Digital transformation is to reshape the organization, strategy, business processes, and business models of enterprises through technologies such as big data, Internet of Things (IoT), artificial intelligence (AI), blockchain, and cloud computing to promote data-driven value creation and core competitiveness enhancement (Wu et al., 2021)[11].Its core is not only the digitization of information, but also the digitization of production factors and processes through digital technology and hardware systems to promote the improvement of business models and effectiveness.[12]Existing studies have measured digital transformation through three main methods: dummy variables (He and Liu, 2019)[13], the proportion of intangible assets of digital technology (Zhang et al., 2021)[14], and the frequency of related words (Wu et al., 2021).This paper synthesizes recent studies and discards the dummy variable method and the intangible asset ratio method, which are difficult to accurately reflect the actual level of digital transformation of enterprises.[15] In contrast, the related word frequency method, with the development of text analysis technology, can more truly reflect the digital transformation status of enterprises, so this paper adopts the related word frequency method proposed by Wu et al.(2021) to measure the degree of digital transformation.[16]

Regarding the definition of new quality productivity, Zhou and Xu (2023) argue that 'new' emphasizes the characteristics of the new economy and new technology, while 'quality' embodies the role of technological breakthroughs in innovation-driven, driving the rapid improvement of productivity, demonstrating high quality and high performance that mark a leap in productivity.[17]Yang and Zhang (2024) pointed out that the new quality productivity is different from the traditional rough and intensive productivity, which is centered on scientific and technological innovation, gets rid of the traditional growth path, meets the requirements of high-quality development, and is the productivity that is more integrated in the digital era and rich in new connotations, and possesses the characteristics of high-tech, high-efficiency and high-quality.[18] Gao(2023) analyzed the connotation of new quality productivity from several angles and elaborated the theoretical basis of its proposal from the perspective of supply and demand. [19]Li(2024) argued that new quality productivity can be considered as all economic activities based on technological advances that increase the scientific and technological content of the unit and value added.[20]Obviously, these views are more systematic elaboration of the connotation of the new quality of productivity, revealing its internal mechanism, and the construction of the corresponding indicator system to measure the new quality of productivity, but the lack of the main micro-level research on the new quality of productivity, and for the energy enterprise as a specific group, the new quality of productivity is relatively lacking in the study, which is worth exploring.

Digital transformation is the key to improve the core competitiveness of enterprises and promote the development of their business model and management model, as well as an important strategic task in the construction of digital China and an important decision to promote the high-quality development of China's digital economy.[21]Enterprise digital transformation is an important hand in building a new form of China's smart economy. [22]Pei et al.(2023) pointed out that enterprise digital transformation is an important engine to drive the high-quality development of enterprises. Enterprises are the basic support unit of the national economy, the micro subject of the market, and the micro bearer of the deep integration of digital technology and the real economy. [23]The contribution of China's enterprise digital transformation to economic output has shown a year-on-year growth trend, and it is expected that the incremental GDP brought about by enterprise digital transformation will reach 13.88 trillion yuan by 2030.[24]Li et al.(2025) stated that digital transformation can improve the efficiency of green land use in cities, thus improving the economic effect.[25]Long(2024) stated that digital transformation in manufacturing firms can improve performance and reduce costs, thus improving the economic effect of the firm.In the “2023 Enterprise Digital Transformation Research Index”, it is shown that, comparing the financial dimension, the global research shows that, compared with other enterprises, enterprises that fully implement digital transformation have 10% higher revenue growth, 13% higher cost improvement effect, and significantly better financial returns than other enterprises. Within six months of promoting transformation actions, their own realized financial value reached 1.3 times that of other enterprises - in the first six months, the ratio of realized financial value to the target value of the transformed enterprise and other enterprises was 11.4% and 8.9%, respectively, and the digital transformation rapidly transformed technological investment into financial returns. This demonstrates the speed with which digital transformation can deliver value growth.[26]

It can be seen that the digital transformation of enterprises has a significant economic effect, is the current reality of the needs of enterprise development, can help enterprises optimize the allocation of resources, reduce costs, improve profitability, and inject a new impetus for the high-quality development of enterprises.However, for the cause and effect relationship between digital transformation and the improvement of economic effects, the research on how to specifically improve the economic effects of enterprises in the middle zone and what kind of tools to use is still vague and lacks systematic analysis.

