Green Technology Innovation of Energy Internet Enterprises: Study on Influencing Factors under Dual Carbon Goals

Abstract

In order to help Energy Internet (EI) enterprises develop sustainably, promote the transformation and upgrading of energy systems and achieve the goal of carbon peaking and carbon neutrality, a study on the influencing factors of green technology innovation (GTI) in EI enterprises was conducted using the Decision-making Trial and Evaluation Laboratory-Adversarial Interpretive Structure Modeling Method (DEMATEL-AISM). Through a literature review and field research, the DEMATEL-AISM-based model of the GTI influencing factors of EI enterprises was constructed on the basis of summarizing the system of GTI influencing factors of EI enterprises, visualizing the interrelationship and hierarchical structure among GTI influencing factors of EI enterprises and finally proposing relevant countermeasures and suggestions. This study shows that the proximity-level factors such as R&D investment and external cooperation directly affect the GTI of EI enterprises; the essential-level factors such as environmental regulation and development strategy are the root causes of the GTI of EI enterprises. The transition-level factors such as market competition and business model are the key nodes of the GTI of EI enterprises, and the above factors should be focused on.

1. Introduction

After global industrialization, the average carbon dioxide (CO₂) concentration in the atmosphere has reached the highest level in the past million years, and the global average temperature is 1.1 °C higher than in the pre-industrial era [1]. In the future, humans will face a series of increasingly severe climate changes and their chain reactions, such as increased extreme weather, sea level rise and ecosystem destruction. According to the Intergovernmental Panel on Climate Change (IPCC), reaching peak CO₂ emissions by 2030 and striving to achieve carbon neutrality by 2060 is expected to limit climate change to 1.5 °C [2]. In September 2020, Chinese President Xi Jinping made a commitment at the 75th general debate of the United Nations that “China will strive to peak its CO₂ emissions by 2030 and work towards achieving carbon neutrality by 2060”.

In 2011, Jeremy Rifkin proposed Energy Internet (EI) in his book “The Third Industrial Revolution”, and made EI one of the cores of the third industrial revolution [3]. EI has the ability to reduce CO₂ emissions by replacing fossil fuels with renewable energy technologies. For example, the combustion of biofuel emits an average of 35% less greenhouse gases compared to diesel fuel [4]. EI enterprises are generating, depending on their type and technical specifications, considerable economic and environmental benefits through a reduction in energy consumption and a reduction in CO₂ emissions [5]. As of 31 December 2020, a total of 66,843 EI enterprises were registered in China, an increase of 70% from the end of 2019. Among them, the number of listed enterprises increased to 332, with a total market capitalization of more than CNY 6 trillion. Green innovation refers to technological innovations that can reduce pollution, avoid energy consumption and improve the ecological environment [6]. Technological innovation is often considered an effective cause of CO₂ emission reduction because it improves energy efficiency and contributes to cleaner production [7]. In this context, green technological innovation (GTI) is expected to be an effective tool to combat climate change [8]. For a period of time, the rapid growth of global electricity demand has led to continuous changes in the internal and external environment faced by EI enterprises. The key technologies supporting the development of EI enterprises have been continuously innovated, and GTI has become an important support for EI enterprises to achieve value growth. At the same time, as an outcome of the integration of information technology and energy technology, the GTI of EI enterprises will promote the transformation and upgrading of energy systems and help the successful achievement of dual carbon goals.

Currently, numerous scholars have conducted extensive research on the factors influencing GTI. Among them, organizational factors are considered as the primary factors driving firms to engage in GTI, including internal factors such as strategy and culture and resources and capabilities, which represent the support and motivation for firms to carry out GTI [9]. In imperfect capital markets, many external investors and bank credits have cautious and conservative investment attitudes toward GTI, resulting in high external financing constraints for GTI activities. Financial system development can broaden financing channels and alleviate the financing constraints of GTI [10]. Due to the special externality of GTI, enterprises can easily lack innovation incentives, which then requires the government to play its regulatory role. Examples include using subsidy policies to stimulate innovation R&D investment and expanding corporate green growth through tax incentives, as well as sending policy signals [11]. It is easy to see that many scholars have explored the issue of factors influencing GTI from different perspectives and have achieved fruitful results. However, due to the limitations of the disciplinary field, many studies tend to focus on one or several aspects of GTI-influencing factors, and the construction of the influencing factor system is not systematic and comprehensive enough to reflect the overall situation of GTI.

