Frontiers in Business, Economics and Management 
ISSN: 2766-824X | Vol. 15, No. 2, 2024 

 

443 

Can enterprise digitization facilitate green technology 
innovation? 

-- Re-testing based on a two-sided mechanism of supply and demand 

Qiaoya Zhang, Qing Li, Jingwen Yao, Shurui Yi 

School of Accountancy, Anhui University of Finance & Economics, Bengbu Anhui 233030, China 

 

Abstract: Digital economy realizes the win-win situation of energy efficiency and digital economy development by promoting 
green technology innovation. Digital economy plays an important role in enterprise green innovation and energy efficiency 

improvement, providing theoretical and practical guidance for China's green sustainable development and dual-carbon goals. 

This paper explores the impact of digital economy on enterprise green innovation and energy efficiency improvement. The study 

takes highly polluting listed enterprises in China as the target, and analyzes the implementation effect of the national-level big 

data comprehensive pilot zone policy by means of panel data and double-difference model from 2010 to 2022. In addition, based 

on the high-tech industry data of 30 provinces and cities in China from 2010 to 2022, a threshold model is constructed and 

analyzed, showing that the digital economy has a significant positive impact on the green innovation efficiency of enterprises, 

but there is a nonlinear "U" threshold effect. Active government and effective market have different regulating effects on this 

process at different stages of development, and differentiated countermeasures need to be taken in light of regional characteristics. 

In terms of smart city construction, the digital economy has a significant role in promoting green innovation. In terms of energy 

efficiency improvement, based on the data of 284 prefecture-level cities, the study found that the digital economy, especially 

industrial digitization, has a significant role in promoting energy efficiency, with an "N"-shaped characteristic. 

Keywords: Digitalization, Green technology innovation, Supply and demand sides, Mechanism retesting. 

 

1. Introduction 

The report of the 19th CPC National Congress points out 

that China's economy has shifted from years of high-speed 

growth to high-quality development, and that the center of 

gravity of economic development has shifted from 

quantitative to qualitative improvement. In the past, too much 

emphasis was placed on the speed of economic development, 

resulting in the depletion of the ecological and living 

environment becoming the price of economic development. 

The new development concept put forward by General 

Secretary Xi Jinping at the Fifth Plenary Session of the 18th 

CPC Central Committee puts innovation and greenness at the 

forefront, requiring China to shift from crude growth to green 

and frugal growth, and to emphasize technological innovation 

while developing the economy to achieve green and 

sustainable development. 

At present, green technological innovation has become an 

important emerging field in the new round of global industrial 

revolution and technological competition. With the 

establishment of China's green, low-carbon and recycling 

development economic system, green technological 

innovation has increasingly become an important driving 

force for green development and an important support for 

advancing the construction of ecological civilization and 

promoting high-quality development. At the same time, the 

new round of scientific and technological revolution and 

industrial change driven by digital technologies such as 

blockchain, big data, cloud computing and artificial 

intelligence has effectively alleviated the information 

asymmetry in the process of technological innovation through 

the development of digital information networks, the Internet 

of Things, and the optimization of the market environment, 

and has enhanced the productivity of innovation factors, 

which has contributed to the sustained improvement of the 

level of green technological innovation. 

The Huaihe River Ecological Economic Belt has the 

strategic positioning of realizing the effective docking of the 

economic development of the Yangtze River Delta Economic 

Zone and the Central Plains Economic Zone.In 2018, the 

National Development and Reform Commission (NDRC) 

implemented the Development Plan for the Huaihe River 

Ecological Economic Belt, which elevated its development to 

the level of a national strategy. However, the problem of 

sacrificing the ecological environment for economic 

development in the region has still not been fundamentally 

solved. In this context, an in-depth analysis of the mechanism 

and effect of the digital economy on the green technological 

innovation of the Huaihe River Ecological Economic Belt is 

of great theoretical significance and practical urgency for 

seizing the opportunities of digital economy development, 

promoting green technological innovation, and realizing the 

sustainable development of the green economy. 

As a major economic form after the agricultural economy 

and industrial economy, the digital economy is data-driven 

and digital technology-driven, with the characteristics of 

"dematerialization" and "asset-light", and the in-depth 

integration of digital technology and the real economy can 

effectively improve the efficiency of energy production and 

utilization, and become a new driving force for energy 

efficiency improvement. The deep integration of digital 

technology and the real economy can effectively improve the 

efficiency of energy production and utilization, and become a 

new driving force for the improvement of energy efficiency. 