Currently, there are more studies on digital transformation to drive new quality productivity. Yang et al.(2024) argues that enterprises can enhance new-quality productivity by improving the quality of internal control. As an important governance mechanism for enterprises, internal control influences decision-making, operation and supervision, aiming to solve the agency problem and information asymmetry, improve the efficiency of resource allocation, and promote the transformation and upgrading of traditional industries.[27]Zhang (2024) pointed out that digital transformation enhances new quality productivity by improving information transparency, information asymmetry is a long-term problem faced by enterprises, and accurate market information is crucial for enhancing new quality productivity.[28] Digital transformation introduces advanced technologies and data analysis tools to help enterprises obtain accurate information, reduce information asymmetry, promote cooperation and technology sharing, accelerate innovation, and enhance competitiveness, thereby increasing new quality productivity.[29]According to Zhang and Li (2024), digital transformation promotes the improvement of new quality productivity through technological innovation and management innovation, with technological innovation being the foundation and management innovation providing institutional guarantee for technology.[30]Zhao (2024) stated that digital transformation plays an important role in stimulating innovative thinking. Digital transformation can help companies understand market needs and technology trends, which can drive new quality productivity in the organization.[31]Zhai and Pan (2024), on the other hand, pointed out that digital transformation plays an important role in the enhancement of new quality productivity, and that the sustainable development of new quality productivity can be facilitated through the digital transformation of the whole region and the enhancement of digital literacy of the whole population.[32]

To summarize, previous works in the related research field are richer in content, and they have been discussed from different perspectives and with different methods for different levels, and they have drawn conclusions of certain value, which also provide a certain reference significance for the development of the subsequent scholars' researches.However, there is not much research on the relationship between the digital transformation of energy enterprises and new quality productivity, and there is still a lot of space for the relevant research on the intermediary mechanism effect generated in the relationship of its process as well as the possible existence of the mechanism of the regulating effect, and an in-depth discussion of the digital transformation of energy enterprises and the formation of the new quality of productivity of the logical structure and the economic effect is a response to the national policy of innovative development and economic transformation.[33] At the same time, it can also lead to the industrial structure adjustment of traditional energy enterprises, improve the production organization, adjust the business model, and promote the overall development of the economy.Then, how to research and analyze the energy enterprises to understand the mechanism and the logical relationship between their digital transformation and the development of new quality productivity?To this end, based on the idea of system engineering, this paper takes the data of Chinese A-share-listed energy enterprises from 2014 to 2023 as the basis, and arranges the data of energy enterprises individually to empirically explore the impact of digital transformation of energy enterprises on the new-quality productivity and its mechanism of action.[34]The results of the study show that, for energy companies, digital transformation significantly contributes to the improvement of new quality productivity of the company, and this effect is mainly achieved by easing financing constraints, improving green innovation and upgrading managers.

The possible research contributions of this paper are mainly the following: First, from the direction of energy enterprises, we synthesized the data of traditional energy enterprises and new energy enterprises, analyzed the impact of digital transformation on new quality productivity in energy enterprises, and enriched the content of related research fields. [35]It makes up for the shortcomings of the evaluation system and research content of new quality productivity in energy enterprises.Second, the systematic impact of digital transformation on the development, operation and management of enterprises is demonstrated at the data level, revealing the direct effect of digital transformation on the enhancement of the new quality productivity of energy enterprises, and at the same time discussing its heterogeneity in terms of scale, property rights and economic benefits, which responds to the intrinsic drivers of the new quality productivity of energy enterprises.[36]Thirdly, the research on the mechanism of enterprise digital transformation on enterprise productivity is examined from the three perspectives of alleviating financing constraints, improving the level of green transformation and managerial level improvement. [37]Currently, there are fewer papers that synthesize whether enterprise digital transformation can affect the development of new quality productivity through alleviating financing constraints, green transformation and managerial level, and this paper confirms that enterprises can promote the development of new quality productivity through alleviating financing constraints, improving the ability of green transformation and improving the level of managers in three perspectives of the SA index Green Index and MA Index, which enriches and expands the related research.[38]Fourthly, from the objective economic factors and internal driving factors of enterprises, it is concluded that the impact of digital transformation on new quality productivity in energy enterprises is moderated by entrepreneurship and cash flow, and it is hoped that these studies can clearly show the logical relationship between the digital transformation of enterprises and the new quality productivity, so as to provide a reference for the formulation of relevant policies for the promotion of the development of the new quality productivity.

The theoretical basis for the direct effect of digital transformation affecting the new quality of productivity stems from Marxist political economy and General Secretary Xi Jinping's theoretical interpretation of the connotation of the new quality of productivity, in which the core elements of productivity include the worker, the means of labor, and the object of labor, the essence of which is the ability of human beings to utilize and transform nature according to their own needs.The concept of new-quality productivity proposed by General Secretary Xi Jinping in 2023 builds on traditional productivity by abandoning the high energy-consuming and inefficient growth model and emphasizing science, technology, and innovation as the leading force in productivity development.[39]The key to new quality productivity is “new” and “quality”. “New” not only reflects the renewal of concepts, technologies and industries compared with traditional productivity, but also highlights the central position of scientific and technological innovation and industrial integration, focusing on the development of strategic emerging industries and future industries. “Quality” emphasizes the high-quality and high-efficiency development of productivity, reflecting the leap from quantitative accumulation of productivity to quality.[40]New-quality productivity is a new form formed under the conditions of informationization and intelligence, relying on scientific and technological innovation, industrial upgrading and technological change, marking a profound transformation of productivity from traditional mode to high-quality development.

