Impact of Green Technology Innovation on Green Economy: Evidence from China

Abstract

The impact of green technology innovation and the digital economy on the sustainability of the green economy is increasing. To delve deeper into this subject, this paper utilizes fixed- effect models and threshold effect models. It examines data from 34 provincial administrative regions of China. The aim is to uncover the patterns of influence the green technology innovation and the digital economy have on the sustainability of the green economy. The research findings are as follows: (1) The green technology innovation, digital economy, and their interaction contribute to promoting the high-quality sustainability of the green economy. The sustainability of the green economy relies on the support of green technology innovation and the digital economy. By optimizing the capabilities of green technology innovation and the level of digital economy, managers could enhance the high-quality sustainability of the green economy. (2) The digital economy exhibits a dual threshold effect in driving the sustainability of the green economy through green technology innovation. When the digital economy surpasses the first threshold, the influence of green technology innovation on the green economy experiences a notable increase. However, once the digital economy surpasses the second threshold, the impact of green technology innovation on the green economy begins to diminish significantly. (3) There are notable regional variations in the impact of green technology innovation and digital economy on the sustainability of the green economy across different regions of China. Considering these findings, it is vital for stakeholders in China to implement customized measures. These measures should aim to actively promote the sustainability of China’s green economy. The relevant stakeholders include businesses and the government.

1. Introduction

In the report of the 20th National Congress of the Communist Party of China, it is proposed that China should expedite the sustainability of the digital economy. China also should foster the profound integration of the digital economy with the real economy and advance the growth of the green economy. At the same time, the sustainability of the green economy and digital economy has emerged as a crucial aspect of China’s ongoing economic progress. Digital economy refers to the economic form based on digital technology and information technology. It is an economic form that promotes economic development, transformation, and upgrading through digital, networked and intelligent means [1]. Consequently, scholars have shifted their focus toward studying green technology innovation, the digital economy, and the green economy within this framework. Data released by the Chinese Academy of Information and Communications Technology reveal that the cumulative value added by the digital economy reached a staggering 38.1 trillion US dollars in 2021 [2]. This value represents 47 prominent nations worldwide and accounts for a noteworthy 45% of their respective GDP. Among them, China’s digital economy reached a staggering 7.1 trillion US dollars, representing over 18% of the total across 47 countries and ranking as the world’s second-largest [3]. At present, the progress of China’s digital economy is advancing rapidly, demonstrating a broad scope of impact and profound influence. It has bestowed upon economic and social development a plethora of “novel catalysts and newfound benefits”, ushering in a transforming era. Additionally, amidst the backdrop of the imperative goals of “carbon peaking” and “carbon neutrality”, it is crucial to further enhance the overall magnitude of green technology innovation in China. Simultaneously, assuring the sustainability of the green economy remains a paramount focus within China’s prospective economic advancement. However, China’s green economy is still in its nascent stage, prompting an increasing number of scholars to delve into the study of its sustainability. Furthermore, the emergence of new challenges is gradually surfacing, warranting attention.

Additionally, the relationship between the digital economy, green technology innovation, and the green economy has still not been studied systematically. The relevant research lacks a certain depth. However, there are relatively many scholars studying the digital economy. However, there is not much literature on combining the digital economy and the green economy. In particular, there are fewer scholars who have studied the relationship between the digital economy and the green economy in different regions [4]. To address these challenges comprehensively, this paper will employ empirical techniques such as the fixed effect model and the threshold effect model. By leveraging data from 34 provincial administrative regions of China, the authors aim to offer valuable insights that could serve as a significant reference for advancing the sustainability of the green economy within the country.

The objectives of this paper are as follows: (1) The primary objective of this paper is to investigate the direct correlation between green technology innovation, the digital economy, and the green economy. The intricate relationship among green technology innovation, digital economy, and green economy necessitates an in-depth examination using relevant data. By doing so, this paper seeks to elucidate the underlying direct impacts of these factors, presenting crucial insights for decision-makers in devising effective management strategies. (2) This paper will unveil the patterns of green technology innovation influence on the green economy, taking into account the dual threshold effect model. With varying threshold levels, the interplay between variables could exhibit notable distinctions. Thus, this paper endeavors to investigate the distinct characteristics of green technology innovation impact on the green economy within the framework of different threshold levels of the digital economy. (3) Our objective is also to unveil the dynamic interplay among green technology innovation, the digital economy, and the green economy across diverse regions. Given China’s expansive geographical expanse, digital economy, the capacity of green technology innovation, and the sustainability of the green economy could exhibit considerable regional disparities. This paper will systematically illuminate the intricate connections among these three factors within varying regional contexts.

The marginal contribution of this paper is as follows: (1) This paper extends the scope of research on green economy by incorporating digital economy variables into both the theoretical and empirical models. Thus, it investigates the impact of the digital economy on green technology innovation. Previous studies have seldom included this variable, making it an important contribution in broadening the research object of green economy [5]. (2) The research content of green economy has been enriched. The investigation focuses on examining the moderating effect of the digital economy on the relationship between green technology innovation and the green economy [6]. Additionally, the authors take into account several additional control variables, such as the level of marketization, the industrial composition, and the human capital magnitude. As a result, it further enhances the breadth of relevant research on the green economy [7]. (3) The application range of empirical analysis methods, such as the threshold model, is expanded. Previous studies have rarely employed the fixed effect model and the threshold effect model to investigate similar issues [8,9]. Thus, the authors serve to broaden the scope of application for these empirical research methods. (4) This paper introduces innovative management recommendations aimed at fostering the long-term viability of China’s green economy. These suggestions offer valuable insights and serve as crucial guidance for effectively advancing the sustainability of the green economy in China [10,11].

The subsequent research arrangements for this study are as follows: (1) Literature review: this section primarily encompasses a comprehensive synthesis of the scholarly literature in relevant domains, including the correlation between the digital economy and the green economy, the interplay between the digital economy and the sustainability of the green economy, and the association between green technology innovation and the sustainability of the green economy; (2) research hypothesis: this section primarily formulates the conjectured correlation among green technology innovation, the digital economy, and the green economy, and moreover, this paper constructs the conceptual framework; (3) methodology: this section encompasses the development of an empirical model, selection of variables and indices, sample selection and data acquisition, as well as multi-correlation analysis; (4) results: this section comprises the initial regression outcomes, analysis of threshold effects, robustness testing, and additional analyses; and (5) conclusions, policy implications, limitations, and future research directions: this portion primarily encompasses the conclusions of the study, policy implications, research limitations, and future research directions.

2. Literature Review

2.1. Relationship between the Digital Economy and Green Economy

Some researchers have established that there exists an intricate and dynamic correlation between the digital economy and the green economy [12]. The digital economy plays a significant role in fostering the sustainability of digital industrialization and the digitization of various industries by gauging the magnitude of the digital economy. By facilitating the profound amalgamation of digital technology with sectors, the digital economy enables the deep integration of these industries. Consequently, the sustainability of the digital economy contributes to the overall sustainability of various sectors [13]. In contrast, the green economy represents a novel economic paradigm with a market-oriented approach. It is rooted in the foundations of the traditional industrial economy and is dedicated to achieving a harmonious balance between economy and environment. It embodies a sustainable state that emerges from the industrial economy, catering to the imperative requirements of environmental preservation and human well-being [14]. Consequently, the sustainability of the green economy relies on the bolstering of advanced and emerging technologies, particularly in the realm of green technology innovation. However, the digital economy plays a vital role in providing a crucial technological foundation [15]. In this context, a multifaceted and dynamic interconnection emerges between the digital economy and the green economy, forming a complex relationship of mutual influence and dependence.

