Research on the Mechanism of the Green Innovation of Enterprises Empowered by Digital Technology from the Perspective of Value Co-Creation

Abstract

To help enterprises utilize digital technologies to increase their green innovation awareness and behavior and further clarify the “black box” of this process, this study first develops a theoretical framework to explain the mechanism of the functional attributes of digital technology, stakeholder value co-creation, and enterprise green innovation. Data are subsequently gathered from 342 manufacturing enterprises, and the meditation and moderation hypotheses are empirically analyzed using hierarchical regression and the bootstrapping method. A robustness test is conducted via data grouping. The findings indicate that digital technology openness and affordance have a positive effect on green product innovation and process innovation through value co-creation between businesses and stakeholders. Additionally, digital technology self-growth positively moderates the indirect effect of digital technology affordance on the green innovation of enterprises through value co-creation.

1. Introduction

Green development is not only an inevitable path to achieving sustainable economic and environmental development but also an inevitable choice for local enterprises to practice sustainable, high-quality development. The new generation of digital technologies such as big data, cloud computing, 5G, the Internet of Things, and artificial intelligence, as the core production factors for the development of new quality productivity, are gradually empowering the production and innovation practice activities of enterprises and promoting the transformation of traditional industries toward digitalization, intelligence, and greening [1]. However, even within the same industry, different enterprises have very different dynamics and characteristics in terms of their degrees of digital technology application and green innovation efficiency and effectiveness [2]. Therefore, in the current era of the digital economy, effectively applying digital technology to promote green innovation and development is urgently needed to realize high-quality development.

Existing studies have confirmed that the application of digital technology by enterprises has the dual role of “improving the quality and efficiency” of green innovation [3] and promoting the establishment of a symbiotic and competitive relationship network between multiple enterprises to realize synergistic green innovation [4]. However, few articles have explored the internal mechanism of green innovation enabled by digital technology. Compared with traditional innovation, green innovation presents the following two significant characteristics: first, a long innovation cycle, large investment, multidisciplinary cross-cutting, and high risk [5] and, second, a significant double positive externality, which not only results in an innovation spillover effect but also triggers an environmental spillover effect by reducing the external environmental costs in the production process [6]. Thus, it is necessary to understand the awareness and behavior of enterprise green innovation from the “social man” perspective rather than from the “economic man” perspective; that is, with the gradual increase in the awareness of green products and services among subjects with multiple interests, a significant “push” toward enterprise green innovation activities is produced. This means that as the awareness of the green products and services of multiple stakeholders gradually increases, it will have a significant “forcing” effect on the green innovation activities of enterprises. Therefore, this study argues that green innovation is actually a process of value co-creation among various types of stakeholders to maximize value and that it is necessary to reveal the interaction and collaboration mechanisms among various subjects.

In summary, from the perspective of value co-creation, this study constructs a process model of the interaction between enterprises and their stakeholders to carry out green innovation, and incorporates the functional attributes of digital technology into the theoretical framework to explore and analyze in depth the role of digital technology in empowering enterprises to carry out green innovation in terms of the related paths and mechanisms.

2. Theoretical Analysis and Research Hypotheses

2.1. Definitions of Relevant Concepts and Theoretical Models

2.1.1. Digital Technology and Its Functional Attributes

Digital technology is a combination of various types of information, computing, communication, and connectivity technologies [7], including hardware, software, and network technology, covering a new generation of information technology, such as artificial intelligence, 5G, big data, cloud computing and the Internet of Things. Some scholars have reported that the reason why digital technology, as a virtual entity, can play a strong role in the practice of enterprise development depends mainly on its two most basic and unique attributes, immateriality and computability [8], as well as its three functional attributes embodied in the application process—openness, affordance and self-growth [9].

First, owing to the immateriality of data, digital objects must rely on physical entities to function [9] and have certain structures and modes; i.e., the same set of digital objects can be embedded in different physical entities to allow the corresponding technology to function, with mobility and non-stickiness, which derives the two major functional attributes of digital technology—openness and affordance. Openness refers to the extent to which a digital technology allows different subjects to participate and share [10], which is usually reflected in the scope and number of immaterial components of the digital technology that are allowed to be connected to the outside world according to the environment and needs of use. Conversely, affordance refers to the extent of the possibility of digital technology providing relevant functions for a specific user [11]. In fact, the process of digital technology functioning is not a simple input–output process but rather a process constructed by users, i.e., the process in which digital technology is combined with application scenarios, interacts with users’ needs and knowledge, and helps users accomplish tasks and create value. Second, at the root, the underlying principle of digital technology is to transform information into binary “0” and “1” values, and it calculates the numbers “0” and “1” in accordance with certain rules regarding the arrangement and combination of data characteristics for the algorithmic operation process [12]; this computability allows digital technology to be based on various types of algorithms for access, modification, or updating, which results in self-growth characteristics. Self-growth is reflected in digital technology in the actual application process of repeated self-editing and self-updating through continuous machine learning and iteration to meet external needs [13]. Therefore, based on the above analysis, as well as previous studies, this study argues that there are three functional attributes of digital technology, including openness, affordance, and self-growth.

The above three functional attributes of digital technology reflect a progressive relationship in real-life applications. Openness emphasizes that digital technology components are migratable and scalable, broadening the boundaries of enterprise production and operations activities, and affordance emphasizes that digital technology is interactive and that users can activate different functions embedded in the material entities of digital objects in accordance with their subjective will, thus, realizing different purposes. Self-growth occurs throughout the whole process of the openness and affordance of digital technology. In the process of continuous “data feeding”, data and algorithms support each other and jointly promote the algorithms to become more intelligent and accurate [14]. In addition, unlike the openness and affordance of human control, self-growth presents the characteristics of autonomy, serendipity, and randomness. With the continuous upgrading of digital technology, its development speed is gradually accelerating with the growth speed of human intelligence, and digital technology may be alienated into a force that is constructed independently from physical reality and transforms the physical world in an all-round and multilevel way [12].

