A systematic framework to improve the digital green innovation performance of photovoltaic materials for building energy system

Under the current ‘double carbon’ policy, the building materials manufacturing industry has seriously restricted the improvement of social and environmental benefits. Digital green innovation (DGI) in photovoltaic building materials enterprises (PBMES) plays a crucial role in solving the problems of high-quality environmental and economic development. In order to make the DGI of PBMES more effective, it is very critical to evaluate the performance of the DGI activities of PBMES. First, the evaluation index system is constructed. Then, it constructs the theoretical framework of the DGI performance evaluation of PBMES. After that, on the basis of combining various evaluation methods, a combination evaluation model based on compatibility and consistency was constructed and the convergence test and consistency test of the combination evaluation results were carried out by means of the variance method and Spearman rank correlation coefficient, which verified the scientificity and validity of the method. Finally, using the evaluation model, 16 PBMES were empirically studied. It reflected that the DGI performance evaluation index system of PBMES is composed of four indexes, namely, technology input, economic output, scientific and technological output, and social effect. The key factors affecting the DGI performance of PBMES are the investment in talent training, the proportion of digital technology in green products, the success rate of digital innovation product development increased by DGI cooperation, and the digital level of adopting environmental management system. This article combines consistency-based evaluation methods to not only obtain reasonable evaluation results, but also fully utilize multi-level methods to better describe the evaluation object. The means provided in this article are a new way to solve the DGI performance evaluation of PBMES.


Introduction
China is the world's largest producer and consumer of building materials.At present, the building materials industry occupies an important position in China's national industrial system, and the building materials industry promotes the rapid development of China's economy.However, with the rapid development of the building materials industry, China's building materials industry has the problem of high pollution and low profit.The problems of high pollution and low profit in the building materials industry have brought serious adverse consequences to China's economic and environmental development and seriously restricted the healthy, high-quality, and sustainable development of China's building materials industry.In September 2020, China made a commitment to the world to achieve the' double carbon' goal at the 75th United Nations General Assembly [1].In June 2022, the 14th Five-Year Plan clarified the main direction and goal of renewable energy development during the 14th Five-Year Plan period, and basically completed a clean, low-carbon, safe, and efficient energy system by 2035 [2].In November 2022, the Ministry of Industry and Information Technology, the National Development and Reform Commission and other four departments jointly issued the Implementation Plan for Carbon Peaking in BMs Industry, which proposed to ensure the carbon peaking in BMs industry before 2030 and encourage qualified industries to take the lead in achieving carbon peaking [3].The BMs industry is a key industry with huge energy consumption and carbon emissions in the industrial field.The BMs industry has a great responsibility for energy conservation and emission reduction and heavy tasks [4].Therefore, the photovoltaic BMs (PBMs) with low carbon and low energy consumption will become the mainstream of the BMs industry.
In recent years, the development of new energy represented by photovoltaic power generation has achieved remarkable results in our country, which provided new impetus for low carbon and green development of BMs industry [5].PBMs, as a new product in BMs manufacturing industry (MI), have incomparable advantages over other environmental protection BMs.At present, most of the environment-friendly BMs products and technologies can only save energy and reduce consumption for the building, but cannot generate energy for the building itself [6].In the long-term development process, the BMs MI cannot achieve the goal of 'zero energy consumption and carbon neutrality'.PBMs are new BMs that combine solar cell modules with ordinary BMs.They can meet the energy needs of buildings with photovoltaic power generation while saving energy and reducing consumption [7].The use of PBMs can greatly reduce energy consumption and environmental pollution, further promote the green development of traditional BMs MI, and accelerate industrial energy conservation and emission reduction [8].To solve the contradiction between BMs manufacturing and the dualcarbon target and energy transformation and upgrading, promote the healthy, sustainable development of China's BMs MI, and enhance the competitiveness of China's BMs industry.
The digital green innovation (DGI) of PBMs enterprises (PBMES) is an inevitable choice based on the current national policy and the rapid development of science and technology.The report to the 20th National Congress of the Communist Party of China proposed that we should respect, accommodate and protect nature, and practice the development concept [9].It is also clearly pointed out in Made in China 2025-Development Outline of China BMs MI formulated by China BMs Association that by 2025, traditional BMs MI should be comprehensively improved, mainly including the function and level of green manufacturing, green application and green cycle.At the same time put forward the strategic task of green development [10].
In recent years, the application and popularization of digital technologies have opened up a new path for the green development of PBMES.Digital technology can promote PBMES to achieve digital transformation and upgrading of energy [11].After PBMs are put into use, digital technology can effectively improve the production management, late operation and maintenance, anti-risk and other capabilities of PBMs, help PBMES to forecast and extract data, reduce costs for the follow-up operation and management of PBMES, and provide convenience for relevant stakeholders [12].At the same time to improve the effectiveness of PBMs enterprise information management, improve the transparency of enterprise information.
Therefore, under the support of relevant national policies, DGI of PBMES should be carried out, and technologies such as Internet of things, big data and artificial intelligence should be used to promote PBMES to closely integrate with today's digital technology, so that PBMES can master the development trend of scientific and technological green innovation (GI), which is conducive to improving the DGI ability of PBMES [13].While maintaining high-quality development of PBMES, problems such as energy consumption and environmental pollution can be effectively solved, which is of great significance for promoting high-quality development of national economy and economic green transformation and upgrading.
Under the premise of the rapid development of today's society and economy, in view of the current situation of energy shortage and environmental damage, the concept of green innovative development has begun to quickly integrate into various industries, and become an inevitable trend of the development of many industries [14,15].However, there is still a huge contradiction between environmental protection and the interest growth of some enterprises, especially in the BMs MI, whose products and processes are mainly developed and produced contrary to the goal of DGI.Generally speaking, the traditional enterprise performance evaluation mostly takes profit maximization as the core index to construct the financial performance evaluation system [16].Under this evaluation system, the enthusiasm of BMs MI for environmental protection, energy conservation and other aspects is greatly reduced, which will restrict the DGI and development of PBMES for a long time [17].We urgently need a set of real and effective DGI performance evaluation model to reflect the relevant performance level of PBMES so as to solve the contradiction between the interests of PBMES and DGI [18].However, China currently lacks the construction of DGI evaluation system.Therefore, we need to find a set of clear and feasible performance construction ideas to provide effective performance evaluation for DGI of PBMES, enhance the enthusiasm of mathematical GI of PBMES, and promote the healthy development of PBMES.
In view of the current performance evaluation of DGI of PBMES, in order to solve the above problems and obstacles, firstly, this paper establishes a DGI performance index evaluation system of PBMES, which can comprehensively reflect the current situation of DGI of PBMES.On the basis of this system, the DGI performance evaluation model of PBMES is constructed.Secondly, a combination evaluation model based on compatibility and consistency was constructed, and the convergence test and consistency test were carried out by means of variance and Spear man rank correlation coefficient.Thirdly, the evaluation results of DGI of PBMES are analyzed.Fourthly, based on the analysis, the empirical study of 16 PBMES was carried out.Fifth, this paper summarizes the conclusions and enlightenment that affect the performance evaluation of DGI of PBMES, and promotes the better integration and development of Chinese PBMES and DGI.
The rest of this paper is as follows.Section 2 elaborates on relevant literature on DGI of PBMES.Section 3 describes the theoretical framework and index system.Section 4 introduces the construction of a combination evaluation model based on consistency.Section 5 is empirical research.Section 6 elaborates on the revelation and deficiency of the conclusion.