Moreover, the sustainability of the digital economy serves as a significant assurance for the sustainability of the green economy across various dimensions. The digital economy plays a pivotal role in providing crucial information technology support for the ongoing sustainability efforts of the green economy. The sustainability of the digital economy actively accelerates the pace of the sustainability of green economy endeavors, fostering a synergistic advancement towards shared environmental and economic goals [16]. The digital economy possesses the capability to enhance the efficient allocation of diverse societal resources. Thus, when considering the elements and resource allocation of the green economy, the digital economy plays a pivotal role in effectively optimizing the various resources essential for the green economy [17]. By successfully optimizing the myriad resources involved in the sustainability of the green economy, a positive impetus is generated, fueling the sustainability of the green economy itself [18]. Moreover, given the dynamic nature of the digital economy, the sustainability of the green economy undergoes significant transformations. This interconnectedness remains dynamic and enduring. It is necessary to explore the complex processes by which the digital economy affects the sustainability of the green economy [19].

2.2. The Relationship between Green Technology Innovation and Green Economy

The green technology innovation holds the potential to offer crucial technical support to bolster the green economy [20]. Green technology innovation constitutes a form of technological innovation that adheres to ecological principles and the laws of ecological economics [21]. The innovative endeavors within green technology are aimed at conserving resources and energy while preventing, mitigating, or minimizing pollution and ecological damage [22]. Green technology innovation encompasses a broad spectrum of “pollution-free” or “pollution-less” technologies and products that strive to minimize adverse ecological impacts [23]. Furthermore, the process of the green economy necessitates substantial investment in a myriad of technical components [13]. It arises primarily due to the paramount focus on the sustainability of the green industry in a green economy. The green industry primarily entails the active utilization of clean production technologies and the adoption of new processes and technologies that are harmless or minimally harmful [24]. Simultaneously, the green industry places greater emphasis on robustly reducing the consumption of raw materials and energy. It aims to accomplish production objectives with minimal pollution [25]. Furthermore, within the domain of green economy, green industry also underscores the utmost elimination of environmental pollutants throughout the production process [26]. Therefore, the implementation of green technology innovation has emerged as a pivotal technical assurance for the sustainability of the green economy. Only through the efficacious dissemination of green technology innovation could the green economy be robustly advanced [27].

Moreover, green technology innovation has evolved into one of the fundamental pillars of the sustainability of the green economy [28]. Derived from the sustainability practices observed in developed nations, the pursuit of the sustainability of a green economy necessitates elevated expectations for green technology innovation endeavors. Simultaneously, green technology innovation assumes a pivotal role in propelling the advancement of the sustainability of the green economy [29]. Hence, in delving into the realm of the sustainability of the green economy, it becomes imperative to delve into the pivotal role played by green technology innovation practices. Furthermore, it is equally essential to examine the intricate interplay between green technology innovation and green economy, unraveling their interconnected [30].

2.3. The Role of the Digital Economy in the Relationship between Green Technology Innovation and Green Economy

Within the realm of the green technology innovation influence on the sustainability of the green economy, noteworthy research by Kozera (2024) highlights the significant regulatory role played by the digital economy [31]. In the intricate interplay between green technology innovation and green economy, various factors wield a substantial impact on their interrelationship. These factors encompass the digital economy, governmental administration, environmental regulations, social customs, human resources, capital, and more. Moreover, as China’s digital economy continues to expand its reach, the pronounced influence of the digital economy on this intricate association is aptly underscored [32]. This phenomenon primarily stems from the multifaceted regulatory capabilities of the digital economy, which enable it to oversee the impact of green technology innovation on the sustainability of the green economy comprehensively. Through the aid of the digital industry, the digital economy adeptly maneuvers to dynamically readjust the intricate dynamics between them [33]. Moreover, the digital economy exerts its regulatory prowess over the impact of green technology innovation on the sustainability of the green economy across various domains, including technology, capital, manpower, and information [34]. Furthermore, the transformation of digital economy composition plays a pivotal role in shaping the magnitude and trajectory of the green technology innovation influence on the sustainability of the green economy [35]. Accordingly, a systematic investigation must be undertaken in conjunction with the digital economy to examine the influence of green technology innovation on the green economy. This integrated approach enables a comprehensive study to explore the effects and implications of green technology innovation in the realm of the green economy [36]. By elucidating the underlying principles governing the digital economy, the promotion of the sustainability of the green economy could be significantly enhanced through the aid of green technology innovation [37]. In summary, delving into the role of the digital economy within the nexus of the two aspects is imperative in order to optimize the dynamics at play [38,39,40].

2.4. Research Gaps

The research findings of the pertinent literature reveal that several scholars have explored the interconnection among the digital economy, green technology innovation, and green economy. However, there are still some deficiencies as follows: (1) Scanty research focusing on the sustainability of the digital economy and green economy in China has been conducted thus far. The majority of scholars have predominantly examined the sustainability of the digital economy and green economy at a localized level, with a dearth of comprehensive and systematic studies on the matter. (2) The majority of scholarly research is predominantly approached from a theoretical standpoint, thereby lacking ample empirical analysis. Furthermore, some of the literature suffers from limited sample sizes, which compromises their persuasiveness and undermines the strength of their findings. (3) In the realm of investigating the impact of green technology innovation on the green economy, some scholars have integrated the examination of the digital economy within this context. This reveals a certain unbalanced perspective in the research regarding these interrelated issues.

To bridge the void in scholarly research, this paper has taken the initiative to define the research title and the contents. The aim is not only to enhance the existing theoretical research but also to furnish a significant point of reference in advancing the sustainability of China’s green economy.

3. Research Hypothesis

3.1. The Influence of Green Technology Innovation on the Sustainability of Green Economy

The improvement of green technology innovation capacity helps to promote the sustainability of the green economy [41]. The concept of green technology innovation includes green technology and product innovation, with special emphasis on the green progress made by enterprises in production technology. For example, in the production process, enterprises strive to reduce the consumption of non-renewable resources and reduce the emission of pollutants [42]. Furthermore, in some cases, they would achieve the ambitious goal of “zero emissions”. Improving the green technology innovation capacity is the key to accelerating the sustainable development of a green economy. This is mainly because the improvement of green technology innovation capacity could improve the efficiency of green economic development and reduce the cost of green economic development [43]. However, when the green technology innovation capacity of enterprises declines, the pace of sustainable development of the green economy will inevitably be hindered. This is mainly because the development of the green economy would be limited by the level of green technology [44]. In addition, green product innovation mainly involves the production of equipment and products produced by enterprises, which must strictly comply with environment-friendly standards. Improving the innovation capacity of these green products plays an important role in promoting the sustainability of the green economy. If the innovation capacity of green products weakens, the long-term sustainability of enterprises with environmental awareness will be limited [45]. Based on the above analysis, this paper proposes the following research hypotheses:

Hypothesis 1 (H1).