2.1.2. Green Innovation of Enterprises

Green innovation is a fusion of green development and innovation, and at the enterprise level, the essence of enterprise green innovation is the process of optimizing product design and creating new production methods, which aim to improve an enterprise’s business performance and reduce its negative impact on the environment by improving the efficiency of its resource utilization. Unlike the literature, which uses green patent data to measure the effectiveness of corporate green innovation, this study uses a results-oriented approach to measure corporate green innovation in the following two dimensions: product innovation and process innovation [15]. Green product innovation refers to the use of environmentally friendly materials and the green upgrading of products to reduce their environmental impact. Green process innovation aims to reduce energy consumption in the production or recycling process and improve resource and energy efficiency.

2.1.3. Value Co-Creation

The concept of value co-creation was first formally proposed by Prahalad and Ramaswamy in 2000, who argued that value co-creation is a model of the co-creation of value between consumers and enterprises [16]. With the development of the theory of value co-creation, the connotation of value co-creation has the following two main representative directions: first, value co-creation based on the logic of customer experience, which emphasizes the provision of personalized products and services for customers [16], and second, value co-creation based on the service-dominant logic, which emphasizes the process of interactions between the various subjects involved in value co-creation [17]. This study follows the mainstream understanding of value co-creation based on the service-dominant logic and defines value co-creation as the process of creating value through the interaction among and integration of multiple resources to maximize the benefits of each participating subject in a certain system for themselves, other participating subjects, and even the system as a whole [18].

2.1.4. Enterprise Green Innovation Value Co-Creation System Based on Digital Technology

Under the guidance of the national high-quality development strategy, enterprises not only consider maximizing their own economic interests but also consider the impact of their production and operations activities on the social environment from the perspective of sustainable development and actively carry out green innovation activities. These activities are actually the result of value co-creation through frequent interactions between enterprises and various types of stakeholders on the topic of social responsibility [19]. With the arrival of the digital economy, enterprises, as the main body of innovation, are more conveniently and closely connected with other social entities by means of various digital technologies, and this study argues that digital technologies empower the process of green innovation by facilitating value co-creation between enterprises and stakeholders.

From the process dimension of value co-creation, value co-creation between enterprises and stakeholders includes the following four main stages: connection and interaction, information acquisition, resource utilization, and performance and feedback [20]. In the context of green innovation, this study constructs a value co-creation system based on digital technology for enterprises’ green innovation (shown in Figure 1).

First, in the stage of connection, interaction, and information acquisition, with the help of the shared digital network platform, enterprise managers can obtain a keen sense of value and establish a strategic direction that meets the dual needs of the market and society, open the mechanism of identifying “green stakeholders”, and establish a value network focusing on green innovation, while at the same time, stakeholders integrate their own demands into the internal control process through the digital platform. Second, in the resource utilization stage, with the help of an enterprise digital production system, through the analysis and processing of diverse and heterogeneous information and resource coupling, the production efficiency of the enterprise can be improved, and the interests of all parties can be achieved in the process of joint production to realize value creation that meets the value demands of all stakeholders and ultimately realize the maximization of green value overflow. Finally, in the performance and feedback stage, with the help of an enterprise information monitoring and feedback system, the enterprise can capture the information changes of green innovation stakeholders, establish a timely response strategy and adjust the production and operation plan according to internal and external environmental changes to maximize the effectiveness of realizing green innovation, further maintain the stability of the enterprise’s green innovation and value co-creating relationship network, and realize the symbiotic development of all participating subjects.

2.2. Research Hypotheses

On the basis of the above theoretical model, this study intends to further test the role of the relationships among various functional attributes of digital technology, value co-creation, and green innovation through the construction of an empirical research framework.

2.2.1. Digital Technology Openness and Enterprise Green Innovation

The impact of the openness of digital technology on enterprise green innovation occurs mainly in the process of the identification and acquisition of internal and external resources by enterprises; i.e., by relying on the openness of digital technology to build various types of information platforms, enterprises are able to break down the information barriers between them and their stakeholders, realize the open sharing of information, and help realize green innovation. From the perspective of information resource acquisition, relevant digital technology can broaden the enterprise’s resource acquisition channels and allow it to realize the collection and organization of green, low-carbon environmental protection and other related information [21]. From the perspective of knowledge integration, digital technology can help increase the breadth and depth of the enterprise’s knowledge search, help it to be more agile and efficient in searching for and finding new technologies and knowledge, and help it realize the reconstruction and updating of the existing green knowledge base. Specifically, with the help of digital technology, on the one hand, an enterprise can strengthen its internal R&D personnel, as well as the communication and learning between enterprises, to encourage enterprises to better absorb cutting-edge knowledge resources and provide a solid foundation for enterprises to realize green product innovation [22]. On the other hand, digital technology can help enterprises follow up on the latest production process, make reasonable adjustments and improvements to the existing production process, optimize the allocation of resources, better control the emission of pollutants, and realize the green process innovation of enterprises [23].

Therefore, this study proposes the following hypotheses:

H1. 

Firms that apply digital technologies with high levels of openness improve their green innovation activities.

H1a. 

Digital technology openness positively affects enterprises’ green product innovation.

H1b. 

Digital technology openness positively influences enterprises’ green process innovation.

2.2.2. Digital Technology Affordance and Enterprise Green Innovation

In the era of the digital economy, data have become one of the important production factors that fuel enterprise development; whether enterprises can take the initiative to grasp this unique resource, actively integrate internal and external knowledge, and internalize production and management knowledge to form a digital processing capability is the key to enhancing their innovative performance [24], and this process is the functional embodiment of digital technology affordance.

