How Digital Government Empowers Public Service Delivery in China: Mechanisms from Public Value and Technological Empowerment Perspectives

Abstract

The construction of a digital government is a significant initiative to modernize the national governance system and enhance governance capabilities, with the creation of public value focused on optimizing the supply level of basic public services within improved governance efficiency. This research begins with public value theory and technology empowerment theory to explain the theoretical mechanisms by which digital government can promote the supply level of basic public services. Utilizing panel data from 31 provinces in China from 2017 to 2021, this study investigates the impact of digital government construction on the supply level of basic public services and further examines the moderating effects of government support, the level of digital technology development, and regional heterogeneity. The research findings indicate that digital government construction can significantly enhance the supply level of basic public services, with more pronounced effects in regions where government support is strong or the level of digital technology development is high. Analysis of regional heterogeneity shows that the improvement in the supply level of basic public services due to digital government construction is more significant in the eastern region compared to the central and western regions. This study, based on the practice of digital government construction, provides a theoretical basis and decision-making reference for optimizing the top-level design of digital government, improving the supply level of public services, and achieving the integration of “digital + public services.”

1. Introduction

Public services play a pivotal role in enhancing people’s livelihoods, fostering social harmony, and promoting equity and justice in China’s modern society [1]. With rising expectations for better educational opportunities, improved residential environments, and higher medical standards, the demand for these services has escalated. Over the past decades, China has made strides in establishing a comprehensive system of basic public services. However, challenges persist, including inadequate supply, subpar quality and efficiency, and mismatches between supply and demand. Particularly in impoverished regions, gaps in public services—especially in areas critical to livelihoods such as social security, education, healthcare, and cultural facilities—are strikingly evident. Traditionally, public service delivery in China has relied on fiscal transfer payments and inter-local government competition [2]. However, the improvements in public services achieved through these mechanisms have fallen short of expectations when juxtaposed with the scale of investment in economic development [3]. Against the backdrop of the current socioeconomic context, exploring pathways to innovate for more effective public service delivery constitutes a critical dimension in the advancement of basic public services in China.

Against the backdrop of the widespread application of digital technologies, the development of digital government—with government digital transformation as its core manifestation—has gradually gathered momentum. By leveraging cutting-edge technologies such as artificial intelligence and big data, it has become feasible to optimize government decision-making mechanisms and elevate the efficiency of public services, which in turn opens up fresh avenues to bolster the delivery of basic public services [4]. On the one hand, digital government integrates cutting-edge information technologies into governmental administrative processes, thereby strengthening interdepartmental collaboration and dismantling bureaucratic silos [4,5]. On the other hand, by virtue of intelligent and digital solutions, government agencies can efficiently collect, process, and analyze data to revamp public service systems, deliver personalized services to citizens, and enhance governmental administrative efficiency and public credibility. Furthermore, digital government facilitates data-driven decision-making, enabling the formulation of intelligent, precise, and evidence-based governance strategies [6].

As a foundational and guiding initiative in advancing Digital China, the development of digital government has become integral to modern governance. It demonstrates distinctive characteristics within the digital ecosystem, functioning not as an isolated technological application but rather as a central hub that integrates the digital economy and digital society [7,8]. Leveraging institutional strengths in top-level design and central-local coordination, it rationalizes resource allocation and fosters systematic synergy and value co-creation across the digital ecosystem. Moreover, by balancing technological innovation with responsiveness to public needs, it channels greater resources into public services and helps address structural imbalances between the supply and demand of such services [9,10]. Existing research literature exploring the nexus between digital government implementation and public services can be categorized into two key perspectives: one point provides that digital government is an enabler or even driver of transformation of public services [11]. Digital government can enhance the effectiveness of governmental departments and optimize the delivery of public services [12,13]. However, due to “Solow Paradox”, some scholars point out that, although digital government construction expands the model of public service, it may affect the quality of public service delivery [14,15]. Therefore, existing research should further quantify and assess the effects of digital government construction on public services [16]. Assessing the performance of digital government initiatives in public service delivery constitutes a core priority for the Chinese government in advancing its digital transformation agenda. This approach also offers valuable insights for other nations engaged in the development of digital public service systems.

Based on this foundation, this paper adopts public value theory and technology empowerment theory to explain the theoretical mechanism by which digital government enhances the supply of basic public services. It further aims to verify the impact of digital government construction on the delivery of these services and to examine the moderating effects of government support, the level of digital technology development, and regional heterogeneity. The objective is to identify viable pathways for digital government construction to improve the supply of basic public services and to offer policy recommendations and practical guidance for local governments. This will help them intensify their digital government initiatives to enhance the level of basic public service delivery.

The rest of the paper is organized as follows. Section 2 reviews relevant issues about digital government and public services. Section 3 draws theoretical analysis and research hypotheses. Section 4 describes the methodology, including data collection, variables and empirical specifications. Section 5 presents the empirical results and further analysis. Section 6 concludes the paper.