Enterprise digital transformation, as an important way to promote the development of new quality productivity, is the process of systematic reconstruction of core business and management mode by enterprises using digital technology, and its core goal is to improve operational efficiency and innovation.[41]Digital transformation is not only limited to the application of technology, but also encompasses in-depth changes in corporate culture, organizational structure, business processes, business models and customer relationships, which are characterized by technology-driven, complexity and dynamic adaptability.[42]By embedding digital technology and data elements into the three major elements of productivity, namely, workers, labor materials and labor objects, enterprise digital transformation essentially endows productivity with digital characteristics, promotes profound changes in the elements, optimizes the structure of productivity, enhances total factor productivity, accelerates the breeding of new forms of industry and industrial upgrading, and ultimately facilitates the growth and development of new-quality productivity.

Specifically, the core of the new quality productivity is the enhancement of workers, tools and objects of labor and their optimal combination, of which workers are the decisive element, and the cultivation of high-quality workers is particularly important.Enterprise digital transformation can effectively promote the cultivation of composite digital talents to meet the demand for talents in the new quality productivity. These talents can be divided into two categories:The first is digital strategic talents, who focus on R&D and innovation of digital technology and develop advanced digital production tools; the second is digital application talents, who have multi-dimensional knowledge structure and are able to skillfully master and apply digital tools so as to promote the digital operation and innovation of enterprises.In addition, digitized means of labour are the core driving force of the new quality of productivity. The digital transformation has made the tools of production intelligent, efficient, low-carbon and safe, greatly liberating labour productivity and broadening the scope of production activities, thus providing a solid material basis for the development of new quality productivity.

In the labor object dimension, enterprise digital transformation expands the scope of labor objects through digital technology innovation.On the one hand, advanced technology breaks through the limitations of natural resources, expands the boundaries of human development and utilization of material resources, and makes the acquisition of material information more convenient and extensive;[43]On the other hand, new types of digital labor objects, such as data elements, have become an important part of labor objects, injecting new vitality into the development of new quality productivity. This enrichment of labor objects provides diversified resource support for enterprises' production and innovation in the context of digitization.

To this end, this paper proposes the following research hypotheses

H1:Digital transformation of energy companies can generate new quality productivity in the enterprise.

According to the Marxist theory of productivity and General Secretary Xi Jinping's important discussion on high-quality development and building a financial powerhouse, the digital transformation of energy enterprises indirectly affects the new quality productivity of enterprises through three ways: alleviating financing constraints, improving the innovation capacity of green technology, and improving the capacity of managers.As far as easing financing constraints is concerned, the digital transformation of energy companies is a slow process that requires adjustments in productivity and improvements in production tools, etc., in which the cost and time investments required are huge, which also means that the financial investment of the company plays a decisive role in the R&D process.[44]Furthermore, energy enterprises face higher environmental constraints and other problems than ordinary enterprises, and need to face problems such as policy pressures and social monitoring requirements, higher costs of obtaining bank loans, and higher financing constraints.And along with the development of the degree of digital transformation, enterprises are able to optimize cost inputs, produce benefits more efficiently, improve information transparency, and therefore better gain the trust of external investors, thus easing the pressure of enterprise financing constraints, enhancing enterprise investment capacity, and improving the level of enterprise innovation and production efficiency.

To this end, the following hypotheses are proposed in this paper:

H2:Digital transformation of energy firms can facilitate the development of new quality productivity of firms by alleviating financing constraints.

As far as green technological innovation is concerned, it has been an important bottleneck for enterprises to obtain production resources, optimize the allocation of labor means, and achieve efficient production and innovative development.As an indispensable technological foundation in the production process, an enterprise's green technology capability directly affects its productivity and competitiveness. However, R&D activities are usually characterized by high investment, long payback period and high uncertainty, which requires enterprises to have sufficient capital reserves to cope with risks and guarantee the continuous promotion of R&D and innovation.In this context, enterprise digital transformation provides an effective solution for the enhancement of science and technology, and as a result, it has a significant effect on the enhancement of the enterprise's new quality productivity.[45]Digital transformation reduces the high-cost investment in traditional labor resources by improving the operational efficiency and optimizing resource allocation, enabling enterprises to use more funds for the allocation of other scarce resources and R&D and innovation activities. Digital transformation promotes the construction of business platforms in the industry, enhances the ability of enterprises to connect with their partners and investment institutions, broadens the learning and communication channels of the enterprises, and helps the enterprises obtain more stable cash flow support.Secondly, based on the perspective of information economics, digital transformation realizes the real-time mining and transparent analysis of enterprise operation data by constructing an efficient information platform, which greatly alleviates the uncertainties and technical difficulties to be overcome in the process of green technology transformation, reduces the potential cost pressure of enterprises, promotes the innovation capability of enterprise green technology, and thus enhances the development of enterprise new quality productivity.