Specifically, on the one hand, with the continuous and deep application of digital technology, enterprises can realize the effects of the mining, processing, and application of various types of information on green innovation with the help of new-generation information technology, such as big data and cloud computing, and the real-time processing of massive amounts of unstructured and nonstandardized information [25]; formulate a product development strategy with users’ greening needs at the core; accurately identify the market’s greening consumer demand; accurately position the product needs of target customer groups [26]; and help realize green product innovation. On the other hand, compared with traditional equipment, the use of digital equipment can replace many low-end programmed labor elements, reduce the loss of raw materials by manual labor, realize refined production [3], maximize the reduction in the levels of raw material consumption and pollutant and waste emissions in the production process, and enhance the performance of green innovation in enterprises. In addition, enterprises can establish more digital and intelligent production control and management measures based on digital technologies such as 5G and artificial intelligence. In addition, a more digital and intelligent production control system established on the basis of digital technologies such as 5G and artificial intelligence can help carry out the continuous tracking and evaluation of the production process of enterprises, make dynamic improvements in a timely manner, improve the ability of enterprises to respond to emission reductions, and, thus, promote the green process innovation of enterprises.

Therefore, this study proposes the following hypotheses:

H2. 

The application of digital technologies with high degrees of affordance by enterprises facilitates their green innovation activities.

H2a. 

Digital technology affordance positively influences enterprises’ green product innovation.

H2b. 

Digital technology affordance positively influences enterprises’ green process innovation.

2.2.3. Mediating Role of Value Co-Creation

According to the theory of value co-creation, the interactive behavior among multiple subjects relies mainly on information exchange and feedback among one another, and the application of digital technology promotes the transparency and availability of information to a large extent [27]; therefore, enterprises can strengthen the degree of value co-creation between them and their stakeholders through relevant digital technology, which in turn empowers the development of green innovation activities.

On the one hand, by relying on some highly open digital technologies, enterprises broaden the channels of value co-creation, helping them establish connections with various stakeholders and form a network of shared digital platforms for green innovation, which can not only enhance the transparency of information to alleviate information asymmetry [28] and prompt enterprises to predict the green innovation expectations of stakeholders, but also broaden the channels of access to the resources of enterprises, enhance the heterogeneity of knowledge and resources, and establish a solid foundation for the development of green innovation activities. Moreover, by building a digital platform, enterprises encourage the government, consumers, suppliers, the media, shareholders and other stakeholders to participate more widely in the decision-making process of enterprise green innovation and, in the process, improve the efficiency of information and resource exchange and cooperation between participating subjects and, to a certain extent, enhance mutual trust, thus, boosting the development of enterprises’ green innovation activities.

Therefore, this study proposes the following hypotheses:

H3. 

Value co-creation between enterprises and stakeholders mediates the relationship between digital technology openness and green innovation.

H3a. 

Value co-creation between enterprises and stakeholders mediates the relationship between digital technology openness and enterprises’ green product innovation.

H3b. 

Value co-creation between enterprises and stakeholders mediates the relationship between digital technology openness and green process innovation.

On the other hand, the application of highly affordable digital technology provides enterprises and their stakeholders with more tools for communication and interaction, and the quality and depth of data-driven information interaction are further improved so that enterprises can build a digital production system that matches their green innovation needs and bring users and other stakeholders together to realize value co-creation with the participation and interaction of multiple subjects. In addition, the powerful data processing capability demonstrated by digital technology can accelerate the integration and application of various types of green innovation knowledge and resources in the value co-creation network of enterprises [29], and the digital technology penetrating all levels of the enterprise business can gradually integrate with its traditional organization and production mode, increasing all aspects of the enterprise’s production and operation activities toward greening and intelligence. In addition, the efficiency of the enterprise’s internal resource allocation can be improved, interdepartmental collaboration can be further strengthened, and the enterprise’s internal resource allocation efficiency can be further enhanced.

Therefore, this study proposes the following hypotheses:

H4. 

Value co-creation between enterprises and stakeholders mediates the relationship between digital technology affordance and enterprises’ green innovation.

H4a. 

Value co-creation between enterprises and stakeholders mediates the relationship between digital technology affordance and enterprises’ green product innovation.

H4b. 

Value co-creation between enterprises and stakeholders mediates the relationship between digital technology affordance and corporate green process innovation.

2.2.4. Moderating Role of Self-Growth in Digital Technology

Unlike the two functional attributes of openness and affordance, self-growth embodies the self-updating and iterating of digital technologies, but such updating and iterating are characterized by the uncertainty of arbitrary development and are a feature of nonhuman control; thus, self-growth itself does not necessarily contribute directly to the value co-creation and green innovation of enterprises and may even bring about certain uncontrollable risks [30]. Thus, self-growth needs to be implemented under the possession of a strong subjective purpose and designed under a framework or platform governance with a strong subjective purpose before it can be successful. This study argues that in the value co-creation system of green innovation, the self-growth of digital technology can be a key element for enterprises to build an information monitoring and feedback system to promote the healthy evolution of the system as a whole.

First, with the construction of the shared digital platform network and digital production system for green innovation, the degree of embeddedness of the digital technology applied by enterprises and their production and operation activities is deepening, and at this time, the advantages of the digital technology itself brought about by its self-updating and iteration are being gradually revealed. In the information-sharing link empowered by the openness of digital technology, the more self-growth the digital technology exhibits, the more it is able to help enterprises continuously optimize the combination of information platform participating subjects [31] and realize the real-time monitoring and processing of massive amounts of nonstandardized and unstructured data from which they screen the knowledge and tools related to green innovation, thus, enhancing their adaptability to the existing production and operation activities of enterprises [14]. In the resource utilization link empowered by digital technology affordance, digital technology with high-level self-growth helps enterprises continuously improve their digital production processes and improve the quality of production. Enterprises can continuously upgrade and iterate their digital production processes, and by storing, analyzing, and feeding back data on innovation efficiency and effectiveness, they can implement more precise planning and control of green innovation activities in a targeted manner and provide more effective optimization solutions for both product innovation and process innovation.

Therefore, this study proposes the following hypotheses:

H5. 