Green technology innovation shows a positive impact on the sustainable development of the green economy through green process innovation and green product innovation.

3.2. The Influence of Digital Economy on Green Economy

The sustainability of the digital economy shows a positive impact on the sustainability of the green economy [46]. The digital economy includes the digital industrialization, the industrial digitization, and the digital industrial infrastructure [47]. The positive development trajectory is pursued by them. It promotes the sustainable development of the green economy. This is mainly because the digital economy could enrich the means of green economic development and form a benign interaction with the green economy [48]. On the contrary, the negative process reflected by digital industrialization, industrial digitization, and digital industrial infrastructure would lead to a negative trajectory of green economic sustainability [49]. It shows that when the digital economy is unfavorable, the green economy would not show a better development. In a world where the pace of the digital economy slows down, the pace of the green economy will slow down [50]. Conversely, when the sustainable development momentum of the green economy accelerates, the sustainable development momentum of the green economy will also accelerate [51]. Based on the above analysis, this paper proposes the following research hypotheses:

Hypothesis 2 (H2).

The digital economy shows a positive impact on the sustainability of the green economy.

3.3. The Digital Economy Regulates the Impact of Green Technology Innovation on the Sustainability of Green Economy

The digital economy could effectively regulate the impact of green technology innovation on the sustainability of the green economy. In the process of the impact of green technology innovation on the sustainability of the green economy, it is worth noting that the digital economy plays a crucial role in regulating [52]. On the one hand, the digital economy provides many important platforms for innovation. The digital economy could provide enterprises with knowledge-intensive technology and innovation resources, thus promoting the sustainability of the organization [53]. At the same time, the digital economy shows a strong green technology innovation ability, which could effectively support the sustainability of the green economy by improving the innovation ability of green technology [54]. From another perspective, the digital economy could also provide a rich means of innovation. The sustainability of the digital economy could promote the effective integration of social resources, including advanced communication technology, the digital management platform of production factors, and skilled human resources [55]. By optimizing the allocation of resources, the digital economy could strengthen the promotion effect of green technology innovation on the green economy and further amplify its positive effect [56]. It could be seen that the digital economy shows the ability to effectively regulate the impact of green technology innovation on the sustainability of the green economy. Based on the above analysis, this paper proposes the following research hypotheses:

Hypothesis 3 (H3).

In the process of green technology innovation influencing the green economy, the regulatory role of the digital economy exhibits certain fluctuations. In the initial stages, the regulatory role of the digital economy is relatively small. As the digital economy develops to a certain level, its positive regulatory effect significantly increases. However, when the digital economy reaches a higher level, its positive regulatory effect may diminish.

Drawing upon the aforementioned analysis, the present study constructs a theoretical model, which is depicted in Figure 1. This figure illustrates the interplay between the three variables of digital economy, green technology innovation, and green economy. Additionally, it elucidates the hypothesis content explored in this paper. The establishment of this theoretical model serves as a crucial theoretical groundwork for the subsequent empirical investigation.

4. Methodology

4.1. Construction of Empirical Model

Construction of Benchmark Regression Model

The authors want to investigate the intricate connections among green technology innovation (GTI), digital economy (DLE), and green economy (GED). Thus, this paper formulates the subsequent regression model, drawing upon the research findings of prominent scholars [57]:

$$\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{E}\mathrm{D}}_{\mathrm{i}\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1\mathrm{L}\mathrm{n}\mathrm{D}\mathrm{L}{\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\alpha }}_2\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{T}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(1)

Among them, lnGED represents the sustainability level of the green economy. lnGTI represents the level of green technology innovation. lnDLE represents the sustainability level of the digital economy. ε_it is the residual term.

To mitigate potential biases arising from omitted variables during the estimation procedure [58], the fresh regression Model (2) is established, building upon the foundation of Model (1). Furthermore, pertinent control variables, which have the potential to influence the sustainability of the green economy, are incorporated into the regression Model (2). The structure of Model (2) is depicted as follows:

$$\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{E}\mathrm{D}}_{\mathrm{i}\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1\mathrm{L}\mathrm{n}{\mathrm{D}\mathrm{L}\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\alpha }}_2\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{T}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\beta }}_{\mathrm{i}}\mathrm{L}\mathrm{n}{\mathrm{N}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(2)

Among them, N_it represents the control variable that shows an impact on the sustainability of the green economy.

To delve deeper into the intricate interplay between green technology innovation and digital economy and its profound implications for the sustainability of green economy, this paper presents the additional regression Model (3). This model is specifically designed to unveil the effects of the interactive terms of the digital economy and green technology innovation on the sustainability of the green economy. The formulation of Model (3) is as follows:

$$\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{E}\mathrm{D}}_{\mathrm{i}\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{T}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{{\mathsf{\alpha }}_2(\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{T}\mathrm{I}}_{\mathrm{i}\mathrm{t}}\times \mathrm{L}\mathrm{n}\mathrm{D}\mathrm{L}{\mathrm{E}}_{\mathrm{i}\mathrm{t}})+\mathsf{\beta }}_{\mathrm{i}}\mathrm{L}\mathrm{n}{\mathrm{N}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(3)

4.2. Panel Threshold Regression Model Construction

In light of the evolving sustainability dynamics of the digital economy, it is plausible that the impact of green technology innovation on the sustainability level of the green economy exhibits a nonlinear pattern [59]. To shed light on this notion, this paper has developed the additional panel threshold regression Model (4). It is specifically tailored to uncover the threshold effect of green technology innovation on the sustainability of the green economy [60]. The formulation of Model (4) is presented below:

$$\mathrm{L}\mathrm{n}{\mathrm{G}\mathrm{E}\mathrm{D}}_{\mathrm{i}\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1\mathrm{L}\mathrm{n}{\mathrm{g}\mathrm{i}}_{\mathrm{i}\mathrm{t}}\times \mathrm{I}(\mathrm{L}\mathrm{n}{\mathrm{d}\mathrm{f}}_{\mathrm{i}\mathrm{t}}\le \mathrm{c})+{\mathsf{\alpha }}_2\mathrm{L}\mathrm{n}{\mathrm{g}\mathrm{i}}_{\mathrm{i}\mathrm{t}}\times \mathrm{I}(\mathrm{L}\mathrm{n}{\mathrm{d}\mathrm{f}}_{\mathrm{i}\mathrm{t}}>\mathrm{c})+{\mathsf{\beta }}_{\mathrm{i}}\mathrm{L}\mathrm{n}{\mathrm{N}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(4)

In Model (4), I(·) represents the indicator function, and c is the threshold value. The median threshold value in this research model corresponds to the sustainability level of the digital economy.