DGI of PBMs
In recent years, with the rapid development of photovoltaic industry, digital innovation (DI) and GI in photovoltaic industry have attracted attention.From the perspective of literature research, Fu and Zhang (2011) conducted research on the solar photovoltaic industry in China and India, and concluded that Chinese enterprises develop rapidly in emerging green industries such as photovoltaic, which mainly focus on independent innovation research and development and are supplemented by investment and cooperation at home and abroad, among which independent innovation plays an important role in the green development of China's solar photovoltaic industry [19].Erik (2014) analyzed the photovoltaic solar power generation chain in combination with the GI value chain (GIVC), and the results showed that there was a financial deficit in each link, and it was necessary to eliminate the adverse effects of its development through technological innovation and other means [20].Riccardo et al (2016) conducted research on photovoltaic and green buildings in northeastern Italy, and the results showed that innovation plays an important role in achieving green development and promoting environmental sustainable development of photovoltaic and green building industries [21].Hussein et al (2021) pointed out that the high capital cost of PBMs requires the support of technological innovation, so as to promote the wide application of PBMs [22].Haitham et al (2021) studied the construction cost and policy support of building integrated PV in Southeast Asian countries, and the results showed that technical GI of building integrated PV should be carried out to reduce the high installation cost [23].Vincenzo et al (2021) studied the photovoltaic solar energy industry and showed through case analysis that some large public utilities have become very active in the photovoltaic industry, and the photovoltaic industry needs continuous innovation and development to meet the market demand [24].Nuria et al (2022) pointed out that there are still challenges such as poor efficiency and insufficient electrical function in integrated building photovoltaics (BIPV), and proposed solutions to these challenges [25].Li et al (2022) applied data envelopment analysis (DEA) and Malmquist index, Tobit model was used to estimate the impact of digital transformation, green technology innovation and other factors on financing efficiency of 205 energy-saving and environmental protection industries in China.The empirical results show that DGI has a significant positive impact on promoting the development of energy-saving and environmental protection enterprises [26].Zhang et al (2023) proposed that digital transformation has a positive impact on promoting the development of GI and reducing enterprise costs [27].
Domestic scholars mainly discussed the GI and DI in MI.Chen et al (2007) analyzed the development of the integration of solar photovoltaic buildings in China and found that China still needs to carry out continuous technological innovation to realize the extensive utilization of solar photovoltaic buildings and narrow the gap with developed countries [28].Ma and Hao (2011) analyzed the problems involved in the integrated application of photovoltaic buildings and proposed to carry out technical innovation on the cost of photovoltaic cells and photovoltaic modules to promote their better development [29].Long and Zhang (2019) proposed to build an Internet platform with BIM as the core and promote the green innovative development of the construction industry by using digital technology [30].Mahian et al (2021) stated that solar energy is the most available and technologically advanced renewable energy in the construction field, and promoted the better application of photovoltaic materials in the construction field through experimental, numerical, optimization, and economic research [31].Klysner et al (2021) proposed standards for the installation of photovoltaic energy in building materials by conducting research on the construction industry, promoting the integration and development of building materials and photovoltaic energy [32].Chen et al (2022) proposed that DI has become a new driving force for regional economic development, and DI in MI is conducive to stimulating the vitality of regional economic development and promoting the coordinated development of regional economy [33].Zhi (2022) analyzed the development status of green and low-carbon BMs, and proposed prospects for digital technology, material innovation, policy support, etc [34].Yin (2023) proposed a new path for the development of digital intelligence and GI in MI on the basis of studying the development status and problems of GI in MI in Hebei Province [35].
Many scholars at home and abroad have fully discussed and studied the DI and GI of photovoltaic industry and BMs MI.Most literatures focus on the development of digital or GI in MI, construction industry, photovoltaic industry and other fields, with a wide range of research objects.However, there are few researches on the combination of DGI and development in the field of PBMs, and there is a lack of targeted research on the specific target subjects of PBMES.In terms of research content, many literatures have scattered discussions on DI or GI, but lack of research on the combination of the two.This paper aims to study and discuss DI and GI for PBMES, a micro subject target, so as to find a more appropriate development path for PBMES.