Digital technology self-growth positively moderates the relationship between digital technology openness and green innovation.

H6. 

Digital technology self-growth positively moderates the relationship between digital technology affordance and green innovation.

Second, the self-growth of digital technology has, to a certain extent, promoted the evolution of value co-creation between enterprises and stakeholders toward the goal of green innovation. In the process of value co-creation focusing on green innovation, the integration between enterprises and internal and external stakeholders is further strengthened, the information in the value co-creation network becomes more transparent, and the various behaviors of the participating subjects are transformed into data, which are monitored in real time by the relevant digital technology and evaluated in terms of all aspects. Whenever any party consciously carries out green innovation activities, the digital technologies in the value co-creation system provide strategic suggestions and programs for other stakeholders to make responsive decisions. Therefore, in this process, digital technologies with high levels of self-growth can help enterprises identify the motives and needs of stakeholders for green innovation more accurately and adjust and restructure their processes and product structures accordingly to ensure that green innovation activities are in line with the expectations of the entire value co-creation system. Therefore, this study argues that the positive impact of value co-creation on enterprises’ green innovation is further strengthened with the increase in the degree of self-growth of digital technology.

Therefore, the following hypothesis is proposed:

H7. 

Digital technology self-growth positively moderates the relationship between enterprises’ value co-creation with stakeholders and their green innovation.

Finally, summarizing the above theoretical analysis, the self-growth of digital technology is found to actually run through the entire process of the green innovation of enterprises empowered by digital technology; i.e., in the value co-creative system of green innovation, the stronger self-growth of digital technology can strengthen the intermediary mechanism of the “openness and affordance of digital technology—value co-creation—on enterprises’ green innovation”. Thus, there is a potential moderating mediation effect. In view of this, the following hypotheses are proposed:

H8. 

Digital technology self-growth positively moderates the mediating effect of digital technology openness on enterprises’ green innovation through value co-creation.

H9. 

Digital technology self-growth positively moderates the mediating effect of digital technology affordance on enterprises’ green innovation through value co-creation.

In summary, this study constructs the following empirical research framework (shown in Figure 2).

3. Research Design

3.1. Sample and Data

This study selects manufacturing enterprises in the Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei region, and Jiangxi Province, where China’s manufacturing industry is more developed, as the research object and identifies the target respondents as the middle and senior managers of enterprises who are more knowledgeable about the cooperation between enterprises and stakeholders as well as the overall operation of enterprises and who have three or more years of industry experience. Before conducting the formal research, a pre-survey phase was conducted to ensure the validity of the large amount of data obtained. The results of the survey were mainly used to test the reliability and validity of the scales used, to identify potential problems with the questionnaire, and to make timely adjustments to determine the final version of the questionnaire for use in the formal research. In the pre-survey stage, 80 questionnaires were collected. The questionnaires mainly included basic information about the enterprises and scale measurements of the relevant variables involved in this study, including digital technology openness, affordance, self-growth, value co-creation, enterprises’ green product innovation, and green process innovation, totaling 28 measurement items. According to the results of the pre-survey questionnaire, the reliability and validity of the questionnaire reached the standard level, and the results were quite satisfactory, which indicated that the questionnaire’s items were set reasonably, so the follow-up study will be conducted after the linguistic presentation of the questionnaire has been improved.

The formal research involved the following methods for distributing the questionnaire: first, through the social network of the research team via the snowball distribution of the questionnaire, and second, through the Credamo platform targeting the distribution of the questionnaire. A total of 447 questionnaires were collected, and 105 questionnaires whose answer times were shorter than 120 s, whose questionnaire quality control questions did not meet the completion requirements, and whose option answers were too consistent were excluded. A total of 342 valid questionnaires were ultimately recovered, with a valid questionnaire recovery rate of 76.51%. The specific information of the sample is shown in

Table 1. Basic information of the sample.

Content	Categories	Number	Proportion/%
Region	Yangtze River Delta	105	30.7
	Pearl River Delta	90	26.3
	Beijing–Tianjin–Hebei region	78	22.8
	Jiangxi Province	69	20.2
Industry	Manufacture of computers, communications equipment, and other electronic equipment	51	14.9
	Manufacture of automobiles and parts	61	17.8
	Electrical machinery and equipment manufacturing	51	14.9
	General and specialized equipment manufacturing	27	7.9
	Rubber and plastic products manufacturing	14	4.1
	Furniture manufacturing	6	1.8
	Pharmaceutical manufacturing	53	15.5
	Food manufacturing	49	14.3
	Textile industry	18	5.3
	Manufacture of recreational, industrial, sports, and entertainment goods	5	1.5
	Other industries	7	2
Age (years since established)	Less than 1	2	0.6
	1–5	63	18.4
	6–10	101	29.5
	11–15	79	23.1
	More than 15	97	28.4
Nature	State-owned enterprise	89	26
	Private enterprises	204	59.6
	Joint venture	48	14
	Other	1	0.3
Size (number of employees)	Less than 20	2	0.6
	21–50	38	11.1
	51–200	128	37.4
	201–500	88	25.7
	More than 500	86	25.1

.

3.2. Variable Measurement

The main variables of this study are measured using the measurement items of existing related studies and partially modified within the context of this study, using a 5-point Likert scale. The measurement items are displayed in Appendix A.

Digital technology openness (ADTO) is measured with four items adapted from Cenamor et al. [32], such as “Digital technology tools have broadened the access to information among enterprises”. Digital technology affordance (ADTA) is adapted from Chatterjee et al. [11] and contains four items, such as “The company applies digital technology tools to successfully realize the reuse of historical business data acquisition”. Digital technology self-growth (ADTG) is adapted from Yoo [13] and contains four items, such as “Our company continuously updates its knowledge of digital technology and its applications”. VCC is adapted from Shahriar et al. [33] and contains eight items covering the following four aspects: connection and interaction, accessibility of information, utilization of resources, performance and feedback; e.g., “We have achieved open and good communication and exchanges with all kinds of partners”. Enterprise green innovation (GI) is adapted from Chang [15] and is measured in the following two dimensions: green product innovation (GPDI) and green process innovation (GPRI). Enterprises’ green product innovation contains four items, such as “We use the least amount of materials for product development or design”. Enterprises’ green process innovation also contains four items, such as “Our manufacturing process reduces the consumption of raw materials”. With respect to the selection of control variables, this study selects industry, age, nature, and size with reference to existing studies.