Therefore, based on the clarification of the concept of GTI in EI enterprises and the three groups of enterprise, society and government, this study proposes a GTI influence factor system for EI enterprises. Then, the Decision-making Trial and Evaluation Laboratory-Adversarial Interpretive Structure Modeling Method (DEMATEL-AISM) is used to construct a model of the influencing factors of GTI in EI enterprises, in order to provide theoretical and methodological support for GTI in EI enterprises and promote the sustainable development of EI enterprises.

2. Background

2.1. Carbon Peaking and Carbon Neutrality

In December 2015, 178 countries from around the world ratified and adopted the Paris Agreement at the 21st United Nations Climate Change Conference (COP21, also known as the Paris Climate Conference), establishing the climate goal of “keeping global warming below 2.0 °C compared to pre-industrial levels, and preferably below 1.5 °C” [12].

The 1.5 °C target requires the world to reach net zero CO₂ emissions around 2050, and the 2.0 °C target requires the world to reach net zero CO₂ emissions around 2070. As of 25 December 2022, 133 countries and regions, including China, the EU and Canada, have proposed carbon neutral initiatives in terms of legislation, agreement submissions and policy statements [13].

2.2. Global Energy Development

2.2.1. Low Carbon Development

The most important issue of low carbon development is the relationship between fossil energy and renewable energy. In recent years, in order to improve the level of wind power, photovoltaic and other renewable energy consumption and utilization ratio, the construction of multi-energy complementary EI has become an important direction of energy system development. EI with distributed renewable energy generation as the core is the key to promote the low carbon transformation of energy structures.

2.2.2. High-Intelligence Development

Intelligent development drives the transformation and upgrading of energy systems to modern energy systems, and the intelligent management model represented by EI is deepening in energy systems. Through real-time and reliable communication networks and efficient and intelligent control algorithms, EI effectively integrates energy production, grid operation, customer demand, energy market and other kinds of data to achieve the goal of energy control.

2.2.3. Market-Oriented Development

Market-oriented development will break industry barriers and promote integration and innovation in the energy sector. The ICT-based EI provides an open platform for all participating entities, reduces market entry costs, conveniently connects supply and demand sides, makes transactions of energy and services more convenient and efficient, realizes win–win situations for all parties, activates public enthusiasm for entrepreneurship and innovation and provides sustainable momentum for the energy revolution.

2.3. EI under Carbon Peaking and Carbon Neutrality

To achieve carbon neutrality, the energy system has to take the lead in achieving net zero emissions and provide negative emissions. Therefore, EI becomes an important means for the energy system to meet the challenges of climate change and achieve the goal of carbon neutrality. Energy production conversion, energy transmission and consumption, energy-aware interconnection and an energy control platform are the four important dimensions of EI to reduce emissions.

2.3.1. Energy Production and Conversion

Energy production conversion mainly refers to the replacement of fossil energy with clean energy on the energy supply side, while multiple types of energy are converted to each other to accelerate the formation of a clean-energy-led energy supply structure, which is the core initiative to control carbon emissions from the source.

2.3.2. Energy Transmission and Consumption

Transmission consumption mainly refers to the energy transmission side in the form of new energy for efficient and stable transmission, to get rid of energy system transmission restrictions. The energy consumption side replaces coal, oil and gas with electricity to get rid of the dependence on fossil energy and to achieve universal access to clean energy.

2.3.3. Energy Awareness and Interconnection

Sensory interconnection mainly refers to the deep interaction and integration of energy systems and information systems, which is an important means to reduce carbon emissions in all aspects by promoting a qualitative leap in the operational efficiency of energy systems through advanced information and communication technologies.

2.3.4. Platform for Energy Controlling

Platform management mainly refers to the control of carbon emissions from EI in many aspects, such as two-way interaction of energy information and multi-energy flow energy management, to realize the supervision and management of carbon emissions in all aspects of energy production, transmission, consumption and trading, which is the basic guarantee and powerful support for carbon emission reduction in EI.

2.4. GTI of EI Enterprises

The energy transition process from firewood to coal and from oil and gas to renewable energy has led to the continuous improvement of energy utilization technologies and energy use efficiency. Braun et al. (1994) proposed the original concept of GTI, which he believed should be described as “the research, development, and application of green technologies, products, and processes, including the entire process of green technology from the source of research and development to the transformation of results and the whole process of green technology from the source of research and development to the transformation and final marketization” [6]. Compared to traditional economic development models, green technology innovation (GTI) plays a fundamental role in achieving sustainable development goals with minimal negative impacts on the natural environment [14]. However, GTI is characterized by long lead times, slow returns, and high risks, making it difficult for companies to carry out a range of green innovation activities [15].