The random effects model and fixed effects model commonly used in panel data analysis have their own strengths and weaknesses. The random effects model could handle heterogeneity and correlation in panel data, providing efficient estimation. However, it overlooks individual fixed effects and endogeneity issues. In contrast, the fixed effects model could capture individual-specific fixed differences and effectively control heterogeneity and endogeneity. Furthermore, it is simple and easy to interpret. The reason for choosing the fixed effects model in this paper is to focus on studying individual fixed differences. The authors also aim to control endogeneity issues and simplify the model for better interpretability. Therefore, the fixed effects model is suitable for the research in this paper.

4.3. Variable Index Selection

4.3.1. Explained Variable

The level of green economy encompasses the sustainable aspects of both human society and the industrial sectors associated with production [61]. Additionally, it encompasses the natural environment in which humanity resides, commonly referred to as the “green environment”. To comprehensively evaluate the sustainability level of the green economy, this paper devises an evaluation index system that consists of 3 key dimensions: green society, green industry, and green environment (as depicted in

Table 1. Evaluation index system of the sustainability of green economy level.

Index	Items	Attribute	Reference
Green society	Scale of CO2 emissions per capita	Negative	Olvera (2011) [62], Rebeck (2014) [63]
	Scale of ammonia nitride emissions per capita	Negative
	Scale of per capita nitrogen oxide emissions	Negative
	Fertilizer application amount per unit cultivated area	Negative
Green industry	Annual wastewater discharge	Negative	Helberger (2022) [64], Salmon (2022) [65]
	Annual solid waste emissions	Negative
	Annual industrial emissions	Negative
	Annual farmland irrigation water consumption	Negative
	Annual non-renewable energy consumption	Negative
Green environment	Concentration of CO2 in the air	Positive	Worthington (2005) [66], Marudhamuthu (2011) [67]
	Concentration of NO2 in the air	Negative
	Concentration of SO2 in the air	Negative
	Water quality up to standard rate	Negative
	Urban green space coverage	Negative
	Average urban environmental noise	Positive

). To measure the sustainability level of the green economy, this paper employs the widely acknowledged method of principal component analysis, which is highly regarded within academic circles.

4.3.2. Explanatory Variables

(a)

The digital economy: Currently, there exists a certain degree of scholarly debate surrounding the methods for measuring the digital economy. Hence, a standardized measurement approach for the digital economy remains elusive [68]. This paper, drawing upon the research findings of esteemed scholars in the field, adopts a measurement method that enjoys significant recognition. Specifically, the authors utilize the digital industrialization index, industrial digitization index, and digital industrial infrastructure index as specific indicators to gauge the digital economy. Additionally, by referring to the relevant literature, the authors select 14 specific indicators that are detailed in Table 2. The selected specific indicators are derived from statistical yearbooks released by various provinces of China.

(b)

The green technology innovation: Currently, a majority of scholars consider the quantity of patent applications in each region as a crucial metric for assessing local technological innovation [69]. Therefore, in formulating a measure for green technology innovation, this paper utilizes the yearly count of patent applications related to green technologies in each province. The pertinent data are sourced from patent application reports issued by the science and technology bureaus of various provinces of China [70].

Table 2. The evaluation index system of the digital economy.

Index	Items	Attribute	Reference
Digital industrialization (DDN)	Annual output value of the digital information industry	Positive	Sterev (2022) [71], Helberger (2022) [64]
	The proportion of the total value of the digital information industry to the fixed assets of the whole society	Positive
	The proportion of employment in the digital information industry to the total population	Positive
	The proportion of the annual output value of the digital information industry to the total value of the tertiary industry	Positive
Industrial digitization (IDN)	Transaction volume of e-commerce platform	Positive	Chen (2021) [72], Dunne (2022) [73]
	Mobile payment penetration	Positive
	Number of industrial Internet platforms	Positive
	Numerical control rate of the core process of industrial firms	Positive
	Agricultural internet coverage	Positive
	The proportion of annual industrial digital output to GDP	Positive
Digital industrial infrastructure (DII)	Number of internet mobile base stations	Positive	Petersen (2022) [74]
	Number of broadband internet access ports	Positive
	Internet domain name number	Positive
	Smart phone penetration	Positive

Table 2. The evaluation index system of the digital economy.

Index	Items	Attribute	Reference
Digital industrialization (DDN)	Annual output value of the digital information industry	Positive	Sterev (2022) [71], Helberger (2022) [64]
	The proportion of the total value of the digital information industry to the fixed assets of the whole society	Positive
	The proportion of employment in the digital information industry to the total population	Positive
	The proportion of the annual output value of the digital information industry to the total value of the tertiary industry	Positive
Industrial digitization (IDN)	Transaction volume of e-commerce platform	Positive	Chen (2021) [72], Dunne (2022) [73]
	Mobile payment penetration	Positive
	Number of industrial Internet platforms	Positive
	Numerical control rate of the core process of industrial firms	Positive
	Agricultural internet coverage	Positive
	The proportion of annual industrial digital output to GDP	Positive
Digital industrial infrastructure (DII)	Number of internet mobile base stations	Positive	Petersen (2022) [74]
	Number of broadband internet access ports	Positive
	Internet domain name number	Positive
	Smart phone penetration	Positive

4.3.3. Control Variable

To mitigate the issue of endogeneity [75], the authors accounted for other variables that possess significant influence. These control variables comprise the following: (a) A level of marketization (MTE); the authors employ the ratio of total market investment to total social investment in fixed assets as a proxy for this indicator; (b) industrial composition (SIS); given the inclusion of the digital economy and green technology within the service industry, the authors adopt the ratio of the tertiary industry to provincial GDP as a measure of industrial structure; (c) human capital magnitude (HML); to capture the presence of highly skilled human resources, the authors utilize the proportion of individuals with a college degree or higher in the local population as an index; (d) external openness (OE); drawing upon principles from international economic theory, the authors employ the total amount of foreign direct investment in China as a representation of this indicator.

Based on the above analysis, this paper summaries all the core variable information involved. As shown in

Table 3. Relevant variables, indicators and data sources of this study.

Variables		Index	Data Source
Explained variable	Green economy	Green society	Ministry of Industry and Information Technology of China
		Green industry
		Green environment
Explanatory variables	Digital economy	Digital industrialization	Statistical yearbooks released by various provinces of China
		Industrial digitization
		Digital industrial infrastructure
	Green technology innovation	Yearly count of patent applications related to green technologies	The science and technological bureaus of various provinces of China
Control variables	Level of marketization	The ratio of total market investment to total social investment in fixed assets	Ministry of Commerce of China
	Industrial composition	The ratio of the tertiary industry to provincial GDP	National Bureau of Statistics of China
	Human capital magnitude	The proportion of individuals with a college degree or higher in the local population	National Bureau of Statistics of China
	External openness	Total amount of foreign direct investment in China	Ministry of Commerce of China

, the relevant variables have corresponding measurement indicators. At the same time, all indicators have corresponding data sources. The determination of these indicators provides an important foundation for subsequent research. The relevant data sources are all from Chinese government agencies. Therefore, these data are reliable.