To facilitate the perception of the following study, the abbreviation of the variables on which the entire study is based is listed in

Table 2. Abbreviation of the variables.

Abbreviation	Name of Variable
ADTO	Digital technology openness
ADTA	Digital technology affordance
ADTG	Digital technology self-growth
VCC	Value co-creation
GI	Green innovation
GPDI	Green product innovation
GPRI	Green process innovation

.

4. Data Analysis and Hypothesis Testing

4.1. Analysis of Common Method Bias and Composite Reliability

To test the reliability of the scales, the validity of the data, and the goodness of fit of each model, reliability is analyzed using SPSS 26.0, while the validity of the scales is tested by AMOS 24.0.

Harman’s single-factor test is used to test the problem of homoscedastic bias. The results of exploratory factor analysis reveal that six factors with characteristic roots greater than one are extracted, among which the variance explained by the first factor before rotation is 29.97%, which is lower than the critical criterion of 40%, indicating that the sample data do not suffer from serious homoscedastic bias problems.

As shown in

Table 3. Results of reliability and validity tests.

Variable	CITC	Cronbach’s α	CR	AVE
ADTO	0.587–0.737	0.819	0.822	0.540
ADTA	0.630–0.727	0.846	0.847	0.582
ADTG	0.593–0.657	0.805	0.806	0.509
VCC	0.646–0.733	0.900	0.900	0.530
GPDI	0.578–0.659	0.805	0.807	0.512
GPRI	0.590–0.671	0.821	0.821	0.535

, Cronbach’s α coefficients for each variable and the corresponding dimension are above the critical value of 0.8, the corrected item-total correlation (CITC) coefficients for each item are greater than 0.5, and the composite reliability (CR) values are greater than 0.8, satisfying the standard requirement of >0.5 and 0.8. This suggests that the scale used in this study proved to have good reliability for subsequent analysis. The average variance extracted (AVE) values are above the critical value of 0.5, which indicates that the scales of the variables have good validity.

In addition, validation factor analysis is used to test the fit of the model. As shown in

Table 4. Model fit coefficients.

Model	$\mathit{\chi }$2/df	RMSEA	AGFI	CFI	TLI
Six-factor (ADTO, ADTA, ADTG, VCC, GPI, GTI)	1.752	0.047	0.874	0.942	0.935
Five-factor (ADTO, ADTA, ADTG, VCC, GPI + GTI)	2.313	0.062	0.818	0.898	0.886
Four-factor (ADTO + ADTA, ADTG, VCC, GPI + GTI)	4.340	0.099	0.662	0.737	0.711
Three-factor (ADTO + ADTA + ADTG, VCC, GPI + GTI)	5.214	0.111	0.603	0.665	0.635
Two-factor (ADTO + ADTA + ADTG + VCC, GPI + GTI)	6.196	0.123	0.571	0.584	0.550
One-factor (ADTO + ADTA + ADTG + VCC + GPI + GTI)	7.495	0.138	0.457	0.479	0.437

Note: If the model fit is excellent, the metrics should meet the following requirements: $\chi$²/df < 3, RMSEA < 0.05, AGFI > 0.8, CFI > 0.9, TLI > 0.9.

, the six-factor model fit coefficients are c²/df = 1.501, root mean square error of approximation (RMSEA) = 0.038, comparative fit index (CFI) = 0.960, Tucker–Lewis index (TLI) = 0.955, and adjusted goodness-of-fit index (AGFI) = 0.887, and all the resulting indicators meet the requirements, indicating that the model has good fit and can be analyzed subsequently.

4.2. Descriptive Statistical Analysis

According to the results in

Table 5. Descriptive statistics and correlation analysis (N = 342).

	Average	Standard Deviation	ADTO	ADTA	ADTG	VCC	GPDI	GPRI
ADTO	3.222	0.914	0.735
ADTA	3.276	0.958	0.163 **	0.763
ADTG	3.596	0.861	0.301 **	0.148 **	0.714
VCC	3.361	0.824	0.462 **	0.298 **	0.301 **	0.728
GPDI	3.250	0.879	0.379 **	0.460 **	0.247 **	0.552 **	0.715
GPRI	3.406	0.876	0.185 **	0.406 **	0.198 **	0.314 **	0.515 **	0.732
VIF	-	-	1.353	1.276	1.149	1.650	1.722	-

Note: Bold numbers on the main diagonal are square roots of AVEs, ** denotes p < 0.01.

, (i) there are significant positive correlations between all the variables; (ii) the correlation coefficients are less than the square root of the AVE, which again indicates that the scale has good discriminant validity; and (iii) the variance inflation factor (VIF) of each variable is less than 5, which indicates that there is no serious problem of multicollinearity among the explanatory variables.

4.3. Hypothesis Testing

This study includes industry, age, nature, and company size as control variables in the multiple linear regression model to construct an empirical regression model to test the main effects. To assess the mediating and moderating effects, bootstrapping analysis, a technique where data is resampled extensively to determine the precision of estimates, is executed using the Process plugin in SPSS. According to Hayes [34], model 15 is used for testing the moderated mediation effect.

4.3.1. Main and Mediating Effects Tests

First, the impacts of digital technology openness and digital technology affordance on enterprises’ green innovation are examined, and the results of hierarchical regression are shown in

Table 6. Results of main effects of hierarchical regression analysis.