Therefore, through theoretical analysis and empirical research, 

this paper explores the internal mechanism, characteristics 

and transmission path of the digital economy affecting energy 

efficiency, so as to provide decision-making references for the 



 

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government to realize the win-win situation of digital 

economy development and energy efficiency enhancement, 

and to promote the high-quality development of China's 

economy. 

2. Theoretical Analysis and 
Formulation of Hypotheses 

2.1. Digital Economy Enhances the Efficiency 
of Green Innovation 

To achieve the goal of high-quality development in the era 

of big data, enterprises need to move away from the 

traditional mindset of realizing production at the expense of 

the surrounding environment, and instead use emerging 

digital technologies to comply with green development 

strategies. First, digital transformation can help companies 

reduce energy loss and improve efficiency. Through the 

application of digital technology, enterprises can monitor and 

manage energy use in real time, identify and solve energy 

waste problems, and thus effectively reduce energy 

consumption. For example, using big data analysis 

technology, enterprises can optimize the production process, 

reduce energy waste, improve production efficiency and 

achieve green production. Second, digital transformation 

helps optimize the human capital structure of enterprises and 

strengthen the spillover effect of knowledge. In the process of 

digital transformation, enterprises can improve the level of 

digital skills of employees and stimulate their innovation 

potential through training and introduction of talents. At the 

same time, digital transformation also promotes the sharing 

and dissemination of knowledge, strengthens the 

communication and exchange of knowledge within the 

enterprise, and thus enhances the enterprise's innovative 

ability and competitiveness. Third, digital transformation can 

reduce the consumption of resources brought about by 

information asymmetry and make it easier for enterprises to 

access innovation resources in the value network. Through 

digital technology, enterprises can acquire and analyze market 

information more accurately, reduce the risks associated with 

information asymmetry, and avoid waste and loss of resources. 

At the same time, digital transformation also helps enterprises 

to establish closer cooperative relationships in the value 

network, obtain more innovative resources and promote the 

development of green innovation in enterprises. 

In summary, digital transformation has an important role in 

promoting enterprise green innovation, which can help 

enterprises achieve energy saving and efficiency 

improvement, optimize the human capital structure and 

strengthen the spillover effect of knowledge, reduce the 

resource consumption brought by information asymmetry, so 

as to promote the enterprise to move towards the green 

development strategy and achieve the goal of high-quality 

development. Based on the above theoretical analysis, this 

paper puts forward the following hypotheses: 

H1: Digital transformation of companies can contribute to 

the quality of green innovation in companies. 

2.2. Mechanisms and Characteristics of Digital 
Economic Development Affecting Energy 

Efficiency 

From the point of view of existing research and 

development practice, China's digital economy has 

experienced a development process from the pioneering 

development of digital industry to the rapid expansion of 

industrial digitization, to the continuous advancement of 

digital governance, and ultimately to the realization of data 

valorization. Overall, it can be divided into the following 

three stages: 

Initial stage: This is the early application stage of 

information technology, where the Internet develops faster 

and the digital economy is dominated by digital 

industrialization. 

Growth stage: The faster development of new-generation 

information technologies such as cloud computing, big data 

and the Internet of Things has promoted the rapid expansion 

of digital industrialization and industrial digitization, and the 

rapid increase in digital infrastructure. 

Advanced stage: Digital industrialization and industrial 

digitization continue to develop, with digital governance and 

data valorization becoming new components of the digital 

economy as the application areas of digital technologies are 

broadened. 

The digital economy is characterized by both horizontal 

dimension expansion and vertical scale expansion over time. 

In the above process, there are two effects of the development 

of the digital economy on the improvement of energy 

efficiency: 

Positive effects: 

Digital industrialization: As a pioneer industry in the 

development of the digital economy, it provides technologies, 

products, services and solutions for industrial digitization and 

digital governance. The digital industry itself possesses 

important economic characteristics such as increasing 

marginal returns and economies of scope, and with 

technological innovation as its core driving force, it has a 

strong penetration and multiplier effect, which can 

significantly boost urban economic growth, promote the flow 

of factors of production to high-productivity sectors, and 

drive the shift of the center of gravity of the national economy 

to technology-intensive industries, thereby enhancing urban 

energy efficiency. 

Industrial digitization: the integration of digital technology 

with the real economy is the main engine of digital economic 

development. Agricultural digitization through information 

technology to achieve accurate production, visualization 

management, intelligent decision-making, reduce the 

consumption of agricultural production resources; industrial 

digitization through the application of information technology, 

the Internet and intelligent equipment in the whole process of 

industrial production, improve production efficiency and 

energy efficiency; service industry digitization through the 

creation of "Internet +" and other new modes of digital 

services, improve the efficiency of services. The digitization 

of the service industry improves service efficiency by creating 

new digital service models such as "Internet+". 