4.4. Data and Method

By utilizing panel data that encompasses 34 provincial administrative regions of China from 2007 to 2021, a comprehensive and in-depth analysis of the research topic becomes attainable. The authors chose data from 2007 to 2021. During this period, China experienced significant changes in the development of its digital economy and green economy. The reason for not studying data from 2024 is that many indicators for that year have not been officially released yet. We are unable to comprehensively obtain relevant data for 2024. However, data for the relevant indicators from 2007 to 2021 are all available. Furthermore, the authors study data from 34 provincial-level administrative regions because China consists of 23 provinces, 5 autonomous regions, 4 municipalities directly under the central government, and 2 special administrative regions, totaling 34 regions. These 34 provincial-level administrative regions could represent the overall development situation of China. Therefore, we choose to study data from these 34 regions.

In terms of data selection, this paper chooses the data from the past 15 years as it represents the most up-to-date and relevant information available. Previous scholars have conducted limited research on this specific time period [28]. Moreover, by analyzing the latest data, the authors provide a more accurate reflection of the current situation. Thus, it leads to scientifically and precisely derived research conclusions.

Panel data, in this context, pertains to a dataset consisting of observations on multiple entities (in this case, the provincial administrative regions) in a specific time period. This approach offers several notable advantages for empirical analysis and significantly bolsters the generalization of the research findings. Furthermore, it is worth noting that the selected samples for this research fully meet the fundamental criteria of panel data. These chosen research subjects possess robust representative, ensuring the validity and reliability of the findings.

To derive data pertaining to digital industrialization in the digital economy, the authors sourced information primarily from the World Input-Output Database. These data concern industrial digitization, digital industrial infrastructure, and the sustainability of the green economy level. The authors primarily rely on data published in the China Statistical Yearbook, China Environmental Statistical Yearbook, provincial statistical yearbooks, and governmental websites throughout the years. Additionally, data regarding green technology innovation primarily originated from official reports and data published by provincial science and technology bureaus. It is worth noting that certain provinces or years may have experienced data omissions. In such cases, the authors employ the mean method to fill in the missing data, ensuring the continuity and coherence of the study.

In terms of research methodology, this paper primarily employed the following research methods: multi-correlations test, baseline regression, fixed effect models, threshold effect analysis, robustness test, and heterogeneity analysis. The reason for choosing these methods is that most scholars in the field have used them to investigate similar issues [13]. These methods are well-suited for studying the relationship between digital economy, green technological innovation, and green economy. Additionally, utilizing these methods allows for a comprehensive and in-depth examination of the aforementioned topics.

4.5. Multi-Correlations Test

To ascertain the interrelationships between variables, this paper employs the Pearson product-moment correlation analysis to examine the correlation among the variables. The primary focus of the analysis is on the interrelationships between green economy, digital economy, and green technology innovation variables. The results of the correlation analysis are presented in

Table 4. The results of the correlation analysis.

	GED	DLE	GTI
GED	1	0.49 * (0.04)	0.33 ** (0.07)
DLE	0.49 * (0.04)	1	0.30 *** (0.01)
GTI	0.33 ** (0.07)	0.30 *** (0.01)	1

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

.

Based on the data from Table 4, it can be observed that the authors primarily conducted 2-tailed Pearson tests to examine the relationships between variables. Despite the presence of some correlation among green economy, digital economy, and green technology innovation variables, the correlation coefficients are relatively small, all being less than 0.5. According to the standards set by most scholars, a correlation coefficient below 0.8 indicates the absence of multi-correlations among variables. Hence, in the present study, there is no issue of multi-correlations among the variables. In other words, there is no substantial correlation between the variables, allowing for further investigation in subsequent studies.

5. Results

5.1. Baseline Regression Result

Table 5. Empirical analysis results of baseline regression.

Variables	(1)	(2)	(3)	(4)
LnDLE	0.10 ** (11.36)	0.27 ** (19.20)
LnGTI	0.01 ** (2.33)	0.028 ** (3.65)	−0.01 (−0.27)	0.00 (0.41)
LnDLE × LnGTI			0.04 ** (7.39)	0.02 ** (3.44)
LnSIS		−0.47 ** (−3.29)		−0.29 ** (−5.83)
LnMTE		0.04 *** (0.51)		0.05 ** (0.82)
LnOE		−0.06 ** (−4.87)		0.10 ** (6.24)
LnHML		−0.09 ** (−5.72)		−0.09 ** (−7.26)
Con_	−3.4572 ** (−88.53)	−2.99 ** (−14.61)	−2.8742 *** (−72.31)	−2.01 ** (−5.30)
Hausman	572.03 *** (0.00)	841.90 ** (0.00)	382.77 ** (0.00)	492.31 *** (0.00)
R2	0.48	0.48	0.36	0.39

Note: N = 6631; ** indicates p < 0.01; *** indicates p < 0.001.

presents the empirical analysis results of the baseline regression conducted. The baseline regression test results in Table 5 indicate that the fixed effect model used demonstrates favorable application effects. Model (1) depicts the regression outcome regarding the impact of green technology innovation and digital economy on the sustainability level of green economy without considering control variables. On the other hand, Model (2) represents the regression outcome with the inclusion of control variables to examine the influence of green technology innovation and the digital economy on the sustainability level of the green economy. Upon observing the regression coefficients in the table, it is evident that both green technology innovation and the digital economy show positive and statistically significant effects on the sustainability level of the green economy. The findings further indicate that both green technology innovation and digital economy exert a positive promoting influence on the sustainability of the green economy. Therefore, both hypothesis 1 and hypothesis 2 are supported by the results.

When describing the interaction between the two variables, using interaction terms as a measure is a common method [76]. Calculating the interaction term can reveal the interaction effects between green technology innovation and the digital economy. If the coefficient of the interaction term is significant and positive, it indicates a positive mutual promotion relationship between the two variables. If the coefficient is significant and negative, it suggests a negative mutual constraint relationship. If the coefficient is not significant, it indicates that the interaction effects between the two are weak or non-existent. Therefore, using interaction terms as a measure could help us, to some extent, understand the interaction between green technology innovation and the digital economy.

Moreover, Model (3) corresponds to the regression outcome regarding the influence of green technology innovation and digital economy on the sustainability level of the green economy, disregarding control variables. On the other hand, Model (4) represents the regression outcome with the inclusion of control variables, examining the impact of green technology innovation and the digital economy on the sustainability level of the green economy. The empirical findings presented in Table 4 demonstrate that the digital economy performs a positive regulating role in the process of green technology innovation, driving the sustainability of the green economy. Therefore, hypothesis 3 also successfully passes the test.

5.2. Threshold Effect Analysis Results

Drawing upon a comprehensive review of the pertinent literature, the authors employed the bootstrap sampling method to confirm the presence of a threshold effect. Esteemed scholars hold a strong consensus regarding the credibility of this approach. Additionally, based on the assumption that a threshold effect indeed exists, the authors would proceed to compute the corresponding threshold quantity and threshold value, advancing the analysis further.

The conclusive outcomes of the threshold effect analysis for the digital economy are presented in

Table 6. Empirical analysis results of the digital economy threshold.