Dependent Variable		GI		GPDI		GPRI
		M1	M2	M3	M4	M5	M6
Control Variable	Industry	0.046	0.010	0.051	0.019	0.029	−0.003
	Age	0.002	−0.031	0.015	−0.022	−0.012	−0.032
	Nature	−0.001	0.020	0.013	0.038	−0.015	−0.003
	Size	0.081	0.080	0.126 *	0.133 *	0.015	0.006
Independent Variable	ADTO	0.320 ***		0.373 ***		0.184 ***
	ADTA		0.493 ***		0.451 ***		0.407 ***
R2		0.113	0.252	0.163	0.227	0.035	0.166
Adjusted R2		0.100	0.241	0.150	0.215	0.021	0.153
F		8.565 ***	22.666 ***	13.046 ***	19.700 ***	2.469 *	13.350 ***

*** denotes p < 0.001, and * denotes p < 0.05.

. According to the results of models 1 and 2, there is a significant positive impact of digital technology openness and digital technology affordance on enterprises’ green innovation (β = 0.320, p < 0.001; β = 0.493, p < 0.001, respectively). H1 and H2 are verified. Models 3 and 4 reflect that digital technology openness and digital technology affordance have a significant positive effect on enterprises’ green product innovation (β = 0.373, p < 0.001; β = 0.451, p < 0.001, respectively), and H1a and H2a are validated. In addition, from the regression results of models 5 and 6, digital technology openness and digital technology affordance have significant positive effects on enterprises’ green process innovation (β = 0.184, p < 0.001; β = 0.407, p < 0.001, respectively), and H1b and H2b are validated.

Next, bootstrapping is used to test the mediating effect, in which the bootstrap sample size is set to 5000 and the confidence interval is set to 95%, the results of which are shown in Table 5. According to the results in Table 5, the indirect effect paths of value co-creation as a mediating variable are all significant (none of the 95% confidence intervals contain 0), which verifies the mediating role of value co-creation, and H3 to H4 are verified. In addition, except for the direct effect of digital technology openness on enterprises’ green process innovation, which is not significant (BootCI of [−0.066, 0.156] contains 0), the direct effects of the remaining paths are all significant, indicating that value co-creation plays a fully mediating role in the relationship between digital technology openness and enterprises’ green process innovation and partially mediates all other paths of action. The specific proportions of direct and indirect effects are shown in

Table 7. Bootstrapping test results for intermediary effects.

	Relationship Paths	Effect	Boot Standard Error	95% Confidence Interval		Effect Ratio
				BootCI Inferior Limit	BootCI Upper Limit
Total effect: H3		0.268	0.043	0.183	0.353
Direct effect	ADTO→GI	0.157	0.047	0.065	0.249	58.50%
Indirect effect	ADTO→VCC→GI	0.111	0.029	0.058	0.172	41.50%
Total effect: H4		0.390	0.034	0.323	0.458
Direct effect	ADTA→GI	0.356	0.033	0.292	0.420	91.19%
Indirect effect	ADTA→VCC→GI	0.034	0.012	0.012	0.061	8.81%
Total effect: H3a		0.359	0.048	0.264	0.454
Direct effect	ADTO→GPDI	0.213	0.052	0.111	0.314	59.20%
Indirect effect	ADTO→VCC→GPDI	0.147	0.033	0.084	0.214	40.80%
Total effect: H4a		0.405	0.041	0.325	0.485
Direct effect	ADTA→GPDI	0.356	0.037	0.283	0.430	88.09%
Indirect effect	ADTA→VCC→GPDI	0.040	0.017	0.019	0.083	11.91%
Total effect: H3b		0.177	0.052	0.076	0.279
Direct effect	ADTO→GPRI	0.101	0.058	−0.012	0.214	57.10%
Indirect effect	ADTO→VCC→GPRI	0.076	0.031	0.021	0.143	42.90%
Total effect: H4b		0.376	0.042	0.293	0.458
Direct effect	ADTA→GPRI	0.355	0.042	0.273	0.438	94.54%
Indirect effect	ADTA→VCC→GPRI	0.021	0.010	0.005	0.043	5.46%

.

4.3.2. Moderating Effects Test

In this study, hierarchical regression is used to test the moderating effect of digital technology self-growth, and the test results are shown in Table 6. According to the results of

Table 8. Hierarchical regression results for moderating effects.

Dependent Variable		GI
		M7	M8	M9	M10	M11	M12
Control Variable	Industry	0.033	0.042	−0.003	−0.005	0.017	0.013
	Age	−0.006	−0.005	−0.034	−0.028	−0.049	−0.049
	Nature	−0.018	−0.019	−0.002	−0.009	−0.005	−0.020
	Size	0.072	0.058	0.066	0.061	0.037	0.021
Independent Variable	ADTO	0.271 ***	0.293 ***
	ADTA			0.468 ***	0.482 ***
	VCC					0.462 ***	0.470 ***
Moderating Variable	ADTG	0.169 **	0.208 ***	0.184 ***	0.200 ***	0.115 *	0.161 **
Interaction Term	int1		0.180 ***
	int2				0.114 *
	int3						0.148 **
R2		0.138	0.168	0.284	0.297	0.262	0.281
Adjusted R2		0.123	0.150	0.272	0.282	0.249	0.266
F		8.963 ***	9.628 ***	22.192 ***	20.137 ***	19.820 ***	18.690 ***

*** denotes p < 0.001, ** denotes p < 0.01, and * denotes p < 0.05.

, the coefficients of the interaction terms int1 (ADTO*ADTG), int2 (ADTA*ADTG), and int3 (VCC*ADTG) are significantly positive (β = 0.180, p < 0.001; β = 0.114, p < 0.05; β = 0.148, p < 0.01, respectively), which suggests that digital technology self-growth positively moderates the effects of digital technology openness, digital technology affordance, and value co-creation on enterprises’ green innovation. Thus, H5, H6, and H7 are verified.