To this end, the following hypotheses are proposed in this paper:

H3: Digital transformation of energy companies can contribute to the development of new qualitative productivity of companies by improving green technology innovation capabilities

As far as improving managerial competence is concerned, in the era of the digital economy, the level of managerial competence is an important factor in determining the core competitiveness of enterprises.[46]Digital transformation not only has a profound impact on an organization's technology and production processes, it also drives new quality productivity by empowering managers to enhance their capabilities.Digital transformation provides enterprise managers with advanced data analysis tools and intelligent decision support systems, enabling them to accurately grasp the key indicators and problems of enterprise operations. [47]By integrating and analyzing enterprise operation data, managers can gain insight into the inadequacy of enterprise resource allocation and bottlenecks in the production process, and thus propose targeted optimization strategies. This kind of data-driven scientific decision-making not only improves the operational efficiency of enterprises, but also significantly optimizes the utilization rate of labor resources, promotes the innovation and upgrading of labor tools, and helps the formation of new quality productivity.At the same time, digital transformation provides managers with multiple opportunities for on-the-job learning and skill enhancement. These learning and practical experiences enable managers to more accurately control the direction of the enterprise's digital development, and lead the enterprise in the direction of higher quality and more innovation.The improvement of managers' capabilities directly affects the efficiency of enterprise labor tools and the quality of the workforce. [48]Managers empowered through digital transformation are able to integrate enterprise resources more effectively, optimize the efficiency of the use of production tools, and promote the development and application of advanced production tools.In addition, managers' precise control over the digital direction of the enterprise can motivate employees to continuously improve their skill levels and drive the establishment of an efficient team culture in the digital era. This improvement in labor quality injects a stronger driving force for the development of new quality productivity.

To this end, the following assumptions are made in this paper:

H4: Digital transformation can lead to an increase in the level of new quality productivity in the enterprise by improving the path of managerial competence

Entrepreneurship is recognized as a key driver of economic dynamism and plays an important role in the process of digital transformation. At its core, it breaks with traditional productivity models through innovation, risk-taking and strategic vision, essentially activating the “change gene”.Entrepreneurs need to have keen insights when promoting new quality productivity and reconstruct the logic of production factor allocation through innovative thinking, so as to create new industries and business models in technological breakthroughs.[49]Driven by entrepreneurial spirit, companies are more willing to proactively explore digital technologies to collaborate with their supply chain partners, solve challenges in digital supply chain integration, improve collaboration efficiency, and contribute to sustained growth in business performance.[50]As a high-risk strategic decision, digital transformation inevitably affects the shaping of entrepreneurial traits. Entrepreneurship, as an embodiment of entrepreneurial traits, reflects a company's pursuit of innovation, identification of opportunities, and risk-taking ability, factors that have a profound impact on a company's digital transformation.

To this end, the following assumptions are made in this paper:

H5: Entrepreneurship plays a positive moderating role in the digital transformation of energy companies to empower new quality productivity journeys.

The level of corporate cash flow signifies a company's financial size and risk tolerance, and with sufficient capital, companies can provide material security for innovative practices through sustainable technology investments, risk buffers and supply chain resilience.[51]Under the influence of the existing environment, state-owned enterprises need to increase investment in scientific and technological innovation, optimize the allocation of funds to consolidate the synergistic development of traditional industries and cultivate new industries, and avoid the resource mismatch of “breaking before establishing”.[52]Empirical studies show that the success rate of digital transformation of enterprises with high cash flow health is 43% higher than the industry average. In addition, cash flow dynamically optimizes supply chain resilience through intelligent procurement systems, maintains production continuity when energy prices fluctuate drastically, and its resource allocation capability directly affects the R&D cycle of advanced production tools, while the establishment of a cash flow early warning system further strengthens the precision of resource allocation, and promotes the development of new-quality productivity through the dynamic adaptation of technology-organization-environment.

To this end, the following assumptions are made in this paper:

H6: Adequate corporate cash flow plays a positive moderating role in the digital transformation of energy companies to empower new quality productivity journeys.

Based on the above theoretical assumptions and their internal logic, a conceptual model of the mechanism of digital transformation's effect on the new quality productivity of energy enterprises is established (Fig. 1).

A study of A-share listed energy companies in Shanghai and Shenzhen from 2014–2023.The energy companies in this paper are selected from the industry codes D44, D45, B07, and C25, which are related to traditional energy companies and new energy companies.For the data time selection, there were relatively few enterprises applying digital technology before 2014. since 2014, the rapid development of mobile Internet has greatly facilitated the digital transformation process. The following samples were excluded: samples lacking important financial indicators; samples with incomplete data; financial samples; and samples with abnormal operation such as ST or *ST.

New quality productivity (NPRO). By drawing on existing studies (Song et al. 2024; Lu et al. 2024; Zhou and Ye ,2024), this paper adopts the entropy method to construct the index of new quality productivity. The specific methods are as follows:

First, energy firms were chosen as the sample for calculating NQP because the purpose of this paper is to discuss the relationship between energy firm transformation and NQP.

