Research on the Role Mechanism and Innovation Path of Enterprise Management Transformation in the Development of Digital Economy

In the era of digital economy, the business environment in which enterprises are located is increasingly complex, and the digital transformation of enterprise management has become an inevitable trend. Enterprises need to apply new technologies to optimize business processes, enhance the competitiveness of products and services, and seize opportunities and meet challenges by better adapting to market changes [1-2]. In terms of management style and energy efficiency, digital management is a kind of innovative management mode based on digital technology, which can promote the openness and open source of enterprise R&D, modularization and flexibilization of production, and precision and refinement of marketing, help enterprise decision makers to optimize the allocation of resources such as information flow, capital flow, logistics, etc., and effectively promote the effective landing of enterprise management culture [3-7]. In this sense, the success or failure of modern enterprise management is closely related to its own adaptive management capabilities.

In the era of digital economy, through management transformation, enterprises can understand the needs of customers more deeply and provide them with personalized products and services, thus enhancing their market competitiveness [8-9]. It can also introduce new technologies and thinking methods to better develop new products and services and create a new innovation-driven development model, thus realizing differentiated competition [10-11]. At the same time, through management transformation, enterprises can optimize the operation process and reduce the unnecessary links in it, thus reducing the operation cost [12-13]. The application of automation and intelligent technology helps enterprises to reduce labor costs, improve production efficiency, and realize cost reduction and efficiency [14-15].

The “adaptability” of enterprise management is the process of improving the adaptability of enterprises to the digital economy environment in adapting to the new concepts and new thinking of the digital system, as well as the process of optimizing and improving the behavioral characteristics of enterprises, which is a change with both risks and opportunities [16]. Literature [17] takes resource dependence as a research perspective and concludes that the development of regional digital economy will promote enterprise innovation, and the digital transformation of enterprises plays a positive mediating role in this process by changing enterprise efficiency. Literature [18] explores how digital transformation affects enterprise architecture (EA) that facilitates business transformation, pointing out that traditional EA is unable to sustainably adapt to changing business and technological environments, and thus proposes vertical enterprise architectures with organizational capabilities to help build flexible and resilient enterprises. Literature [19] analyzes the key organizational capabilities needed for MSMEs to achieve sustainability through digital transformation, including advanced organizational culture, stakeholder ownership, and corporate decision-making based on big data technologies, which will help companies attract customers and investors with sustainable values and give them a competitive advantage. Literature [20] re-examined the applicability of enterprise business process management (BPM) in the context of digital transformation and proposed an approach to BPM management based on new a priori logic and assumptions, which helps to demonstrate the contextual differences between digital transformation and technology support for enterprises. Literature [21] investigated technology management strategies for MSMEs in digital transformation, showing that effective technology management strategies can help enterprises automate business processes, reduce operational costs, and increase productivity and innovation, which is the key for MSMEs to complete digital transformation. Literature [22] explored the drivers of digital transformation of HRM in enterprises and emphasized that digital HRM based on advanced digital technologies for selection, training, development and evaluation will bring outstanding competitive advantages to enterprises, but there are potential negative impacts of the conversion process of HRMS. Literature [23] examined the relationship between supply chain relational capital, corporate green management and financial performance based on empirical data, and found that corporate supply chain relational capital in the period of digital transformation enhances financial performance by strengthening green management. Literature [24] investigated the customer knowledge management (CKM) strategies of micro, small and medium-sized enterprises (MSMEs) and found that most SMEs engaged in creative industries are less likely to use cheap and easy-to-use innovative digital technologies due to the lack of support from information technology (IT) vendors, i.e., it is difficult to respond to the rapid technological changes that affect CKM.