To visualize the results of the moderating effects, this study further plots the moderating effects of digital technology self-growth, as shown in Figure 3a–c. First, Figure 3a,b illustrate that with an increase in the degree of digital technology self-growth, the influence of digital technology openness on enterprises’ green innovation is amplified. Similarly, the effect of digital technology affordance on enterprises’ green innovation is also heightened. This suggests that digital technology self-growth exerts a positive moderating influence on both the connection between digital technology openness and enterprises’ green innovation and the link between digital technology affordance and enterprises’ green innovation. H5 and H6 are verified. Second, Figure 3c shows that enterprises with high levels of digital technology self-growth are better able to enhance the positive impacts of value co-creation on enterprises’ green innovation than enterprises with low levels of digital technology self-growth, which accounts for the digital technology self-growth having a positive moderating effect on the connection between value co-creation and enterprises’ green innovation, meaning H7 is validated.

4.3.3. Moderated Mediation Effects Test

On the basis of the previous tests of moderating and mediating effects, this study further tests the mediating effect with moderation according to model 15 in the Process plugin, controlling for industry type, years of establishment, nature of the enterprise, and enterprise size, and the results are shown in

Table 9. Moderated mediation effect testing results.

Variable	ADTG	Effect	Boot Standard Error	95% Confidence Interval
				BootCI Inferior Limit	BootCI Upper Limit
ADTO→VCC→GI	M − 1SD	0.128	0.033	0.067	0.198
	M	0.163	0.031	0.106	0.226
	M + 1SD	0.198	0.041	0.122	0.280
Moderated mediating effect		0.041	0.024	−0.005	0.090
ADTA→VCC→GI	M − 1SD	0.058	0.018	0.025	0.094
	M	0.083	0.017	0.0211	0.118
	M + 1SD	0.109	0.021	0.068	0.153
Moderated mediating effect		0.030	0.012	0.009	0.054

. The results in Table 9 again verify the mediating role of value co-creation in the relationships among digital technology openness, digital technology affordance, and enterprises’ green innovation, and the mediating effect of value co-creation gradually increases as the level of digital technology self-growth increases, which indicates that digital technology self-growth plays a positive moderating role in the mediating effect of value co-creation. However, the 95% confidence interval [−0.005, 0.090] of digital technology self-growth regulating the mediating effect of value co-creation on the relationship between digital technology openness and enterprises’ green innovation is zero, indicating that there is a nonsignificant moderated mediating effect, and H8 is not verified. Conversely, the 95% confidence interval of digital technology self-growth regulating the mediating effect of value co-creation on the relationship between digital technology affordance and enterprises’ green innovation [0.009, 0.054] does not contain 0, indicating that there is a significant mediating effect of moderation and that the moderation is in the second half of the path; thus, H9 is supported.

4.3.4. Results of the Hypothesis Test

First, the main tests are tested, which suggest that digital technology openness and affordance have a positive impact on enterprises’ green innovation including product innovation and progress innovation, and H1, H1a, H1b, H2, H2a, and H2b are verified. Second, bootstrapping is used to test the mediating effects of value co-creation which indicates that value co-creation has a mediating role between digital technology openness, affordance, and enterprises’ green innovation including product innovation and progress innovation, and H3, H3a, H3b, H4, H4a, and H4b are supported. Third, bootstrapping analysis is conducted to test the moderating effects of digital technology self-growth exerts on the direct effects between digital openness, affordance, value co-creation, and enterprises’ green innovation, and H5, H6, and H7 are verified. Fourth, the further moderated mediation effect tests are conducted, which suggest that there is a nonsignificant moderated mediating effect between the mediating effect of value co-creation on the relationship between digital technology openness and enterprises’ green innovation, and H8 is not verified. However, there is a significant moderated mediating effect between the mediating effect of value co-creation on the relationship between digital technology affordance and enterprises’ green innovation, and H9 is supported.

The full structural model with path coefficients is shown in Figure 4.

4.4. Robustness Test

The heterogeneity of the data sources may affect the robustness of the findings; therefore, this study conducts group tests for different types of manufacturing enterprises on the basis of the control variables (industry type, year of establishment, the nature of enterprises, and enterprise size), and the results are shown in

Table 10. Robustness test results.

Path	Ungrouped Data	Industry 1	Age (Less than 10)	Nature (Private Enterprise)	Size (Less than 200)
Number	342	176	166	204	168
ADTO→GI	0.320 ***	0.280 ***	0.303 ***	0.307 ***	0.288 ***
ADTO→VCC	0.461 ***	0.391 ***	0.472 ***	0.438 ***	0.428 ***
ADTA→GI	0.493 ***	0.532 ***	0.450 ***	0.460 ***	0.477 ***
ADTA→VCC	0.287 ***	0.281 ***	0.287 ***	0.230 ***	0.234 **
VCC→GI	0.496 ***	0.571 ***	0.494 ***	0.466 ***	0.441 ***
ADTO→VCC→GI	0.441 ***	0.545 ***	0.452 ***	0.409 ***	0.388 ***
ADTA→VCC→GI	0.384 ***	0.456 ***	0.397 ***	0.379 ***	0.348 ***
int1→GI	0.180 ***	0.172 *	0.188 *	0.186 **	0.226 **
int2→GI	0.114 *	0.116	0.140	0.078	0.079
int3→GI	0.148 **	0.131	0.250 ***	0.106	0.193 **
Path	Ungrouped Data	Industry 2	Age (More than 10)	Nature (Nonprivate Enterprise)	Size (More than 200)
Number	342	166	176	138	174
ADTO→GI	0.320 ***	0.392 ***	0.312 ***	0.355 ***	0.324 ***
ADTO→VCC	0.461 ***	0.562 ***	0.439 ***	0.498 ***	0.505 ***
ADTA→GI	0.493 ***	0.428 ***	0.519 ***	0.583 ***	0.483 ***
ADTA→VCC	0.287 ***	0.286 ***	0.279 ***	0.394 ***	0.343 ***
VCC→GI	0.496 ***	0.390 ***	0.472 ***	0.543 ***	0.528 ***
ADTO→VCC→GI	0.441 ***	0.252 **	0.415 ***	0.486 ***	0.492 ***
ADTA→VCC→GI	0.384 ***	0.290 ***	0.353 ***	0.374 ***	0.415 ***
int1→GI	0.180 ***	0.176 *	0.152 *	0.171 *	0.127
int2→GI	0.114 *	0.164 *	0.094	0.160 *	0.114
int3→GI	0.148 **	0.230 **	0.027	0.195 *	0.077

