A Study on the Impact of Enterprise Digital Evolution on Outward Foreign Investments

Abstract

In the age of the digital economy, digital evolution has emerged as a central focus in academic research. The achievement is of paramount importance for augmenting their international investments. This research utilizes data from publicly listed manufacturing firms in China from 2010 to 2021 to examine the influence of enterprise digital evolution on outbound foreign investments. The research findings reveal that enterprise digital evolution has a significant positive impact on the outward foreign investments of enterprises and exhibits heterogeneity in terms of region, company size, and industry type. Mechanism tests reveal that the impact of enterprise digital evolution on outward foreign investments can be realized through four pathways: enhancing ESG performance, reducing debt financing costs (COD1) (representing the proportion of interest costs to the total of long and short-term debts), company age, and debt financing costs (COD2) (denoting the proportion of financial expenses to the total of long and short-term debts). In the context of digitization, enterprise digital evolution continues to hold positive significance for outward foreign investments, contributing to the enrichment of the theoretical research on the subject to a certain extent.

1. Introduction

The development of the digital economy, centered around technologies such as the Internet, big data, and 5G, has become the trend of the times. “Digital development” is increasingly reflected in the production and operation of enterprises. For example, enterprises are gradually transitioning to intelligent production and management models by leveraging digital technologies. This transition reduces the cost of market information search, enables resource sharing, and necessitates a transformation in both enterprise resource management capabilities and digital technology capabilities. To adapt to the trend of digital development and transition from traditional enterprise management systems to digital ones, enterprise digital evolution has become the primary task for promoting technological innovation, facilitating information exchange among entities, and enhancing market competitiveness.

Enterprise digital evolution refers to the process whereby businesses utilize digital technologies to enhance resource efficiency, reduce production costs, and ultimately improve overall efficiency. Digital evolution not only impacts the production and operational efficiency of enterprise but also exerts an influence on innovation and outward investments. Enterprise digital evolution encompasses the overhaul of production methods, organizational structures, and other facets spurred on by the widespread adoption of digital technology [1]. It constitutes a disruptive technological shift [2], necessitating companies to deeply integrate modern digital intelligent technologies such as blockchain, big data, and artificial intelligence into their existing production systems [3]. This transformation drives the digitization of production factors and processes [4], augmenting operational efficiency, optimizing resources, and promoting enterprise green technology innovation [5]. As microeconomic entities in economic development, enterprises, amidst the digital economy’s backdrop, are undergoing shifts in their management approaches grounded in digital evolution [6]. They are reshaping traditional business operations, utilizing tools like digital technology for achieving digital evolution, thereby ensuring a dynamic alignment between enterprise development and the external environment [7]. Given the ongoing enhancement in corporate digital evolution and innovation capabilities, comprehending the effects and mechanisms of how digital evolution influences outward foreign investments holds significant value. In summary, prevailing academic research on enterprise digital evolution has primarily concentrated on augmenting internal production and operational efficiency, improving innovation capabilities, and enhancing the overall economic benefits through avenues like fostering innovation and reducing costs. Nevertheless, there has been limited exploration into how digital evolution impacts enterprises’ outward foreign investments and the underlying mechanisms. Therefore, it is imperative to investigate the influence of enterprise digital evolution on outward foreign investments and the associated processes.

Building upon the previously mentioned context, the paper employs data from public manufacturing companies in China across the years 2010 to 2021 to analyze the effect of company digital evolution on outward foreign investments. Furthermore, it analyzes the processes through which digital evolution facilitates outward foreign investments. In comparison to previous research, this paper’s marginal contributions may include the following:

• Firstly, it is confirmed that the corporate digital evolution of listed companies exerts a substantial positive influence on their outward investments. Existing research has found that enterprise digital evolution has a positive impact on outward foreign investments [8,9]. Regression analysis using a two-way fixed effects panel model verifies the positive influence of digital evolution on outward foreign investments. Robustness tests involving lagged explanatory variables, changes in time samples, and instrumental variable usage support this conclusion. Therefore, such influence is enhancing the extent to which digital evolution can foster the development of outward foreign investments for companies.
• Secondly, it was found that the influence of company digital evolution on the outward investments of public companies exhibits regional heterogeneity, firm size heterogeneity, and industry heterogeneity. Building upon Guo Juanjuan’s research [10], this paper extends the analysis to explore the regional, scale, and industry differences in how enterprise digital evolution impacts outward foreign investments. Corporate digital evolution has a substantial promotional impact on the outward investments of enterprises in the eastern region and a noticeable inhibitory effect on enterprises in the northeastern region, and digital evolution significantly promotes the outward investments of medium-sized and very large enterprises, while it has no significant effect on small and micro-sized enterprises, as well as large enterprises. Corporate digital evolution has a notable promoting effect on the outward investments of the enterprises in high-tech and non-polluting industries, while it does not have a significant impact on the enterprises in non-high-tech and polluting industries.
• Thirdly, how corporate digital evolution mediates the impact on enterprises’ outward investments is examined. The research investigates the mediation effects of digital evolution on outward foreign investments [11]. It investigates the correlation between digital evolution and corporate ESG performance, revealing that digital evolution enhances ESG performance, which, in turn, reinforces innovation development and promotes outward foreign investments [12,13]. Additionally, digital evolution reduces debt financing costs (COD1), thereby facilitating outward foreign investments.
• Fourthly, how corporate digital evolution moderates the impact on enterprises’ outward investments is investigated. Existing studies have found that the age of enterprises has an impact on Chinese enterprises’ OFDI in developing and developed countries [14]. The research finds that the age of the company and debt financing costs (COD2) act as moderating factors in the relationship between digital evolution and outward foreign investments.

In summary, most of the existing studies have focused on the study of the direct effect of enterprise digital evolution on outward investment, as well as performing heterogeneity analysis. The innovations of this paper are as follows: In terms of the conclusion, firstly, it is found that the impact of enterprise digital evolution on outward investment can be achieved through two paths: improving ESG performance and reducing the cost of debt financing COD1. Secondly, it is found that the greater the age of the enterprise the stronger the positive impact of enterprise digital evolution on outward investment, and a greater cost of debt financing COD2 will inhibit the positive impact of enterprise digital evolution on outward investment. In terms of theory, the research on the theoretical aspects of enterprise digital evolution on outward investment is enriched. Existing research focuses on the theoretical study of technological progress, artificial intelligence, and other outward investment of enterprises, and this paper studies the influence of the digital evolution of enterprises on the outward investment of enterprises, which enriches the theoretical research related to the digital transformation of enterprises and outward investment of enterprises. In terms of methodology, a methodological test of the impact of extended enterprise digital transformation on corporate outward investment is presented. Previous studies have used the fixed effects model to test the relationship between the two, and this paper uses the mediating effect model and the moderating effect model for further testing, providing diversified thinking for the study of enterprise digital evolution and outward investment. It is worth noting as follows: First, the study only controlled for firm-level variables. It did not control other factors that may affect the relationship between them, and there are certain deficiencies. Second, the impact of digital evolution on different types of investment is not discussed. In the case of different types of investment, is it true that enterprises’ digital evolution is positively promoting enterprises’ outbound investment? The study does not discuss this and such matter could be further studied in the future.