2. Literature Review

2.1. Factors Affecting the Level of Basic Public Service Supply

In the context of rapid economic and social development, citizens are increasingly demanding diversified, high-quality, and personalized basic public services [17]. Investigating the factors that influence the level of basic public service delivery not only helps clarify the key drivers that enhance these service levels, but also deepens our understanding of the role that digital government construction plays in this delivery.

Local governments endowed with a higher degree of centralized administrative authority are better positioned to deliver more efficient public services. However, the involvement of too many stakeholders in the delivery of public services can lead to increased budgetary costs and reduced service efficiency [18], which is not conducive to the improvement of the level of basic public service delivery. The government’s positioning of urban functions can reshape the level of regional public service delivery. Industrial development-oriented cities, in order to attract further aggregation of industries and form a competitive environment for public service development quality with surrounding cities, aim to enhance the scale of public services to attract more enterprises to gather. However, when a cluster is formed by pollution-intensive industries, although regional health expenditure can be increased by improving medical services, its public service effect is still limited [19]. At the same time, the economic strength of the region plays a crucial role in the supply effect of basic public services. Favorable economic conditions will motivate the government to seek higher-quality basic public services, while unfavorable economic conditions will make it difficult to maintain the effective supply of public services [20,21,22]. Divergent political orientations, rooted in disparate value systems and governance objectives, give rise to distinctly differentiated public service systems. Conversely, the core attributes and delivery modes of public services exert tangible impacts on political commitments and public trust in governments.

2.2. Digital Government and Basic Public Services

Digital technology-driven government construction is widely recognized as a pivotal pathway for reshaping public service delivery modalities in the context of global governance transformation, yet scholarly consensus remains sharply divided on whether such initiatives can effectively elevate the overall quality of public service delivery. Digital technology enables government departments to shift from how to better produce public services to how to provide public services that better meet the needs of the public [23]. Moreover, digital government’s use of digital technologies such as the Internet and big data has reduced the cost of government public services and improved the efficiency of government departments at all levels, driving innovation in public services [24]. A growing body of studies demonstrates that government digital transformation, through the deep integration of digital technologies, can markedly improve public service efficiency, augment citizen participation in governance processes, and strengthen government accountability [25]; a salient illustration is China’s “One-Stop Service” reform, which leverages cross-departmental digital coordination to streamline administrative procedures and enhance the transparency of essential public service delivery [26]. However, digital technologies inherently carry dual-use risks: governments may also deploy such tools to impose restrictions, conduct surveillance, and exercise tighter control over citizens [27]. In addition, in certain developing countries where digital government initiatives lack robust institutional support systems, related undertakings often exacerbate public service supply imbalances by diverting resources of technology-centric investments, with over-optimistic political expectations, stakeholder conflicts, and budgetary constraints [28].

This divergence primarily stems from two core limitations of existing research: first, most studies focus on macro-level normative evaluations, which lack large-scale empirical analyses to verify the boundary conditions governing the effectiveness of digital government in different institutional contexts; second, there is a lack of in-depth exploration into the micro-mechanisms through which digital technologies drive improvements in public service delivery. While a subset of studies grounded in collaborative governance theory has highlighted the value of digital platforms in facilitating citizen-to-government (C2G) collaboration [29], optimizing service supply structures by accurately capturing public demand preferences, and advancing the viability of platform-based governance models [30], the current research remains confined to isolated case studies or fragmented thematic explorations.

3. Theoretical Analysis and Research Hypotheses

The core essence of digital government resides in facilitating the deep integration of social governance and public services through the in-depth mining and value conversion of data resources. Its ultimate goals encompass three dimensions: enhancing governance efficiency, advancing public welfare, and fostering the coordinated development of industries [31,32]. The traditional bureaucratic governance model is plagued by a dual structural predicament. On the one hand, governments are afflicted by information asymmetries in identifying public demands, which gives rise to mismatches between the supply of public services and actual societal needs [2]. On the other hand, pervasive inter-departmental “information silos” and administrative barriers impede the efficiency of collaborative resource allocation, ultimately culminating in governance bottlenecks marked by the low quality and inefficiency of basic public service delivery [33].

To address the structural predicament, this paper constructs a theoretical framework for advancing public service delivery via digital government initiatives, adopting public value theory and technological empowerment theory as core analytical paradigms to explicate the underlying mechanisms. Public value theory prioritizes public needs and social welfare, positing that government’s core function is to create and enhance public value through efficient public resource allocation and service delivery optimization [34]. Within the context of digital government and public service integration, this theory establishes a benchmark for examining the value essence of digital government development—that is, digital government empowers public services essentially by restructuring the public value production chain and elevating supply efficiency through digital technologies [35]. Technological empowerment theory focuses on the interaction between digital technologies and governance practices, emphasizing that digital technology is not merely a tool-based carrier but a core variable permeating government governance’s organizational forms, process architectures, and service modalities. By dismantling information barriers, optimizing resource allocation efficiency, and innovating government-citizen interaction mechanisms, digital technology provides endogenous momentum for advancing governance capabilities. This theory offers a core analytical perspective for understanding how digital government influences public services: leveraging digital technology’s enabling effects, digital government resolves structural dilemmas in traditional public service delivery and drives a paradigm shift in service delivery from a government-led supply orientation to a public demand orientation [36].