Threshold Type	Threshold Value	F Statistic	p-Value	10% Threshold	5% Threshold	1% Threshold
Single	8.34	292.31 ***	0.00	98.32	112.40	147.08
Double	5.79	66.87 ***	0.00	44.27	62.09	97.31
Triple	12.73	21.33 *	0.00	83.06	95.21	106.73

Note: N = 6631; * indicates p < 0.05; *** indicates p < 0.001.

. Upon careful examination of the data within the table, one can observe that both the single threshold and double threshold of the digital economy have successfully passed the test of statistical significance. However, the triple threshold, on the other hand, does not yield statistically significant results. Therefore, it could be inferred that the threshold effect of the digital economy manifests as a double threshold. Specifically, the two thresholds are determined to be 5.7920 and 8.3374.

The p-values and threshold were obtained by repeated sampling 900 times by bootstrap sampling.

The findings regarding the double threshold test results of the digital economy are presented in

Table 7. Empirical analysis results of threshold regression.

Variable Name	Coefficient	Std.	t-Value	p-Value
LnGTI(LnDLE ≤ 5.7920)	0.02 **	0.01	5.30	0.00
LnGTI(5.7920 < InDLE ≤ 8.3374)	0.06 **	0.00	6.21	0.00
LnGTI(InDLE > 8.3374)	0.10 **	0.00	3.88	0.00
LnSIS	−0.18 **	0.03	−2.75	0.00
LnMTE	0.05 ***	0.03	0.39	0.00
LnOE	0.02 **	0.06	2.17	0.00
LnHML	−0.06 **	0.02	−2.91	0.00
Con_	−7.00 *	0.67	−6.61	0.00

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

and Figure 2. The results are displayed as follows:

(1)

In situations where the digital economy has not surpassed the threshold of 5.7920, the influence of green technology innovation on green development appears to be relatively modest. The coefficient of its influence is merely 0.0198, which has successfully passed the significance test at the 5% level. During this phase, one possible reason for green technology innovation’s limited impact could be attributed to the comparatively underdeveloped sustainability of the digital economy. The relatively less advanced state of digital economy sustainability impedes the full realization of support efficiency for innovation-driven enterprises. Consequently, the positive effect of green technology innovation on the green economy remains relatively constrained.

(2)

As the digital economy falls within the range of the first threshold value of 5.7920 to the second threshold value of 8.3374, the impact of green technology innovation on green sustainability experiences a notable enhancement. The estimated coefficient of green technology innovation increases from 0.0198 to 0.0621. It signifies that as the sustainability of the digital economy improves, its capacity to assimilate and integrate social resources is greatly amplified. Consequently, the role of the digital economy in facilitating green technology innovation is significantly enhanced. Simultaneously, the digital economy empowers green technology innovation to effectively contribute to the advancement of green sustainability.

(3)

Once the digital economy surpasses the second threshold value of 8.3374, the influence of green technology innovation on the sustainability level of the green economy undergoes a reduction. The estimated coefficient declines from 0.0621 to 0.00982. This indicates that as the digital economy reaches a certain level of development, its impact on green technology innovation gradually diminishes.

The reasons for this situation are as follows: (1) The focus of the digital economy may shift. As the digital economy develops to a certain level, its influence on green technology innovation gradually weakens. This is because the focus of the digital economy gradually shifts towards other fields or technological directions rather than green technology innovation. (2) The digital economy may face new challenges after reaching a certain stage of development. These challenges require more resources and efforts to address, which may lead to a decrease in support for green technology innovation. (3) Green technology innovation may have advanced to a point where it no longer requires support from the digital economy. After the digital economy has developed to a certain stage, green technology innovation has already achieved a certain level of success and progress. In this context, green technology innovation itself has acquired a certain level of self-propelling force and developmental drive. The combined effect may result in the digital economy’s reduced impact on the sustainability level of the green economy through green technology innovation.

Consequently, the promoting effect of green technology innovation on the sustainability of the green economy experiences a further deceleration. This test outcome serves as another affirmation of the robustness of the previously conducted study’s correlation findings.

5.3. Robustness Test

To enhance the accuracy and reliability of the research conclusions, a robustness test was conducted on the empirical model. Prior to the robustness test, the authors applied scientific data-dealing techniques. Trimming of outliers was performed on the data in order to eliminate their influence. However, this trimming procedure is not conducted during the robustness test. The results of the robustness test are presented in

Table 8. Robustness test results.

Variables	(1)	(2)	(3)
lnDLE	0.33 ** (0.02)	0.49 ** (0.02)	0.45 * (0.03)
lnGTI	0.26 * (0.04)	0.27 *** (0.05)	0.31 ** (0.04)
lnMTE	4.28 *** (0.09)	4.56 * (0.06)	4.98 ** (0.09)
lnSIS	4.54 * (0.41)	3.90 *** (0.57)	2.19 ** (0.38)
lnHML	0.49 ** (0.02)	0.73 * (0.03)	0.82 * (0.04)
lnOE	6.13 * (2.80)	7.11 ** (2.34)	7.43 *** (1.99)
C	0.02 * (0.02)	0.04 ** (0.02)	0.04 ** (0.02)
R2	0.73	0.75	0.88

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

. The coefficients of the main variables, including the green economy, the digital economy, and green technology innovation, demonstrate consistent impact directions and statistical significance compared to the previous study. This finding indicates that both the specified correlation model and the regression results are reliable and robust.

5.4. Further Analysis

5.4.1. The Digital Economy of Each Dimension Regression Analysis Results

Based on the aforementioned investigation, to thoroughly examine the impact of different dimensions of the digital economy on the sustainability of the green economy, this paper undertakes a regression analysis. The authors primarily integrate the effects of digital industrialization, industry digitization, and digital industry infrastructure on green sustainability to perform the regression analysis. The outcomes of the regression analysis are presented in

Table 9. Regression empirical analysis results of the digital economy in each dimension.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	Digital Industrialization		Digital Industry Infrastructure		Industry Digitization
DDN	0.09 ** (7.11)
DII			−0.02 * (−0.35)
IDN					0.07 ** (8.34)
LnGTI	0.06 * (7.36)	0.04 *** (0.59)	0.07 ** (7.59)	0.09 ** (5.33)	0.07 * (7.90)	0.01 ** (0.81)
LnGTI × LnDDN		0.08 ** (6.11)
LnGTI × LnIDN				0.06 ** (3.19)
LnGTI × LnDI						0.04 ** (5.91)
Control	Y	Y	Y	Y	Y	Y
Con_	−1.33 * (−2.66)	−3.59 * (−6.71)	−3.93 * (−7.80)	−4.30 ** (−8.03)	−3.79 ** (−5.18)	−3.95 ** (−5.31)
Hausman	304.71 (0.00)	492.88 (0.00)	299.54 (0.00)	439.88 (0.00)	673.91 (0.00)	893.62 (0.00)
R2	0.54	0.49	0.49	0.44	0.46	0.42

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

. Both digital industrialization and industry digitization exhibit a positive and significant impact on the sustainability of the green economy at the 1% level, signifying their promotion. Conversely, the influence coefficient of the digital industry infrastructure on the green economy is negative and does not pass the significance test. This result could be attributed to the fact that the construction of the digital industry infrastructure serves as the foundation of the digital economy as it determines the upper limit of the digital economy. Currently, China’s digital technology is still in need of improvement, as various challenges persist in achieving sustainability in the Chinese digital economy. Particularly, there is a notable delay in the development of digital industry infrastructure in China, hampering the effective role of the digital economy in promoting the sustainability of the green economy. Hence, it is plausible that the digital industry infrastructure may exert a negative influence on the green economy. Moreover, the data presented in Table 9 illustrate that regardless of the specific dimension of the digital economy being considered, each dimension exhibits a positive impact on the sustainability of the green economy. This finding underscores the consistent and favorable influence of the digital economy on green technology innovation. Consequently, this empirical evidence further validates the reasonableness of hypothesis 2.