In February 2018, the State Grid of China Co., Ltd. made it clear for the first time in its information and communication work conference that it would “Build a full-service ubiquitous power Internet of Things, build a smart enterprise, and lead a world class energy Internet enterprise with excellent competitiveness”. Wang et al. (2018) argued that an EI enterprise is a modern enterprise that integrates advanced energy technology, intelligent control technology and modern information technology with the investment, construction and operation of EI as its core and the safe, clean, efficient and intelligent use of energy as its orientation [16]. This study pioneered the concept and connotation of EI enterprise, which laid an important theoretical foundation for GTI in EI enterprises.

For a period of time, the global electricity demand has been growing rapidly, the internal and external environments faced by EI enterprises have been changing, and the key technologies supporting the development of EI enterprises have been innovating. The energy revolution, characterized by clean, low carbon, safe and efficient energy, has prompted EI enterprises to accelerate the pace of GTI, promote the development of renewable energy generation, electric vehicles and other technologies, increase the integration of energy systems with modern information technology and form a modern energy system with EI as its core. Therefore, promoting the transformation and upgrading of the energy system with GTI of EI enterprises is the key to achieving the dual carbon goals.

3. Materials and Methods

3.1. Influential Factors of GTI

Through a literature review and field research, combined with the connotation of GTI in EI enterprises, 16 factors influencing GTI in EI enterprises were sorted out and divided into 3 groups: enterprise, society and government (

Table 1. System of factors influencing GTI in EI enterprises.

Classification	Code	Factors
Enterprise	$F_1$	Technical characteristics
	$F_2$	Infrastructure
	$F_3$	Enterprise scale
	$F_4$	Human resources
	$F_5$	Organizational culture
	$F_6$	R&D investment
	$F_7$	External cooperation
	$F_8$	Business model
	$F_9$	Development planning
Society	$F_{10}$	Financial system
	$F_{11}$	Market competition
	$F_{12}$	Demand orientation
Government	$F_{13}$	R&D subsidy
	$F_{14}$	Standard protocols
	$F_{15}$	Environmental regulation
	$F_{16}$	Development strategy

).

3.1.1. Enterprise

• Technical characteristics;

GTI is characterized by long cycles, high costs, high risks and low profits, and its technology investment and operating costs are quite expensive, which makes it difficult for enterprises to promote green transformation [15]. In addition, GTI has environmental externalities, and enterprises thus bear excessive costs for green innovation and lack incentives for innovation [17].

• Infrastructure;

GTI is limited by the availability of infrastructure. For example, high power losses in aging grids and the inability of renewable energy to be consumed are serious impediments to GTI [18]. Meanwhile, an open EI trading market requires advanced communication infrastructure and real-time response [19].

• Enterprise scale;

Enterprise scale is an important factor affecting enterprise GTI [20]. Affected by the characteristics of the technology itself, there is a minimum economic scale for the innovation and use of green technologies [15]. The capital, talents and ideas that enterprises have can provide sufficient guarantee for GTI and guide them to the direction of low carbon and environmental protection.

• Human resources;

In the end, R&D activities are all about the dissemination and innovation carried out by “people”. Human resources play an active role in improving green innovation capability and promoting innovation in enterprises [21]. Human resource management can improve the innovative thinking of employees, and then influence and drive GTI [22].

• Organizational culture;

Organizational culture is the code of conduct that members of an organization follow in the long-term development process; if an organization has a green-related corporate culture, the more enthusiastic it is to carry out green innovation. For example, Wang et al. showed that a green organizational culture is conducive to promoting GTI [23].

• R&D investment;

R&D investment directly affects enterprise GTI, and its financial investment and personnel investment are regarded as the core factors of GTI [24]. Without funding, technological innovation cannot be carried out; the greater the financial investment, the more technological innovation results tend to be achieved. In addition, Miao et al. pointed out that the number of R&D personnel has a positive impact on GTI [25].

• External cooperation;

The lack of independent R&D capability is an important factor that hinders enterprise innovation, and external cooperation is necessary for enterprise GTI [26]. Enterprises can cooperate with multiple entities such as research institutes or related enterprises to accelerate the process of R&D of technological knowledge [27]. Global technological cooperation in the form of import and investment substantially increases the opportunities for the technological innovation of enterprises [28].