Drawing on theoretical analysis, the pathways through which digital government enhances public service delivery can be specifically decomposed into the following three dimensions:

Firstly, digital government enhances organizational change capacity. As an effective strategic tool for public management reform, digital government breaks traditional information channels, achieving the separation of institutional structure and work structure within government organizational structures, creating new work structures and collaboration models [37]. By adjusting and allocating resources using digital technologies, digital government facilitates interaction between different departments to achieve resource sharing and business collaboration. Therefore, digital government construction enables governments to break away from fragmentation in organization and processes, reconstruct public governance processes centered on public needs, integrate resources scattered across various departments and organizations, and avoid information silos.

Secondly, digital government provides the capacity for innovative public services. Digital government is a prerequisite for achieving digital governance, capable of reducing transaction costs at all levels of government, and shifting from bureaucracy-centered services to customer-centered services to meet citizens’ expectations. It is seen as a means to restore public trust and improve service quality [38]. Relying on government platforms, it offers services such as data mining, cleaning, integration, analysis, visualization, and secure management, providing intuitive and visual data support for scientific decision-making, personalized services for the public and enterprises, and integrated data resources for government staff to achieve collaborative office work, enhancing the work efficiency of government personnel.

Thirdly, digital government construction is an essential pathway to change traditional decision-making methods and improve scientific decision-making capabilities. The digital literacy of public officials directly dictates the decision-making efficacy of digital governments by empowering them to harness data tools for information value mining and elevate the quality and efficiency of data-to-decision conversion [39]. By employing advanced information technologies such as artificial intelligence, big data, and blockchain, digital government can grasp a vast array of scientific data, potentially bringing new research insights, promoting economic development, and providing information for decision-making and policy formulation, generating new policies beneficial to government services and the public [40]. Using modern data technology to collect, analyze, and judge data enables governments to formulate more precise decision-making mechanisms, greatly enhancing the accuracy, scientific nature, and foresight of decisions, supporting better government decision-making [41]. Based on this, the paper proposes the following hypothesis:

H1. 

Digital government construction has a significant promoting effect on the level of basic public service supply.

Digital government applies digital technology to achieve organizational transformation and ultimately enhance the delivery of basic public services. Therefore, in this process, it is inevitably regulated by the level of development of digital technology.

In areas with a higher level of digital technology development, channels of interaction between citizens and the government have been established [42], thereby digital technology aids in the precise delivery of public services. Digital technology effectively addresses the discrepancies between public services and the actual needs of the public, integrating fragmented and diverse demand information, proactively identifying public needs, and providing precise demands, thus maximizing social welfare.

Digital technology can enhance the government’s ability to transform its organization. The latest developments in information and communication technology innovation can affect the internal logic and structure of bureaucratic organizations, thereby changing governance processes through the government [43]. Digital technology has achieved “network connectivity”, “data connectivity”, and “business connectivity”, solving the problem of cross-regional and cross-departmental verification of key data at the technical level. After this, many approval processes have gradually shifted from single-operation processes to collaborative interaction processes. Once business processes are fully digitized, the cost of flexibly adjusting business processes according to business needs will also be greatly reduced. Many places have implemented services such as “only run once”, “one thing done at a time” and “one network for all affairs”, which are vivid examples of process optimization driven by technological change. In areas with lower levels of digital technology development, there is a lack of channels for citizens to directly participate in political activities, making it difficult for government departments to collect citizens’ genuine thoughts and needs, leading to issues of resource waste and irrational resource allocation. Moreover, government departments have cumbersome administrative processes and low efficiency; the internal organization of the government is relatively closed, which is not conducive to information data sharing and resource integration, leading to widespread issues of sectoral division and information barriers between government departments at all levels. Based on this, the article proposes the following hypothesis:

H2. 

Digital technology can significantly promote the impact of digital government construction on the level of basic public service delivery.