5.4.2. The Results of Regression Empirical Analysis of All Dimensions of Green Economy Level

Based on the preceding investigation, this paper further partitions the sustainability of the green economy into three dimensions: green industry, green environment, and green society. All the dimensions are encompassed in the model deployed in this paper. The effects of green technology innovation and digital economy on these aforementioned dimensions of green sustainability are presented in

Table 10. Results of regression empirical analysis of each dimension of green economy level.

Variable	(1)	(2)	(3)
	Green Society	Green Industry	Green Environment
LnDLE	0.57 ** (9.04)	0.14 ** (1.62)	0.23 (5.71)
LnGTI	0.57 ** (8.22)	0.19 *** (0.94)	0.03 * (0.36)
LnSIS	4.10 * (8.03)	−0.32 *** (−1.22)	−0.19 * (−0.72)
LnMTE	3.72 ** (5.39)	−0.18 ** (−3.85)	0.10 *** (0.31)
LnOE	2.79 * (2.29)	0.11 ** (3.88)	0.35 ** (2.04)
LnHML	−0.14 * (−1.15)	−0.04 ** (−0.99)	0.69 ** (7.49)
Con_	−4.95 ** (−2.28)	5.80 * (3.88)	7.26 ** (4.81)
Hausman	473.81 (0.00)	218.04 (0.00)	74.92 (0.00)
R2	0.51	0.50	0.43

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

and

Table 11. Empirical analysis results of correlation effect regression of each dimension of the green economy.

Variable	(1)	(2)	(3)
	Green Society	Green Industry	Green Environment
LnGTI	0.17 * (0.93)	0.04 *** (0.14)	0.01 (0.29)
LnGTI × LnDLE	0.39 ** (5.29)	0.07 *** (1.63)	0.09 (1.82)
LnSIS	7.06 *** (8.38)	−1.92 ** (−6.24)	0.37 ** (1.06)
LnMTE	0.60 * (2.10)	−0.92 *** (−4.66)	0.72 ** (1.58)
LnOE	0.82 ** (3.99)	0.18 * (1.06)	0.21 ** (4.81)
LnHML	−0.27 * (−4.18)	−0.14 ** (−3.91)	−0.11 ** (−4.03)
Con_	−9.04 *** (−5.62)	4.17 ** (4.93)	2.89 *** (1.52)
Hausman	478.22 (0.00)	307.81 (0.00)	89.62 (0.00)
R2	0.42	0.29	0.1518

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

.

The empirical findings in Table 10 reveal that the digital economy exerts a positive influence in fostering the sub-dimensions of green society and green industry. However, the impact of the digital economy on the green environment is not statistically significant. Similarly, the empirical data in Table 11 indicate that the correlation effect under the conjunction of the digital economy does not yield a significant impact on the green environment. Nevertheless, green technology innovation could stimulate improvements in the realms of green society, green industry, and green environment, albeit to varying degrees of promotion.

5.4.3. Heterogeneity Analysis Results of Different Regions

The research conducted by previous scholars indicates that there exist substantial disparities in technology, economic circumstances, and industrial composition among diverse regions [77]. These dissimilarities may consequently result in divergent impacts of the digital economy and green technology innovation on the level of sustainability in the green economy across different regions. Hence, relying on data obtained from the National Bureau of Statistics, the authors classified China’s 34 provincial-level administrative regions into three distinct regions: the eastern region, the central region, and the western region. The outcomes, demonstrating the regional heterogeneity in the influence of green technology innovation and digital economy on the sustainability level of green economy in the aforementioned three regions, are delineated in

Table 12. Results of regression empirical analysis of heterogeneity in different regions.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	Western Region		Central Region		Eastern Region
LnDLE	0.57 * (11.38)		0.2043 ** (6.63)		0.7905 *** (14.93)
LnGTI	0.01 * (1.37)	0.3825 (0.76)	0.0175 *** (2.83)	0.0462 (1.10)	0.0773 ** (4.29)	−0.0164 (−0.16)
LnDLE × LnGTI		0.0944 (0.71)		0.0382 ** (2.19)		0.5709 * (4.62)
LnSIS	−0.09 * (−2.81)	−0.0572 * (−1.30)	−0.4982 ** (−4.07)	−0.5892 ** (−4.65)	−0.3782 ** (−2.91)	−0.4022 *** (−3.17)
LnMTE	−0.00 (−0.15)	−0.0008 (−0.17)	0.0742 * (2.33)	0.0591 * (1.84)	0.0932 *** (2.53)	0.0874 ** (2.39)
LnOE	0.66 ** (9.01)	0.3972 * (2.27)	−0.3955 * (−2.64)	−0.3326 ** (−2.27)	−0.6932 ** (−7.83)	−0.5528 *** (−6.62)
LnHML	−0.18 * (−4.36)	−0.1804 * (−4.71)	−0.1372 ** (−3.61)	−0.1385 ** (−3.88)	−0.1184 *** (−2.93)	−0.1472 *** (−2.96)
Con_	−8.08 ** (−2.99)	−7.4283 ** (−3.01)	−5.7045 ** (−3.26)	−4.8823 ** (−2.76)	−3.9962 ** (−2.80)	−5.7290 ** (−4.63)
Hausman	22.30 (0.00)	21.75 (0.03)	62.93 (0.00)	39.81 (0.00)	102.71 (0.00)	94.72 (0.00)
R2	0.72	0.70	0.89	0.89	0.52	0.50

Note: N = 6631; * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001.

.

The findings presented in Table 12 illustrate that across the three regions, namely the eastern, central, and western regions, green technology innovation, the digital economy, and their interaction terms exhibit a positive influence on the sustainability level of the green economy. However, in the case of the western region, the regression coefficients of the digital economy and its interaction terms do not achieve statistical significance. It suggests that the digital economy exerts a comparatively lesser positive impact on the green economy in the western region. The primary reason for this disparity lies in the concentration of sustainability factors related to the digital economy in the eastern and central regions. Additionally, the majority of provinces in the western region are situated deep inland, characterized by a disadvantaged natural environment and relatively underdeveloped technological and economic sustainability. Consequently, the effective transfer and utilization of the digital economy sustainability elements pose challenges in the western region. Consequently, the ability of the digital economy to enhance green technology innovation and the green economy in the western region is diminished.