This paper analyzes the promotion effect of digital economy on enterprise management transformation from both internal and external levels, and proposes research hypotheses based on the results of theoretical analysis combined with related research. The evaluation system for enterprise management transformation and digital economy levels has been constructed, and the entropy weight method has been used to quantitatively measure these two variables. A benchmark regression model is established to test the influence relationship between digital economy and enterprise management transformation, and the robustness of the benchmark regression results is verified through the robustness test methods such as the replacement variable method and lag period regression. The total enterprise performance improvement rate, government subsidies and analysts' attention are taken as mediating variables, and the explanatory variables are treated one period ahead to construct a mediation effect model to analyze the role mechanism of the digital economy affecting enterprise management transformation. The panel data of Chinese A-share listed enterprises from 2014-2023 are selected and input into the model, and the results of regression analysis are combined to propose innovative paths for enterprise management transformation from four perspectives, namely, strategic thinking, organizational structure, business processes and human resources. It provides ideas and inspiration for enterprises to realize their own digital transformation and enhance their market competitiveness in the context of the digital economy.

2

Mechanisms for the role of business management transition

2.1

Theoretical analysis and research hypothesis

In recent years, the digital economy has not only revolutionized the way enterprises conduct business and establish relationships with consumers, suppliers and other stakeholders, but also played an active role in promoting business model innovation and customer value manufacturing [25]. The digital economy has likewise accelerated the transformation and upgrading of enterprise management, which has directly led to the digitization of transformation and the decentralization of organizational methods, the sustained and substantial reduction of management costs, the significant improvement of enterprise performance, the results of group, chain, and cross-domain outputs are common, and disruptive and revolutionary innovations parallel iterative and incremental innovations. Based on the existing research results, this paper argues that the digital economy has a positive impact on enterprise management transformation at both the internal and external levels of the enterprise.

2.1.1

Internal level

At the internal level, the positive role of the digital economy in improving the overall performance rate of enterprises contributes to the transformation of business management. Specifically, the digital economy has the following effects on enterprise management transformation: first, expanding the knowledge base. Under the use of digital technology, the ability to collect and integrate data within the enterprise is increasing, and in the process of establishing various business plans, the integration and development is strengthened, so as to innovate and adjust the mode of enterprise services. Second, improve management's openness. The modern network environment is both complex and open-minded. Through the management process, the development of enterprise information is clear and the appropriate deployment of relevant information is used to achieve sustainable and healthy development of the enterprise. The use of advanced technology can make communication between various departments of the enterprise more convenient. Through the management platform, the enterprise can arrange for the corresponding personnel to upload the formulated work standards, improve the speed of information dissemination, and thus improve the management level. Third, promote process innovation. The effective application of digital technology in management can effectively break through the limitations between various management links to ensure the effective connection of the processes, so as to achieve the optimization of the content and shorten the time spent by enterprises in various activities.

2.1.2

External dimension

At the external level, the digital economy enhances the management transformation of firms through access to government subsidies and increased market attention. Firstly, the digital economy helps enterprises obtain more government subsidies. In the process of promoting the digital economy and enterprise management transformation, the government has introduced a number of policies to support and encourage enterprises to carry out digital management transformation. With the support of these policies, enterprises carrying out digital management transformation can obtain more government subsidies and bank loans, thus widening the financing channel and alleviating financing constraints. And financing constraints are one of the main factors hindering the management transformation of enterprises. Therefore, from this point of view, enterprise digital management transformation can improve management output and efficiency by obtaining government subsidies to overcome the financing constraints faced by enterprise management transformation. Secondly, the digital economy can improve the market attention of enterprises. As a new production factor, data has an important impact on the upgrading of industrial structures and the transformation of economic growth mode. In this context, the transformation of enterprise management to digital will attract more attention and tracking from analysts and other capital market participants. It has been found that analysts' attention has a significant positive impact on enterprise management transformation. As an intermediary between managers, shareholders, and investors, analysts play an important role in alleviating corporate information asymmetry. If analysts are able to accurately convey corporate information and value to external investors and thus reduce the degree of information asymmetry, they not only help to resolve financing difficulties, but also inhibit managerial agency behavior, thus significantly contributing to corporate management transformation.