The following sections of the paper are structured as follows: the second part includes a review of the existing literature and hypotheses, the third part covers empirical models, indicators, and data, the fourth part provides empirical results, and the fifth part concludes with insights. The analytical logic and technical methods used in the research process are illustrated in Figure 1.

2. Review of the Literature and Theoretical Hypotheses

2.1. Impact of Enterprise Digital Evolution on Outward Foreign Investments

Based on the advancement background of the digital economy, the depth of company digital evolution has continuously been enhanced, and research in the academic community has grown. Currently, research outcomes primarily focus on three aspects: the factors impacting corporate digital evolution digital evolution, the economic effects resulting from it, and the methodologies for achieving enterprise digital evolution.

Firstly, the influencing factors in relation to corporate digital evolution were explored. The factors influencing corporate digital evolution primarily revolve around three key aspects: digital technology, the characteristics of managers and their social capital, and the resources and capabilities of the enterprise. External factors such as changes in the environment, support from relevant national policies, infrastructure development, the background characteristics of corporate management, and social resources are crucial driving forces propelling enterprise digital evolution [15]. In the realm of digital technology, there is a significant positive relationship between digitalization and green innovation [16]. At the same time, investment in enterprise digitalization shows an “inverted U-shaped” relationship with capacity utilization [17]. There is a positive direct relationship between business digitalization and business performance, and innovation can moderate the relationship between firm digitalization and its economic and financial performance [18]. From the perspective of enterprise digital evolution, good ESG performance significantly promotes green innovation, and digital evolution plays a positive moderating role in the relationship between ESG performance and green innovation [19]. The manufacturing industry follows digital evolution with the goal of digital manufacturing with competitive and sustainable production systems, strengthening investment in 5G technology, and promoting manufacturing performance [20]. Regarding managerial characteristics and their social capital, there is a direct positive correlation between digital evolution and innovation performance, and a CEO’s financial background will affect the positive impact of an enterprise’s digital evolution [21]. The more confident CEOs, Celebrity CEOs, and CEOs with information technology backgrounds are [22,23,24] can significantly promote the digital evolution of enterprises. Some scholars further found that technology and ecosystem capabilities have a positive and significant impact on digital evolution and innovation, while organizational capabilities have a positive impact on innovation but a negative impact on digital evolution [25]. Concerning enterprise resources and capabilities, top IT managers will significantly promote the technology diversification of SMEs [26], and the age of directors will hinder the innovation of the company [27].

Secondly, the economic outcomes of enterprise digital evolution were explored. Enterprise digital evolution influences the efficiency of production and operation, stock market performance, and the overall economics of companies. In terms of enterprise production and operation efficiency, enterprise digital evolution can effectively promote the growth of enterprise innovation efficiency, in which financial information disclosure plays an important mediating role [28]; digital transformation has a significant role in promoting the production efficiency of manufacturing enterprises [29]. In terms of stock market performance, digital evolution improves stock liquidity [4], increases the level of corporate risk taking [30], enhances corporate performance [31], and thus promotes corporate growth [32]. In terms of business economic development, digital transformation in high-performance firms promotes business performance [33], enhances the cost of debt financing for firms [34], and facilitates business development. In addition, some scholars believe that cloud computing, as a digital technology, has an impact on the performance and sustainable development of SMEs [35]. The application of green technologies and internal supply chain management is linked to organizational results and financial performance and can contribute to business sustainability [36].

Thirdly, the methods of achieving corporate digital evolution were explored. Foreign scholars believe that to carry out radical technological change, SMEs must have some capabilities [37]; strengthening the ability of individuals to perform the tasks of the sales force is a key factor in the company’s industrial innovation [38].

In summary, it is widely acknowledged in academic circles that enterprise digital evolution has an impact on outward foreign investment. Through a review of the existing literature, it is found that digital evolution positively affects outward foreign investment, but only certain factors influencing enterprise digital evolution are considered; hence, there are certain limitations.

This paper starts from the perspective of enterprises, considering more factors that influence enterprises to undergo digital evolution. It is believed that enterprise digital evolution enables enterprises to leverage digital technologies to integrate market and internal information, thereby promoting the development of outward foreign investment. Accordingly, the paper proposes the first hypothesis.

Hypothesis 1: 

Corporate digital evolution dramatically promotes external investments by enterprises.

2.2. The Mechanism of How Enterprise Digital Evolution Affects Outbound Investments

2.2.1. Enterprise Digital Evolution, ESG Performance, and Outbound Investment

Studies on the relationship between enterprise digital evolution and ESG performance in outward foreign investment mainly focus on digital evolution and enterprise ESG performance, ESG performance and outward investment, as well as the benefits generated by ESG performance.

Firstly, regarding the research on enterprise digital evolution and enterprise ESG performance, the existing literature points out that enterprise digital evolution can significantly improve the ESG performance of enterprises [11,39,40,41,42,43]. Meanwhile, strengthening enterprise digital evolution can improve enterprise performance [31]. Digital evolution can help promote green innovation, improve information transparency, and improve corporate governance, thereby enhancing ESG performance [44]. Furthermore, enterprise digital evolution can improve enterprise ESG performance by increasing the level of green innovation and internal control quality; innovation-driven policies have a positive moderating effect on the relationship between enterprise digitalization and ESG performance [42]. Foreign scholars believe that smart city logistics can achieve ESG goals based on digital tools [45].

Secondly, regarding the research on the relationship between ESG performance and enterprise outward foreign investment, digital technology and corporate social responsibility for SME SFP improvement are considered [46]; corporate social responsibility positively affects corporate performance [47]. Some scholars believe that ESG participation can reduce the problem of over-investment by enterprises, and under the scenario of under-investment, ESG participation is only beneficial to enterprises with high information asymmetry [48].

Thirdly, regarding the research on corporate ESG performance, currently, the research on corporate ESG performance mainly focuses on its impact on corporate innovation, cost reduction, risk mitigation, and performance. Firstly, enterprise ESG performance contributes to higher innovation quality, and this effect is more significant when enterprises have better internal control or higher risk tolerance [49]; corporate social responsibility has an impact on corporate finance, and green innovation has a moderating effect on the relationship between the two [50]. IT empowerment and corporate social responsibility have a positive impact on the long-term value of enterprises [51]. Secondly, scholars have found that ESG investments can significantly reduce the systemic risks in the banking sector [52], and enhance bank stability [53]. The entry of green investors improves the ESG performance of enterprises by alleviating internal financing constraints and external public environmental concerns [54]. Finally, corporate ESG performance has a significantly positive impact on an enterprise’s economic benefits [55]; ESG has a positive and significant impact on the company’s financial performance [56].