Factors related to DGI performance
At present, most scholars mainly elaborate from two aspects: DI performance and GI performance.
On the one hand, a large number of scholars have found that digital transformation will have a positive impact on enterprises' GI.Nyangon and Byrne (2021) used the SDEM model to study the adoption trends of EEMs based on the socio-economic, architectural, and household demographic characteristics of New York.The study demonstrated that energy efficiency policies have a significant positive effect in promoting EEM adoption [36].Hu et al (2022) found that the balance between local DGI network (LDGIN) and remote DGI network will have an impact on the DGI performance of manufacturing enterprises [37].He and Su (2022) found that regulatory pressure and international opportunities would magnify the impact of digital transformation on enterprises' GI [38].Saretta et al (2022) proposed the view that digitization is closely related to the photovoltaic industry.The benefits and advantages provided by digitization in the photovoltaic industry can achieve the benefits of reducing costs and improving performance [39].Zhao et al (2022) empirically tested the positive impact of digital economy development on improving carbon productivity based on panel data from 285 prefecture level cities in China, using a bidirectional fixed effects model, an intermediary mechanism model, and a threshold mechanism model [40].Ji et al (2023) pointed out that digital service has a significant positive impact on improving the performance level of MI and reducing the production cost of enterprises, and as an intermediate variable, it can effectively improve the innovation level of manufacturing enterprises to reduce carbon emissions and ultimately promote the digital green and sustainable development of enterprises [41].Gao et al (2023) carried out analysis and research from the perspective of government support and stakeholders, and found that government subsidies, as an intermediary, affect the digitization level of enterprises and thus affect the GI of enterprises, and the fulfillment of corporate social responsibility also has a positive impact on GI [42].Ge et al (2023) conducted a study on the correlation between digital technology innovation network embedding and enterprise innovation performance, and the results showed that knowledge acquisition intermediary network embedding played an intermediary role in digital technology innovation performance, proving that digital technology and enterprise performance have a positive influence relationship [43].Dong et al (2023) conducted a static and dynamic empirical study on the integrated construction supply chain (IBSC) of construction enterprises, and the results showed that the digital integration degree of IBSC and the green knowledge collaboration ability between enterprises are conducive to improving the DGI performance of enterprises [44].Ma and Wang (2023) proved through empirical research that big data, digital dynamic capability and organizational management update all have positive impacts on the digital transformation of manufacturing enterprises to varying degrees [45].
On the other hand, a large number of scholars have analyzed the factors affecting the DI performance and GI performance of enterprises from the internal and external environment.From the perspective of the combination of internal and external environment, Sun and Cao (2016) believe that the performance of DI and GI mainly includes green culture, innovation input, innovation management, institutional environment, resource environment and cultural environment [46].Li et al (2015) conducted an empirical study on 249 Chinese manufacturing enterprises, and the results showed that market orientation, policy orientation, organizational redundancy, and managers' environmental concerns all have a positive impact on enterprises' GI performance [47].Pan and Tian (2017) found that environmental leadership and organizational environment culture together have a positive impact on green organizational identity, and green organizational identity directly affects corporate GI performance [48].From the perspective of internal environment, Wong et al (2012) divided the GI performance of manufacturing enterprises into green product innovation performance and green process innovation performance [49].Suresti et al (2018) found that an enterprise's innovation capability is closely related to its own factors and external factors such as government policies [50].Guo et al (2018) have studied green products and processes, and the results show that GI in processes and products is conducive to improving the development level of green technology in enterprises [51].Meng et al (2022) pointed out that human capital is a key factor in corporate GI, and the senior management team with overseas experience is an effective driving force to promote corporate GI performance [52].From the perspective of external environment, Rumanti et al (2017) based on the case study method, pointed out that the level of knowledge sharing under the open background will effectively promote the efficiency of GI [53].Sun et al (2019) analyzed regional performance with entropy weight TOPSIS, and the results showed that environmental factors had an important impact on regional innovation ability [54].
To sum up, although DI and GI have received more and more academic attention in recent years, relevant researches still have the following deficiencies: First, most of the research objects of DI performance and GI performance are macro subjects such as MI and heavy industry, while micro subjects such as a specific enterprise need to be further studied.Secondly, at present, most scholars have conducted a lot of research and discussion on DI performance and GI performance respectively, but lack of research on DGI performance combined with the two.Finally, at present, scholars pay more attention to the DI performance and GI performance of a specific aspect, and only analyze from the external environment or internal environment, lacking a unified and complete performance standard.