• Business models;

The challenge of emerging smart energy to traditional energy sources is driving innovation of green technologies in the consumer market [29]. EI business models will be shaped and become a key support for GTI [30]. GTI in EI companies requires new business models that are data driven and low carbon oriented.

• Development planning;

Green development planning facilitates the organization to implement GTI in the future. For example, under the guidance of green development planning, it is easier for managers and internal stakeholders to integrate organizational resources, thus mitigating the risk of the technological innovation process [31]. Furthermore, Ryszko found that an active environmental strategy has a strong impact on technological eco-innovation [32].

3.1.2. Society

• Financial system;

The financial system has a positive contribution to R&D financing and is an important factor influencing corporate GTI. To promote GTI, a green investment bank in the United Kingdom (UK) provides direct financial support to different industries [33]. Without the support of the financial system and its capital allocation mechanism, it is difficult for firms to carry out technological innovation activities [34].

• Market competition;

Market competition can improve the ability of firms to innovate in green technology and drive the efforts of the whole industry in technological innovation. When market competition is very intense, firms usually choose to carry out R&D activities that meet market demand in order to gain a favorable position, and their GTI is significantly and positively influenced [35,36].

• Demand orientation;

The stronger the demand for green products in the consumer market, the more corporate GTI will be stimulated. For example, El Zailani [37] et al. and Kassar [38] et al. argue that green product demand has a direct impact on GTI and is an important driver of green innovation practices in firms.

3.1.3. Enterprise

• R&D subsidies;

GTI is characterized by high investment and a long cycle, and the lack of R&D subsidies will lead to insufficient R&D investment by enterprises and make it difficult to enhance GTI [39]. The government usually gives R&D subsidies and other preferential policies to enterprise R&D projects to improve the efficiency of enterprise GTI [40].

• Standard protocols;

The realization of EI plug-and-play capability relies on standard communication interfaces, and standard conformance is a key challenge for the coordinated scheduling of EI infrastructure [41]. In the absence of security standards and communication protocols to identify device types based on load characteristics, GTI in EI companies will be seriously affected [42].

• Environmental regulation;

Environmental regulation is an important driver for enterprises to make green technology changes [43]. For example, studies by Qi et al. [26] and Ali [44] have shown that environmental regulation has a positive impact on firms’ GTI. After the strict implementation of the new Environmental Protection Law in China, firms were more inclined to carry out green innovation activities [45].

• Development strategy;

The evolution of EI is as a coexistent shared network of distributed energy systems coupled with traditional energy systems in the short and medium term. The government must provide development strategies to support this future energy innovation, with steps and targets set that will ensure that GTI can be achieved more clearly and reliably [33,46].

3.2. DEMATEL-AISM Method

The individual steps of the integrated DEMATEL-AISM method are given below, where the four preliminary steps of the DEMATEL method are used to calculate the overall interactions between the various factors and to identify the critical factors. Then, the adversarial hierarchy of the system is determined by integrating the AISM method.

3.2.1. DEMATEL

1.

Establish the direct influence matrix $O={\left[o_{ij}\right]}_{n\times n}$. Set the semantic scale of expert evaluation of influence factor relationships (Table 2), and invite experts to evaluate the strength of relationships among GTI influence factors of EI enterprises to obtain the direct influence matrix O.

$$O=\frac{1}{m}{{\displaystyle \sum }}_{k=1}^m{o}_{ij}\left(k=1,2,\dots ,m\right)$$

(1)

where $o_{ij}$ denotes the degree of influence of factor $F_i$ on $F_j$ and m denotes the number of scoring experts.

Table 2. Expert evaluation of semantic scales.

Semantic Variables	No Impact	Weak Impact	General Impact	Strong Impact
Scale	0	1	2	3

Table 2. Expert evaluation of semantic scales.

Semantic Variables	No Impact	Weak Impact	General Impact	Strong Impact
Scale	0	1	2	3

2.

Calculate the normative influence matrix $N={\left[n_{ij}\right]}_{n\times n}$. The direct influence matrix O is normalized to obtain the normative influence matrix N.

$$N=\frac{1}{\underset{1\le i\le n}{\max }{\sum }_{j=1}^n{o}_{ij}}O$$

(2)

3.

Calculate the comprehensive influence matrix $T={\left[t_{ij}\right]}_{n\times n}$. Coupling the direct influence and indirect influence relationship between the GTI influence factors of EI enterprises, the comprehensive influence matrix T is obtained.

$$T=\underset{k\to \infty }{\lim }\left(N+N^2+\dots +N^k\right)=N{\left(I-N\right)}^{-1}$$

(3)

4.