In summary, the research on the relationship between enterprise digital evolution, outward foreign investments, and ESG performance mainly focuses on the impact of digital evolution on ESG performance, the relationship between ESG performance and outward foreign investments, and the benefits generated by ESG performance. However, there is a lack of clear investigation into the mediating effects of ESG performance when examining the impact of enterprise digital evolution on outward foreign investments. Therefore, this section proposes the following hypothesis:

Hypothesis 2: 

Digital evolution promotes outward investment by enhancing ESG performance. The better a company’s ESG performance, the more evident the facilitative influence of digital evolution on outward investment.

2.2.2. Enterprise Digital Evolution, Debt Financing Cost (COD1), and Outward Investment

Many scholars currently focus on the impact of digital evolution on the cost of debt financing and the factors influencing it. Their viewpoints are generally as follows:

• Firstly, concerning the research on the relationship between enterprise digital evolution and debt financing, the studies on the relationship between enterprise digital evolution and the cost of debt financing can generally be classified into two categories: reduction and increase. Some scholars, based on the perspective of cost reduction, argue that the speed of digital evolution can effectively mitigate agency risks, information risks, and reputation risks, thereby reducing the cost of debt financing for enterprises [57]; environmental information disclosure can help enterprises increase bank credit support, reduce debt financing costs, and transform their external pressure into internal motivation [58]; other scholars also hold similar views [12,13]. Conversely, some scholars argue that enterprise digital evolution will significantly increase the cost of debt financing for enterprises [33]; the cost of debt financing for SMEs decreases as firms age [59].
• Secondly, regarding the research on factors influencing the cost of debt financing, in addition to being affected by digital evolution, the cost of debt financing is also influenced by factors such as enterprise ESG performance, internal and external policies, and external economic uncertainty. Firstly, corporate ESG performance has a positive effect on corporate debt financing costs [60,61]. Higher ESG performance and digital financing improve corporate financing efficiency at the 1% significance level [62]. Secondly, internal and external policies affect the cost of debt financing for enterprises. Some scholars take Korean enterprises as research objects and the combined impact of monetary policy uncertainty and firm characteristics on the short- and long-term capital structure of Korean heterogeneous enterprises [63]; in times of high economic uncertainty, firms raise capital more frequently, preferring debt financing [64]. Lastly, external economic uncertainty affects the cost of debt financing for enterprises. Increasing macroeconomic uncertainty significantly reduces the scale of debt financing for private enterprises and leads to an increase in the cost of debt financing for private enterprises [65].

Based on the research on the relationship between enterprise digital evolution, outward investment, and debt financing costs, the following deficiencies are identified: Firstly, the relationship between enterprise digital evolution and debt financing costs lacks clarity. The academic community holds two main views—either that digital evolution reduces or increases debt financing costs. This study considers enterprise-level factors such as company size and conducts empirical analysis to clarify the relationship between digital evolution and debt financing costs. Secondly, there are numerous factors influencing enterprise debt financing costs, with scholars often focusing on aspects such as enterprise ESG performance, policies, and external economic uncertainty. However, there is relatively less consideration from the perspective of the enterprise itself regarding debt financing costs. Therefore, this study introduces enterprise-level factors to further analyze the relationship between digital evolution, outward investment, and debt financing costs. This section proposes the following hypothesis:

Hypothesis 3: 

Digital evolution fosters outward investment by reducing corporate debt financing costs (COD1). As the COD1 decreases due to digital evolution, it facilitates outward investment.

2.2.3. Enterprise Digital Evolution, Company Age, and Outward Investment

The current academic research predominantly focuses on the correlation between a company’s age and aspects such as technological innovation or innovation-related revenue. The perspectives of scholars can be summarized as follows:

• Firstly, company age to some extent influences the technological innovation within the company, thereby affecting its innovation revenue. Some scholars believe that the age of enterprises has an impact on Chinese enterprises’ foreign direct investment (OFDI) in developing and developed countries [14]. Older and more mature companies may struggle to leverage the innovation potential within alliances, and greater company age diminishes the likelihood of innovation value creation [66]. Therefore, some scholars have explored the configurational effects of digital evolution on companies using factors such as company age, company size, and innovation environment. They found that companies characterized by younger age and strong technological research and development are more likely to achieve digital evolution [67]. Age moderates the inverse U-shaped relationship between green innovation activities and firm marketization performance, and it is more difficult for more mature firms to use environmental innovation to improve their corporate performance than younger ones [68].
• Secondly, company age influences a company’s outward investment. Company age plays a moderating role in the relationship between institutional factors and a company’s outward investment. It moderates the promotion of a company’s outward investment, weakening the impact of the institutional environment of Belt and Road host countries on the direct performance of Chinese companies abroad [69]. Some scholars have found that firm age and firm size can regulate the knowledge input and innovation value of firms [70]. Under the combined action of other factors, enterprise age has a significant positive impact on the profit probability of small and micro enterprises [71]. Wang Zhenshan and colleagues suggest that with the increase in company age and the emergence of credit agencies and credit rating agencies, the information environment of companies continuously improves, and the problem of information asymmetry is gradually alleviated. Moreover, in recent years, the People’s Bank of China has intensified its credit policy tilt towards small and medium-sized enterprises, leading to a continuous reduction in the financing costs for these enterprises [59].

In conclusion, company age not only affects a company’s technological innovation and innovation income but also influences its outward investment. However, there is limited literature that focuses on the issues of outward investment faced by companies of different ages after undergoing digital evolution. Therefore, this section proposes the following hypothesis:

Hypothesis 4: 

Company age moderates the connection between digital evolution and outward investment. The older the company, the more pronounced the inhibitory influence of digital evolution on outward investment.

2.2.4. Enterprise Digital Evolution, Debt Financing Cost (COD2), and Outward Investment

Firstly, regarding the relationship between enterprise digital evolution and debt financing costs, as mentioned earlier, numerous scholars have explored how digital evolution affects a company’s debt financing costs [12,13,33], and they have divided their opinions into two categories: “increase” and “decrease”. Additionally, companies can turn the external pressure of environmental information disclosure into internal motivation, which can help enterprises increase their bank credit support and reduce debt financing costs [58]. Moreover, it is argued that companies of different ages face different financing costs [59].