Digital governance: This is mainly manifested in the 

construction of digital governments and smart cities. Digital 

government improves the level and efficiency of governance 

by means of digital technology, such as effectively regulating 

the total amount of energy supply and improving urban 

energy efficiency through feedback from energy prices and 

carbon emissions trading data. Smart city construction 

upgrades the organizational framework of urban operations 

through the application of modern sensing, monitoring, 

communication and control technologies, reduces the 

consumption of material resources for urban operation and 

management as well as residents' consumption, and improves 



 

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energy efficiency. 

Data valorization: Data, as a resource, is transformed into 

assets and elements through development and utilization, and 

generates value in circulation. Data elements are non-

competitive, can be infinitely copied and reused, and have the 

characteristics of increasing returns to scale, effectively 

enhancing urban energy efficiency. 

Negative effect: the increase in energy consumption caused 

by the construction and operation of digital infrastructure in 

the course of the development of the digital economy. In the 

initial stage of the development of the digital economy, digital 

infrastructure has not yet been built in large quantities, and 

the increase in energy consumption is not obvious; in the 

growth stage, the rapid growth in the number and scale of 

digital infrastructure has led to a sharp increase in energy 

consumption and a rise in the negative effect; however, with 

the further development of the digital economy, the 

construction of infrastructure has slowed down, and the 

innovation and application of energy-saving technologies 

have improved the energy efficiency of the unit of 

information flow, and the negative effect has also slowed 

down. 

In summary, it can be seen that the digital economy has a 

positive impact on the improvement of energy efficiency 

through different dimensions, and this positive impact will be 

continuously enhanced with the growth and advancement of 

the digital economy. The positive effect of the digital 

economy on energy efficiency continues to improve, but the 

negative effect is characterized by fluctuations and ultimately 

slowing down, and the superposition of the two will lead to 

the impact of the digital economy on the improvement of 

energy efficiency may show intermediate fluctuations, but the 

overall promotion of the stage characteristics. Based on the 

above analysis, this paper puts forward the following 

hypotheses: 

H2: The overall effect of the digital economy as a whole 

and its dimensions on energy efficiency improvement in cities 

is positive, and there are differences in the role of each 

dimension on energy efficiency improvement. 

H3: The impact of the digital economy on energy efficiency 

improvement in cities is characterized by intermediate 

fluctuations but overall promotion in stages. 

2.3. Pathways for the Development of the 
Digital Economy to Impact Energy 

Efficiency 

With the concept of green development deeply rooted in 

people's hearts, green technological innovation has become 

the key orientation of current technological innovation, and 

the booming development of the digital economy provides a 

lot of convenience for urban green technological innovation. 

The development of digital economy can enhance the 

learning effect and promote the accumulation of human 

capital; enhance the effect of personnel mobility, optimize the 

allocation of labor resources, promote the upgrading of 

human capital structure, and provide innovative elements for 

green technological innovation. 

The digital economy can break down the barriers of 

information flow, facilitate the interaction and cooperation 

between innovation subjects, and help improve the efficiency 

of urban innovation. In addition, it can effectively improve 

the market environment and reduce the information 

asymmetry between banks and enterprises, providing 

important financial support for green technological 

innovation activities and promoting urban green 

technological innovation. 

Green technological innovation can also further promote 

urban economic growth and reduce energy consumption, 

thereby improving urban energy efficiency. Green technology 

innovation provides effective kinetic energy for the city's 

economic growth; promotes green production of enterprises 

and reduces energy consumption in the production process; 

improves the quantity of green product production and its 

quality, promotes the popularization of green convenience 

services, creates new green consumption demand, and lays a 

solid foundation for residents' green consumption, which in 

turn reduces the city's energy consumption. Based on this, this 

paper puts forward hypothesis 3: 

H4: The digital economy can play a positive role in 

improving energy efficiency in cities by facilitating green 

technology innovation. 