DGI evaluation method
At present, scholars often use traditional evaluation methods such as AHP, factor analysis, fuzzy comprehensive evaluation and projection tracking evaluation model to evaluate DI and GI.Zhao et al (2009) evaluated the sustainable development ability of China's regional MI by using AHP [55].Duan and Liu (2011) evaluated the technological innovation capability of Chinese equipment MI by using factor analysis method [56].Li (2012) used the basic method of fuzzy mathematics and DEA method to evaluate the GI system of MI [57].Li et al (2014) analyzed and evaluated the comprehensive development ability of China's regional MI with the comprehensive evaluation method of grey correlation projection [58].Bikesin et al (2015) studied the impact of technology transfer on the GI performance of China's MI, and conducted an empirical evaluation on it by using the RAGA-PPE evaluation model [59].Li and Wang (2017) used the projection pursuit model to evaluate the green competitiveness of China's regional MI [60].Wang et al (2017) used the DEA-RAM model to analyze and evaluate the GI performance of China's MI [61].Wen et al (2019) used OLS+ robust standard error method to analyze the mechanism between digital economy and regional innovation capability [62].Chen et al (2022) evaluated the digital transformation of manufacturing enterprises with DEMATEL [63].Fan and Xin (2022) evaluated the electronic information MI at the value chain level by using analytic hierarchy process [64].Shen and Yang (2023) used the bidirectional fixed effect model to evaluate the coordinated effect and mechanism of industrial digital intelligent innovation on enterprise green development [65].
Some scholars have made innovations on the basis of traditional evaluation methods.Qi et al (2006) innovated based on fuzzy comprehensive evaluation method, proposed dynamic alliance performance evaluation method, and optimized the evaluation method of continuous dynamic monitoring performance [66].Yin et al (2022) built a combination evaluation model based on consistency on the basis of traditional evaluation methods, which effectively improved the scientific nature of evaluation methods [67].Yin et al (2022) innovatively proposed the research framework of joint venture investment 3W1H-P with integrated logic relations, and based on fuzzy prospect theory and VIKOR's comprehensive selection method, provided a reference for partner selection in DGI management activities of prefabricated construction enterprises (PCE) [68].Sarfraz et al (2022) used quantitative method and Harman single factor method to study the significant correlation between innovation capability, green process innovation, digital leadership and sustainable performance of manufacturing enterprises [69].Dong et al (2023) adopted the dynamic fuzzy decision method to select and analyze the DGI investment projects of PBMES [70].
As described in the summary, scholars have respectively used different evaluation methods to evaluate DI performance and GI performance, but there are still the following deficiencies: First, the above evaluation methods have advantages and disadvantages.For example, although fuzzy comprehensive evaluation method can solve multi-level and complicated problems, its index weight is subjective and easy to be disturbed by human factors.Secondly, there is no evaluation method for the DGI performance of PBMES among many evaluation methods at present.Finally, most scholars start from a single evaluation method for evaluation, there is a problem of single evaluation methods, lack of a set of effective comprehensive and objective evaluation methods for DI performance evaluation of PBMES.

Theoretical framework
The DGI performance evaluation of PBMES refers to the evaluation, summary and analysis of the achievements achieved by PBMES [71].With the rapid development of photovoltaic enterprises, we urgently need to develop a set of effective DGI performance evaluation index system for PBMES.The system can provide reliable reference value for PBMES, and help to evaluate the DGI ability of PBMES.It is helpful for PBMES to effectively optimize the implementation process of DGI activities.PBMES are newly developed manufacturing enterprises aiming at energy conservation and emission reduction [72].The diversity, comprehensiveness and development of DGI activities of PBMES determine the complexity and diversity of DGI performance evaluation of PBMES [73].
Combined with the above characteristics, the selected DGI performance evaluation indicators of PBMES should be scientific, diverse, practical, referable, digital technology progress, green development and other characteristics.This requires that the DGI performance evaluation index system of PBMES should pay attention to the following principles: (1) Scientific principle.When constructing the DGI performance evaluation index system of PBMES, we should start from the whole process of DGI of PBMES, which can fundamentally reflect the DGI level of PBMES.(2) The principle of diversity.Since the DGI process of PBMES is dynamic, there are many uncertainties in the innovation process.Therefore, when designing evaluation indicators, on the premise of ensuring the authenticity and effectiveness of evaluation indicators, it is necessary to enrich the DGI performance evaluation indicators of PBMES as much as possible.(3) The principle of practicality.The selection of performance evaluation indicators should be practical, effective and of practical significance to ensure that the evaluation results of DGI performance of PBMES can truly reflect the reality.(4) The principle of referenceability.In order to improve their own development level, PBMES need to compare the performance evaluation results of DGI with similar enterprises.Therefore, in order to enhance the referable degree of evaluation results, clear and representative performance evaluation indicators should be selected as far as possible.(5) The principle of digital technology progress and green development.The main purpose of DGI performance evaluation for PBMES is to put forward solutions.Therefore, the selection of DGI evaluation indicators should be conducive to the digital technology progress of PBMES.
From the effect of DGI performance of PBMES, the beginning and final result of DGI of PBMES are to meet market needs and promote sustainable development of social environment [74].Successful and effective DGI activities will bring huge green economic benefits to PBMES, improve the market competitiveness of PBMES, and improve the ecological environment [75].Judging from the degree of investment in DGI of PBMES, the DGI process of PBMES mainly relies on the input of factor technology, and should be given key consideration when evaluating the performance of DGI of PBMES [76].From the output level of DGI of PBMES, the ultimate purpose of DGI of PBMES mainly includes improving enterprise economic benefits, improving enterprise scientific and technological research and development ability, and making contributions to social energy conservation and emission reduction [17].Therefore, in terms of output level, economic output, scientific and technological output, and social effect of PBMES should be emphasized [77].
Based on the above analysis, this paper constructs a theoretical framework for DGI performance evaluation of PBMES, as shown in figure 1.
Figure 1 shows that the digital technology development of PBMES and the research and development of PBMs jointly affect the whole process of DGI of PBMES.Digital technology has an impact on factor technology input, economic output, scientific and technological output and social effect through GI, among which digital technology innovation and factor technology input are mutually influencing and interacting.The influence of innovation in digital and green through intermediate factors will ultimately affect the improvement of DGI level of PBMES.The common progress of innovation in digital and green ultimately reflects the performance level of DGI of PBMES.

