# Construction and Path Analysis of Enterprise Green Technology Innovation Model Using Data Mining

Authors: Xiuxiu Chen; Hua Bu
Journal: Mobile Information Systems
 (2022)

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## Abstract

With the rapid increase of resource consumption and ecological protection demand, the economic growth model of China has also changed to focus on efficiency and quality. In the future, the circular economic model will be the main direction of sustainable development. According to the analysis of international development trends, green consumption has become the development trend of the times. Some developing countries also put forward the concept of green trade in the process of trade. It results in a severe living environment and challenges for some Chinese enterprises. For this challenge, China should grasp the economic development trend and change the business model by adopting the green technology innovation model. It will reduce consumption and pollution, improve efficiency, and, also, build the enterprise green technology innovation model to greatly improve the production efficiency and resource utilization of the enterprises. This paper uses data mining technology to establish a mathematical model of cluster analysis. It describes the process of enterprise technological innovation in detail and analyzes the power source of enterprise technological innovation and several commonly used models. Through this model, the enterprise technological innovation ability can be comprehensively improved. It focuses on the analysis of the enterprise green technology innovation path based on data mining. It analyzes the enterprise green technology innovation path from the points of reducing transaction costs and improving the allocation efficiency of innovation elements. According to this path, the enterprise transaction costs can be reduced to a certain extent and the allocation efficiency of enterprise elements can also be realized.


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## Body

## 1. Introduction

As a result of the significant environmental difficulties that have arisen due to China’s economic expansion in recent decades, the Chinese government has backed the notion that clean water and lush mountains are priceless assets. Green technological innovation may be utilized to develop green technology and green goods into competitive advantages for businesses. In the context of green development, it is important to consider whether a company can use green technological innovation to continually improve its competitiveness. The important means for enterprises to implement sustainable development strategies is green technology innovation. The green technology innovation should be consistent with the needs of environmental development, realize the improvement of resource utilization rate, and save enterprise raw material investment and energy to a certain extent. It should also reduce gold exchange pollution and external losses in production and consumption links and strengthen the internalization ability of environmental costs. The goal is to comprehensively popularize enterprises’ green technology innovation, green marketing ability, green products, and green consumption and improve enterprises’ green technology innovation ability. Green innovation capability has a decisive impact on the industry, enterprise, and product market competitiveness of the country. The improvement of green technology innovation can better update management measures, improve factor allocation efficiency, and accelerate economic development.There are various aspects of green technology innovation having effects on business success. Green manufacturing has a considerable beneficial influence on environmental and social performance. According to the impacts of green technological innovation on financial performance, environmental performance, and social performance of businesses, green process innovation may have a large beneficial impact on organizational sustainability. However, green product innovation has no meaningful impact on any sort of performance. The data mining technology used in this paper integrates many different subjects, such as machine learning, artificial intelligence, recognition pattern, database, statistics, and visualization technology. An important branch of data mining is cluster analysis. It belongs to unsupervised pattern recognition. Due to the current surge in the number of data objects, it is becoming more and more cumbersome. The scale of enterprises is also expanding rapidly. A large number of enterprises began to build green technology innovation models and explore the development path of this aspect. Therefore, they urgently hope to use data mining techniques to study the green technology innovation models and paths.The main innovations of this paper are as follows:(a)
When studying enterprise green technology innovation, this paper first describes the process of enterprise green technology innovation and analyzes the power source and the two commonly used driving models. It then establishes the enterprise green technology innovation model on this basis(b)
A large amount of data is to be studied when analyzing the green innovation technology of enterprises. Therefore, the data mining technology, which is widely used at present, is adopted. By introducing the data mining process, describing the basic structure of the data mining system, the clustering analysis mathematical model given to data mining is established along with important technical supportThe rest of the research paper is organized as follows: Section2 will explain the related work done in this research. It is being followed by data mining and other concepts related to data mining in Section 3. Enterprise green technology innovation model construction and analysis of enterprise green technology innovation path based on data mining is explained in Sections 4 and Section 5, respectively. Finally, Section 6 includes the concluding remarks about this research paper.