Secondly, debt financing costs are an important factor influencing the relationship between enterprise digital evolution and outward investment. Companies turn the external pressure of environmental information disclosure into internal motivation, which can help enterprises increase their bank credit support and reduce debt financing costs [58]. A mediation effect model is constructed, and the analysis shows that enterprises’ active fulfillment of social responsibility can improve the level of enterprise innovation, and debt financing cost plays a partial intermediary role between corporate social responsibility and enterprise innovation [72]. In addition, some scholars believe that the rising uncertainty of monetary policy leads to a significant rise in debt financing costs, which in turn reduces corporate investment [73].

Based on the above, the impact of enterprise digital evolution on outward investment is influenced by the enterprise’s debt financing costs. The implementation of digital evolution enhances the operational performance of the enterprise, thereby reducing its debt financing costs. Consequently, the enterprise has more funds available for outward investment. Therefore, this study proposes the following hypothesis:

Hypothesis 5: 

Debt financing cost (COD2) moderates the connection between digital evolution and outward investment. The higher the COD2, the more pronounced the inhibitory effect of digital evolution on outward investment.

3. Model, Indicators, and Data

3.1. Quantitative Model

3.1.1. Baseline Regression Model

To analyze the influence of company digital evolution on outward foreign investment, the paper presents the baseline regression model as follows:

$${LnIV}_{it}={\alpha }_0+{\alpha }_1{X2}_{it}+\sum C_{it}+{\lambda }_i+{\mu }_t+{\epsilon }_{it}$$

(1)

In Equation (1), i and t represent the listed company and the year, respectively. ${IV}_{it}$ is the explained variable, representing the outbound investment for public company i in year t. ${X2}_{it}$ is the key explanatory variable, representing the digital evolution of public company i in year t. $C_{it}$ represents the control variables for the public company i in year t. The control variables include company size, company age, operating income growth ratio, proportion of independent directors, dual leadership structure, equity concentration, and board size. ${\lambda }_t$ represents individual fixed effects, ${\mu }_t$ represents time fixed effects, and ${\epsilon }_{it}$ represents a random error term. ${\alpha }_1$ and ${\alpha }_0$ are parameters, with ${\alpha }_1$ being the key parameter of interest in this paper, employed to analyze the effect process of corporate digital evolution on a company’s outward investment. The specific criteria are as follows: When ${\alpha }_1$ > 0, it indicates that corporate digital evolution stimulates outward investment. When ${\alpha }_1$ < 0, it signifies that enterprise digital evolution hinders outward investment. When ${\alpha }_1$ = 0, it suggests that corporate digital evolution does not affect outward investment.

3.1.2. Mediation Effects Model

This passage describes that the study further examined the mechanism through which digital evolution affects a company’s outward investment. Building upon Equation (1), the study adopts a research method from Wen Zhonglin and Ye Baojuan (2014) [74]. The study constructs a linear regression equation for the mediating variables concerning digital evolution, and the specific setup of the model for testing the mediating effects is as follows:

$$M_{it}={\vartheta }_0+{\vartheta }_1{X2}_{it}+\sum {\Pi }_{it}{C}_{it}+{\lambda }_i+{\mu }_i+{\epsilon }_{it}$$

(2)

$$\mathrm{L}\mathrm{n}{IV}_{it}={\Pi }_0+{\Pi }_1{X2}_{it}+{\Pi }_2{M}_{it}+\sum {\rho }_i{C}_{it}+{\mu }_i+{\epsilon }_{it}$$

(3)

$M_{it}$ represents the mediating variable, and the mediating variables considered in the study are the enterprise’s ESG performance and debt financing cost (COD1). Equation (1) analyzes the direct effect of digital evolution on a company’s outward investment. Equation (2) is used to test the effect of digital evolution on the mediating variables, and Equation (3) is used to examine the mediating impact of digital evolution on an enterprise’s outward investment. On the basis of the significance of ${\alpha }_0$, if ${\vartheta }_1$ and ${\Pi }_2$ are significant, and ${\Pi }_1$ is significant, it indicates the presence of partial mediation; if ${\Pi }_1$ is not significant, it suggests complete mediation. If at least one between ${\vartheta }_1$ and ${\Pi }_2$ is not significant, a Bootstrap test is conducted. If the test is successful, it indicates the presence of partial mediation.

3.1.3. Moderation Effect Model

This article further extends the baseline regression model by incorporating enterprise age and debt financing cost COD2 as moderating variables. It constructs a moderation effect model with interaction terms between enterprise age and digital evolution, as well as between debt financing cost COD2 and digital evolution. This aims to delve deeper into the moderating effects within the influencing mechanism of digital evolution on a company’s foreign investment. Building upon the baseline regression model, this article introduces interaction terms between enterprise age and digital evolution, as well as between debt financing cost COD2 and digital evolution, forming the following moderation model:

$${LnIV}_{it}={\beta }_0+{\beta }_1{X2}_{it}+{\beta }_2{X2}_{it}\ast C2+\sum {\varphi }_{it}{C}_{it}+{\lambda }_i+{\mu }_i+{\epsilon }_{it}$$

(4)

$${LnIV}_{it}={\beta }_0+{\beta }_3{X2}_{it}+{\beta }_4{X2}_{it}\ast y19+\sum {\varphi }_{it}{C}_{it}+{\lambda }_i+{\mu }_i+{\epsilon }_{it}$$

(5)

In Equations (4) and (5),${X2}_{it}$ ∗ C2 represents the interaction term between digital evolution and enterprise age for listed companies, ${X2}_{it}$ ∗ y19 represents the cross-term ranging from digital evolution to the expenses of debt financing COD2, and ${\beta }_2$ and ${\beta }_4$ are the main parameters of interest.

3.2. Indicator Selection

3.2.1. Explained Variable

The explained variable in the study is interpreted as a company’s outward foreign direct investment. Drawing upon relevant research [8], this paper measures the variable by taking the natural logarithm of the sum of outward foreign direct investment amounts by listed companies in year t.

3.2.2. Explanatory Variable

This study’s explanatory variable of interest is the digital evolution of enterprises. Currently, the measurement of the degree of enterprise digital evolution is still to be developed, so this paper draws on the research of related scholars [4] and uses Python 3.10 to mine the digital evolution information involved in the annual reports of listed companies, and ultimately forms an enterprise digital evolution index. This paper uses the enterprise digital evolution of listed company i in year t as the core explanatory variable.

3.2.3. Mediating Variable

Aiming to further examine the influence mechanism of corporate digital evolution on external investment, the paper constructs a mediating influence model with ESG performance and debt financing cost (COD1) as mediating variables. Enterprise digital evolution improves corporate ESG performance [39]. Corporate financial strength increases with corporate ESG performance and is able to consider more funds for foreign investment. Considering the effect of ESG performance, ESG performance is selected as the first mediating variable. ESG performance represents the governance, environmental, and social aspects of an enterprise. The ESG rating is divided into nine levels, with higher levels indicating better company performance. Digital evolution can influence a company’s external investment through its ESG performance. Related research found that the digital evolution of enterprises has an impact on the debt financing cost of enterprises [34], and debt financing cost COD1 was selected as the second mediating variable to consider the impact of the cost of debt financing. Debt financing cost COD1 is quantified by the proportion of interest expenses to the entire amount of long-term and short-term debts. A higher COD1 indicates higher debt financing costs for the company.