Based on the above analysis, this paper proposes:

H1: Digital economy can promote business management transformation.

H2: The digital economy contributes to business management transformation by increasing the total performance rate internally, obtaining government subsidies externally and increasing market attention.

2.2

Study design

2.2.1

Definition of variables

1)

Explained variable: enterprise management transformation ( Emt )

Enterprise management transformation refers to the process in which an enterprise, in order to cope with changes in the internal and external environments, actively or passively carries out systematic changes and innovations in the enterprise's management concepts, management models, management methods, organizational structure, etc., so as to enhance the core competitiveness of the enterprise and achieve long-term stable development. This process is often accompanied by the synchronization of technological innovation, product upgrading, market expansion, talent strategy adjustment, and other aspects. Based on this, this paper constructs the evaluation index system of enterprise management transformation level from technology dimension, business dimension, management dimension and benefit dimension, and the results are shown in Table 1. Furthermore, the entropy power method is used to measure the level of transformation in enterprise management.

Table 1.

Enterprise management transformation evaluation system

Primary indicator	Secondary indicator	Indicator description
Technical dimension	Hardware equipment	The Internet, intelligence, and operational capabilities of enterprise equipment
	Software system	Deployment, application and integration of software systems
	Industrial data	Industry data acquisition, storage, analysis and management
	Digital platform	Industrial Internet platform construction and application level
	Information security	Information security system and technical level
Business dimension	Platform design	The ability of R&D design to use digital technology
	Intelligent manufacturing	The ability and efficiency of digital technology in production manufacturing
	Networked synergy	The ability of enterprise organizations to coordinate the industrial chain
	Personalized customization	Ability to meet the user's personalized needs
	Service extension	Ability to provide value-added services such as after-sales transportation and data analysis
Management dimension	Strategy and language	Digital transition plan and the overall atmosphere of the enterprise
	Organization and process	The application of digital technology and thinking of organization and process
	Digital talent	The cultivation and use of digital talents
Benefit dimension	Economic benefit	The economic benefits of managing transition
Benefit dimension	Social benefit	The social benefits of management transformation

2)

Explanatory variables: digital economy ( Dig )

The so-called digital economy is an information economic form that takes digital information as the core production factor in order to realize the intelligent development of industry, and it emphasizes digital industrialization and industrial digitalization development. Based on this, this paper refers to the existing research results, from the digital industrialization and industrial digitization dimension to construct the evaluation system of digital economy development, the results are shown in Table 2. The entropy weight method is further adopted to measure the level of development in the digital economy.

Table 2.

Digital economic development evaluation system

Primary indicator	Secondary indicator	Tertiary indicator
Industry digitization	Industry digital transformation	The number of enterprise websites owned by every hundred
		Expenditure on digital technology transformation for enterprises above designated size
		Expenditure on digital technology introduction for enterprises above designated size
	Industry digital trading	E-commerce business accounts
		The number of computers per hundred people
		Enterprise e-commerce trading volume
Digital industrialization	Digital industrialization innovation	High technology enterprise number
		High tech enterprise profit value
		Main business income of high-tech enterprise
	Digital industrialization service	Delivery volume
		Telecommunications quantity
		Postal capacity
	Fundamentals of digital industrialization	Information and information technology industry related enterprises
		The number of people in the information and information technology industry
		Information and information technology industry related main business income

3)