## 2. Related Work

One of the main activities of the daily operation of enterprises is green technology innovation. As the scale of enterprises continues to expand, the application of green technology innovation can reduce the production pollution of enterprises and significantly improve the economic benefits. In 1994, Braun and wield scholars first put forward the concept of green technology innovation. It pointed out that green technology innovation is divided into recycling technology, pollution control technology, and ecological process technology [1]. In the same year, Chinese academics proposed green technology innovation, arguing that the main substance of green technology innovation is reflected in green goods, green technology, and green energy, in order to increase strategic awareness of green innovation [2]. Gasparin et al. proposed that green technology is derived from ecological innovation and provides a more ideal environment for ecological innovation through the application of green strategy [3]. The European Commission defines green technology innovation as innovation of improving the application efficiency of natural resources by focusing on sustainable development, reducing and avoiding interference with the environment [4]. Sergey et al. also defined green technology innovation as a technical system based on economic laws and ecological principles. However, it can only give play to its advantages in saving resources, but it cannot reduce the negative effects of the ecological environment, such as recycling technology and green products [5]. Xian et al. compared the traditional innovation activities and green technology innovation based on the definition that exploratory innovation can realize new technology routes and new knowledge, reduce pollution during enterprise production and manufacturing, and has high economic benefits [6]. Analyzing the external factors of enterprises, Peiran pointed out that the main motivation of enterprise green technology innovation is the improvement of public environmental protection awareness, pressure from government management, and international trade demand [7]. Fan pointed out from the research on the current situation that government leadership belongs to the mainstream phenomenon. At the same time, the government supervision directly affects the green technology innovation ability of enterprises. The government has formulated strict policy requirements to improve the green technology innovation ability of enterprises due to which the supervision is strengthened [8]. Rashid et al. used the structural equation model to explore 148 manufacturing and modeling enterprises in the Pearl River Delta of Guangdong Province. The findings revealed that the government’s required rules and regulations, as well as competitive pressure, had a direct influence on firms’ green environmental protection innovation successes. However, the public environmental protection pressure and government environmental laws and regulations had little effect [9]. The factors that affect the green technology innovation of enterprises also include customer income and environmental protection consciousness. The strengthening of customer environmental protection consciousness can promote green technology innovation to a certain extent. From the internal perspective of enterprises, some scholars pointed out that green technology capability and green orientation have an impact on green technology innovation [10]. Chars conducted a comprehensive survey of foreign-funded enterprises in China and pointed out that internal and external green guides will have a positive impact on the strategic environment enterprise. It includes green technology capability of environmental management system, R&D cost investment, and strategic flexibility. These factors can greatly promote the green innovation technology enterprise [11].


## 3. Data Mining

In this section, the concepts of data mining, clustering analysis method based on data mining, and mathematical model of cluster analysis based on data mining will be discussed. It will help clarify the overall structure of data mining and how it is resolving technology-related issues. The explanation is given below.


### 3.1. Data Mining Concepts

Data mining is defined as extracting or mining knowledge in a large amount of data. Mining belongs to vivid words. Some unprocessed and processed materials can be grasped, and some useful value features can also be found [12]. Data mining integrates multidisciplinary technologies, mainly pattern analysis, data analysis, statistics, high-performance computing, machine learning, data visualization, neural network, and information retrieval.Some scholars regard data mining as a knowledge discovery process. The following is the process flow of knowledge discovery:(a)
Data Cleaning: It filters noise and inconsistent data(b)
Data Integration: It combines multiple different types of data sources or single data source(c)
Data Selection: analysis and retrieval of various data(d)
Transform Data: It uses aggregation or summary to transform data into an optimal mining format(e)
Data Mining: It intelligently extracts knowledge information(f)
Pattern Evaluation: It recognizes the potential pattern of knowledge by measuring some interest(g)
Knowledge Representation: It uses knowledge representation and visualization technology to display all the knowledge information minedThis paper uses the traditional concept of data mining in which the data mining is the process of mining knowledge in data warehouse, database, and other information bases. Figure1 shows the basic process of data mining [13].Figure 1
Basic process of data mining.The main components of traditional data mining system are as follows [14]:
(a)
Data Warehouse, Database, and Other Information Base: It is one of a groups of data warehouses, databases, and spreadsheets, the latter information base can integrate and clean up data(b)
Data Warehouse or Database Server: It is based on the data mining request sent by the user; the responsibility of the data server is to extract all kinds of required data [15](c)
Knowledge Base: It belongs to domain knowledge and can guide the search or evaluate the degree of interest in the resulting pattern(d)
Data Mining Engine: It is the main part of the data mining system. The component includes a group of functional modules, which can realize data association analysis, characterization research, cluster analysis, classification, deviation analysis, and evolution(e)
Pattern Evaluation: Through the interactive data mining module and pattern evaluation module, interest measurement is introduced into the search for potentially interesting patterns(f)
Graphical User Page: The function of this module is to realize the information interaction between the data mining system and users. Users can set data mining tasks on the system, plan the query process, realize focused search, and carry out exploratory data mining based on the intermediate results of data mining [16]. Figure 2 shows the structure of the data mining systemFigure 2
Data mining system structure.The advanced stage of online analytical processing (OLAP) is called data mining. It can use high-level data understanding technology. Compared with data warehouses, data mining has strong analysis and processing ability and has certain development potential [17].


### 3.2. Clustering Analysis Method Based on Data Mining

Cluster analysis may be classified in a variety of ways. When analyzing a single implementation approach, it can typically be separated into many categories, including pedigree clustering, clustering based on the target function, clustering based on equivalence relationships, and clustering based on graph theory. The clustering method is regarded to be judged by the partition set and part contained in the sample set. Whether the clustering analysis result is accurately judged or not according to the selected method and clustering principle.Fuzzy clustering based on objective function is usually called prototype-based clustering because it is necessary to establish an accurate objective function according to the clustering prototype. The traditional clustering analysis can only detect the spherical feature points. Bezdek proposes a new clustering prototype when detecting spherical clusters, and its characteristics are described in the following Table1.Table 1
Compare prototype features.
Clusters of dimensionsClustering principleFunctional featuresr=0P0(v’,Ø) = v:PointDetect subsets of hyperspheres and toroidal structuresr=1P1(v’,s) = L(v,‘s):LineDetect a subset of patterns of linear structuresr=2P2(v’,s1,s2) = L(v,‘s1,s2):PlaneDetect a subset of patterns for planar structures2≤r≤p−1Pn-1(v’,{si}) = HP(v,’{si}):HyperplaneDetect a subset of patterns of hyperplane structuresThe fuzzy clustering analysis algorithm based on objective function is dependent on clustering prototype. It is necessary to reasonably use a priori knowledge to select the best prototype mode and formulate a criterion for judging reasonable similarity in combination with distance measure analysis [18].