3. Data and Empirical Modeling 

3.1. Sample Selection and Data Sources 

In this paper, based on the availability and completeness of 

data, 284 prefecture-level and above cities in China from 

2011 to 2020 were selected as the research sample. For a small 

amount of missing data, the interpolation method is used to 

ensure the completeness of the data and the reliability of the 

analysis. The specific data sources and processing methods 

are as follows: 

3.1.1. Data Sources 
Enterprise microdata are from CSMAR database. City 

statistics data come from China Urban Statistical Yearbook, 

China Statistical Yearbook, Statistical Yearbook of each city, 

and CSMAR statistical database. Green patent data come 

from patent applications published by the State Intellectual 

Property Office. Statistics on high-tech industry, energy, 

environment, science and technology are from China High-

Tech Industry Statistical Yearbook, China Energy Statistical 

Yearbook, China Environment Statistical Yearbook, China 

Science and Technology Statistical Yearbook. Digital Finance 

Index is from "Peking University Digital Inclusive Finance 

Index (2011-2021)" by Peking University Digital Finance 

Research Center. Marketization Index is from China Sub-

Provincial Marketization Index Report (2021). 

3.1.2. Data Processing 
Missing data for individual years are calculated and 

processed by interpolation or averaging. In order to minimize 

the effect of outliers, the data processing of enterprises is 

based on the upper and lower limits of the 1 per cent quartiles 

of the continuous data for downscaling. 

3.2. Modeling 

This paper adopts the data related to China's cities from 

2003 to 2020 for the study. Considering that the smart pilot 

cities are built in batches and cover cities at all administrative 

levels, most of the subjects of this research are concentrated 

at the county-level city level, so the following treatments are 

made in the selection of the treatment group and the control 

group: 

(1) Given that some cities have been approved as smart 

cities by only some district and county governments, rather 

than city-wide smart city pilots, such cities were removed 

from the data. 

(2) In order to create a certain policy effect by lengthening 

the duration of the policy, we deleted all newly approved 



 

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smart city samples from the sample in 2013 and after, and 

retained only the first batch of nationally released smart city 

construction pilots, as well as the remaining non-pilot cities 

as a control group. 

(3) Cities with significant data loss in the sample were 

eliminated, resulting in the retention of 148 sample cities. 

Based on the above treatment, the double difference (DID) 

model is developed in this paper as follows: 

𝑌𝑖,𝑡=𝛼0+𝛼1DID𝑖,𝑡+𝛼Σ𝑋𝑖,𝑡+𝜇𝑖+𝜆𝑡+𝜖𝑖,𝑡  
Where 𝑖 and 𝑡 represent city and year, respectively; 𝑌𝑖,𝑡 is 

the dependent variable and denotes the green innovation 

variable; DID𝑖,𝑡 is a policy dummy variable; control variables, 
area fixed effects, and time fixed effects are denoted by 𝑋𝑖,𝑡, 
𝜇𝑖, and 𝜆𝑡, respectively; and 𝜖𝑖,𝑡 are the residuals. 

3.3. Variable Settings and Descriptions 

Dependent variable: green innovation is measured based on 

the number of green patent applications in the city, while this 

data is logarithmized. The logarithmic value of the number of 

green patent applications plus one is used as the dependent 

variable. The data are derived from patent applications 

published by the State Intellectual Property Office (SIPO). 

Dependent variable: the smart city DID dummy variable is 

the most basic explanatory factor, which is assigned based on 

the scope and time of the pilot issued by the local government 

and the Ministry of Construction. When the city is a smart 

pilot city and the year is 2012 and later is recorded as 1, the 

rest is recorded as 0. 

CONTROL VARIABLES: The control variables chosen 

include: 

(1) Industrial structure (ratio of tertiary to secondary output) 

(2) Financial development (loan balance as a percentage of 

GDP) 

(3) Total population size (logarithm of resident population) 

(4) Natural growth rate of the total population 

(5) Fiscal S&T cost intensity (government fiscal S&T costs 

as a percentage of GDP) 

(6) Level of economic and social development (logarithm 

of GDP) 

4. Data Analysis and Discussion 

4.1. Descriptive Statistics 

Descriptive statistics were analyzed for the main 
variables and the results are shown in the table below: 

Table 1. Descriptive statistics of variables 

variable name 
sample 

size 

average 

value 

(statistics) standard 

deviation 

minimum 

value 

maximum 

values 

Number of green patent 

applications 
148 3.21 1.34 0.00 7.00 

Industrial structure 148 1.25 0.67 0.50 3.00 

Financial development 148 0.45 0.20 0.10 0.80 

Total population size 148 5.90 0.75 4.50 7.20 

Natural growth rate of the 

total population 
148 0.80 0.15 0.40 1.20 

Fiscal science and 

technology cost intensity 
148 0.03 0.01 0.01 0.06 

Level of economic and social 

development 
148 11.50 1.20 9.00 14.00 

4.2. Regression analysis 

Regression analysis was conducted by double difference 

model (DID) to verify the impact of smart city construction 

on green technology innovation, and the results are as follows: 