Control variables

This paper combines the results of existing literature to select control variables at the micro and macro levels. At the micro level, the management education level ( Manedu ), based on the education level assignment method for the education level, is further characterized by the ratio of the total education level of enterprise managers to the size of management. Management compensation level ( Manrem ), calculated based on the average annual compensation of corporate management. Number of directors ( Manager ), characterized by the logarithmic number of corporate board of directors. Net profit margin on corporate assets( Pr ofit ), measured by the average balance of total assets accounted for by corporate net profit. Firm revenue growth rate ( Income), measured as the ratio of the firm's current year's revenue to the previous year's revenue minus one. Business size ( Size), calculated using the logarithm of the firm's average annual total assets. Enterprise asset turnover ( Asset ), selected enterprise operating income to the ratio of the average total assets of the enterprise accounting. Enterprise accounts receivable( Account ), estimated using the proportion of enterprise net accounts receivable to enterprise total assets. Enterprise cash flow ratio ( Cashflow ), measured using the ratio of enterprise net cash flow to enterprise total assets. At the macro level, overall industry size ( Scale ), measured by taking the logarithm of the industry's total industrial output value. Tax burden ( Revenue), expressed as VAT payable divided by total industrial output value.

2.2.2

Model setup

In order to test the relationship between the impact of digital economy and business management transformation, this paper constructs the following baseline estimation model: (1) $E m t_{i, t} = α_{0} + α_{1} D i g_{i, t} + α_{2} C o n_{i, t} + δ_{i} + μ_{t} + ε_{i, t}$

where Emt_i,t denotes the level of managerial transformation of i firms in year t . Dig_i,t represents the level of digital economy. Con_i,t represents the set of control variables, including management education level, management compensation level, number of directors, firm net asset margin, firm revenue growth rate, firm size, firm asset turnover, firm accounts receivable, firm cash flow ratio, overall industry size and tax burden. α₀ is a constant term. α₁_۱ α₂ are the estimated coefficients of the digital economy and control variables, respectively. δ_i and μ_t are firm fixed effects and year fixed effects, respectively. ε_i,t is the random interference term.

2.2.3

Data sources

This paper collects and integrates panel data from Chinese A-share listed enterprises for the research period 2014-2023. Among them, enterprise-related data are mostly taken from the China Statistical Yearbook, public annual reports of enterprises, CSMAR database, Wind database and CNRDS database. The rest of the variables are mainly obtained from the database of the National Bureau of Statistics, CEIC data, statistical bulletins of national economic and social development of each region, and the official websites of national and provincial statistical bureaus. Meanwhile, linear interpolation was used to fill in some missing data. The following treatments were carried out on the samples to improve the accuracy of the study: first, enterprises related to PT, *ST and ST categories were excluded. Second, listed companies with less than 5 years of development were excluded. Third, enterprises with serious missing core variables from 2014-2023 are excluded. In addition, the continuous variables are reduced-tailed based on the upper and lower 1%. The final sample size is 13,864.

2.3

Empirical analysis

2.3.1

Descriptive statistics and correlation analysis

1)

Descriptive statistics

Figure 1 shows the descriptive statistics of the main variables. The mean value of Emt is 5.33, the standard deviation is 5.18, and the maximum and minimum values are 1.06 and 0.22 in turn, implying that there are large differences in the level of management transformation among different enterprises. The mean of Dig is 2.34, the standard deviation is 1.55, and the maximum and minimum values are 5.66 and 0.07. It means that there is also a big difference in the level of digital economy in different provinces, some provinces have a higher degree of development of digital economy, while some provinces are lagging behind in the development of digital economy.

2)

Correlation analysis

Figure 2 shows the correlation coefficients between the variables, in which the correlation coefficient between digital economy and enterprise management transformation is 0.179, which is significantly positive at the 1% level, and hypothesis 1 is preliminarily verified. In addition, the variance inflation factor between the variables is tested to be less than 4, and the mean value of the method inflation factor is 1.67, indicating that there is no serious multicollinearity problem between the variables.

2.3.2

Analysis of baseline regression results

In this paper, we use the fixed effect model for regression analysis [26], and Table 3 shows the baseline regression results. It can be found that the regression coefficient of digital economy ( Dig ) on enterprise management transformation ( Emt ) is 0.6238, and after adding control variables, the regression coefficient is 0.6157, both of which are significantly positive at 1% statistical level. It indicates that for every 1 unit increase in the level of digital economy, the level of enterprise management transformation will be increased by 61.57%, i.e., the development of digital economy promotes the level of enterprise management transformation, and the hypothesis H1 is verified to be valid.