3.2.4. Moderating Variable

According to the assumptions mentioned earlier, this paper selects corporate age and debt financing cost (COD2) as moderating variables. As a company ages, firm experience increases with financial strength to be able to make risky investments [75]; therefore, firm age is selected as the first moderating variable in this paper, where company age is a continuous variable calculated using the current year minus the year the listed company was founded. On the basis of related studies [34,57], further considering the moderating role of debt financing cost, debt financing COD2 cost is selected as the second moderating variable in this paper. Debt financing cost COD2 is quantified based on the proportion of financial expenses to the entire amount of long-term and short-term debts. A higher COD2 indicates higher debt financing costs for the company.

3.2.5. Control Variable

To avoid the overlooking of variables that may affect the estimation results of the research, a range of control variables are introduced. Drawing on related scholars’ studies [2,4], the control variables include the following: company size, firm age, revenue growth rate, proportion of independent directors, equity concentration, dual CEO-chair roles, board size, and other control variables. Individual and time effects are also incorporated to effectively mitigate the risk of omitted variable bias. Relevant definitions are presented in

Table 1. The definitions of the main variables.

Name	Identifier	Definition
Enterprise digital evolution	x2	Continuous variable reflecting the degree and extent of a company’s management and application of digital evolution.
Outward Investment	IV	The logarithm of the total amount of a company’s outward investments.
ESG Performance	X1	Assigned values based on Huazheng ESG ratings. For example, if the rating is C, then ESG is designated the value of 1; if the rating is CC, then ESG is designated the value of 2, and so on.
Debt Financing Cost COD1	y1	The proportion of a company’s interest expenses to the entire amount of long-term and short-term debts.
Debt Financing Cost COD2	y19	The proportion of a company’s financial expenses to the total amount of long-term and short-term debts.
Company Size	c1	Continuous variable, representing the total asset scale of the company.
Company Age	c2	Continuous variable, calculated as the age of the enterprise, which is equal to the current year minus the year of the enterprise’s establishment.
Revenue Growth Rate	c3	Continuous variable, calculated as the revenue growth rate, which is equal to (increase in operating revenue/total operating revenue of the previous year) × 100%.
Proportion of Independent Directors	c4	Continuous variable representing the ratio of non-executive directors, calculated as the number of non-executive directors divided by the entire number of board members.
Dual CEO-Chair Roles	c5	Dummy variable where 1 represents the combination of the roles of Chairman and CEO, and 0 represents the separation of the two roles.
Equity Concentration	c6	Continuous variable, expressed as the ratio of shares held by the largest shareholder.
Board Size	c7	Continuous variable, expressed as the number of board members.

.

3.3. Data Source

This research used panel data from manufacturing public enterprises of Chinese covering the duration from 2010 to 2021 for research. The data on listed companies were sourced from the CSMAR database and Wind data. In relation to the data used, the study conducted preliminary processing, including outlier removal and missing value imputation. Specifically, the statistical findings of the factors are as

Table 2. Descriptive statistics for the key variables.

Variable	Observations	Mean	Std. Dev.	Min	Max
IV	12,588	7.203	9.357	0	31.975
x2	12,588	2.598	1.157	0	5.811
x1	12,588	6.395	1.132	2	9
y1	12,588	0.009	0.035	−0.162	0.071
y19	12,588	0.022	0.016	0	0.066
c1	12,588	22.232	1.252	19.091	26.101
c2	12,588	2.506	0.614	0	3.367
c3	12,588	0.257	0.85	−0.783	9.184
c4	12,588	0.375	0.063	0.25	0.6
c5	12,588	0.245	0.429	0	1
c6	12,588	33.035	14.171	8.6	75
c7	12,588	2.33	0.204	1.792	2.89

.

4. The Main Findings

4.1. Primary Regression Findings

In this study, Equation (1) was employed to analyze the effect of corporate digital evolution on outward investment, and the findings are outlined in

Table 3. Baseline regression results.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	IV	IV	IV	IV	IV	IV	IV	IV
x2	0.543 ***	0.424 ***	0.415 ***	0.418 ***	0.416 ***	0.417 ***	0.418 ***	0.418 ***
	(0.152)	(0.156)	(0.156)	(0.156)	(0.156)	(0.156)	(0.156)	(0.156)
c1		0.922 ***	0.712 ***	0.706 ***	0.701 ***	0.702 ***	0.694 ***	0.692 ***
		(0.250)	(0.250)	(0.250)	(0.250)	(0.250)	(0.251)	(0.251)
c2			3.365 ***	3.363 ***	3.372 ***	3.364 ***	3.443 ***	3.445 ***
			(0.591)	(0.591)	(0.591)	(0.591)	(0.623)	(0.623)
c3				0.112	0.111	0.112	0.107	0.107
				(0.087)	(0.087)	(0.087)	(0.088)	(0.088)
c4					−1.113	−1.107	−1.115	−1.105
					(1.607)	(1.607)	(1.604)	(1.598)
c5						−0.077	−0.077	−0.076
						(0.287)	(0.287)	(0.287)
c6							0.009	0.009
							(0.019)	(0.019)
c7								0.070
								(0.518)
_cons	4.536 ***	−15.119 ***	−16.812 ***	−16.716 ***	−16.214 ***	−16.195 ***	−16.492 ***	−16.624 ***
	(0.370)	(5.342)	(5.266)	(5.267)	(5.304)	(5.302)	(5.369)	(5.466)
Time Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Individual Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
N	12,588	12,588	12,588	12,588	12,588	12,588	12,588	12,588
r2	0.061	0.064	0.071	0.071	0.072	0.072	0.072	0.072

Standard errors are in parentheses, *** p < 0.01.

. In the first column, no additional variables are considered, only time and individual controls. The findings indicate that the coefficient of digital evolution is positive and significant at the 1% standard, suggesting a significant optimistic impact of corporate digital evolution on outward investment. Columns (2) to (8) gradually add control variables related to other aspects of corporate operations and governance, and the results remain robust. As indicated in column (3), even when controlling for other variables, time differences, and individual differences, corporate digital evolution significantly increases outward investment, with a coefficient of 0.415 and significance at the 1% standard. These regression results confirm Hypothesis 1, supporting the notion that corporate digital evolution has a significant impact on outward investment. This conclusion aligns with existing research in the theoretical domain [8,9]. The higher the extent of digital evolution in an enterprise, the better its development in outward investment.