Evaluate the influence degree $e_i$, the influenced degree $f_i$, the central degree $c_i$ and the cause degree $r_i$ of each factor.

$$e_i={\sum }_{j=1}^n{t}_{ij}\left(i=1,2,\dots ,n\right)$$

(4)

$$f_i={\sum }_{i=1}^n{t}_{ij}\left(j=1,2,\dots ,n\right)$$

(5)

$$c_i=e_i+f_i$$

(6)

$$r_i=e_i-f_i$$

(7)

where $e_i$ indicates the degree of coupling influence of factor $F_i$ on other factors; $f_i$ indicates the degree of coupling influence of factor $F_i$ by other factors; $c_i$ indicates the degree of importance of factor $F_i$ in the system and $r_i$ indicates the logical influence relationship of factor $F_i$ on other factors.

3.2.2. AISM

1.

Calculate the overall impact matrix H, then consider the impact of own factors on the basis of the integrated impact matrix.

$$H=I+T$$

(8)

2.

Establish the reachable matrix $R={\left[r_{ij}\right]}_{n\times n}$, then structure the elements of the overall influence matrix by introducing a threshold value λ.

$$r_{ij}=\{\begin{array}{c}1, if h_{ij}\ge \lambda \left(i,j=1,2,\dots ,n\right)\\ 0, if h_{ij}<\lambda \left(i,j=1,2,\dots ,n\right)\end{array}$$

(9)

where $\mathsf{\lambda }=\overline{x}+\mathsf{\sigma }$, $\overline{x}$ is the mean of the factors of the matrix T and $\mathsf{\sigma }$ is the standard deviation.

3.

Calculate the reachable set $R\left(F_i\right)$, the prior set $A\left(F_i\right)$ and the common set $C\left(F_i\right)$, and perform the adversarial hierarchy with UP and DOWN rules, respectively.

If:

$$R\left(F_i\right)/A\left(F_i\right)=C\left(F_i\right)$$

(10)

then it means that all factors in $R\left(F_i\right)/A\left(F_i\right)$ can find antecedents in $C\left(F_i\right)$, and the factor is judged to be a higher/lower tier factor. Meanwhile, the ith factor in $R\left(F_i\right)/A\left(F_i\right)$ is crossed out, and this step is repeated until all factors are crossed out.

4.

Calculate the reduced point matrix $R^{\prime }$. The strongly connected factors in each level of the reachable matrix R (if $F_i$ and $F_j$ satisfy the relationship of $r_{ij}=r_{ji}=1$, then $F_i$ and $F_i$ are strongly connected factors) are taken as factors to obtain the shrinkage point matrix $R^{\prime }$.

5.

Calculate the skeleton matrix S.

$$S=R^{\prime }-{\left(R^{\prime }-I\right)}^2-I$$

(11)

4. Results

4.1. DEMATEL Calculation

First, six experts engaged in the field of EI research were invited to evaluate the degree of influence among the factors influencing GTI in EI enterprises; the expert group consisted of three university professors and three senior engineers of EI enterprises, each with eight years or more of research or practice experience. Based on the results of the degree of influence among the factors evaluated by the experts, a direct influence matrix O was derived (

Table 3. Direct impact matrix O.

O	${\mathit{F}}_1$	${\mathit{F}}_2$	${\mathit{F}}_3$	${\mathit{F}}_4$	${\mathit{F}}_5$	${\mathit{F}}_6$	${\mathit{F}}_7$	${\mathit{F}}_8$	${\mathit{F}}_9$	${\mathit{F}}_{10}$	${\mathit{F}}_{11}$	${\mathit{F}}_{12}$	${\mathit{F}}_{13}$	${\mathit{F}}_{14}$	${\mathit{F}}_{15}$	${\mathit{F}}_{16}$
$F_1$	0	3	0	0	0	3	0	3	0	0	0	0	0	3	0	0
$F_2$	0	0	0	0	0	3	1	0	0	0	0	0	0	0	0	0
$F_3$	0	2	0	2	0	2	2	0	0	0	1	0	0	0	0	0
$F_4$	0	0	0	0	0	1	1	0	0	0	3	0	0	0	0	0
$F_5$	0	0	0	0	0	3	1	0	0	0	3	0	0	0	0	0
$F_6$	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0
$F_7$	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
$F_8$	0	0	0	0	0	1	1	0	0	0	3	0	0	0	0	0
$F_9$	0	0	0	2	0	3	1	2	0	0	2	0	0	0	0	0
$F_{10}$	0	0	0	0	0	1	1	0	0	0	0	0	2	0	0	0
$F_{11}$	0	0	0	0	0	1	3	0	0	0	0	0	0	0	0	0
$F_{12}$	0	0	0	0	2	3	0	0	0	0	3	0	0	0	0	0
$F_{13}$	0	0	0	0	0	1	1	0	0	2	0	0	0	0	0	0
$F_{14}$	0	2	0	0	0	1	3	2	0	0	3	0	0	0	0	0
$F_{15}$	0	0	0	2	3	1	0	2	3	0	0	3	0	0	0	0
$F_{16}$	0	3	0	0	0	3	0	3	0	0	0	0	0	3	0	0