Second, the new quality productivity indicator system is constructed according to the two-factor productivity theory.The paper chose four major indicators, namely, live labor, labor objects, hard technology and soft technology, in constructing the indicator system of new quality productivity. The basis for choosing the above indicators is based on General Secretary Xi Jinping's definition of new quality productivity, which is a new product of the development of traditional productivity, a leap forward based on traditional productivity with the addition of new technology to traditional productivity.While the main components of traditional productivity are living labor and materialized labor, new technology is a product of both hard and soft technology. Adding new technologies to traditional productivity elements constitutes new quality productivity, so it is relatively reasonable to choose the above four indicators to measure new quality productivity in a comprehensive manner.

Thirdly, the entropy method was used to further calculate the weights of the relevant indicators, which were summed up to obtain the indicators of new quality productivity, and the specific results are shown in Table 1.

Digitalization and Transformation (DIG). With reference to existing research (Ge and Huang, 2024), this paper adopts the “Enterprise Digital Transformation Word Bank” in the CSMAR database to extract the digitization level of enterprises for measurement, which is created by analyzing the word frequencies in the annual reports of listed enterprises and fund-raising announcements. The CSMAR database is created by analyzing the word frequencies in the annual reports and fundraising announcements of listed companies.

The study involves three mediating variables, one is the corporate financing constraint index (FC). According to Zhao (2024), the SA index is chosen to represent the level of financing constraints in this paper.Second, the managerial level (MA) According to Zhanget al. (2019), the ratio of the firm's current year input-output efficiency to the industry's optimal level is regressed through the Tobin model, and the regression residuals can be used as a measure of managerial ability.Third, green innovation capability (Green), according to Yang (2024), the level of green innovation is mainly assessed by taking the logarithm of the sum of the number of green invention patents plus green utility model patents of the enterprise plus 1.

The study involves two moderating variables. One is entrepreneurship (Spi), in order to reflect the connotation of entrepreneurship, this paper refers to the study of Li (2021), and selects the number of enterprise patent applications, per capita fixed assets, per capita income, per capita intangible assets, and board of directors' independence to measure entrepreneurship comprehensively. The entropy weighting method is applied to measure the weights of the above indicators to arrive at a comprehensive result, and the natural logarithm of this result is taken to measure entrepreneurship.The second is the level of corporate cash holding (Cash), which is one of the most important indicators of corporate resources, especially cash resources. This study refers to Guo(2024), which utilizes (money funds + trading financial assets) /( total assets - money funds - trading financial assets) to measure the level of corporate cash holding.

According to the research methodology of related literature (e.g., Zhao and Li, 2024), the following variables were selected as control variables in this study:SIZE, LEV, ROA, GROWTH, FIRMAGE, DUAL, BOARD, TOP1. Specific measurements are shown in Table 2

The purpose of this study is to explore the process of enterprise digital transformation affecting the enterprise's new quality productivity, in order to absorb the relevant fixed effects, the two-way fixed effects model was used to control the individual effects and time effects for estimation, and the following model was constructed

In model (1), new quality productivity is denoted by “Npro” and digital transformation of enterprises is denoted by “Dig”, i denotes different enterprises, t denotes year, X denotes other control variables, denotes a constant term, and and both denote the estimated coefficients, denoted as enterprise and are estimated coefficients, denoted as firm fixed effects, denoted as year fixed effects, and denoted as random disturbance terms.Medium denotes the mechanism variable in model (2), and FC, Green, and MA are used as the explanatory variables in the regression to represent the relationship between digital transformation and the level of financing constraints, green technological innovation, and managerial competence, respectively.Moderating variables are expressed in model (3), and the coefficients reflect the moderating effects of the moderating variables on the direct impact of digital transformation and the formation of new quality productivity.

Table 3 shows that the mean value of new quality productivity is 11.372, the minimum value is 1.22, and the maximum value reaches 36.991, which is closer to the findings of Song et al. (2024). Its variance is 8.194, which indicates that there are some differences in the level of new quality productivity among enterprises. The mean value of digital transformation of enterprises is 0.832, the maximum value is 4.205, and the minimum value is 0, which indicates that there is a significant difference in the degree of digital transformation among different enterprises, and this result is consistent with the findings of Wu et al. (2021).

Based on the fixed-effects model constructed in the previous section, the following tests are done respectively on the enterprise digital transformation affecting the new quality productivity of the enterprise.The results of the test are shown in Table 4, where column (1) is the effect of firms' digital transformation on firms' new quality productivity without considering control variables. Columns (2) and (3) are the effects of enterprise digital transformation on enterprise new quality productivity after gradually adding control variables. The results show that digital transformation of firms significantly contributes to the development of new quality productivity of firms and is significant at the 1% level, and hypothesis 1 is confirmed.

To address possible endogeneity problems, this paper controls for two aspects: the introduction of lagged variables and the instrumental variables approach.

First, the lagged variable method. Considering the long-term characteristics of the enterprise's new quality productivity improvement, the impact of enterprise digital transformation may have a certain lagged effect. For this reason, this paper includes the explanatory variable DIG lagged one period (i.e., L1DIG) in the regression model to eliminate potential endogenous disturbances and verify the lagged effect.The results in columns (1) and (2) of Table 5 show that the regression coefficients are significantly positive, which suggests that after the introduction of lagged variables, the digital transformation of firms still contributes significantly to the improvement of new quality productivity.