6. Conclusions, Policy Implications, Limitations, and Future Research Directions

6.1. Conclusions

The findings derived from this paper reveal that green technology innovation, digital economy, and their interaction play a constructive role in advancing the high-quality sustainability of green economy. Furthermore, the digital economy exhibits a dual threshold effect on the green economy when driven by green technology innovation. Once the digital economy surpasses the first threshold, it significantly enhances the impact of green technology innovation on the sustainability of the green economy. This research conclusion also indirectly supports the correctness of Ryosuke’s (2022) research findings regarding the green economy [78]. As the digital economy surpasses the second threshold, the influence of green technology innovation on the sustainability of the green economy begins to decline significantly. Nonetheless, the impact of green technology innovation and the digital economy on the sustainability of the green economy differs significantly across various regions of China. In the western region, the effect of the digital economy is comparatively lower. Conversely, in the central and eastern regions, the digital economy plays a substantial role in promoting the green economy.

The interplay among green technology innovation, the digital economy, and their interaction fosters the advancement of high-quality sustainability within the realm of the green economy. This is primarily due to the fact that a heightened level of digital economy sustainability provides an expanded array of sustainability measures for the green economy. Moreover, elevating the level of green technology innovation serves as crucial technical support for enhancing the high-quality sustainability of the green economy. Simultaneously, through the positive interaction between green technology innovation and the digital economy, the sustainability of the green economy could be effectively permeated and propelled forward. Furthermore, the digital economy, the green technology innovation, and their synergy collectively play a significant role in promoting the high-quality sustainability of the green economy. This research conclusion further extends and enriches the findings of Lin (2021) [79]. Hence, to facilitate the advancement of high-quality sustainability in the green economy, pertinent administrative bodies and stakeholders should proactively promote green technology innovation and steer the sustainability of the digital economy.

The digital economy exhibits a dual threshold effect on green technology innovation, thereby contributing to the advancement of the green economy. Upon surpassing the first threshold, the impact of green technology innovation on the sustainability of the green economy is significantly amplified. However, once the digital economy goes beyond the second threshold, the influence of green technology innovation on the sustainability of the green economy starts to diminish noticeably. It is evident that during the initial phase of the digital economy, the green technology innovation promotion effect on the green economy could be effectively and positively adjusted. Nevertheless, as the level of the digital economy progress reaches a certain point, it becomes less effective in regulating the green technology innovation impact on the green economy. This implies a shift in the regulatory role of the digital economy. This conclusion not only confirms the findings of Liu (2023) but also enriches the content of related conclusions [80]. Consequently, individuals responsible for oversight should adeptly harness the window of opportunity afforded by the digital economy to promote the sustainability of the green economy to its fullest potential.

The influence of green technology innovation and digital economy on the green economy varies significantly across different regions of China. In the western region, the efficacy of the digital economy is limited due to the underdeveloped auxiliary infrastructure, which hampers its full potential. Consequently, both green technology innovation and the digital economy play a relatively minor role in driving the sustainability of the green economy in the western region. Conversely, in the central and eastern regions, green technology innovation and digital economy play a substantial part in promoting the sustainability of the green economy. Compared with the findings of Smit (2015), the conclusions of this study are more aligned with the current reality of China’s green economic development [81]. The conclusions hold greater practical significance. As a result, administrators in these regions should proactively leverage the advantages of green technology innovation and the digital economy to effectively advance the sustainability of the green economy.

6.2. Implications

(1)

The pertinent governmental entities should proactively enhance the infrastructure pertaining to the digital economy. The digital economy serves as a crucial catalyst for advancing green technology innovation and green economy [66]. Nonetheless, the sustainability of the digital economy relies on comprehensive infrastructure support. Thus, the relevant administrative departments should take proactive measures to augment financial backing for the digital economy initiatives and facilitate the development of associated facilities. These departments should expand the number of internet mobile base stations within the region, increase the availability of internet broadband access ports and internet domain names, and promote the adoption of smartphones to elevate their penetration rate. By optimizing the infrastructure related to the digital economy, the full potential of the digital economy functions could be effectively harnessed, thereby propelling the sustainability of the local green economy.

(2)

The pertinent bodies should endeavor to facilitate the seamless integration of green technology innovation and the digital economy. Governments with jurisdiction ought to proactively implement management policies concerning the digital economy and green technology innovation. From a policy perspective, the government should take an active role in guiding the deep integration of the digital economy and green technology innovation within society. The provision of policy guarantees serves as a vital foundation for promoting the sustainability of the green economy through the utilization of green technology innovation and the digital economy [59]. Simultaneously, relevant enterprises should also embark upon enhancing their own production practices and actively elevate the comprehensive level of green technology innovation through its initiatives undertaken by firms empowered by the digital economy. Only through the comprehensive integration of green technology innovation and the digital economy can the sustainability of the regional green economy be effectively advanced.

(3)

Management departments in different regions should take different management measures. On the one hand, managers in the western region should not focus on the digital economy. The region should prioritize the development of the infrastructure needed for green technological innovation and green economic development. The western region needs to be further promoted by the digital economy only after its related infrastructure has been developed to a certain level. On the other hand, in the central and eastern regions, government administrators should fully strengthen the catalytic role of the digital economy. The region should actively build on the digital economy and use green technology innovation to promote green economy development. In particular, the government should make use of the talent, information, and capital brought by the digital economy to actively promote the sustainability of the green economy.

6.3. Limitations and Future Research Directions

Due to the study’s constraints in terms of length, as well as the time and energy of the authors, there are certain limitations in the research conducted. These limitations also serve as areas of focus for future researchers: (1) The variables within the theoretical model established would benefit from further enrichment and adjustment. The current focus revolves around the relationship between green technology innovation, the digital economy, and the green economy, overlooking numerous other variables that influence the sustainability of the green economy. As a result, future research endeavors would incorporate additional variables into the theoretical mode. They include environmental regulations, government policies, social culture, the business environment, economic structural adjustment, energy consumption patterns, and environmental pollution emissions. By expanding the scope of variables, a more comprehensive understanding of the factors impacting the sustainability of the green economy could be achieved. (2) The sample scope of this study would benefit from a broader expansion. Currently, the investigation focuses solely on the relationship between green technology innovation, the digital economy, and the green economy in various regions of China. It is without considering these issues in other countries. In future studies, the authors intend to explore the green economy in different countries, including the United States, Japan, the European Union, Brazil, India, and beyond. By encompassing a more diverse range of countries, a more comprehensive understanding of the green economy dynamics on a global scale could be gained. (3) The research methods employed in this study could benefit from further enrichment. Currently, the paper relies solely on the fixed effect model and threshold effect model. However, in future research endeavors, the authors intend to incorporate additional empirical methods, such as structural equation modeling, virtual simulation, robustness testing, and other empirical approaches. The utilization of these diverse empirical methods is instrumental in enhancing the reliability and stability of the research conclusions, ensuring a more robust and comprehensive analysis of the problems at hand. (4) The effects of the digital economy components separately are not analyzed in this paper. Due to the limitation of length, they do not further analyze the effects of the digital economy components separately. In future studies, the authors will take a closer look at the effect of digital industrialization, industrial digitization, and digital industrial infrastructure. In particular, they would examine how these indicators influence the process of the green economy and green technology innovation.