The development level of digital government hinges on governmental supportive commitment, which embodies the integration of public value into the government’s policy implementation processes. If there is a lack of sufficient resources and capabilities to build a digital government or if the government is unwilling to invest financial resources in building a digital government, even with good technical conditions, it is difficult for digital government construction to make progress. Purvis points out that senior leaders can manipulate the institutional structure of meaning, legitimization, and domination, thereby influencing or changing individual structural behavior [44]. For example, senior leaders can clarify a new organizational vision, treating information technology as an organizational strategy. This creates a new structure of meaning, causing individuals to begin to recognize the strategic connection between information technology and organizational business. Similarly, senior leaders can express a positive attitude towards information technology, strengthening government departments at all levels in the use of information technology, thereby improving the level of basic public service delivery. Secondly, government organizational change and innovation in public services require the support of government legitimacy. In the public sector, especially within government agencies, the willingness of grassroots governments to innovate development to some extent depends on the financial and policy support that higher-level departments can provide, which is also the case in digital government construction. If government support can be obtained, then more financial and resource construction of digital government can be achieved, thereby promoting organizational change and innovation in public services. In areas with lower levels of government support, digital government construction is not valued, there are information barriers between government departments, which are not conducive to message flow and thus hinder cooperation and communication between departments; and the government and citizens are in a one-way output, with a problem of information asymmetry between supply and demand, therefore, it is not conducive to organizational change and innovation in public services. Based on this, the article proposes the following hypothesis:

H3. 

The level of government support can significantly promote the impact of digital government construction on the level of basic public service delivery.

4. Research Analysis

4.1. Sample Selection and Data Sources

This paper selects panel data from 31 provinces from 2017 to 2021 as the sample to examine the impact of digital government construction on the level of basic public service delivery. Due to data availability, this paper only selects data from 2017 to 2021. Based on the three major economic regions of China, this paper analyzes the eastern, central, and western regions. Due to data missing issues, the selected sample does not include Hong Kong, Macau, and Taiwan.

The main sources of data collection for this paper are the “China City Statistical Yearbook,” the “China Statistical Yearbook,” and the “Survey and Evaluation Report on the Online Government Service Capacity of Provincial Governments and Key Cities” published by the Electronic Government Research Center of the Party School of the Central Committee of the Communist Party of China (National School of Administration). To better handle missing values in the sample, first, missing data are supplemented by consulting relevant statistical yearbooks; for some data that cannot be supplemented in the yearbooks, a simple interpolation method is used to fill them in.

4.2. Model Specification and Variable Definition

To test the impact of digital government construction on the level of basic public service supply, the least squares method is employed, and the following regression model is specified:

$${Level}_{i,t}={\alpha }_0+{\alpha }_1{Gov}_{i,t}+{\alpha }_2{SFE}_{i,t}+{\alpha }_3{Open}_{i,t}+{\alpha }_4{IL}_{i,t}+{\alpha }_5{UR}_{i,t}+{\alpha }_6{PGpc}_{i,t}+{\epsilon }_{i,t}$$

(1)

In the model, the variables are defined as follows:

(1)

Explanatory Variable: Level of Basic Public Service Delivery (Level)

Based on a scientific understanding of the connotation of the level of basic public service delivery and the prevailing practices in existing research [45], this paper uses 5 first-level indicators and 15 second-level indicators, including basic education services, basic medical services, social security services, public cultural services, and infrastructure services, as shown in

Table 1. Measurement indicators of the supply level of basic public services.

Variables	Primary Index	Secondary Index	Calculation Formula
Level of Basic Public Service Delivery (Level)	Basic education service	Number of students enrolled in primary schools	Number of primary school students/year-end resident population
		Number of full-time teachers in primary schools	Number of full-time primary school teachers/year-end resident population
		Number of primary schools	Number of primary schools/year-end resident population
	Basic medical service	Number of health institutions	Number of health institutions/resident population at year end
		Number of personnel in health facilities	Number of staff in health institutions/resident population at year-end
		Number of beds in health institutions	Number of beds in health institutions/year-end resident population
	Social security service	Participation rate of basic medical insurance	Number of medical insurance enrollees/year-end resident population
		Old-age insurance participation rate of urban residents	Number of old-age insurance participants for urban residents/permanent residents at the end of the year
		Unemployment insurance participation rate	Number of residents participating in unemployment insurance/permanent residents at the end of the year
	Public cultural service	Number of pieces in museum collections	Number of museum pieces/permanent resident population at the end of the year
		The number of books in the library	Library holdings/annual resident population
		Radio and television industry coverage	Number of radio and television industry coverage/year-end resident population
	Infrastructure services	Railway mileage	Railway mileage/year-end resident population
		Number of civilian cars owned	Number of civilian cars owned/permanent resident population at the end of the year
		Total volume of post and telecommunications services	Total business volume of posts and telecommunications/resident population at the end of the year

.

(2)

Core Explanatory Variable: Digital Government Construction (Gov)

Measurement criteria for digital government development exhibit notable heterogeneity. To gauge the development level of digital government, this paper adopts the assessment findings from “the Provincial Governments and Key Cities Online Government Service Capability Survey and Evaluation Report” issued by the Chinese National Academy of Governance; rooted in the United Nations Global E-Government Assessment System, this report provides an accurate reflection of the digital government development level among local governments in China. This paper sets the online government service capability as a virtual variable, assigning a value of 1 for capabilities above 90 points, a value of 2 for capabilities between 80 and 90, and a value of 3 for capabilities between 65 and 80.