Second, the instrumental variables approach. Firms' digital transformations are usually influenced by the digital transformations of other firms in their region, but these influences do not generally act directly on the firm's new quality productivity.Based on this, this paper refers to the study of Xi and Zhao (2022), and constructs an instrumental variable (DIG_IV) by selecting the mean value of digital transformation of other enterprises within the same industry in the region where the enterprise is located.The results are shown in columns (3) and (4) of Table 6. The analysis shows that after controlling for endogeneity through the instrumental variables approach, the digital transformation of firms still has a significant contribution to the development of new quality productivity.

To further ensure the robustness and credibility of the benchmark results, this paper also adopts the following methodology for testing:

In order to reduce the impact of the fluctuation of the external environment on the research results, this paper excludes the sample data of 2015 and 2016, when the stock market was violently shaken, as well as 2020, which was seriously affected by the new crown epidemic, and re-runs the regression analysis. According to the results in column (1) of Table 6, the Digit coefficient is still positive at the 1% significance level after excluding these abnormal years, indicating that the effect of digital transformation on the improvement of the new quality productivity level of enterprises still holds.

China's municipalities have special characteristics in economic development, and provincial capital cities also have certain economic differences due to their status. Listed companies in these regions tend to be influenced by stronger financial and policy factors. Therefore, this paper excludes the samples of firms in the four municipalities directly under the central government and the provincial capital cities, and re-runs the regression analysis.As can be seen from the results in column (2) of Table 6, the Digit coefficient is still significantly positive at the 1% level after excluding these particular cities, further confirming the positive effect of digital transformation on firms' new qualitative productivity gains.

There are discontinuities in the indicator data of some listed companies, in order to reduce the interference caused by abnormal data, this paper eliminates these discontinuous samples, recalculates the sample size and conducts regression analysis.According to the results in column (3) of Table 6, the Digit coefficient remains positive at the 1% significance level after excluding discontinuous samples, indicating that the contribution of digital transformation to firms' new quality productivity remains robust.

To mitigate the possible impact of endogeneity on the regression results, this paper uses the propensity score matching (PSM) method for validation. The specific steps are as follows:First, the logit regression model was used to estimate the relationship between enterprise digital transformation and new quality productivity, controlling for relevant variables and fixed effects; second, the control variables were used as covariates, and the caliper value of 0.05 was set to perform nearest-neighbor matching; and lastly, regression analyses were performed again on the 889 samples that were successfully matched.The results in column (4) of Table 6 show that the Digit coefficient is positive at the 1% level of significance, which indicates that digital transformation of firms has a significant positive impact on the level of new quality productivity, validating the previous findings.

Next, this paper will launch a detailed analysis of the effects of digital transformation on different types of enterprises, aiming to reveal the differential impacts of digital transformation on new quality productivity exhibited by enterprises with different characteristics, so as to further complement and improve the research conclusions of this paper.

First, the analysis of enterprise property rights heterogeneity. The key to new quality productivity lies in the breakthroughs and innovations in core technologies, which require large upfront investments and are difficult to see returns in the short term.There are certain differences between state-owned enterprises and non-state-owned enterprises in terms of capital investment capacity as well as scientific and technological innovation capacity, etc. Therefore, for enterprises with different nature of property rights, the impact of their digital transformation on the new quality of productivity may be somewhat different.In this paper, the firms in the sample are divided into regressions according to two parts: state-owned enterprises and non-state-owned enterprises. According to columns (1) and (2) of Table 7, the regression coefficients of SOEs are higher than those of non-SOEs, which suggests that the digital transformation of SOEs is better able to enhance their new quality productivity level compared to non-SOEs.The main reason may be because SOEs are more advanced in terms of capital scale as well as technological level, more responsive to policies and better able to excel in key areas.

Second, firm size heterogeneity is analyzed. Given the significant differences between large-scale and small-scale firms in China in terms of policy support, risk resistance and industry status, these factors will inevitably have an impact on the role of digital transformation in promoting new-quality productivity in enterprises.Drawing on existing research, this paper allocates firms according to their size according to the size level in the sample, according to the mean, into large-scale and small-scale firms, and conducts regression analyses on each of them, with the results shown in columns (3) and (4) of Table 7.The results of the study further show that small and medium-sized enterprises (SMEs) contribute more significantly to the development of new quality productivity by upgrading their digital transformation than large enterprises.The main reason for this is that large enterprises usually have relatively well-developed production systems and management processes, and digital transformation requires a longer period of time as well as a large amount of capital investment, which leads to a longer reaction cycle for the improvement of their new quality productivity levels.While small and medium-sized enterprises (SMEs) are more focused on specific fields or market segments, the scale and cycle of their digital transformation investment is relatively small, and thus they have higher flexibility and are more likely to quickly adapt to technological changes and achieve innovation and optimization of their business models.In addition, SMEs can more efficiently establish close ties with their supply chains and partners, thus jointly promoting digital transformation and new quality productivity levels. As a result, small-scale enterprises are better able to take advantage of their scale, respond to policy analysis in a timely manner, and change their management mode flexibly during the transformation process.