Through the study, it was found that other variables also have an influence on an enterprise’s outward investment. Specifically, firm size (C1) is remarkably positive at the 1% standard, expressing a significant positive impact of firm size on outward investment. Different companies of varying sizes follow different paths to achieving digital evolution, resulting in diverse economic outcomes. Large-scale companies have more disposable resources and a rich array of resource allocation choices, enhancing the autonomy of their transformation. They also have more room for trial and error, aiding in obtaining and maintaining a competitive advantage [67]. Therefore, large-scale enterprises tend to have a higher extent of digital evolution than small-scale enterprises. Company age (C2) is dramatically optimistic at the 1% standard, suggesting a significant positive impact of company age on outward investment. Younger companies, in their growth phase, may lack resources and capabilities, but their strong profitability can compensate for these disadvantages [67]. On the other hand, older companies, with abundant resources and capabilities, are more likely to attract innovative talents and adopt innovative technological methods, making it more feasible for them to undergo digital evolution and consequently promoting outward investment. Other variables have a relatively weaker impact on a company’s outward investment. The relevant results are shown in Table 2.

4.2. Robustness Test

4.2.1. Using Lagged Values of Explanatory Variables

The focus of this paper is on the relevance between corporate digital evolution and outward investment. Digital evolution is employed as the explanatory variable. To better understand the relevance between corporate digital evolution and its outward investment, a robustness test was conducted by introducing a one-period lag for corporate digital evolution. The findings of the test are outlined in

Table 4. Robustness test regression results.

	Lagged Explanatory Variable		Change in Study Time		lv2sls
	(1)	(2)	(3)	(4)	(5)	(6)
	One-Period Lag	Two-Period Lag	2010~2019	2020~2021	First Stage	Second Stage
Variables	IV	IV	IV	IV	x2	IV
x2			0.423 **	0.312		0.839 ***
			(0.166)	(0.428)		(0.225)
Control Variables	Yes	Yes	Yes	Yes	Yes	Yes
L.x2	0.406 **				0.484 ***
	(0.163)				(0.008)
L2.x2		0.278 *
		(0.161)
Constant	−16.486 ***	−8.933	−20.665 ***	2.268	−0.867 **	−27.472 ***
	(5.937)	(6.520)	(6.144)	(22.177)	(0.352)	(4.613)
Observations	11,539	10,490	10,490	2098	11,539	11,539
R-squared	0.067	0.059	0.078	0.005	0.821	0.491

Standard errors are in parentheses, * p < 0.1, ** p < 0.05, *** p < 0.01.

.

Columns (1) to (2) represent the results with a one-period and two-period lag for corporate digital evolution, respectively. The empirical results indicate that the coefficients of digital evolution are both significant at the 5% and 10% levels, suggesting an optimistic and significant influence of the current level of digital evolution on outward investment in the next period. This implies a lagged effect of digital evolution on a company’s outward investment, validating the robustness of the baseline results presented earlier in the text.

4.2.2. Changing Time Samples

This study used sample data from public companies from 2010 to 2021. Starting from the end of 2019 and continuing into 2020–2021, the external environment has been affected by the influence of the COVID-19 pandemic, to some extent influencing the degree of corporate digital evolution and consequently affecting outward investment. Therefore, this study took 2019 as the time node and analyzed the influence of company digital evolution on outward investment development using sample data from 2010 to 2019 and 2020 to 2021.

The results for the two time periods are presented in Table 4, columns (3) to (4). The findings express that the coefficient of digital evolution for the period 2010–2019 is significantly optimistic at the 5% standard. The size of the coefficient is similar to the baseline regression results, suggesting that, even when changing the study period and excluding the significant events such as the COVID-19 pandemic, corporate digital evolution can dramatically improve a corporate’s outward investment. This consistency with the primary regression outcomes demonstrates the stability of the model.

4.2.3. Using Instrumental Variable Two-Stage Regression (IV-2SLS)

Considering the potential endogeneity issues in the baseline regression model, this study continued to use the IV-2SLS to examine the robustness of the regression results. Specifically, the lagged term of corporate digital evolution (L.X2) was used as the instrumental variable, and the endogeneity of the model was tested through instrumental variable two-stage least squares regression (IV-2SLS).

Columns (5) to (6) in Table 4 present the estimates of the IV-2SLS. Column (5) expresses the findings of the first-stage regression, indicating that the coefficient of the lagged term of corporate digital evolution in the previous year was 0.484, significant at the 1% standard. This suggests that a higher standard of corporate digital evolution in the previous year was associated with better outward investment development in the next year. Column (6) shows the results of the second-stage estimation. The coefficient of the core explanatory variable, corporate digital evolution, was 0.839 and noteworthy at the 1% standard. This implies that a 1% change in the extent of corporate digital evolution leads to a 0.839% increase in the total amount of outward investment. This aligns with the baseline regression results, confirming the stability of the model.

4.3. Heterogeneity Analysis Results

4.3.1. Analysis Based on Different Geographical Locations

In this section, the total sample is grouped into samples from the Northeastern, Western, Central, and Eastern regions to analyze the differences in digital evolution among enterprises in different regions. The regression findings are shown in

Table 5. Regression results for the regional samples.

	(1)	(2)	(3)	(4)
	East	Central	West	Northeast
Variables	IV	IV	IV	IV
x2	0.546 ***	0.260	0.270	−1.091 *
	(0.196)	(0.449)	(0.345)	(0.592)
Control Variables	Yes	Yes	Yes	Yes
Constant	−10.867	−18.964	−30.797 ***	−19.179
	(7.504)	(13.720)	(10.968)	(24.668)
Time Fixed Effects	Yes	Yes	Yes	Yes
Individual Fixed Effects	Yes	Yes	Yes	Yes
Observations	7632	1788	2556	612
R-squared	0.084	0.063	0.081	0.101
Number of id	636	149	213	51

Standard errors are in parentheses, * p < 0.1, *** p < 0.01.

, where columns (1)–(4) correspond to the regression findings for the samples from the Eastern, Central, Western, and Northeastern regions, respectively.

The findings indicate that digital evolution significantly affects outward investment in the Eastern region, with a coefficient of 0.546, significant at the 1% standard. In the Northeastern region, the effect is also significant, with a coefficient of −1.091, significant at the 10% standard but negative. However, the effects in the Central and Western regions are not significant. The possible causes for these results is that the Eastern region, with its higher standard of economic advancement and more complete infrastructure, experiences a more pronounced impact of the extent of digital evolution on outward investment for enterprises. Because of the advantages of its resource structure and industrial layout, Northeast China has market demand and potential opportunities. In addition, in recent years, the three provinces in Northeast China have also responded to the call to develop science and technology, and continuously improve the development vitality of the old industrial base in Northeast China. Under the combined effect of these factors, the region has become an important destination for foreign investment [76].