(3)

Moderating Variables

Government support and digital technology are identified as moderating variables in this study, with the former operationalized as the ratio of per capita local general public budget expenditure to regional gross domestic product (GDP), and the latter operationalized as the ratio of regional mobile internet users to the annual average resident population.

(4)

Control Variables

Five control variables are selected from the dimensions of population, politics, economy, ecology, and infrastructure: urbanization rate, degree of openness to foreign trade, fiscal expenditure scale, per capita park green space area, and infrastructure level. The specific measurement methods are shown in

Table 2. Description of variables.

Variables	Variable Name	Description of Variables
Explanatory Variable	Level of Basic Public Service Delivery (Level)	The entropy method measures the value
Core Explanatory Variable	Digital Government Construction (Gov)	Online government service capability
Control Variables	Degree of Openness to Foreign Trade (Open)	Total imports and exports/Gross regional product
	Urbanization Rate (UR)	Urban population/total population
	Fiscal Expenditure Scale (SFE)	General public budget expenditure/total population
	Per Capita Park Green Space Area (PGpc)	Per capita green park area
	Infrastructure Level (IL)	Highway km/total population
Moderating Variables	Government Support (Support)	Per capita local general public budget expenditure/gross regional product
	Digital Technology (Technology)	Mobile Internet users/annual average population in the region

.

5. Empirical Analysis

5.1. Descriptive Statistics of Variables

The results of the descriptive statistics are shown in

Table 3. Descriptive statistical analysis.

Variables	Sample Size	Mean Value	Standard Deviation	Minimum Value	Maximum Value
Level of Basic Public Service Delivery (Level)	155	0.080	0.027	0.045	0.288
Digital Government Construction (Gov)	155	1.865	0.712	1.000	3.000
Degree of Openness to Foreign Trade (Open)	155	0.362	0.361	0.008	3.297
Fiscal Expenditure Scale (SFE)	155	17,706.490	12,139.520	4363.612	91,155.830
Urbanization Rate (UR)	155	59.406	11.878	33.380	89.300
Infrastructure Level (IL)	155	0.005	0.007	0.001	0.043
Per Capita Park Green Space Area (PGpc)	155	5.491	2.652	0.731	16.635
Digital Technology (Technology)	155	0.403	0.187	0.173	1.372
Government Support (Support)	155	0.286	0.202	0.002	1.283

. From this, it can be observed that the maximum value of the explained variable, the level of basic public service delivery, is 0.288, and the minimum value is 0.045, with a standard deviation of 0.027. The relatively small average value and standard deviation indicate a significant disparity in the level of basic public service delivery across different regions in China. The mean value is only 0.080, which reflects that the basic public service delivery level in various areas of China is relatively low. The core explanatory variable, digital government construction, has an average value of 1.865 and a standard deviation of 0.712. The large standard deviation indicates that there are differences in digital government construction among different regions. The statistical results of the other variables are all within reasonable ranges and will not be described again.

5.2. Analysis of Baseline Regression Results

This paper employs the least squares method to test the net effect of digital government construction on the level of basic public service supply.

Table 4. Regression results of the benchmark model.

	Model 1	Model 2
	Level	Level
Gov	0.007 **	0.010 ***
	(2.150)	(3.930)
Open		0.010 **
		(2.060)
UR		−0.001 ***
		(−3.990)
IL		1.522 **
		(2.340)
SFE		0.000
		(0.700)
PGpc		0.005 ***
		(5.520)
_cons	0.068 ***	0.057 ***
	(11.370)	(5.740)
R2	0.029	0.493
adj.R2	0.023	0.473
F	4.626	24.010

Note: ** p < 0.05, *** p < 0.01. Parentheses report standard errors (N = 155).

presents the regression results of the baseline model. Model 1 includes only the core explanatory variable, and the estimated coefficient of digital government construction (Gov) is significantly positive at the 5% statistical level, indicating that digital government construction significantly drives the improvement of the level of basic public service supply. Model 2 adds control variables on the basis of Model 1. The estimated coefficient of digital government construction (Gov) is significantly positive at the 1% statistical level, and the pseudo-R-squared, which measures the overall model fit, increases from 0.023 to 0.473. This suggests that after including more control variables, the estimated coefficient of digital government construction on the level of basic public service supply becomes more robust. The reason may be that the extensive application of digital government construction within organizations has strengthened the communication and information interaction between government organizations, thereby enhancing the government’s ability to transform. Digital government enhances the government’s proactive response to people’s welfare needs and helps the government accurately identify the diverse and heterogeneous public demand preferences of the social public, reducing the information asymmetry between the government and the social public. In addition, digital government can use digital technology to enable a “top-down” and “bottom-up” two-way interactive mechanism between the government and the public, enhancing citizens’ trust in the government and political identification with public service decision-making, thereby improving the quality of basic public service supply.