Index system 3.2.1. Preliminary screening of indicators
According to the relevant literature on innovation in digital and green performance evaluation of PBMES, the DGI performance of PBMES is evaluated from the aspects of direct and indirect performance, process performance and output performance, enterprise internal development performance and external environmental performance.Basically, they focus on technological input, economic output of innovation, technological output of innovation, social effect of innovation and so on.DGI element technology investment is reflected in each stage of PBMs enterprise (PBMES) innovation, mainly including human, material and capital investment.The economic output of DGI of PBMES mainly measures the practical process of the application of digital technology and GI of PBMES, and the economic income obtained by the sales of DGI products of PBMES.In addition, it should also include the additional economic income based on the preferential subsidies given by the government to the progress of the emerging environmental protection industry.The output of DGI technology of PBMES is mainly reflected in the output of green digital technology and related technology application.The social effects of DGI of PBMES should include the effects brought by innovation, such as easing employment pressure, improving resource and environment development and promoting social sustainable development.Therefore, performance evaluation indicators for digital GI of PBMES includes four aspects: technology input, economic output, scientific and technological output, and social effect.Table 1 shows the initial performance evaluation index system.

Pretest index
Table 1 is constructed based on the summary of domestic and foreign literature, which has certain theoretical value.However, in order to make the index system more practical, we scored the indicators in table 1 by experts, so as to select the indicators that experts think have both theoretical value and practical significance.We invited 6 managers of DI items of PBMES and 4 experts of DGI research of PBMs to evaluate the indicators in table 1 according to 1 (very insignificant) to 7 (very important).The final 10 experts agreed.Through expert scoring, we eliminate indicators whose average score is less than 5.In the primary indicators, we eliminate three indicators: input in digital reconstruction ability, export exchange rate of digital green products and Resource consumption per unit of output loss.The evaluation values of the selected indicators in this paper are all greater than or equal to 5.

Formal test index
According to the characteristics of DGI of PBMES, the designed questionnaire includes two parts.First, the basic characteristics of the company, including the nature of the enterprise, enterprise scale, establishment years, etc The second is the DGI performance indicators of PBMES.This part mainly investigates the DGI projects of PBMES and requires the filling personnel to comprehensively consider all the DGI projects.The research object was set as the person in charge of at least three DGI projects of PBMES in the past five years.
To ensure the quality of the source data, we developed a pre-survey questionnaire prior to the formal survey using indicators from the relevant literature and measurements from leading industry researchers, 50 questionnaires were issued, 42 were recovered, and the questionnaire was revised according to the results.The research scope of this paper covers Beijing, Shijiazhuang, Baoding and other cities with specific social media relations to ensure the credibility and reliability of the research data.In this paper, 500 survey cards were issued and 328 were recovered, with a recovery rate of 65.60%.After correcting errors and deficiencies, the number of valid questionnaires was 188, and the accuracy rate of the questionnaires was 87.20%, basically meeting the requirements of empirical research.According to survey statistics, 86.23% of employees have a bachelor degree or above, 38.56% are technicians, 45.16% are technical supervisors, and 23.55% are middle managers.Tables 2,  3, 4 and 5 shows the correlation test results.
)/ / Cronbach's alpha is a measure of reliability: Based on questionnaire survey and related analysis, we conducted factor analysis, and the results were shown in table 6. Cronbach α values of the four core dimensions were all greater than 0.70, and factor loads of the indicators in the dimensions were all higher than 0.70, indicating that the four core dimensions of the DGI performance evaluation index system of PBMES were reasonable.Indicators in each dimension can reflect the real situation of the dimension.In addition, we find that the economic output and factor technology input of DGI have received extensive attention, which corresponds to the goal of PBMES to pursue profit maximization, and the social effect index of DGI has also received secondary attention.Validity test is used to characterize whether the evaluation system can truly reflect the objective reality.The DGI performance evaluation index system of PBMES in this paper is based on the summary of literature, through expert argumentation and questionnaire survey, and based on a variety of research methods.Therefore, from the perspective of validity, the appraisal index system of DGI performance of PBMES in this paper is reasonable.

DGI performance appraisal index system of PBMES
The DGI performance appraisal index system of PBMES designed in this paper is shown in table 6.It truly reflects the performance of DGI of PBMES.

Model selection analysis
At present, most evaluation methods belong to single evaluation method.In fact, different evaluation methods have different evaluation mechanisms and subjects.If the same question is evaluated with different evaluation methods, problems arise when one evaluation method gives different evaluation results.Current research focuses on combining evaluation weights (composite weight method) and combining evaluation conclusions.There have been some scholars on the combination of the weights of evaluation results, build the combination weighting method and applied to evaluate decisions.Common combinatorial evaluation methods based on evaluation conclusions mainly include Deviation Maximization method, Borda method, Average method, Copeland method and other optimization combinatorial evaluation methods.However, in the practical application of combination evaluation, due to the different combination evaluation methods of combination mechanism, combination evaluation value and application objects, the combination evaluation conclusions will appear inconsistent and convergence is poor.
To solve this problem, Chen and Li (2005) proposed a complex combination evaluation method, and verified the convergence of combination evaluation through computer simulation experiments [78].Therefore, Peng et al (2016) propose a quadratic combination scoring method based on the scoring conclusions [79].But the evaluation methods of complicated combination mostly focus on the theoretical exploration stage, and the application research is relatively few, and complex combination evaluation has not formed a systematic method system.Although the combination error of the quadratic combination evaluation method is smaller, it still has the problem of poor convergence.Therefore, combined scoring methods should be further explored, so as to reduce the error of the combination evaluation results and provide new ideas for the DGI performance evaluation of PBMES.In view of the above problems, based on the existing evaluation methods, a DGI performance evaluation method of PBMES based on compatibility and consistency was proposed.Entropy weight method, TOPSIS method and deviation maximization method were integrated by drift degree method, grey correlation degree method and mean value method respectively.Through multiple combination evaluation, the evaluation results of DGI performance of PBMES tend to be consistent under the three kinds of combination evaluation, and finally get the consistent DGI performance evaluation conclusion.It can not only combine evaluation methods of the same nature together, but also achieve the effect of a single evaluation method to complement each other's strengths.Moreover, multi-level information can be used to conduct more multi-angle and all-round research, which is closer to the overall picture of the evaluation object.In the meantime, the inconsistency of evaluation results of various methods can be eliminated, which provides a new idea for the DGI performance evaluation of PBMES.