4.3.2. Analysis Based on Different Enterprise Sizes

This study conducted heterogeneity analysis based on different enterprise sizes. The relevant results are shown in Table 5. Previous research has shown that enterprise size influences high-tech innovation corporate performance [77]. Additionally, there is heterogeneity in the effects of innovation policy support among enterprises of different sizes [78]. Different enterprise sizes possess varying resources, leading to differences in the extent of digital evolution.

In this study, all the enterprises were categorized into large companies, medium-sized companies, small companies, micro-enterprises, and extra-large companies based on the logarithm of total assets. The findings in Table 5 indicate that in medium-sized and extra-large enterprises, digital evolution significantly affects outward investment. The coefficients are 0.786 and 0.863, both significant at the 5% standard. This suggests that for every 1% increase in digital evolution, medium-sized and extra-large enterprises can achieve a 0.789% and 0.836% increase in outward investment, respectively.

4.3.3. Analysis Based on Different Industry Types

In this section, industry types are grouped into high-tech industries and heavy pollution industries for discussion. The relevant results are shown in

Table 6. Analysis based on different enterprise sizes.

	(1)	(2)	(3)	(4)	(5)
	Micro Enterprises	Small Enterprises	Medium-Sized Enterprises	Large Enterprises	Extra-Large Enterprises
Variables	IV	IV	IV	IV	IV
x2	−0.059	0.283	0.786 **	−0.316	0.836 **
	(0.269)	(0.339)	(0.352)	(0.406)	(0.381)
Control Variables	Yes	Yes	Yes	Yes	Yes
Constant	−17.477	−78.606 ***	30.096	−11.801	7.190
	(14.009)	(29.538)	(33.112)	(29.834)	(25.430)
Individual Fixed Effects	Yes	Yes	Yes	Yes	Yes
Time Fixed Effects	Yes	Yes	Yes	Yes	Yes
Observations	2518	2518	2517	2518	2517
R-squared	0.094	0.089	0.093	0.083	0.075
Number of id	472	605	633	565	363

Robust standard errors are in parentheses *** p < 0.01, ** p < 0.05.

. Previous research has shown that the promoting impact of digital evolution on innovation is more significant in high-tech companies [79]. Digital evolution can promote green technology innovation, and the research samples in the high-tech industry are more significant [80]. Therefore, this study used different industry types, categorizing industries into high-tech and heavy-pollution industries for analysis. Table 6 indicates the findings of the heterogeneity analysis for different industry types. Columns (1)–(2) represent high-tech and traditional industries, while columns (3)–(4) represent heavy-pollution and non-heavy-pollution industries.

The analysis results of industry type heterogeneity are shown in

Table 7. Analysis based on different industry types.

	High-Tech Industry		Heavy Pollution Industry
	(1)	(2)	(3)	(4)
Variables	IV	IV	IV	IV
x2	0.315 *	0.821 **	0.186	0.496 **
	(0.179)	(0.353)	(0.240)	(0.219)
Control Variables	Yes	Yes	Yes	Yes
Constant	−18.131 ***	−10.639	−15.941 *	−14.824 *
	(6.355)	(13.707)	(8.579)	(7.891)
Time Fixed Effects	Yes	Yes	Yes	Yes
Individual Fixed Effects	Yes	Yes	Yes	Yes
Observations	9892	2531	5335	7132
R-squared	0.074	0.078	0.053	0.095
Number of id	848	234	477	621

Standard errors are in parentheses, * p < 0.1, ** p < 0.05, *** p < 0.01.

. The findings in columns (1)–(2) indicate that in high-tech industry, digital evolution has a significant impact on outward investment, with a coefficient of 0.315, significant at the 10% standard. In non-high-tech industry, digital evolution also significantly affects outward investment, with a coefficient of 0.821, significant at the 5% standard. The results in columns (3)–(4) show that in heavy-pollution industry, digital evolution does not significantly affect outward investment. However, in non-heavy-pollution industry, digital evolution significantly influences outward investment, having a coefficient of 0.496, with a significance standard of 5%. The reason for these results may be that companies in high-tech and non-heavy-pollution industries are more likely to possess conditions conducive to innovation, such as advanced innovative technologies, top-notch talents, and sufficient funds, making it easier to achieve digital evolution and subsequently promoting outward investment.

4.4. Mechanism Analysis

4.4.1. Mediation Effect

In this section, the mediation effects model is used with ESG performance (x1) and debt financing cost COD1 (y1) as mediating variables to analyze the mechanism by which digital evolution affects outward investment. The hypothesis is that digital evolution can boost outward investment by enhancing ESG performance and reducing debt financing expenses. In the academic community, there are inconsistent views on whether digital evolution promotes or inhibits corporate debt financing costs. Digital evolution can dramatically reduce corporate debt financing costs [12,13], while digital evolution can significantly increase corporate debt financing costs [34]. Therefore, this section examines the mechanism by which digital evolution affects outward investment through debt financing costs and ESG performance. The relevant results are shown in

Table 8. Mediation effect regression results.

	ESG Performance			Debt Financing Cost COD1
	(1)	(2)	(3)	(4)	(5)	(6)
Variables	IV	x1	IV	IV	y1	IV
x2	0.418 ***	0.046 ***	0.407 ***	0.418 ***	−0.001 **	0.407 ***
	(0.156)	(0.016)	(0.156)	(0.156)	(0.001)	(0.155)
x1			0.218 *
			(0.122)
y1						−8.513 **
						(3.734)
Control Variables	Yes	Yes	Yes	Yes	Yes	Yes
Time Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes
Individual Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes
_cons	−16.624 ***	2.377 ***	−17.142 ***	−16.624 ***	−0.115 ***	−17.603 ***
	(5.466)	(0.694)	(5.425)	(5.466)	(0.019)	(5.456)
N	12,588	12,588	12,588	12,588	12,588	12,588
r2	0.072	0.048	0.072	0.072	0.117	0.072

Standard errors are in parentheses, * p < 0.1, ** p < 0.05, *** p < 0.01.

.

(1)

The mediating effect primarily centered around enterprise ESG performance.

Columns (1)–(3) present the regression results when ESG rating functions as an intermediary link. Under column (2), the results show that digital evolution is positively significant at the 1% standard with ESG performance, with 0.046 as the coefficient, indicating that for every 1% increase in digital evolution, the ESG performance of the enterprise improves. In column (3), after adding the mediating variable, ESG performance, digital evolution remains significant at the 1% standard, with 0.407 as the coefficient. This suggests that for every 1% increase in digital evolution, the enterprise can increase outward investment by 0.407%, indicating that the effect of digital evolution on outward investment can be achieved by improving the ESG performance. Thus, enhancing outward investment can be achieved not only by improving the digital evolution but also by promoting outward investment through improved ESG performance. This result verifies Hypothesis 2.