### 3.3. Mathematical Model of Cluster Analysis Based on Data Mining

Assuming thatX=x1,x2,⋯,xn represents all objects to be clustered, that is, people often say the universe. Any object xi1≤i≤n in the universe is a sample. The object is described using several parameter values, and the parameter values represent the attributes of each item. Therefore, each object Xi corresponds to a vector Pxi=xi1,xi2,⋯,xim), and 1≤j≤m in xij is the assignment of xi feature on the j, and Pxi represents the feature vector of xii. Cluster analysis is used to study the spatial distances and distribution characteristics of the featured vectors corresponding to samples in domain X. Based on the relationship of the distances between different samples, redivide X1, X2,...Xn, and among which Xn represents the noninteractive pattern subsets {x1, x2,...,xn}, those subsets meet the following conditions:
(1)X1∪X2∪⋯∪XK=X,Xi∩Xj=Φ1≤i,j≤k,i≠j.Wij membership function represents the membership relationship between sample xj1≤J≤n and subset class xi1≤i≤k, which is expressed by the following formula:
(2)wxixj=wij=1xj∉Xi0xi∈Xj.The above formula indicates that the membership function should meet the requirements ofwij∈Mhk. Each sample can only belong to one class, and each subclass is a non-empty set.
(3)Mhk=wikwij∈0,1,∑i=1kwij=1,∀j;0<∑j=1nwij<n,∀i.The sample membership does not belong to either or state in the real environment. It is necessary to introduce fuzzy clustering into the fuzzy theory and divide the sample set X into a large number of fuzzy subsets, represented byX~1,X~2,⋯,X~k, so that the wij sample membership function can be extended from the binary case of {0,1} to the [0,1] area and meet the following conditions:
(4)∪i=1ksuppX~i=X,wij∈0,1,∑i=1kwij=1∀,0<∑j=1nwij<n.The above expression sup is the support set of fuzzy set.


## 3.1. Data Mining Concepts

Data mining is defined as extracting or mining knowledge in a large amount of data. Mining belongs to vivid words. Some unprocessed and processed materials can be grasped, and some useful value features can also be found [12]. Data mining integrates multidisciplinary technologies, mainly pattern analysis, data analysis, statistics, high-performance computing, machine learning, data visualization, neural network, and information retrieval.Some scholars regard data mining as a knowledge discovery process. The following is the process flow of knowledge discovery:(a)
Data Cleaning: It filters noise and inconsistent data(b)
Data Integration: It combines multiple different types of data sources or single data source(c)
Data Selection: analysis and retrieval of various data(d)
Transform Data: It uses aggregation or summary to transform data into an optimal mining format(e)
Data Mining: It intelligently extracts knowledge information(f)
Pattern Evaluation: It recognizes the potential pattern of knowledge by measuring some interest(g)
Knowledge Representation: It uses knowledge representation and visualization technology to display all the knowledge information minedThis paper uses the traditional concept of data mining in which the data mining is the process of mining knowledge in data warehouse, database, and other information bases. Figure1 shows the basic process of data mining [13].Figure 1
Basic process of data mining.The main components of traditional data mining system are as follows [14]:
(a)
Data Warehouse, Database, and Other Information Base: It is one of a groups of data warehouses, databases, and spreadsheets, the latter information base can integrate and clean up data(b)
Data Warehouse or Database Server: It is based on the data mining request sent by the user; the responsibility of the data server is to extract all kinds of required data [15](c)
Knowledge Base: It belongs to domain knowledge and can guide the search or evaluate the degree of interest in the resulting pattern(d)
Data Mining Engine: It is the main part of the data mining system. The component includes a group of functional modules, which can realize data association analysis, characterization research, cluster analysis, classification, deviation analysis, and evolution(e)
Pattern Evaluation: Through the interactive data mining module and pattern evaluation module, interest measurement is introduced into the search for potentially interesting patterns(f)
Graphical User Page: The function of this module is to realize the information interaction between the data mining system and users. Users can set data mining tasks on the system, plan the query process, realize focused search, and carry out exploratory data mining based on the intermediate results of data mining [16]. Figure 2 shows the structure of the data mining systemFigure 2
Data mining system structure.The advanced stage of online analytical processing (OLAP) is called data mining. It can use high-level data understanding technology. Compared with data warehouses, data mining has strong analysis and processing ability and has certain development potential [17].