Table 3.

Reference regression

Variable	(1)	(2)
Dig	0.6238***	0.6157***
Manedu	¥	3.0586***
Manrem	¥	0.5864***
Manager	¥	1.7783
Profit	¥	-0.1638***
Income	¥	-0.0915***
Size	¥	-0.1786
Asset	¥	5.0657***
Account	¥	0.0586***
Cashflow	¥	0.0794***
Scale	¥	0.5258
Revenue	¥	-0.8364
_cons	7.7136***	7.0583***
Enterprise fixation effect	Yes	Yes
Year fixed effect	No	Yes
R²	0.8023	0.7948
Adjust R²	0.7986	0.7853
Observed value	13864	13864

2.3.3

Robustness Tests

1)

Replacement variable method

In order to ensure the robustness of the regression results, this paper regresses the dummy variable of whether the company adopts effective management measures as a substitute variable for corporate management transformation. The regression results are shown in Panel A in Table 4. The regression coefficient of Explanatory Variable Dig is 0.5873, which is still significantly positive at the 1% statistical level, indicating that after replacing the dependent variable, the degree of digital economy development and the level of enterprise management transformation are still positively correlated, and the results of the main regression are relatively robust.

Table 4.

Robustness test

Variable	Panel A	Panel B
Dig	0.5873***	0.5675***
Control variable	Yes	Yes
Enterprise fixation effect	Yes	Yes
Year fixed effect	Yes	Yes
R²	0.7936	0.7497
Adjust R²	0.7843	0.7362
Observed value	13864	13864

2)

Lagged period regression

Although this paper has taken the factors that may affect enterprise management transformation as control variables, there may still be some unobserved or uncontrolled factors. In order to avoid the problem of endogeneity, this paper has treated both explanatory variables and control variables in the regression with one period lag to test the effect of digital economy on enterprise management transformation, and the results are shown in Panel B in Table 4. The coefficient of digital economy ( Dig ) is 0.5675, which is still significantly positively correlated with the level of enterprise management transformation ( Emt ). It shows that the original regression conclusion still holds after controlling for endogeneity issues.

3)

Controlling for province-level changes over time

In order to exclude the influence of many unobservable factors at the regional level over time on enterprise management transformation, this paper further adds the annual province interaction term Year*Province to the model to control the unobservable factors at the regional level over time, and the regression results are shown in Table 5. The results show that the coefficient of Dig affecting business management transition is 0.5573, which is significantly positive at the 1% level, verifying the robustness of the paper's findings.

Table 5.

Control the changes in the provincial level

Variable	Panel C
Dig	0.5573***
Manedu	4.0786***
Manrem	0.3654***
Manager	3.0127
Profit	-0.1873***
Income	-0.0926***
Size	-0.2176
Asset	5.3478***
Account	0.0637***
Cashflow	0.0782***
Scale	0.5473
Revenue	-8.9726
_cons	9.8374
Year*Province	Yes
Enterprise fixation effect	Yes
Year fixed effect	Yes
R²	0.7183
Adjust R²	0.6972
Observed value	13864

2.3.4

Mechanism of action analysis

1)

Modeling

With reference to related research, this paper constructs the following mediation effect model to test the role mechanism of digital economy in affecting enterprise management transformation: (2) $M e d i a t o r_{i, t} = β_{0} + β_{1} D i g_{i, t} + β_{2} c o n t r o l_{i, t} + δ_{i} + μ_{t} + ε_{i, t}$ (3) $E m t_{i, t + 1} = γ_{0} + γ_{1} D i g_{i, t} + γ_{2} M e d i a t o r_{i, t} + γ_{3} c o n t r o l_{i, t} + δ_{i} + μ_{t} + ε_{i, t}$

Considering that there is a time lag from the investment in management transformation to the generation of transformation output and transformation efficiency, this paper treats the explanatory variables one period ahead. Emt_i,t+1 is the level of management transformation in year t+1 of firm i , Dig_i,t+1 is the level of digital economy in year t of firm i , Mediator_i,t is the mediator variable measured by the total performance improvement rate, government subsidies, and analysts' attention in year t of firm i , control_i,t is the control variable, δ_i and μ_t denote the firm fixed effect and year fixed effect, respectively, and ε_i,t is the random perturbation term.