In terms of control variables, the level of infrastructure has a significant positive impact on the level of basic public service supply, indicating that the level of infrastructure (IL) can improve the conditions of production and life, create high-quality living spaces for the social public, meet the people’s needs for a better life, and thus enhance the level of basic public service supply. The degree of openness to the outside world (Open) has a significant positive effect on the level of basic public service supply, indicating that the degree of openness can increase the government’s opportunities to learn from advanced regions, absorb practices from other regions to improve the level of basic public service supply, pay more attention to the investment in basic public services such as education, healthcare, and social security, and thereby improve the level of basic public service supply. The per capita area of urban green space (PGpc) has a significant positive impact on the level of basic public service supply, indicating that the ecological environment couples ecosystem services with human well-being, and is an important way to improve the living environment and people’s livelihoods. This means that the higher the per capita area of urban green space, the more conducive it is to providing residents with rich ecosystem services, which helps to improve the quality of life for residents, promote the physical and mental health of residents, and thereby help to improve the level of basic public service supply. However, the urbanization rate (UR) has a negative effect on the level of basic public service supply, which may be due to the fact that urbanization brings about the aggregation of the population, the more urban population, the more complex the personnel, increasing the difficulty for the government to provide basic public services accurately, increasing the cost of basic public service supply, thereby producing a negative effect of the urbanization rate on the level of basic public service supply. The scale of fiscal expenditure (SFE) did not have an impact on the level of basic public service supply, which may be due to the impact of various factors, the government is facing the problem of fiscal expenditure reduction, thereby suppressing the role of the scale of fiscal expenditure in promoting the level of basic public service supply. This has effectively verified Hypothesis 1.

5.3. Robustness Test

This section primarily examines the endogeneity issues of the model and whether the model is robust. In the research of this paper, endogeneity issues are present and inevitable. Theoretically, this paper may face issues such as omitted variables, reciprocal causality between variables, and dynamic panels. To address these potential issues, this paper sequentially employs the instrumental variable method and the system GMM to resolve endogeneity. Considering the difficulty in finding suitable instrumental variables, this paper uses the lagged value of the economic development level as the instrumental variable.

Table 5. Robustness test results.

Variables	(1)	(2)	(3)	(4)
	2SLS		GMM System	Robustness Test
	The First Stage	The Second Stage	Level	Level-1
L.Level			−0.430 (0.575)
Gov		0.013 *** (0.005)	0.019 * (0.011)	0.019 *** (0.005)
L.Gov	0.608 *** (0.064)
Open	0.351 *	0.014	0.031	0.016
	(0.196)	(0.009)	(0.020)	(0.012)
UR	0.000	−0.001 ***	0.000	−0.001 ***
	(0.004)	(0.000)	(0.002)	(0.000)
IL	−8.408	0.000	6.370	3.003 **
	(16.906)	(0.000)	(5.608)	(1.412)
SFE	−0.000	0.000 ***	−0.000	0.000
	(0.000)	(0.000)	(0.000)	(0.000)
PGpc	0.021	0.003 ***	0.007	0.010 ***
	(0.022)	(0.001)	(0.009)	(0.002)
_cons	0.736 ***	0.067 ***	0.006	0.122 ***
	(0.262)	(0.013)	(0.101)	(0.022)
N	124	124	124	155
R2	0.595	0.454	-	0.494

Note: * p < 0.1,** p < 0.05, *** p < 0.01. Parentheses report standard errors.

, column (1), presents the results of the first-stage regression, where the coefficient of L.Gov is significantly positive, indicating that the instrumental variable for digital government construction meets the relevance requirement. According to the results in column (2), the coefficient of Gov is 0.013 and is significant at the 1% level, indicating a positive correlation between digital government construction and the level of basic public service supply. The two-stage least squares (2SLS) regression yields essentially consistent results with the benchmark regression. Considering the lag effect between digital government construction and the level of basic public service supply, where there is a dynamic influence from the previous period’s level on the current period, this paper utilizes the system GMM for estimation, with a specific lag period of 1 period, and column (3) shows the results of the system GMM with a lag of 1 period. Among them, the AR(2) p-value is 0.422, indicating that the model does not have second-order autocorrelation, and the p-value of the Hansen test is 0.593, greater than 0.1, indicating that all instrumental variables in the model are valid. As shown in Table 5, column (3), there is still a significant positive correlation between digital government construction (Gov) and the level of basic public service supply (Level), indicating that using the system GMM model for estimation yields results consistent with the benchmark regression. Finally, this paper changes the measurement method of the level of basic public service supply by using principal component analysis to obtain a comprehensive score of basic public service supply, Level-1, and uses it to replace the explained variable of the level of basic public service supply in the regression. The coefficient of Gov remains significantly positive, indicating that digital government construction has a promoting effect on the level of basic public service supply.