## 3.2. Clustering Analysis Method Based on Data Mining

Cluster analysis may be classified in a variety of ways. When analyzing a single implementation approach, it can typically be separated into many categories, including pedigree clustering, clustering based on the target function, clustering based on equivalence relationships, and clustering based on graph theory. The clustering method is regarded to be judged by the partition set and part contained in the sample set. Whether the clustering analysis result is accurately judged or not according to the selected method and clustering principle.Fuzzy clustering based on objective function is usually called prototype-based clustering because it is necessary to establish an accurate objective function according to the clustering prototype. The traditional clustering analysis can only detect the spherical feature points. Bezdek proposes a new clustering prototype when detecting spherical clusters, and its characteristics are described in the following Table1.Table 1
Compare prototype features.
Clusters of dimensionsClustering principleFunctional featuresr=0P0(v’,Ø) = v:PointDetect subsets of hyperspheres and toroidal structuresr=1P1(v’,s) = L(v,‘s):LineDetect a subset of patterns of linear structuresr=2P2(v’,s1,s2) = L(v,‘s1,s2):PlaneDetect a subset of patterns for planar structures2≤r≤p−1Pn-1(v’,{si}) = HP(v,’{si}):HyperplaneDetect a subset of patterns of hyperplane structuresThe fuzzy clustering analysis algorithm based on objective function is dependent on clustering prototype. It is necessary to reasonably use a priori knowledge to select the best prototype mode and formulate a criterion for judging reasonable similarity in combination with distance measure analysis [18].


## 3.3. Mathematical Model of Cluster Analysis Based on Data Mining

Assuming thatX=x1,x2,⋯,xn represents all objects to be clustered, that is, people often say the universe. Any object xi1≤i≤n in the universe is a sample. The object is described using several parameter values, and the parameter values represent the attributes of each item. Therefore, each object Xi corresponds to a vector Pxi=xi1,xi2,⋯,xim), and 1≤j≤m in xij is the assignment of xi feature on the j, and Pxi represents the feature vector of xii. Cluster analysis is used to study the spatial distances and distribution characteristics of the featured vectors corresponding to samples in domain X. Based on the relationship of the distances between different samples, redivide X1, X2,...Xn, and among which Xn represents the noninteractive pattern subsets {x1, x2,...,xn}, those subsets meet the following conditions:
(1)X1∪X2∪⋯∪XK=X,Xi∩Xj=Φ1≤i,j≤k,i≠j.Wij membership function represents the membership relationship between sample xj1≤J≤n and subset class xi1≤i≤k, which is expressed by the following formula:
(2)wxixj=wij=1xj∉Xi0xi∈Xj.The above formula indicates that the membership function should meet the requirements ofwij∈Mhk. Each sample can only belong to one class, and each subclass is a non-empty set.
(3)Mhk=wikwij∈0,1,∑i=1kwij=1,∀j;0<∑j=1nwij<n,∀i.The sample membership does not belong to either or state in the real environment. It is necessary to introduce fuzzy clustering into the fuzzy theory and divide the sample set X into a large number of fuzzy subsets, represented byX~1,X~2,⋯,X~k, so that the wij sample membership function can be extended from the binary case of {0,1} to the [0,1] area and meet the following conditions:
(4)∪i=1ksuppX~i=X,wij∈0,1,∑i=1kwij=1∀,0<∑j=1nwij<n.The above expression sup is the support set of fuzzy set.


## 4. Constructing Enterprise Green Technology Innovation Model

In this section, the enterprise green technology innovation process, analysis on the power source of green technology innovation, and building a green technology innovation model will be discussed. It will help explain the construction of green technology innovation model enterprise. The explanation is given below.


### 4.1. Enterprise Green Technology Innovation Process

The essence of green technological innovation is a special technological innovation because it adds social and environmental benefits to different links of technological innovation. As a result, a complex technological innovation is formed. It is the combination of Rosenberg’s technological innovation process to form a new comprehensive model which is shown in Figure3. Thus, a green technological innovation process can be obtained [19].Figure 3
Green technology innovation process.People are transforming the demand for green products into the demand of the green market. The progress of green requirements for science and technology has become an inexhaustible driving force to speed up the innovation of green science and technology. Once green demand and green technology intersect, the enterprise will conceive a new idea. For example, the idea is consistent with the future development interests of the enterprise, and the enterprise will apply the idea to the enterprise’s R&D stage. If the product can only be sold when the social green demand is met at the R&D stage, the social green demand will also affect the product’s sales volume and subsequently the final sales volume.


### 4.2. Analysis of the Power Source of Green Technology Innovation

Generally, the core of innovation theory lies in the role of market demand and technological development in promoting technological innovation. There are distinctions between green innovation and standard innovation activities, as well as paying attention to the environmental advantages of innovation. Therefore, the power source of green innovation comes from the market acting on technological demand. It also pays attention to the interference of the environment to innovation. Nowadays, the academic field has formulated a unified view on green innovation, and experts have formulated a two-source model and three-source model for green innovation.