Third, the analysis of enterprise profitability level heterogeneity. The profitability level of an enterprise represents whether an enterprise can continue to develop and the potential space for development, and also profoundly affects the development status of the enterprise's new quality productivity.In this paper, with reference to the firms' net profit margins on total assets, the sample firms with profit margins higher than the average are categorized as high-profit firms, and those with profit margins lower than the average are categorized as low-profit firms, and group regression analyses are carried out, and the regression results are shown in columns (5) and (6) of Table 7.The results of the study show that the contribution of digital transformation to the new quality productivity of firms is more significant in highly profitable firms.Obviously, enterprise development can not be separated from the development of the enterprise economy, can not be separated from the enhancement of corporate profitability, the higher the level of corporate profitability, the more funds available for the development of the enterprise will be able to positively promote the development of the new quality of the enterprise's productive forces, at the same time, the development of the new quality of the enterprise's productive forces can be positively fed back to the level of corporate profitability, to achieve a positive cycle.

According to the characteristics of digital transformation, and combined with the theoretical analysis of the previous paper, this paper explores the role mechanism of digital transformation on the improvement of the level of new quality productivity from two paths: the level of green innovation, and the ability of managers.

In the process of enterprise digitization, as the degree of digitization continues to improve, the continuous upgrading of production tools, the efficiency of its resource allocation will continue to be optimized, thus enhancing the confidence of outside investors and banks to invest in the enterprise, easing the level of corporate financing constraints, improving the possibility of enterprises to obtain market investment, providing financial security for the technological breakthroughs of enterprises, and ultimately promoting the development of the enterprise's new quality of productivity.This paper uses the FC index to measure the level of financing constraints, which is directly expressed by the size of the SA index.The smaller the value of FC, the lower the level of financing constraints of the firm.According to columns (1) and (2) of Table 8, it can be seen that the implementation of digital transformation can significantly alleviate the pressure of the firm's financing constraints, and the reduction of the firm's financing constraints pressure will have a positive effect on the increase of the firm's new quality productivity level. Therefore, the hypothesis H2 of this paper is verified.

With the continuous advancement of enterprise digital transformation, the barrier of information asymmetry is gradually eliminated. The wide application of digital technology has substantially improved the efficiency of information flow and the accuracy of matching, effectively promoting the development and improvement of the green innovation level of enterprises.In addition, digital transformation can increase enterprises' investment in innovation and significantly improve the allocation efficiency and utilization of labor resources, thus further promoting the level of new quality productivity of enterprises.This paper adopts the Green Index to measure the degree of green innovation level, which mainly evaluates the level of green innovation through the number of green innovation patents and R&D patents of enterprises. the smaller the value of Green, the lower the green innovation ability of enterprises.According to columns (3) and (4) of Table 8, it can be seen that the implementation of digital transformation can significantly increase the level of green innovation technology of enterprises, and the increase in the level of green innovation technology of enterprises will have a positive effect on the increase in the level of new quality productivity of enterprises. Therefore, hypothesis H3 of this paper is verified

In the process of enterprises promoting digitalization, the digital literacy and innovation ability of managers will be gradually improved, which not only helps managers master more advanced information technology and business models, but also promotes the optimization of organizational structure and the enhancement of data-driven decision-making, thus facilitating the expansion of enterprises in emerging fields and markets, which is manifested in the enhancement of the productivity of the new quality.According to Zhang et al. (2019), the ratio of the firm's current year's input-output efficiency to the industry's optimal level is regressed by Tobin's model, and the regression residuals can be used as a measure of managerial ability (MA), which is analyzed in this paper as a mediator variable for mechanism analysis.From the results in columns (5) and (6) of Table 8, it can be seen that the depth of digital transformation enhances managerial competence, optimizes the efficiency of firms' internal controls, and further contributes to the improvement of firms' new qualitative productivity levels, and therefore, the H4 hypothesis is validated.

In order to verify the hypothesis of the above moderating effect and analyze the moderating factors in the process of digital transformation of energy enterprises affecting the output of new quality productivity, regression analysis is carried out to analyze the role of moderating variables in the model (3), and the results are shown in Table 9.

In Column 1 of Table 9, the coefficient of the interaction term of digital transformation and entrepreneurship (Dig*Spi) on firms' new quality productivity is 0.0768 and passes the 5% significance test.This indicates that the moderating effect of entrepreneurship on the process of digital transformation to generate new quality productivity exists and is a positive effect, that is, with the enhancement of entrepreneurship, the enterprise's innovation culture and mission spirit are also in the process of enhancement, which ultimately provides a solid foundation for the output of new quality productivity, and the hypothesis H5 holds.In Column 2 of Table 9, we can see that the coefficient of the interaction term between digital transformation and the level of firms' cash holdings (Dig*Cash) on firms' new quality productivity is 0.507 and passes the 10% significance test.This shows the existence of the moderating effect of the firm's cash level on the process of digital transformation to generate new qualitative productivity, and the more the firm's cash flow, the higher the level of cash holding, the more the firm will use to invest in scientific research and innovation, which can significantly and positively contribute to the development of the firm's digital transformation, and thus contribute to the output of the firm's new qualitative productivity, and Hypothesis H6 is verified.