5.4. Heterogeneity Analysis

5.4.1. Government Support Heterogeneity

Existing research indicates that the greater the level of government support, the higher the level of digital government construction. Therefore, differences in the degree of government support may lead to heterogeneity in the impact of digital government construction on the level of basic public service supply. To test the impact of digital government construction on the level of basic public service supply in areas with different levels of government support, the regions are divided into those with high and low government support based on the average level of government support. Empirical verification is conducted separately, and the results are shown in

Table 6. Heterogeneity analysis.

	Government Support		Digital Technology
	Low	High	Low	High
	Model (1)	Model (2)	Model (3)	Model (4)
	Level	Level	Level	Level
Gov	0.007 **	0.012 ***	0.007 *	0.012 ***
	(2.040)	(4.170)	(1.830)	(4.950)
Open	0.021 **	0.002	0.010 *	0.015 *
	(2.180)	(0.360)	(1.740)	(1.980)
UR	−0.001 ***	−0.000	−0.001 ***	0.000
	(−3.170)	(−1.380)	(−3.000)	(0.710)
IL	2.489 ***	0.326	2.322 **	0.767
	(2.810)	(0.330)	(2.610)	(0.820)
SFE	7.200	0.000	−0.000	0.000 *
	(0.160)	(1.240)	(−0.420)	(1.700)
PGpc	0.005 ***	0.002	0.007 ***	−0.002
	(4.470)	(1.320)	(5.390)	(−1.070)
_cons	0.060 ***	0.050 ***	0.058 ***	0.032 **
	(4.330)	(3.700)	(3.980)	(2.670)
N	100	55	102	53
R2	0.537	0.541	0.537	0.498
adj.R2	0.508	0.483	0.508	0.433
F	18.010	9.417	18.390	7.610

Note: * p < 0.1,** p < 0.05, *** p < 0.01. Parentheses report standard errors.

, Models (1) and (2). The results show that, in areas with low or high government support, the estimated coefficient of digital government construction is significant at the 5% and 1% levels, respectively, at 0.007 and 0.012. This indicates that digital government construction promotes the level of basic public service supply under different levels of government support. The reason may be that government support can enhance the use of information technology across departments and bring financial and policy support to digital government construction, which is conducive to organizational change and innovation in public services in the government, thereby strengthening the relationship between digital government construction and the level of basic public service supply. This implies that increasing government attention to digital government construction can help improve the basic public service supply level in the region. This strongly validates Hypothesis 3.

5.4.2. Digital Technology Heterogeneity

To test the impact of digital government construction on the level of basic public service supply in regions with different levels of digital technology development, the regions are divided into those with high and low levels of digital technology development based on the average level of digital technology development. Empirical verification is conducted separately, and the results are shown in Table 6, Models (3) and (4). The results show that, in areas with low or high levels of digital technology development, the estimated coefficient of digital government construction is significant at the 10% and 1% levels, respectively, at 0.007 and 0.012. This indicates that digital government construction promotes the level of basic public service supply under different levels of digital technology development. The reason may be that digital technology broadens the channels for public participation, allowing the public to choose their own ways to interact with the government. This disrupts the traditional top-down behavior pattern, truly achieving two-way communication between citizens and the government. Moreover, digital technology reduces information asymmetry between the government and the public, improving the accuracy, matching, and scientific nature of government basic public service supply. Furthermore, digital technology, by using “data to speak,” has shifted from empirical judgment to scientific decision-making. This implies that improving the level of digital technology development can enhance the promoting effect of digital government construction on the level of basic public service supply. This strongly validates Hypothesis 2.

5.5. Further Analysis

The previous sections have examined the positive impact of digital government construction on the level of basic public service supply. However, it is still worth further exploring whether there are differences in the heterogeneous effects of basic public service supply level under different economic development levels. To this end, this paper further divides the entire sample into three sub-samples based on different levels of economic development and analyzes whether the positive effect of digital government construction on the level of basic public service supply will differ across samples.

This section, following the division of China’s three major economic regions, conducts empirical analysis separately for the eastern, central, and western regions, with the results shown in

Table 7. Regional heterogeneity.