#### 4.2.1. Two-Source Driven Model

In the early 1980s, a mode of promoting market development with technology was launched in the form of a two-source driven model, which is shown in Figure4. The two-source driving model points out that the market driving force and technology driving force are the main driving forces for the enterprises to carry out green innovation. Once the demand driving force and technology driving force form a joint force, it will accelerate the development of green technology innovation. Technological power factors include technological equipment, technological level, green technology, technological capability, technological opportunity, reserved knowledge, and input innovation resource capability. Market power factors include market growth, market demand, market competition, prediction of market prospect, innovation profit, and product structure. Market factors and technological factors are directly related to enterprise innovation power, ability, innovation decision-making, and pressure. Science and technology have advanced at such a quick pace that they have become the technological foundation for green innovation. It determines the future development trend of enterprise green innovation in combination with the market demand and jointly promotes the rapid development of enterprise green innovation under the reasonable function.Figure 4
Two-source driving force model of green innovation.


#### 4.2.2. Three-Source Driven Model

At present, the most commonly used is the three-source driven model, which promotes enterprise green innovation based on market, technology, and environmental regulation, as shown in Figure5. Enterprise green innovation behavior also forms results under the action of the market, technology, and environmental regulation. The three driving elements in the green innovation system have diverse roles that have a direct influence on the changing form of system behavior. The combination of the three drives the enterprise innovation system to form a circular state. The basic condition for enterprises to apply green innovation is the driving force of environmental regulation. Without this driving force, enterprises can only complete traditional innovation and not green innovation. The basis of green innovation is the driving force of the market. The purpose of enterprises is to pursue interests. Based on this feature, enterprises can be promoted to choose green innovation mode only when not only the green demand in the market is large but the profit space is large. The basic guarantee for enterprises to implement green innovation drives technological progress. Technology’s quick advancement enhances the likelihood of green innovation technology’s success and also provides technical assistance for green innovation.Figure 5
Three-source driving force model of green innovation.


### 4.3. Building a Green Technology Innovation Model

At present, with the rapid development of computer technology, system science, and technology tools, it has become technical support for studying the functions of green technology innovation systems. Scholars have repeatedly tried to form a causal relationship between different objects in the innovation system and study various behaviors in the green technology innovation system. The essence of the green technology innovation mechanism is the mode formed between different functions, structures, and characteristics in the green technology innovation system. Based on the basic principle of system science dominance, it is concluded that the green technology innovation mechanism in the behavior of the green technology innovation system belongs to a dominant parameter. Different green technology innovation mechanisms also have differences with their corresponding models in forming a variety of behavior performances of green technology innovation systems. Therefore, exploring and analyzing green technology innovation technology is the key for enterprises. The main body of green technology innovation is the enterprise, which is reflected in all levels of the green technology innovation system. Each enterprise’s technological innovation culture, technological innovation experience, and ability have a direct impact on its technological innovation behavior and attitude. The basic characteristics are slow to change speed and strong stability. Based on the basic control principle of slow variables over fast variables, enterprise innovation experience, culture, and ability can be selected as control parameters to control the variables of technological innovation mechanism. The green technology innovation mechanism is illustrated in Figure6. On the basis of existing technological innovation experience, culture, and ability, green technology innovation businesses dominate the operating mechanism of technological innovation. The solidification state of the mechanism is the basic system and system of green technology innovation and further dominates the structural behavior of the green technology innovation system, which is opposite to the direction, attitude, evaluation, and cognition [20].Figure 6
Dynamic mechanism model of green technology innovation.


## 4.1. Enterprise Green Technology Innovation Process

The essence of green technological innovation is a special technological innovation because it adds social and environmental benefits to different links of technological innovation. As a result, a complex technological innovation is formed. It is the combination of Rosenberg’s technological innovation process to form a new comprehensive model which is shown in Figure3. Thus, a green technological innovation process can be obtained [19].Figure 3
Green technology innovation process.People are transforming the demand for green products into the demand of the green market. The progress of green requirements for science and technology has become an inexhaustible driving force to speed up the innovation of green science and technology. Once green demand and green technology intersect, the enterprise will conceive a new idea. For example, the idea is consistent with the future development interests of the enterprise, and the enterprise will apply the idea to the enterprise’s R&D stage. If the product can only be sold when the social green demand is met at the R&D stage, the social green demand will also affect the product’s sales volume and subsequently the final sales volume.


## 4.2. Analysis of the Power Source of Green Technology Innovation

Generally, the core of innovation theory lies in the role of market demand and technological development in promoting technological innovation. There are distinctions between green innovation and standard innovation activities, as well as paying attention to the environmental advantages of innovation. Therefore, the power source of green innovation comes from the market acting on technological demand. It also pays attention to the interference of the environment to innovation. Nowadays, the academic field has formulated a unified view on green innovation, and experts have formulated a two-source model and three-source model for green innovation.


### 4.2.1. Two-Source Driven Model

In the early 1980s, a mode of promoting market development with technology was launched in the form of a two-source driven model, which is shown in Figure4. The two-source driving model points out that the market driving force and technology driving force are the main driving forces for the enterprises to carry out green innovation. Once the demand driving force and technology driving force form a joint force, it will accelerate the development of green technology innovation. Technological power factors include technological equipment, technological level, green technology, technological capability, technological opportunity, reserved knowledge, and input innovation resource capability. Market power factors include market growth, market demand, market competition, prediction of market prospect, innovation profit, and product structure. Market factors and technological factors are directly related to enterprise innovation power, ability, innovation decision-making, and pressure. Science and technology have advanced at such a quick pace that they have become the technological foundation for green innovation. It determines the future development trend of enterprise green innovation in combination with the market demand and jointly promotes the rapid development of enterprise green innovation under the reasonable function.Figure 4
Two-source driving force model of green innovation.