).

The direct influence matrix was normalized according to Equation (2), and then the combined influence matrix T was obtained according to Equation (3). Based on the influence matrix T, the influence degree, influenced degree, centrality degree and cause degree of each influence factor were obtained according to Equations (4)–(7). In order to visualize the results, a coordinate system was constructed with centrality and causality as horizontal and vertical coordinates, and the calculated results were plotted on the coordinate system (Figure 1).

4.2. AISM Calculation

According to the comprehensive influence matrix T, the node degree was more appropriate when $\mathsf{\lambda }=0.05$, which was conducive to the factor hierarchy division (Figure 2), and then the reachability matrix R was calculated according to Equations (8) and (9) in turn. On the basis of the reachability matrix R, the confrontation hierarchy division of each factor was carried out according to Equation (10) (

Table 4. Confrontation hierarchy classification results.

Levels	Results Priority	Reasons Priority
L1	$F_6$, $F_7$	$F_6, F_7$
L2	$F_2$, $F_{10}, F_{11}$, $F_{13}$	$F_{11}$
L3	$F_4$, $F_5$, $F_8$	$F_2$, $F_4$, $F_5$, $F_8$
L4	$F_3$, $F_9, F_{12}$, $F_{14}$	$F_9$, $F_{10}, F_{12}$, $F_{13}, F_{14}$
L5	$F_1$, $F_{15}, F_{16}$	$F_1$, $F_3, F_{15}, F_{16}$

). The skeleton matrix S was obtained with point reduction of the reachable matrix R according to Equation (11) (

Table 5. Skeleton matrix S.

O	${\mathit{F}}_1$	${\mathit{F}}_2$	${\mathit{F}}_3$	${\mathit{F}}_4$	${\mathit{F}}_5$	${\mathit{F}}_6$	${\mathit{F}}_7$	${\mathit{F}}_8$	${\mathit{F}}_9$	${\mathit{F}}_{10}$	${\mathit{F}}_{11}$	${\mathit{F}}_{12}$	${\mathit{F}}_{13}$	${\mathit{F}}_{14}$	${\mathit{F}}_{15}$	${\mathit{F}}_{16}$
$F_1$	0	3	0	0	0	3	0	3	0	0	0	0	0	3	0	0
$F_2$	0	0	0	0	0	3	1	0	0	0	0	0	0	0	0	0
$F_3$	0	2	0	2	0	2	2	0	0	0	1	0	0	0	0	0
$F_4$	0	0	0	0	0	1	1	0	0	0	3	0	0	0	0	0
$F_5$	0	0	0	0	0	3	1	0	0	0	3	0	0	0	0	0
$F_6$	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0
$F_7$	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
$F_8$	0	0	0	0	0	1	1	0	0	0	3	0	0	0	0	0
$F_9$	0	0	0	2	0	3	1	2	0	0	2	0	0	0	0	0
$F_{10}$	0	0	0	0	0	1	1	0	0	0	0	0	2	0	0	0
$F_{11}$	0	0	0	0	0	1	3	0	0	0	0	0	0	0	0	0
$F_{12}$	0	0	0	0	2	3	0	0	0	0	3	0	0	0	0	0
$F_{13}$	0	0	0	0	0	1	1	0	0	2	0	0	0	0	0	0
$F_{14}$	0	2	0	0	0	1	3	2	0	0	3	0	0	0	0	0
$F_{15}$	0	0	0	2	3	1	0	2	3	0	0	3	0	0	0	0
$F_{16}$	0	3	0	0	0	3	0	3	0	0	0	0	0	3	0	0

).

Further, based on the results of the hierarchical analysis and the skeleton matrix F, a counteracting multilevel recursive structural model was drawn (Figure 3).