Construction of evaluation model 4.2.1. Index normalization
The efficacy function of each index of DGI performance evaluation of PBMES should be determined.v ij is the j index of the i system, namely the order parameter, ij a represents the upper bound and ij b represents the lower bound.p ij is the contribution of v ij to the system.Therefore, the power coefficient is

Single evaluation method
(1) Entropy is an unordered measure of the whole system according to the basic principle of information theory.
1. Let f ij be the specific gravity of the index is calculated as follows.
Here, v ij is the raw data of the j DGI performance evaluation index of the i PBMES.
2. Let h j be the value of entropy of the j indicators and w j be the weight of the j indicators, then we have 3. Let P i denote the DGI performance score of PBMES, then the formula for calculating the score is (2) TOPSIS method.TOPSIS method is a kind of approach to ideal value ranking analysis method, which is suitable for multiple indexes and the comparison and selection of multiple evaluation subjects.The essence of the method is to determine the positive and negative ideal solutions for each index.
1. Create data weighting matrices for performance index.Let the set of PBMES be M and index set be S, then M i to index S j is marked as p , ij Each index weight w j is multiplied with the dimensionless matrix to get the weighting matrix R r , Calculate ideal PBMES-DGI performance.Based on the above data weighting matrix of DGI performance index of PBMES, ideal values are calculated ) of the DGI performance of PBMES can be obtained.
3. Calculate distance between the DGI performance score of PBMES and the ideal score.Let d i + be distance between the DGI performance score of the i PBMES and the positive ideal score, and d i -be distance between the DGI performance score of the i PBMES and the negative ideal score, then . DGI performance score results of PBMES.The relative proximity between the performance score and the positive ideal score is set as )and the larger the C i value is, the higher the DGI performance of PBMES is.
(3) The steps of maximizing deviation are 1.E w ij ( ) describes the entire deviation of the DGI performance index values between PBMES i and all other PBMES k n 1, 2, ..., , = ( ) then . Let E w j ( )denote the total deviation of performance index values among PBMES as follows.5. Let v i denote the performance score of DGI performance of PBMES, then the formula for calculating the score is

Combined evaluation method
It is necessary to set the method set M 0 to construct the evaluation model based on compatibility.According to the method concentration method, the DGI performance evaluation index of PBMES is selected, and the specific research method of evaluating the DGI performance of PBMES based on the combination evaluation method is (1) Combined evaluation method of drift degree 1.In a variety of single evaluation method of average as a frame of reference of drift measure, there is the related coefficient r t j k ( )between the evaluation value u t ij k ( ) obtained at t k time and the frame of reference u t .
k ( ) The drift degree of TOPSIS, entropy weight, and maximum deviation methods are calculated Where, j b k N 1, 2, ..., ; 1, 2, ..., = = 3. Let the value u t ij k ( ) of the j method of the i PBMES at t k time.Therefore, the result is Grey correlation degree combination evaluation method 1.There are n PBMES, and each PBMES has m single evaluation methods for DGI performance evaluation, and the data of DGI performance evaluation results of PBMES.Set x 0 is the ideal value, the x 0 and x i relative to the correlation coefficient of the k element.
nation coefficient and takes the value of 0.5.
2. Let w k denote the weight, then there are i single evaluation results and the correlation degree of the ideal result is for the same evaluation unit, the evaluation results obtained by different evaluation methods have similar characteristics.The Spearman method formula is Where i r j r 1, 2, ..., ; 1, 2, ..., .= = d s denotes where denotes the grade difference of the two combined evaluation methods.If r ij >0, methods are positively correlated; If r ij <0, negative correlation; If r ij = 0, it is not relevant.
(2) Convergence and bias tests.On the basis of obtaining the evaluation results of DGI performance of PBMES, the formula for calculating the mean value of variance is The error sum of each PBMES and the 'true value' of DGI performance was calculated using the formula SSE r r 20 Among them, r i is the mean value of the portfolio evaluation value of DGI performance of all PBMES.Detailed steps are shown in figure 2.