### 4.2.2. Three-Source Driven Model

At present, the most commonly used is the three-source driven model, which promotes enterprise green innovation based on market, technology, and environmental regulation, as shown in Figure5. Enterprise green innovation behavior also forms results under the action of the market, technology, and environmental regulation. The three driving elements in the green innovation system have diverse roles that have a direct influence on the changing form of system behavior. The combination of the three drives the enterprise innovation system to form a circular state. The basic condition for enterprises to apply green innovation is the driving force of environmental regulation. Without this driving force, enterprises can only complete traditional innovation and not green innovation. The basis of green innovation is the driving force of the market. The purpose of enterprises is to pursue interests. Based on this feature, enterprises can be promoted to choose green innovation mode only when not only the green demand in the market is large but the profit space is large. The basic guarantee for enterprises to implement green innovation drives technological progress. Technology’s quick advancement enhances the likelihood of green innovation technology’s success and also provides technical assistance for green innovation.Figure 5
Three-source driving force model of green innovation.


## 4.2.1. Two-Source Driven Model

In the early 1980s, a mode of promoting market development with technology was launched in the form of a two-source driven model, which is shown in Figure4. The two-source driving model points out that the market driving force and technology driving force are the main driving forces for the enterprises to carry out green innovation. Once the demand driving force and technology driving force form a joint force, it will accelerate the development of green technology innovation. Technological power factors include technological equipment, technological level, green technology, technological capability, technological opportunity, reserved knowledge, and input innovation resource capability. Market power factors include market growth, market demand, market competition, prediction of market prospect, innovation profit, and product structure. Market factors and technological factors are directly related to enterprise innovation power, ability, innovation decision-making, and pressure. Science and technology have advanced at such a quick pace that they have become the technological foundation for green innovation. It determines the future development trend of enterprise green innovation in combination with the market demand and jointly promotes the rapid development of enterprise green innovation under the reasonable function.Figure 4
Two-source driving force model of green innovation.


## 4.2.2. Three-Source Driven Model

At present, the most commonly used is the three-source driven model, which promotes enterprise green innovation based on market, technology, and environmental regulation, as shown in Figure5. Enterprise green innovation behavior also forms results under the action of the market, technology, and environmental regulation. The three driving elements in the green innovation system have diverse roles that have a direct influence on the changing form of system behavior. The combination of the three drives the enterprise innovation system to form a circular state. The basic condition for enterprises to apply green innovation is the driving force of environmental regulation. Without this driving force, enterprises can only complete traditional innovation and not green innovation. The basis of green innovation is the driving force of the market. The purpose of enterprises is to pursue interests. Based on this feature, enterprises can be promoted to choose green innovation mode only when not only the green demand in the market is large but the profit space is large. The basic guarantee for enterprises to implement green innovation drives technological progress. Technology’s quick advancement enhances the likelihood of green innovation technology’s success and also provides technical assistance for green innovation.Figure 5
Three-source driving force model of green innovation.


## 4.3. Building a Green Technology Innovation Model

At present, with the rapid development of computer technology, system science, and technology tools, it has become technical support for studying the functions of green technology innovation systems. Scholars have repeatedly tried to form a causal relationship between different objects in the innovation system and study various behaviors in the green technology innovation system. The essence of the green technology innovation mechanism is the mode formed between different functions, structures, and characteristics in the green technology innovation system. Based on the basic principle of system science dominance, it is concluded that the green technology innovation mechanism in the behavior of the green technology innovation system belongs to a dominant parameter. Different green technology innovation mechanisms also have differences with their corresponding models in forming a variety of behavior performances of green technology innovation systems. Therefore, exploring and analyzing green technology innovation technology is the key for enterprises. The main body of green technology innovation is the enterprise, which is reflected in all levels of the green technology innovation system. Each enterprise’s technological innovation culture, technological innovation experience, and ability have a direct impact on its technological innovation behavior and attitude. The basic characteristics are slow to change speed and strong stability. Based on the basic control principle of slow variables over fast variables, enterprise innovation experience, culture, and ability can be selected as control parameters to control the variables of technological innovation mechanism. The green technology innovation mechanism is illustrated in Figure6. On the basis of existing technological innovation experience, culture, and ability, green technology innovation businesses dominate the operating mechanism of technological innovation. The solidification state of the mechanism is the basic system and system of green technology innovation and further dominates the structural behavior of the green technology innovation system, which is opposite to the direction, attitude, evaluation, and cognition [20].Figure 6
Dynamic mechanism model of green technology innovation.


## 5. Analysis of Enterprise Green Technology Innovation Path Based on Data Mining

This section explains how to reduce the transaction cost of enterprise green technology innovation and shows the methods to improve the allocation efficiency of enterprise green technology innovation elements. As a result, it will help analyze the enterprise green technology innovation path based on data mining. The explanation is given below.