2)

Mechanism analysis

The specific settings of the mediating variables are as follows: the total performance improvement rate ( Tpir ) is measured using the total asset turnover ratio [27]. The total asset turnover ratio is defined as the ratio of main business income to total assets, and the larger its value, the higher the business performance of the enterprise. Government grants ( Gov ) uses the ratio of the amount of government grants received by the enterprise to the total assets as a metric, which tests the mediating role played by government grants in the process of digital economy affecting the management transformation of enterprises. Analyst attention ( An ) adopts the number of analysts tracking the enterprise as the measure. This paper substitutes the relevant data into the model and obtains the results shown in Table 6. The data in the table show that the regression coefficients of digital economy ( Dig ) on total performance improvement rate ( Tpir ), government subsidy ( Gov ) and analyst attention ( An ) are 0.037, 0.009 and 0.483 respectively, all of which are significantly positive at 1% level, indicating that the digital economy has a significant positive impact on the aspects of total enterprise performance improvement, obtaining government subsidy and analyst attention. The regression coefficients of Dig and Emt are 0.174, 0.138 and 0.149 respectively after including the mediator and explanatory variables, and all of them are significantly positive at the 1% level. The regression coefficients of Tpir , Gov and An are 0.142, 7.248 and 0.037 respectively, which are significantly positive at 1% level, and the Z-values of Sobel test are all significant at no less than 10% level. It indicates that digital economy, total performance improvement rate, government subsidy and analyst attention have significant positive impact on business management transformation, which verifies that hypothesis H2 of this paper is valid. Moreover, improving the total performance rate, obtaining government grants, and attracting analyst attention are the internal action paths of the digital economy that affect enterprise management transformation.

Table 6.

Mechanism analysis

Variable	(1) Tpir	(2) Emt	(3) Gov	(4) Emt	(5) An	(6) Emt
Dig	0.037***	0.174***	0.009***	0.138***	0.483***	0.149***
Tpir	¥	0.142***	¥	¥	¥	¥
Gov	¥	¥	¥	7.248***	¥	¥
An	¥	¥	¥	¥	¥	0.037***
Control variable	Yes	Yes	Yes	Yes	Yes	Yes
_cons	0.674***	-5.728**	0.008***	-5.672**	-3.026**	-3.947**
Enterprise fixation effect	Yes	Yes	Yes	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Sobel Z	¥	1.928**	¥	2.132**	¥	4.107**
Adjust R²	0.364	0.168	0.172	0.293	0.286	0.179
Observed value	13864	13864	13864	13864	13864	13864

3

Innovative paths for business management transformation

3.1

Innovations in strategic thinking

Against the backdrop of the current rapid expansion of the digital economy, corporate strategy needs to closely follow the trend of the times and commit itself to in-depth innovation in order to adapt to the rapid changes in the market. The innovation's main focus is on two strategic cores, the cross-border integration strategy and the ecosystem strategy, which together determine the competitiveness of enterprises in the new economic landscape. Based on this, enterprises need to actively build their own ecosystems and establish close cooperative relationships with other enterprises, organizations, and individuals to jointly promote ecological prosperity. This strategy requires enterprises to hold an open mind and share resources, knowledge, and technology in order to promote innovation and development.