Based on the idea of system engineering, this paper analyzes the relationship between enterprise digital transformation and new quality productivity from multiple angles by using the data of listed companies of energy enterprises from 2014–2023. The main research conclusions are as follows:

(1) Digital transformation has a direct effect on the generation of new quality productivity in energy enterprises. Digital transformation promotes the intelligence of production tools, the refinement of management and the transparency of supply chain integration through the in-depth integration of digital technology with the production and management processes of enterprises, and this direct effect is more significant in state-owned enterprises, small-scale enterprises and enterprises with high profit margins.

(2) Digital transformation has a mediating effect on the generation of new quality productivity in energy enterprises. This mediating effect is reflected in three channels: alleviating financing constraints, improving green innovation and enhancing managerial capabilities.That is, digital transformation can optimize the efficiency of enterprise resource allocation, improve the confidence of banks and investors in enterprises, alleviate financing constraints, and help improve enterprise productivity; through digital transformation, the green innovation capability of enterprises has been improved, the efficiency of information circulation and the accuracy of matching have been enhanced, and the enterprise's ability to apply new technologies and develop new markets has been promoted, so as to realize the leap in enterprise productivity; through the Improvement of enterprise managers' ability, it promotes the optimization of organizational structure and the strengthening of data-driven decision-making, thus facilitating the expansion of enterprises in emerging fields and markets.

(3) The impact of digital transformation on the new quality productivity of energy firms is moderated by entrepreneurship and the level of firm cash.In the process of digital transformation empowering enterprises' new quality productivity, entrepreneurs' innovation and risk-taking spirit play a positive moderating role; the cash level of enterprises enhances their investment confidence and promotes the improvement of their production tools, which provides a solid material foundation for the development of new quality productivity.

(1) Focus on upgrading enterprises' green innovation technologies and alleviating their financing constraints.Government departments should pay full attention to the market value and strategic significance of the development of new quality productivity, adhere to the development direction of digital industrialization, expand digital common technology and its application, focus on digital infrastructure construction, and promote enterprise innovation investment in order to enhance the green innovation capability of enterprises;Incentive policies for digital transformation should be developed, transparent market management should be implemented, digital financial services should be promoted, and enterprises' financial investment in digital transformation development should be guaranteed to alleviate their financing constraints;Strengthen digital skills training, enhance the digital literacy of high-quality talents, send more excellent managers to enterprises, give full play to the ability of enterprise managers, combine the development of new quality productivity concepts with enterprise values, accelerate the pace of digital transformation, seek development in the transition, promote transformation in the development, and achieve a benign combination of economic development and the development of new quality productivity, and promote the high-quality development and sustainable development of enterprises. The company will also promote the development of high quality and sustainable development of the enterprise.

(2) Promote the process of enterprise intelligence and seek common development of enterprises.Government departments should accelerate the promotion of new infrastructure construction and build a firm foundation for enterprise digital transformation. Improve the financial market mechanism, promote the coordinated development between the industry and the industry, build an exchange platform, promote the exchange and cooperation between enterprises, mutual benefit and win-win situation, develop economies of scale, and seek common development of enterprises.At the same time, it focuses on the development of small-scale enterprises and provides focused support to small-scale enterprises with potential to produce phenomenal technology enterprises such as deepseek. Emphasize the economy of scale of state-owned enterprises, develop the role of regional leader, integrate all kinds of production factors, open up the connection between equipment, data and network, and promote the comprehensive and coordinated development of enterprises.

(3) Promote entrepreneurship, raise the level of corporate cash, and promote digital transformation.Government departments can create a high-quality business environment that helps innovation and entrepreneurship, safeguard the reasonable rights and interests of entrepreneurs, increase their enthusiasm for entrepreneurship and confidence in development, guide enterprises to the high-tech level, seize the dividends of the era of digital transformation, promote the digital transformation of enterprises, and promote the intelligent enhancement of enterprises as a whole.At the same time, it can broaden enterprise financing channels, promote consumer investment enthusiasm, create a good external environment for enterprises in digital transformation, maintain good government-enterprise relations, and reduce the cost of enterprise digital transformation, so as to improve the cash level of enterprises, increase the confidence of enterprises in innovation investment, and effectively promote the development of digital transformation in all segments and sectors of the enterprise.

The limitation of this paper's research is that it focuses on energy enterprises and systematically explores the direct, mediating and possible moderating effects of digital transformation on the formation of their new quality productivity, but it lacks the expansion of the research on the participation of the governmental level and the public level in the digital transformation to empower the new quality productivity and the deepening of the research on the mechanism of the interaction between mediating and moderating variables, which is the focus and direction of the future further research.