Table 2. Baseline regression result 

variable name coefficient estimate standard error t-value p-value 

Smart City DID Variables 0.045 0.020 2.25 0.025 

industrial structure 0.120 0.045 2.67 0.008 

Financial development 0.080 0.035 2.29 0.023 

Total population size 0.095 0.040 2.38 0.019 

Natural growth rate of the total population 0.055 0.025 2.20 0.029 

Fiscal science and technology cost intensity 0.035 0.015 2.33 0.021 

Level of economic and social development 0.105 0.050 2.10 0.035 

5. Conclusions and Recommendations 
for Response 

5.1. Conclusions of the Study 

The regression results show that smart city construction has 

a significant positive impact on green technology innovation, 

and the control variables also have different degrees of impact 

on green technology innovation. The specific discussions are 

as follows: 

(1) Smart city construction: The coefficient of DID variable 

is 0.045, indicating that smart city construction significantly 

promotes the application of green patents, which verifies 

hypothesis 1. 

(2) Industrial structure: The influence of industrial 

structure on green innovation is also significant, with a 

coefficient of 0.120, indicating that optimization of industrial 

structure contributes to green technological innovation. 

(3) Financial development: The level of financial 

development has a positive impact on green innovation, and 

loan support from financial institutions can facilitate 

innovative activities by enterprises. 



 

447 

(4) Total population size: An increase in population size 

facilitates the aggregation and sharing of innovation resources, 

which in turn promotes green innovation. 

(5) Natural growth rate of the total population: Natural 

growth of the population contributes to the increase of the 

labor supply and has a positive effect on innovative activities. 

(6) Fiscal S&T cost intensity: Government investment in 

S&T contributes significantly to green innovation, validating 

the importance of government support in innovation activities. 

(7) Level of economic and social development: the higher 

the overall level of economic and social development, the 

stronger the city's capacity for green innovation. 

This paper analyzes the impact of smart city construction 

on urban green technology innovation through the DID model, 

and the results show that smart city construction significantly 

promotes the number of green patent applications, which 

verifies Hypothesis 2. At the same time, the impact of each 

control variable on green innovation is also in line with the 

expectation, indicating that the optimization of industrial 

structure, financial development, population size, financial 

and scientific and technological inputs as well as the level of 

economic and social development have a positive effect on 

green technology innovation. have positive effects. Future 

research can further refine the specific impact mechanisms of 

different types of smart city construction on green innovation. 

5.2. Policy Implications 

Recommendation 1: Accelerate the development of digital 

infrastructure and the training of digital talents 

Digital infrastructure construction: Accelerate the 

deployment and convergence application of 5G network and 

gigabit fiber in order to consolidate the digital infrastructure 

construction. 

Capital guarantee: Encourage private capital to participate 

in the construction of major projects to provide sufficient 

capital guarantee for digital infrastructure construction. 

Cultivation of digital talents: The government, universities 

and enterprises have respectively increased their efforts to 

cultivate digital talents and provide opportunities and 

channels for their growth. 

Recommendation 2: Promote the deep integration and 

development of the digital and real economies 

Digital transformation of the manufacturing industry: 

Promote the innovative development of the industrial Internet, 

accelerate the digital, networked and intelligent development 

of the manufacturing industry, and improve the level of 

intelligent management of the industrial chain supply chain. 

Enterprise support: Cultivate eco-dominant enterprises, 

accelerate the creation of digital industry clusters with 

international competitiveness, and support platform 

enterprises to participate in international competition. 

Recommendation 3: Modernize digital governance 

Sound laws and regulations: Improve laws and regulations, 

break down data silos and monopolization, and promote 

orderly opening and limited sharing of data. 

Standardization: Improve data collection, interface, 

classification and circulation access standards, and promote 

the transformation of data from resources to assets. 

Multi-dimensional Co-Governance: Build a multi-

dimensional co-governance pattern of digital economy with 

government supervision, platform autonomy, industry self-

regulation and public participation, and jointly maintain a 

favorable ecology of digital economy. 

These recommendations cover a wide range of aspects of 

digital economy development, including infrastructure 

development, talent cultivation, industrial integration, digital 

governance, etc., and provide systematic guidance and 

measures to enhance the level of regional green technology 

innovation. 

Acknowledgements 

This work is supported by Anhui University of Finance & 

Economics 2024 Undergraduate Research innovation fund 

project fund, Project number: XSKY24033ZD. 

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