5. Discussion and Suggestion

5.1. Enfluence Analysis

5.1.1. Centrality Analysis

Centrality is one of the most important tools widely used to analyze influence relationships. The larger the value of centrality of the factor, the more important the factor is. As can be seen from Figure 1, the top five ranking of the influencing factors in order of centrality are R&D investment, external cooperation, market competition, environmental regulation and development strategy. Therefore, the above factors play a dominant role in the GTI of EI enterprises and should be focused on.

5.1.2. Causality Analysis

Causality reflects the degree to which a factor influences other factors and the degree to which it is influenced by other factors. Factors with larger values of causality are reason factors, which are more likely to influence other factors; factors with smaller values of causality are result factors, which are more likely to be influenced by other factors.

From Figure 1, we can see that the top three factors in terms of causality are environmental regulation, development strategy and technical characteristics. Therefore, the management of the above-mentioned factors with large values of causality should be focused on. Similarly, the bottom three factors in terms of causality are external cooperation, R&D investment and market competition. Therefore, when controlling factors with small values of causality, we need to pay attention to the control of the upstream factors connected with it.

5.2. Structure Analysis

5.2.1. Loop Analysis

The presence of a directed arrow line between factors in the structure chart of the dyadic hierarchy indicates that there is a causal relationship between the factors. If the factors are bi-directional arrows, the connection is called a loop, which is a strong connection, indicating that the group of factors are causally related to each other. From Figure 3, it can be seen that there are two groups of loops among the factors influencing GTI in EI enterprises: R&D investment $F_6$ and external cooperation $F_7$, financial system $F_{10}$ and R&D subsidies $F_{13}$, indicating that the two groups of factors are strongly connected and mutually causal within the group itself. Therefore, when creating green technology, the above two groups of factors should be controlled in an integrated way to improve management effectiveness.

5.2.2. Hierarchical Analysis

From Figure 3, we can see that the GTI influencing factors of EI enterprises form a top-down hierarchical structure of five levels and three steps. The system is divided into three levels: the essential level constituted by the lowest level (L5) factors, the transitional level constituted by the middle level (L2–L4) factors, and the proximity level constituted by the uppermost level (L1) factors. The lower level indicates a stronger cause attribute, and the upper level indicates a stronger result attribute.

The essential level, the concurrent set of technical characteristics $F_1$, enterprise scale $F_3$, environmental regulation $F_{15}$ and development strategy $F_{16}$ that confront the lowermost factors in the hierarchical diagram, only affects other factors and is not influenced by other factors, indicating that the essential level factors are the most fundamental causes of GTI in EI enterprises. If we want to manage the GTI of EI enterprises fundamentally, we should focus on the attention or control of technology characteristics $F_1$, environmental regulation $F_{15}$ and development strategy $F_{16}$.

The proximity level, the confrontation with the uppermost factor in the hierarchical diagram of the concurrent set of R&D investment $F_6$ and foreign cooperation $F_7$, is only influenced by other factors without affecting other factors, indicating that the essential level factors are the most direct factors affecting the GTI of EI enterprises. To regulate the GTI of EI enterprises quickly and effectively, we can start from the proximity-level factors. However, the proximity-level factors are easily influenced by other factors, so when controlling the proximity-level factors, attention should also be paid to the control of their antecedent factors or cutting the link between them and the antecedent factors.

The transitional level, i.e., the factor located in the middle of the antagonistic hierarchy chart after removing the essential and proximate level factors, can be influenced by and affect other factors. The transitional level factors in the system both assume the role of spreading (transitional) influence and can become the source of influence themselves, affecting other factors. Therefore, it is necessary to control the transition-level factors, especially the factors with high centrality: market competition $F_{11}$, standard protocol $F_{14}$ and development planning $F_9$, and the factors with high causality: enterprise size $F_3$, standard protocol $F_{14}$ and demand orientation $F_{12}$. In addition, in most cases, it is very difficult or even impossible for EI enterprises to control some of the essential-level factors, such as technology characteristics $F_1$ and environmental regulation $F_{15}$, but the combined impact on GTI can be regulated by modulating transitional-level controllable factors (e.g., organizational culture $F_{11}$).

5.3. Methodology Analysis

From the above analysis, it can be seen that AISM is more comprehensive and requires less work than ISM in the hierarchical classification of influencing factors, and that it can clearly portray the differences in the hierarchical classification of the system from both the result and cause perspectives, and the confrontation multi-level recursive structure model constructed based on it provides managers with ideas for solving problems from both the cause and result perspectives.