### 5.1. Reduce the Transaction Cost of Enterprise Green Technology Innovation

The transaction cost of carrying out green technology market transaction activities is very high, and the technology transaction cost has a direct impact on the enterprise transaction mode. Therefore, in the optimal decision-making environment, an economic subject cannot sell or buy the same products at the same time. Here, the green technology R&D labor and technical labor of enterprises are divided into the following three different situations, namely, the internalization mode of technology trading service, the closed technology innovation mode, and the externalization mode of technology trading service. When enterprises adopt the closed green technology innovation mode, they should carry out green technology innovation (X) and general technology innovation (Y) from the needs of enterprise development. The entire technical innovation capability is now weak, and the efficiency of sharing technology is low. Table2 lists the types and measures of enterprise green technology innovation.Table 2
Types and measures of enterprise green technology innovation.
Type of enterprise green technology innovationEnterprise green technology innovation measuresThe weightInnovation in green production technologyGreen product design0.21Green material0.13Green technology0.11Green equipment0.17Green recycling treatment0.28Green packaging technology0.1Green production management innovationEnterprise green cost management0.11Green enterprise management mechanism0.16Green marketing mechanism0.13Construct environmental assessment and management system0.25Green networked supply chain0.35Among the measures of green production technology innovation in the above table, the one with the highest weight is the green recycling treatment, and the weight value is 0.28. As an important content of green production technology innovation, green recycling treatment can significantly reduce the input cost of enterprises and realize the recycling of production materials. In the green production management innovation, the green networked supply chain has the highest weight, and its weight is 0.35. Establishing a networked green supply chain can drive all links, reduce the input cost of all links, and improve the green technology innovation ability of enterprises.Nowadays, by refining the division of labor of scientific research in enterprises, the efficiency of technology transactions is rapidly improved in order to effectively improve the efficiency of joint technology transactions and reduce the price of technology transactions. If the third-party technology platform has very high production efficiency, the transaction mode adopted by the enterprise’s green technology innovation is the externalization of technology transaction services. Once the integrated management efficiency on the technology transaction platform decreases, the joint technology transaction efficiency of the internalization mode decreases compared to the externalization mode. At present, the number of enterprises settled on the platform has increased rapidly. The average management cost spent in the platform by each company has dropped. Therefore, the market transaction mode has a certain diffusion effect on the green technology innovation achievements of enterprises, reducing transaction costs and comprehensively improving the efficiency of technology application. The ultimate goal of marketization is to reduce the transaction cost of green technology. It is also the consequence of factor allocation optimization. At present, China is building a “green technology bank,” which has certain advantages in reducing transaction costs and providing technology docking.


### 5.2. Improve the Allocation Efficiency of Enterprise Green Technology Innovation Elements

When carrying out green technology innovation, enterprises should select green technology that matches their factor resources to improve their self-generating ability. The self-generating ability of an enterprise refers to the independent survival ability under the premise of competition and an open market environment without protection and other external help. It can get the expected profit of the market at the same time. During the operation period, the enterprise should minimize the production cost and select green technology based on the relative price of production factors. Therefore, we should make full use of the characteristics of the factor allocation structure to select corresponding services, green products, and green technologies. At the same time, the factor relative price system can express the richness of economic factors. The relative prices of different factors in the effective market can reflect the richness of the factor structure at each time point. There is no artificial interference to the factor market, and the relative prices that enterprises can see are very real. It demonstrates how the pricing system and price signal may be used to achieve the best resource allocation. The following Table3 details the numerous aspects that influence the pricing of corporate technological innovation components, both favorably and adversely.Table 3
Positive and negative factors of enterprise technological innovation factor pricing.
Positive factorsProportion of each factor (%)Negative factorsProportion of each factor (%)Resource authorization registration5%Excessive consumption of resources and energy39%The power exchange market10%Reduce performance to compete with cost27%Technological innovation achievements trading market23%Excessive pursuit of corporate interests12%Optimize resource allocation18%Aim to accumulate wealth11%According to the proportion of positive and negative factors affecting the pricing of enterprise technological innovation factors listed in the above table, the most influential of the positive factors is the technological innovation achievement trading market, which accounts for 23%. It indicates that the opening of the technological innovation achievement trading market plays a great role in promoting enterprise technological innovation. All enterprises communicate in the market to improve the innovation power of enterprises. Among the negative factors, enterprises’ excessive consumption of resources and energy accounts for the highest proportion, accounting for 39%. The results show that enterprises’ excessive dependence on resources and energy will reduce their technological innovation ability.


