, and other facilities, establish village-level electronic reading rooms, and improve the quality of rural public cultural services.

(4) In terms of digital people’s livelihood, on the whole, all regions attach more importance to digital people’s livelihood, and the central region has the highest evaluation score. A major concern of the people is their livelihood, and we need to continue to maintain investment in the livelihood of the people. In terms of Internet + education, county governments should increase investment in rural education, and municipal education departments should actively communicate and contact with county education departments to share more educational resources through digital technology access, such as the improvement of rural teachers’ ability and the cultivation of students’ digital literacy. In terms of Internet + medical care, Wu Zhongan et al. found through the household survey data of farmers that the convenience of obtaining medical information through the Internet has a significant positive impact on the satisfaction of the new rural cooperative Medical care system, but the distance from the city has a negative impact. Therefore, it is necessary to pay attention to meet the needs of different age groups and different groups, and build diversified rural medical services. As a vulnerable group, farmers have low awareness of the new rural cooperative Medical system (NRCMS) and have a fluke mentality. Therefore, county governments should make more efforts to publicize the NRCMS policy. Secondly, they should reform the management mode of the traditional NRCMS fund and integrate external resources to help farmers have a better understanding of the NRCMS. In terms of new professional farmers, county governments should seize the opportunity of digital rural construction to create a digital platform rural industry chain cultivation model—that is, to combine the training of new professional farmers with the operation of the agricultural industry chain, and achieve seamless connection between training and employment.

(5) In terms of digital government affairs, the digital government affairs service is an important service and guarantee for the implementation of rural governance modernization and rural revitalization strategy. The eastern and western regions have launched the corresponding digital construction network technology of rural government services, which has created favorable conditions for each subject of rural digital governance. Therefore, all regions need to continue to give full play to the positive role of digital government in policy communication, public opinion transmission, village affairs disclosure, dispute mediation, etc., increase the proportion of online information disclosure, improve the network government platform, and fully protect the supervision and participation rights of villagers. In terms of comprehensive management at the grassroots level, the “Xueliang project” not only ensures the safety of villagers and maintains social security, but also promotes innovation in rural governance. To this end, it is necessary to continue to broaden the coverage of the “Snow bright project”, upgrade infrastructure, increase participants, realize the “whole network sharing” of data resources, enhance the “precision” of rural governance, and improve the modernization level of rural governance.

With the development of information technology, digital governance has become an important trend in rural development. Developed countries have gained certain experience in rural digital governance. For example, rural digital governance in the United States focuses on continuous technological innovation and renewal. The government encourages enterprises and social organizations to carry out technological research and development and innovation activities to provide more technical support for rural digital governance. At the same time, the government also regularly evaluates existing digital governance technologies and models, adapting and improving them as needed. This attitude of continuous innovation and renewal helps to maintain the vitality and adaptability of rural digital governance; European rural development plans focus on infrastructure and social welfare. Rural governance in Asian countries focuses on agricultural modernization and environmental protection. These strategies and practices provide a beneficial reference for the development of rural digital governance.

Although rural digital governance has many advantages, it also faces some challenges. For example, some rural areas are struggling to achieve digital transformation due to their low level of economic development and weak infrastructure. In addition, issues such as data security and privacy protection also need attention. However, with the continuous progress of technology and the continuous improvement of governance system, the opportunities of rural digital governance are becoming more and more obvious. By exploring and utilizing these opportunities, high-quality and sustainable development of rural governance can be achieved.

5.3. Limitation

(1) Considering the availability of data, this paper only collected the relevant data of 31 provinces in 2021, which makes the analysis based on cross-sectional data unable to reflect the dynamic change of the corresponding county level of rural digital governance in each province.

(2) As far as measurement indicators are concerned, there is no direct reference for how to measure some specific measurement indicators in some aspects. Therefore, this paper is based on combing relevant studies to find specific measurement methods, which may harm the universality of indicators.

(3) Based on the fact that most of the data used in the research are objective data and the objectivity of the entropy weight method, the entropy weight TOPSIS model is chosen to assign weights to the measurement indicators, but the comparative advantages of the subjective weighting method are ignored to some extent.