Results
This study aims to seek ways to improve the DGI performance evaluation level of DGI in PBMs companies.We propose a theoretical framework for measuring DGI performance, including the evaluation means and evaluation system of DGI performance of PBMES, as shown in figure 3.
In order to validate the proposed PBMES-DGI performance evaluation index system and evaluation method is scientific and effective, this paper selects 16 representative PBMES (omitting specific enterprise names) and evaluates the DGI performance of these 16 PBMES.The research data in this paper comes from the questionnaire survey of the formal test index in the performance evaluation index system of DGI of PBMES.There are 16 PBMES (A1 to A16).Firstly, the original data obtained are normalized to obtain the normalized value v ij of the j index of the i PBMES, where i j 1, 2, ...,16; 1, 2, ...,36.= = We evaluated 16 PBMES using TOPSIS, entropy weight and bias maximization method.Table 7 shows the results.
It can be seen from table 7 that there are differences.To test the reliability and feasibility of the first joint assessment, the Spearman rank correlation coefficient is used to test the consistency of the results, as shown in table 8.
Table 8 shows that Spear man rank correlation coefficients obtained between the evaluation results of DGI performance of PBMES obtained by using three single evaluation methods and the average of the evaluation results of TOPSIS, maximum deviation and entropy weight method are 0.973, 0.964 and 0.979, respectively.Table 9 shows that the evaluation results of the mean evaluation, the drift degree evaluation and the grey correlation evaluation method in the combination method.Table 9 reflects that the evaluation results of DGI performance of PBMES.Based on this, the convergence test is carried out by using the variance average method, and the S 0 mean 1 2 = ´is obtained.The consistent evaluation conclusion is obtained.According to the first drift degree combination evaluation, grey correlation degree combination evaluation and mean value combination evaluation method, the ranking of DGI performance evaluation results of PBMES from excellent to inferior is: A8, A7, A12, A15, A6, A2, A16, A13, A11, A10, A4, A1, A9, A3, A5, A14.The evaluation results were fed back to the 16 participating PBMES respectively.The managers of DGI projects of PBMES were satisfied with the evaluation order in the above evaluation results, which was in line with the order of DGI performance of their own enterprises in the 16 PBMES.6, among these factors, the level of digitization of the adoption of EMS is the most important.This shows that the PBMES to follow and improve the digital level of environmental management system is an important factor affecting DGI.The adoption of the digital level of environmental management system plays an essential role of DGI of PBMES to realize social effect.Only by truly following and improving the digital level of environmental management system, the improvement of digital green effect can be truly realized [16].

Core element analysis
Figure 3 shows that the performance evaluation system of DGI of PBMES consists of four parts: digital green innovation factor technology investment, digital green innovation technology output, digital green innovation economic output and social effects of digital green innovation.The DGI process of PBMES is divided into four stages: factor technology input, economic output, science and technology output, and social effect.Specifically, the factor technology input of DGI includes human and material resources input of PBMES, digital green technology input, such as talent introduction fund investment, internal research and development investment of digital green products [72].

Analysis of method characteristics
The purpose of joint scoring is to combine the scoring results of multiple individual scoring methods to reduce random errors and biases.The DGI performance evaluation model of PBMES based on consistency can not only combine evaluation methods of the same nature to achieve the effect of single evaluation method evaluation results learning from each other, but also can use multi-level information, more multi-angle and comprehensive research, and closer to the whole picture of the evaluation object.At the same time, it also eliminates the nonconsistency problem of the evaluation results of various single evaluation methods to a certain extent.As for the evaluation score in table 9, the gap of the score was generally accepted by the managers.For the evaluation system, PBMES should adjust the index content according to their own actual situation from the actual situation of feedback DGI performance, so as to achieve the requirements of comprehensive feedback and appropriate feedback, and provide important support for improving the efficiency and effect of DGI activities of PBMES.

Conclusions and implications
How should this process reflect the economic effects of PBMs driven by DGI more systematically and objectively?Whether need to meet the requirements of the construction of ecological civilization DGI performance evaluation index system [16,17].Solving this problem has become the key to improve the DGI mechanism of PBMES.Therefore, a theoretical framework is constructed in this study to measure the DGI performance of PBMs companies.This study has important theoretical and practical significance.
In the theoretical sense, the relevant research on enterprise performance evaluation has always been a hot research issue, but the research on performance evaluation from the perspective of DGI is rarely involved.This paper systematically constructs the DGI performance evaluation index system and method of PBMEs.Based on the evaluation method combining compatibility and consistency, through constructing the DGI performance evaluation system of PBMEs, it provides a scientific and effective decision-making method for scientific and reasonable DGI performance evaluation activities of PBMEs.Through the definition and analysis of the DGI performance evaluation behavior of PBMEs, it is helpful to carry out systematic research on the DGI activities of PBMEs, and expand the theoretical connotation of DGI performance evaluation.Through the in-depth analysis of the DGI activities of PBMEs in many aspects and the whole process, the theoretical system of the DGI process of PBMEs is enriched at this stage.By systematically constructing the theoretical system and evaluation method of DGI performance evaluation of PBMEs, it not only fully considers the characteristics of PBMEs, but also expands the existing theoretical system and research perspective of DGI performance evaluation, providing new ideas for the research of DGI performance evaluation related fields.Help to improve the DGI ability and enthusiasm of PBMEs.
In a practical sense, DGI in the manufacturing industry is one of the main driving forces to promote the high-quality development of China's economy.With the support of national policies, DGI of PBMEs is conducive to improving the digital innovation and green innovation capability of China's manufacturing industry, stimulating the vitality of DGI in the manufacturing industry, and conducive to the efficient and innovative development of Chinese enterprises.Based on the combination evaluation model based on compatibility and consistency, this paper explores the DGI activities of PBMEs, and puts forward a reasonable DGI evaluation index and evaluation system.First of all, the DGI activities of PBMEs are studied, and the feasibility and effectiveness of the implementation of DGI activities of PBMEs are analyzed and judged, so as to optimize the DGI activities of PBMEs and contribute to the smooth operation of DGI activities of enterprises.Effectively realize the digital creation of enterprise green knowledge, the digital transformation of green technology, the promotion of digital green products and other activities, and constantly improve the digital green value-added effect of PBMEs.Secondly, by incorporating relevant government information into the performance evaluation index system and studying the government's influence on the DGI activities of PBMEs, the government can effectively promote the DGI development of PBMEs to put forward reasonable and effective suggestions and countermeasures, and provide help for the government to formulate scientific and reasonable DGI policies of PBMEs.Support the development of DGI in PBMEs.Finally, through in-depth research on the DGI activities of PBMEs, understanding the current problems faced by PBMEs in DGI activities, practical and targeted suggestions and countermeasures can be accurately and efficiently put forward, providing new directions, new methods and new paths for the DGI development of PBMEs.We will promote the sustainable development of China's manufacturing industry and the high-quality development of the Chinese economy.
According to the research results of this paper, the DGI process of PBMEs includes four stages: factor technology input stage, science and technology output stage, economic output stage and social effect stage.We propose the following: In the stage of factor technology investment, the key factors that affect factor technology investment include internal research and development investment in digital green products, the intensity of domestic and foreign digital technology introduction, talent introduction and training funding investment, and other factors.PBMEs need to increase technology investment in DGI, improve the introduction and training of digital technology talents, and comprehensively improve the level of digital innovation of the enterprise.In the science and technology output stage, the key factors affecting science and technology output include the number/level of digital green new products, the number/level of digital green invention patent applications, the proportion of digital technology in green products, the growth rate of digital green products patent and other factors.PBMEs should improve the utilization of enterprise digital technology, and efficiently use digital technology for green product research and development.Deeply integrate digital technology and green product innovation, and improve the conversion rate of digital green technology achievements of enterprises.In the economic output stage, the key factors affecting economic output include the sales growth rate of digital green products, sales revenue of digital green products, the proportion of green new processes (products, services) in the market, and the preferential treatment and subsidies given by the government based on the production of digital green products.PBMEs should increase the proportion of green products and services in the total output value.Improve the return on investment of DGI projects, strictly control the whole process of DGI activities, and improve the success rate of relevant research and development results.Make use of national policies, increase promotion efforts, improve the market share of digital green products, and improve user recognition by using brand effect and social effect.In the social effect stage, the key factors affecting the social effect include the number of new jobs created by digital green new processes (products and services), the reduction rate of energy consumption per unit of output value, carbon emission intensity, the digital level of the adoption of environmental management system and other factors, PBMEs in the DGI activities, to strictly comply with the relevant national regulations.Production of digital green technology products that meet standards.Enterprises should take the initiative to assume social responsibilities, use digital technologies to reduce carbon emission intensity and energy consumption, provide more digital innovation-related jobs, and increase employment.
Extensive and sufficient practical testing during this process was not possible due to the lack of data.More empirical studies on DGI of PBMES are needed in the future.