## 5.1. Reduce the Transaction Cost of Enterprise Green Technology Innovation

The transaction cost of carrying out green technology market transaction activities is very high, and the technology transaction cost has a direct impact on the enterprise transaction mode. Therefore, in the optimal decision-making environment, an economic subject cannot sell or buy the same products at the same time. Here, the green technology R&D labor and technical labor of enterprises are divided into the following three different situations, namely, the internalization mode of technology trading service, the closed technology innovation mode, and the externalization mode of technology trading service. When enterprises adopt the closed green technology innovation mode, they should carry out green technology innovation (X) and general technology innovation (Y) from the needs of enterprise development. The entire technical innovation capability is now weak, and the efficiency of sharing technology is low. Table2 lists the types and measures of enterprise green technology innovation.Table 2
Types and measures of enterprise green technology innovation.
Type of enterprise green technology innovationEnterprise green technology innovation measuresThe weightInnovation in green production technologyGreen product design0.21Green material0.13Green technology0.11Green equipment0.17Green recycling treatment0.28Green packaging technology0.1Green production management innovationEnterprise green cost management0.11Green enterprise management mechanism0.16Green marketing mechanism0.13Construct environmental assessment and management system0.25Green networked supply chain0.35Among the measures of green production technology innovation in the above table, the one with the highest weight is the green recycling treatment, and the weight value is 0.28. As an important content of green production technology innovation, green recycling treatment can significantly reduce the input cost of enterprises and realize the recycling of production materials. In the green production management innovation, the green networked supply chain has the highest weight, and its weight is 0.35. Establishing a networked green supply chain can drive all links, reduce the input cost of all links, and improve the green technology innovation ability of enterprises.Nowadays, by refining the division of labor of scientific research in enterprises, the efficiency of technology transactions is rapidly improved in order to effectively improve the efficiency of joint technology transactions and reduce the price of technology transactions. If the third-party technology platform has very high production efficiency, the transaction mode adopted by the enterprise’s green technology innovation is the externalization of technology transaction services. Once the integrated management efficiency on the technology transaction platform decreases, the joint technology transaction efficiency of the internalization mode decreases compared to the externalization mode. At present, the number of enterprises settled on the platform has increased rapidly. The average management cost spent in the platform by each company has dropped. Therefore, the market transaction mode has a certain diffusion effect on the green technology innovation achievements of enterprises, reducing transaction costs and comprehensively improving the efficiency of technology application. The ultimate goal of marketization is to reduce the transaction cost of green technology. It is also the consequence of factor allocation optimization. At present, China is building a “green technology bank,” which has certain advantages in reducing transaction costs and providing technology docking.


## 5.2. Improve the Allocation Efficiency of Enterprise Green Technology Innovation Elements

When carrying out green technology innovation, enterprises should select green technology that matches their factor resources to improve their self-generating ability. The self-generating ability of an enterprise refers to the independent survival ability under the premise of competition and an open market environment without protection and other external help. It can get the expected profit of the market at the same time. During the operation period, the enterprise should minimize the production cost and select green technology based on the relative price of production factors. Therefore, we should make full use of the characteristics of the factor allocation structure to select corresponding services, green products, and green technologies. At the same time, the factor relative price system can express the richness of economic factors. The relative prices of different factors in the effective market can reflect the richness of the factor structure at each time point. There is no artificial interference to the factor market, and the relative prices that enterprises can see are very real. It demonstrates how the pricing system and price signal may be used to achieve the best resource allocation. The following Table3 details the numerous aspects that influence the pricing of corporate technological innovation components, both favorably and adversely.Table 3
Positive and negative factors of enterprise technological innovation factor pricing.
Positive factorsProportion of each factor (%)Negative factorsProportion of each factor (%)Resource authorization registration5%Excessive consumption of resources and energy39%The power exchange market10%Reduce performance to compete with cost27%Technological innovation achievements trading market23%Excessive pursuit of corporate interests12%Optimize resource allocation18%Aim to accumulate wealth11%According to the proportion of positive and negative factors affecting the pricing of enterprise technological innovation factors listed in the above table, the most influential of the positive factors is the technological innovation achievement trading market, which accounts for 23%. It indicates that the opening of the technological innovation achievement trading market plays a great role in promoting enterprise technological innovation. All enterprises communicate in the market to improve the innovation power of enterprises. Among the negative factors, enterprises’ excessive consumption of resources and energy accounts for the highest proportion, accounting for 39%. The results show that enterprises’ excessive dependence on resources and energy will reduce their technological innovation ability.


## 6. Conclusions

Overall, a company’s capacity to innovate green technologies has a major beneficial impact on its competitiveness. Furthermore, it has a large positive influence on product differentiation; nevertheless, product differentiation also has a considerable mediation effect on the link between an enterprise’s green technological innovation potential and its competitiveness. The driving force of green development comes from green technological innovation, which is also the basis of ecological civilization construction. To ease the contradiction between environmental protection and economic development, the government has adopted several laws and regulations and adopted administrative means to put pressure on enterprises. Under this pressure, enterprises must take new measures which include green technological innovation to reduce the cost of occupying resources, reduce economic penalties, and greatly improve production efficiency. Therefore, this paper studies the enterprise green technology innovation model and path analysis based on data mining technology. It establishes the cluster analysis mathematical model based on data mining, establishes the enterprise green technology innovation model, analyzes the power source of enterprise green technology innovation, and lists two commonly used data source models, namely, two-source driven models and three-source driven models. On this basis, the dynamic mechanism model of enterprise green innovation is established to strengthen the ability of enterprise green technology innovation. Simultaneously, the path of corporate green technology innovation is examined in depth from two perspectives: transaction cost and factor allocation efficiency, demonstrating that strengthening enterprise green technology innovation capability may help the company grow.



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*Source: 9405579-2022-04-21.xml*