Note: To make the sample sizes of the two groups close to one another, industry 1 includes computer, communication equipment, and other electronic equipment manufacturing; automobile and parts manufacturing; general and special-purpose equipment manufacturing; rubber and plastic products manufacturing; furniture manufacturing; and recreation, industry, sports, and entertainment supplies manufacturing. Industry 2 includes electrical machinery and equipment manufacturing, pharmaceutical manufacturing, food manufacturing, textiles, and other industries. *** denotes p < 0.001, ** denotes p < 0.01, and * denotes p < 0.05.

. Regarding the grouping test of the main and mediating effects, the effects of digital technology openness and digital technology affordance on enterprises’ green innovation are positive and significant in all groupings, and the mediating effect of value co-creation is also significant. The results of the group test of the moderating effect of digital technology self-growth show that the significance of the moderating effect of digital technology self-growth varies somewhat across groups, which, on the one hand, is limited by the sample capacity and, on the other hand, provides a new way of exploring the influence of different types of manufacturing enterprises on the model.

5. Conclusions and Recommendations

5.1. Research Conclusions

This study explores the role of various functional attributes of digital technology in influencing the value co-creation and green innovation between enterprises and stakeholders. The main findings are as follows. (i) Digital technology openness and digital technology affordance have a positive effect on enterprises’ green product innovation and green process innovation. (ii) Value co-creation mediates the relationships among digital technology openness, digital technology affordance, and enterprises’ green innovation. (iii) Digital technology self-growth enhances the positive effects of digital technology openness, digital technology affordance, and value co-creation between enterprises and stakeholders on green innovation to a certain extent and positively moderates the mediating effect of value co-creation between digital technology affordance and enterprises’ green innovation, which is a moderated mediating effect.

5.2. Theoretical Contributions

The theoretical contributions of this study include, first, revealing the factors influencing enterprises’ green innovation in the digital economy era from the perspective of the application function of digital technology. Unlike existing studies that focus only on the impact of a single dimension of enterprise digitization, this study examines the role of multiple functional attributes of digital technology in relation to enterprise green innovation, deepening the understanding of digital-technology-enabled enterprise green innovation practices. Second, this work expands the research on new methods and new contexts of value co-creation theory. This study develops a theoretical model and an empirical framework for the mechanism of the value co-creation process between enterprises and stakeholders in the specific context of green innovation, which, to a certain extent, makes up for the insufficiency of the extant research on the mechanism of conducting enterprises’ green innovation behaviors using digital technologies. Third, this study reveals the unique role of the functional attribute of digital technology’s self-growth. This study reveals that digital technology openness and affordance have a direct effect on enterprises’ green innovation, whereas self-growth, as a distinctive feature of digital technology that distinguishes it from traditional information technology, has an indirect effect on green innovation; i.e., stronger self-growth is able to reinforce the system in existing digital technological frameworks or platform networks, which makes it clear that various types of digital technology empower enterprises’ green innovation. This finding clarifies the boundary conditions for various types of digital technologies to enable enterprise green innovation.

5.3. Practical Contributions

In contrast to the theoretical contributions in the previous section, the practical contributions mainly focus on how the various stakeholders of the enterprises should take action to promote the green innovation activities of the enterprise. First, at the government level, the government plays a leading role. On the one hand, the government should rationally plan the implementation of green innovation incentives, pollution taxes, and fees to help enterprises realize their economic benefits and promote their green innovation activities. On the other hand, the government should also do a good job of increasing public awareness, attracting public participation in monitoring, while reducing the cost of public participation, guaranteeing that the public can voluntarily express public opinion, so that the public’s strategy evolves in the direction of monitoring. Second, at the level of the public, the public should play the role of public supervision. The public should be aware of green consumption, set up the green product consumption concept, and strengthen the supervision of the enterprise’s environmental pollution behaviors, and then force the enterprise to implement green innovation activities. Third, at the level of universities and research institutes, actively carry out university-enterprise cooperation. University-enterprise collaboration in the integration of production, learning, and research can not only promote the linkage of enterprise demand and university scientific research, realize the innovation and upgrading of production technology, and improve the efficiency of enterprise resource utilization, but it can also strengthen the independent training of top innovative talents, and create a group of excellent enterprise scientific and technological innovation talents through the joint cultivation of talents, providing a strong source of power for the enterprise’s green innovation.

5.4. Managerial Insights

First, enterprises should attach great importance to the positive impact of digital technology on their green innovation and continuously consolidate the foundation of digital technology; at the same time, to clarify the role of digital technology in empowering their green innovation practices, enterprises should apply digital technology in a more targeted way to assist the production and operation activities of enterprises and make efforts to realize the transformation of the results of enterprises’ green innovation. Second, when enterprises carry out green innovation, they should proactively identify the needs of various stakeholders in carrying out green innovation activities, strengthen communication and cooperation with stakeholders, and encourage stakeholders to provide relevant knowledge and resources, all of which help enterprises eliminate traditional thinking and stereotypes to seek green products to meet the needs of multiple parties and the green concepts of enterprises’ production and operations. Finally, in the era of the digital economy, the internal and external environments of enterprises are constantly changing, and enterprises should maintain a high degree of sensitivity, iterate and upgrade their digital technology tools in a timely manner, enhance their self-growth, and adjust their production and operations strategies according to their own resources and the external environment to increase green innovation efficiency.