In addition, Figure 3 shows that the centrality of factors calculated based on DEMATEL does not have a clear correlation with the hierarchy classified based on AISM, because the centrality of factors is obtained by summing the influence degree of factors and the influenced degree of factors, which dilutes their influence and influenced attributes, making them less relevant to express the influence effect transmission relationship.

However, Figure 3 shows a more significant relationship between the causality and the hierarchical results of factors. In general, the higher the causality of a factor, the lower the hierarchy of the factor; the lower the causality of a factor, the higher the hierarchy of the factor. This indicates that the results of the factors derived from the two methods can be checked, proved and interpreted by each other.

5.4. Suggestions

Based on the analysis of the calculation results, this study puts forward targeted suggestions for GTI in EI enterprises. The targeted development suggestions are as follows.

5.4.1. “Increase R&D” Is the Primary Content of GTI

By increasing the R&D investment of enterprises, the layout of green technology in the energy field is driven, and the effective connection between GTI and industrial upgrading development of EI enterprises is promoted; through the cooperation and innovation of enterprises, the upstream and downstream of the EI industry chain and the integration of innovation of large, medium and small enterprises are promoted, and the leading role of the government in basic research and public research is brought into play to concentrate advantageous resources to fight the battle of key core technologies.

5.4.2. “Market Operation” Is an Important Way of GTI

Through enterprise market competition to stimulate enterprise innovation, improve independent innovation ability, promote EI enterprises to user demand oriented and improve the function and experience of users with energy; through the social demand oriented pull of green economic development, create huge market demand, “reverse innovation effect” to induce EI enterprises to increase innovation investment and the formation of enterprise. The “reverse innovation effect” induces EI enterprises to increase innovation investment and form the endogenous power of innovation.

5.4.3. “Enterprise Construction” Is an Important Tool for GTI

By building a good innovation environment in enterprises, actively cultivating professional and high-level researchers, promoting the gathering of innovative talents in EI enterprises and creating a professional talent team for GTI; by creating a culture of innovation in enterprises, spreading the culture and spirit of innovation as the core and guiding various resource elements in enterprises to support GTI.

5.4.4. “Financial Support” Is an Important Guarantee for GTI

Through the development of a social GTI financial system, improve the diversified sustainable green financial guarantee mechanism, broaden the financing channels of EI enterprises and support the R&D investment of enterprises; through the government to promulgate incentive system and support policies, strengthen financial and taxation support, relieve EI enterprises of large expenses and related learning costs in the early stage of GTI and reduce the difficulty of enterprise innovation.

5.4.5. “Strategic Planning” Is an Important Prerequisite for GTI

Through the government to strengthen the implementation of all aspects of environmental regulation, the combination of environmental pollution payments and clean production tax reduction, the formation of enterprises and the market’s awareness of environmental responsibility, to stimulate EI enterprises’ GTI; through the government to implement the innovation-driven development strategy, improve the industrial policy system to stimulate technological innovation and promote effective competition and to stimulate the new momentum of high-quality development of the EI industry.

6. Conclusions

This study couples the DEMATEL-AISM method to construct a model of GTI influence factors of EI enterprises under the dual carbon goals, measures the multi-factor-driven GTI influence paths and hierarchical distribution of EI enterprises, reveals the driving structure and action mechanism of the influence factors and finally puts forward some suggestions. The main conclusions drawn from this study are as follows.

The refined index system was constructed specifically for the GTI of EI enterprises through a literature review and field research. The system has three groups, including enterprise, society and government, and 16 factors, including R&D investment, external cooperation, environmental regulation, market competition and business model. The construction of the system was systematic and comprehensive, which can effectively reflect the overall situation of the GTI of EI enterprises.

The hierarchical structure model of the GTI of EI enterprises was constructed using the DEMATEL-AISM method, which includes the essential level constituted by the lowest level (L5) factors, the transitional level constituted by the middle level (L2–L4) factors, and the proximity level constituted by the uppermost level (L1) factors. In addition, the proximity-level factors such as R&D investment and external cooperation directly affect the GTI of EI enterprises; the essential-level factors such as environmental regulation and development strategy are the root causes of GTI of EI enterprises; the transition-level factors such as market competition and business model are the key nodes of the GTI of EI enterprises.

Suggestions for EI enterprises and their stakeholders based on the different attributes and influencing relationships between factors, including increasing R&D, market operation, enterprise construction, financial support and strategic planning.