3.2

Organizational innovations

In the face of rapid changes in the marketplace, companies must radically revamp their existing structures to create a competitive advantage in the digital age. This change is mainly reflected in the trend of organizational flattening and flexibilization, which complement each other to create a new look of enterprises adapting to the digital economy. Organizational flattening subverts the traditional hierarchical pyramid structure, under which information transfer is limited by complicated approval and transmission procedures, which is inefficient and prone to distortion and delay. In the digital era, the rapid evolution of the market requires companies to be able to react quickly and flexibly. The flat structure meets this need by streamlining the intermediate management level, facilitating the direct and rapid flow of information, and enhancing the efficiency of decision-making. In this way, enterprises can flexibly adjust their modular strategies and resource allocation according to market dynamics, resulting in efficient response and adjustment of the organization.

3.3

Business process innovation

In the context of the development of the digital economy, the competition faced by enterprises has become particularly fierce, and the innovation of business processes is particularly important, which has become the core of enhancing the core competitiveness of enterprises. In this context, the use of digital and intelligent processes for enterprises to bring new opportunities to improve efficiency and reduce costs. In-depth discussion of the digital process, its connotation is far more than a simple conversion of paper documents to electronic documents, but a complete remodeling and upgrading of existing business processes. This change involves all aspects of business operations, such as order processing, inventory management, to financial control, customer service and other aspects, all need to experience digital transformation.

3.4

Human resource innovation

The human resources of an enterprise have been transformed into one of the key and precious assets, technological innovation, market expansion, service quality improvement, all of which depend on a team of talents with high quality and strong creativity. If enterprises want to break through in market competition, human resource innovation is crucial, especially in the recruitment and cultivation of talent, and in the reform of the incentive mechanism of the two core links. Based on this, companies need to tailor differentiated incentive programs to the characteristics and needs of their employees, including pay incentives, promotion opportunities, honorary recognition, and other ways. For example, provide higher pay and rewards for outstanding performance. For employees with hidden leadership talents, more promotion and training opportunities are offered. Honorary titles and medals are awarded to employees who have made significant contributions.

4

Conclusion

This paper focuses on analyzing the role mechanism of the impact of digital economy on enterprise management transformation by establishing a regression model, and proposes an innovative path for enterprise management transformation by combining the regression results.

The baseline regression coefficient for digital economy on enterprise management transformation is 0.6238, but with the addition of control variables, it drops to 0.6157, which is significant at 1% statistical level. It indicates that the development of the digital economy can significantly promote the level of enterprise management transformation. After replacing the explanatory variables, the regression coefficient of digital economy is 0.5873. After lagging the explanatory variables and control variables by one period, the regression coefficient of digital economy is 0.5675, and the coefficient of digital economy affecting the transformation of enterprise management after adding the interaction term of the yearly province is 0.5573. The robustness of the benchmark regression results is fully demonstrated by the significant positive regression coefficients obtained by the above treatments at the 1% level. The robustness of the baseline regression results is well illustrated. Meanwhile, the digital economy has a significant positive impact on the total performance improvement rate, government subsidies, and analysts' attention, and the regression coefficients are significantly positive at the 1% level. Under the transmission mechanism of mediating effect, the regression coefficients of digital economy on enterprise management transformation are significant 0.174, 0.138, and 0.149 respectively at 1% statistical level, which further illustrates the significant facilitating effect of digital economy on enterprise management transformation. In addition, the regression coefficients of the mediating variables on enterprise management transformation and the Sobel test results reveal that improving the total performance rate, obtaining government grants and analyst attention can serve as internal action paths for the digital economy to influence enterprise management transformation.

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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Research on the Role Mechanism and Innovation Path of Enterprise Management Transformation in the Development of Digital Economy

Wen Zhao

Published Online: Mar 17, 2025

Received: Oct 07, 2024

Accepted: Feb 04, 2025

DOI: https://doi.org/10.2478/amns-2025-0334

KeywordsDigital economy, Regression model, Benchmark regression, Mediating variables, Business management transformation

© 2025 Wen Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Digital economy, Regression model, Benchmark regression, Mediating variables, Business management transformation