Figure 1 .
Figure 1.Theoretical framework of DGI performance evaluation of PBMES.Note: This figure is drawn by the author.

4 .
. Conditional on entire deviation, DGI performance indicator values of all PBMES is maximum, the objective function with respect to weighting vector w j is Apply the Lagrangian to the above optimization model and take the partial derivatives to obtain the weight vector.

4 .( 1 )
Mean combined evaluation method Let x ij be the evaluation result of the DGI performance, where i n j m 1, 2, ..., ; 1, 2, ... , = = then the DGI performance evaluation results of PBMES under the average combination evaluation are The consistency and convergence tests of the conclusions are evaluated Consistency check.Different evaluation methods give different evaluation results for different points, but

Figure 2 .
Figure 2. Construction idea of DGI performance evaluation model for PBMES.

Figure 3 .
Figure 3. Theoretical framework for measuring DGI performance of PBMES.

Table 1 .
Initial index system of DGI performance evaluation of PBMES.Conversion rate of digital green technology achievements Patent growth rate of digital green products Number of papers included in SCI published jointly The number of projects submitted by the United Nations The proportion of digital green products in new product development Number of national and provincial well-known digital green products DGI economic output Sales growth rate of digital green products Bi et al (2013) [72] Digital green product sales revenue Yin (2019) [62] Digital green products export exchange rate Ji et al (2023) [36] Green new technology (products, services) in the market share The output value of green new technology (products and ser-

Table 2 .
Correlation test of DGI input indicators.

Table 3 .
Correlation test of DGI output indicators.

Table 4 .
Correlation test of economic output indicators.

Table 5 .
Correlation test of DGI social effect indicators.

Table 6 .
DGI performance appraisal index system for PBMES.
. The weight of the j method at t k time is

Table 7 .
DGI performance evaluation results of PBMES based on a single evaluation method.

Table 8 .
[62]ngle evaluation method evaluates the results of the Spearman hierarchy correlation coefficient matrix.Figure3shows that the key factors affecting the technological investment of DGI factors include the investment of talent training funds, the investment of talent introduction funds, the investment of digital dynamic capabilities, the investment of digital perception capabilities, and the introduction intensity of foreign digital technologies.As shown in table 6, investment in talent training funds and investment in talent introduction funds are the most important influencing factors.These two factors show that PBMES must increase the investment in the training of relevant talents and the cost of talent introduction for DGI.Only with excellent professional and technical talents can we comprehensively promote the improvement of DGI ability of PBMES[62].The key factors affecting the output of DGI technology include the proportion of digital technology in green products, the number/level of digital green new products, the number/level of jointly published SCI papers, and the number/level of digital green invention patent applications.The key factors affecting the economic output of DGI include the success rate of DI product development increased by DGI cooperation, the proportion of green new process (product, service) output value in the total output value, the user's acceptance degree of digital green technology, and the sales revenue of digital green products.The key factors affecting the social effect of DGI include the digital level of adopting environmental management system, carbon emission intensity, the growth rate of digital low-carbon transformation rate, the number of new jobs created by digital green new processes (products and services), and the number of national or industrial digital green technology standards.As shown in table

Table 9 .
The first joint evaluation of DGI performance results.