	East	Middle	West
	Model (1)	Model (2)	Model (3)
	Level	Level	Level
Gov	0.010 ***	0.006	0.003
	(3.470)	(1.380)	(0.540)
Open	0.001	0.004	0.023
	(0.460)	(0.620)	(1.180)
UR	−0.001 ***	0.001 **	−0.003 **
	(−3.650)	(2.120)	(−2.540)
IL	2.133	2.455	3.307
	(0.560)	(1.270)	(0.630)
SFE	0.000 *	−0.000	−0.000
	(1.900)	(−1.510)	(−0.490)
PGpc	0.005 ***	0.002	0.011 **
	(5.260)	(0.390)	(2.200)
_cons	0.069 **	0.040 **	0.173 ***
	(2.430)	(2.470)	(3.000)
N	55	40	60
R2	0.775	0.403	0.490
adj.R2	0.747	0.294	0.433
F	76.920	7.684	6.443

Note: * p < 0.1,** p < 0.05, *** p < 0.01. Parentheses report standard errors.

. The results indicate that, in the eastern region, the estimated coefficient of digital government construction is 0.010, which is significantly positive at the 1% level, while the coefficients in the central and western regions do not pass the significance test. This suggests that digital government construction has a promoting effect on the level of basic public service supply in the economically developed eastern region, while its effect is not significant in the less developed central and western regions. The reasons may be as follows: First, the economy is the material basis for improving basic public service supply. Raising the level of economic development can enhance the local government’s ability to pay for basic public services, increase fiscal revenue, and thus further improve the level of basic public service supply [46]. The increase in fiscal revenue is conducive to the government investing more funds in the construction of digital government, thereby increasing the level of basic public service supply. Second, economic development can drive scientific and technological progress and promote the rapid development of the digital economy. With the trend of information networking and digitization, digital services develop rapidly, and the government can provide higher-level basic public services to the public in more advanced ways, reducing unnecessary resource waste in the supply of basic public services and facilitating the emergence of new service models [47]. Compared to the eastern region of China, the central and western regions are relatively economically backward, and local governments are more eager to achieve economic catch-up. This economic catch-up pressure (i.e., economic growth pressure) makes them more inclined to invest fiscal funds in economic construction fields, hoping to quickly promote regional economic growth in the short term and achieve better political achievements. This weakens the impact of digital government on the level of basic public service supply. This means that, in regions with a higher degree of economic development, digital government construction can better promote the improvement of the level of basic public service supply.

6. Conclusions and Recommendations

Drawing on provincial-level panel data for China spanning the period 2017–2021, this study conducts an empirical examination of the impact exerted by digital government development on the delivery of basic public services. The findings reveal that digital government initiatives exert a more pronounced facilitating effect on basic public service delivery against the backdrop of sophisticated digital technology development and robust government support, with such impacts demonstrating significant regional heterogeneity. Building on these findings and integrating the public value theory and technology-enabled governance theory, this paper puts forward targeted policy recommendations tailored to the differentiated developmental realities of various regions.

First, deepen technological empowerment to unleash the public value of digital governance. With technological empowerment as the core orientation, advance the transformation of digital government from tool application to value creation. Establish cross-regional and cross-departmental data sharing and governance mechanisms to eliminate data silos, and convert public welfare-related data into evidence-based foundations for public service decision-making. Harness big data analytics to achieve precise matching of service supply and demand, thereby enhancing the equity and adaptability of public services. Leverage emerging technologies including artificial intelligence and blockchain to optimize service delivery processes, construct a streamlined service system, and strengthen two-way interaction between the government and citizens to elevate the level of public engagement. Attach priority to digitally vulnerable groups, adjust technological applications and expand service coverage to narrow the digital divide, and ensure the equitable distribution of digital dividends across regions and population groups, thus embodying the equity attribute of public services.

Second, optimize governmental support mechanisms to consolidate the foundation for digital government development. With governmental backing as a fundamental safeguard, provide institutional and resource guarantees for technological empowerment. Integrate digital government into the core framework of regional development strategies, improve laws and regulations on data security and service standards, and refine performance evaluation systems. Incorporate public value creation and technological empowerment outcomes into assessments to guide governments in enhancing service quality and efficiency. Optimize fiscal allocation based on inter-regional disparities, prioritizing support for digital infrastructure, technological R&D, and talent cultivation. Implement targeted transfer payments and cross-regional assistance to address deficiencies in less developed regions. Establish cross-regional collaboration mechanisms to facilitate the circulation of advanced technologies and mature practices, optimize public service resource allocation, and elevate overall economies of scale and public value returns.

Third, establish differentiated empowerment pathways based on regional disparities. Tailor development strategies to align with each region’s technological foundation and service demands. Technologically advanced regions should focus on innovation and upgrading, leveraging digital advantages to explore cutting-edge applications, promote the transformation from supply-oriented to demand-responsive services, and construct personalized and intelligent service systems as demonstration models. Regions with moderate foundations should prioritize addressing deficiencies by expanding digital infrastructure coverage, leveraging technology to break down departmental barriers, standardizing and improving the accessibility of basic services, and gradually narrowing the gap with developed regions. Underdeveloped regions should first ensure the digitization of basic services, utilize technology to mitigate resource constraints, establish streamlined and efficient service models, guarantee equitable access to basic public services, and lay the foundation for subsequent development.