(2)

The mediating effect primarily centered around COD1, representing debt financing costs.

Columns (4)–(6) present the regression results when debt financing cost COD1 is used as a mediating variable. In column (5), the findings show that the effects of digital evolution on debt financing cost COD1 is significant at the 5% level, with −0.001 as the coefficient, implying that for every 1% rise in digital evolution, debt financing cost COD1 decreases by 0.001%. In column (6), after adding the mediating variable debt financing cost COD1, the regression coefficient of digital evolution remains significant at the 1% standard, with 0.407 as the coefficient. Meanwhile, debt financing cost COD1 is significant at the 5% standard, with a coefficient of −8.513. This implies that the effect of digital evolution on outward investment can also be achieved by reducing the enterprise’s debt financing cost COD1, thereby promoting outward investment. This result verifies Hypothesis 3.

4.4.2. Moderation Effects

In this part, the moderation effect model is employed to further analyze the mechanism through which the digital evolution of a company affects its outward investments, using enterprise age and debt financing cost COD2 as interaction terms. The relevant findings are shown in

Table 9. Moderation effects test.

	(1)	(2)
Variables	IV	IV
x2	−1.020 **	1.130 ***
	(0.518)	(0.224)
c2	2.762 ***
	(0.680)
x2×c2	0.570 ***
	(0.201)
y19		30.361 *
		(18.311)
x2×y19		−33.425 ***
		(6.937)
Control Variables	Yes	Yes
Time Fixed Effects	Yes	Yes
Individual Fixed Effects	Yes	Yes
_cons	−13.646 **	−18.363 ***
	(5.568)	(5.390)
N	12,588	12,588
r2	0.073	0.080

Standard errors are in parentheses, * p < 0.1, ** p < 0.05, *** p < 0.01.

.

(1)

The moderating effect primarily centered around the age of the enterprise.

Column (1) reports the regression results with enterprise age as the moderating variable. The findings represent that the coefficient of the interaction term between digital evolution and enterprise age is significantly positive at the 1% standard, indicating that enterprise age has a significant moderating effect on the relationship between digital evolution and outward investment. The coefficient of digital evolution is opposite in sign to the coefficient of the interaction item, suggesting that older enterprises weaken the impact of digital evolution on outward investment. The possible reason for these results is that older enterprises, despite having abundant resources, may exhibit weaker innovation capabilities, making it challenging to adapt to the rapidly evolving digital economy, thereby constraining the realization of digital evolution. This regression result supports Hypothesis 4.

(2)

The moderating effect primarily centered around the debt financing cost COD2.

Column (2) presents the results with debt financing cost COD2 as the moderating variable. The findings represent that the coefficient of the interaction term between digital evolution and debt financing cost COD2 is dramatically negative at the 1% standard, with a coefficient of −33.425. This indicates that debt financing cost COD2 pays a moderating role. Similarly, the coefficient of digital evolution is opposite in sign to the coefficient of the interaction term, suggesting that debt financing cost COD2 weakens the effect of digital evolution on outward investment. This result supports Hypothesis 5.

5. Conclusions and Implications

5.1. Research Conclusions

This paper analyzes the impact of corporate digital evolution on outward foreign investment by enterprises, exploring the existence of heterogeneity, intermediary effects, and moderating effects. This paper utilizes panel data of Chinese manufacturing listed companies from 2010 to 2021. The following issues were studied using methods such as the two-way fixed effects panel regression model, the mediation effects model, and the moderation effect model: Does the digital evolution of enterprises lead to changes in outward investment? Is there heterogeneity in the impact of the digital evolution of enterprises on outward investment? What is the pathway through which the digital evolution of enterprises influences outward investment? Based on the above research, this paper draws the following conclusions:

• Firstly, enterprise digital evolution facilitates outward investment. By leveraging digital technology to enhance resource utilization efficiency, more funds can be freed up to explore overseas markets. The findings obtained through methods such as indicator substitution and instrumental variable analysis are consistent with the academic literature.
• Secondly, the digital evolution of enterprises exhibits heterogeneity in its impact on outbound investments as follows. Regional heterogeneity: due to differences in digitization levels between the eastern and northeastern regions, the digital evolution of enterprises in the eastern region stimulates outbound investments, while in the northeastern region, it inhibits such investments. Scale heterogeneity: the digital evolution of medium and large-scale enterprises promotes outbound investments. Industry heterogeneity: digital evolution in industries with advanced technology and those in non-heavy-polluting sectors stimulate outbound investments.
• Thirdly, the digital evolution of enterprises has an intermediary effect on outbound investments. Enterprise digital evolution can enhance the ESG performance, leading to increased foreign investments. Thus, good ESG performance enhances the promoting effect. This means that when making outbound investments, enterprises are increasingly considering sustainable development indicators such as environmental, social, and governance factors. Furthermore, reducing a company’s debt financing cost (COD1) also contributes to the promoting effect of digital evolution on outbound investments.
• Fourthly, the study verifies the presence of a moderating impact of company digital evolution on outward investments. Company age and COD2 were found to weaken the influence of digital evolution on outbound investments. This is likely to be due to the fact that older enterprises, despite having abundant resources, often lack innovation capabilities, making it challenging for them to adapt to the rapidly evolving digital economy. Additionally, the study found that digital evolution itself could further reduce a company’s debt financing cost (COD2), suggesting that debt financing cost plays a striking moderating role in the relevance between digital evolution and outbound investments.

5.2. Implications of the Study

Firstly, this study enriches the theoretical understanding of how enterprise digital evolution affects outward investment. Using panel data from Chinese manufacturing listed companies spanning from 2010 to 2021, this paper empirically analyzes the relationship between digital evolution and outward investment. The research findings indicate a positive relationship between enterprise digital evolution and outward investment, with variations observed in terms of regions, scales, and industries. Additionally, this relationship is influenced by factors such as enterprise ESG performance, company age, and debt financing costs. These results contribute to a deeper understanding of how enterprise digital evolution impacts outward investment.

Secondly, this research offers insights for sustainable development and digital evolution in enterprises. On one hand, when implementing digital evolution, enterprises can achieve sustainable development by enhancing their environmental, social, and governance (ESG) performance, thus ensuring long-term growth. On the other hand, digital evolution can improve production efficiency, enhance performance, and facilitate outward investment. As leaders of enterprises, it is essential to prioritize the enhancement of social responsibility, internal governance, and environmental practices.

Thirdly, the findings offer insights for the government to enhance policies related to the advancement of enterprise digital evolution. The findings provide insights for the government to enhance policies connected to the advancement of corporate digital evolution. The country should improve the top-level design of the digital economy and refine the policies regarding corporate digital evolution. Addressing the current state of digital evolution and considering its impact on outbound investments, the government should formulate and implement relevant policies aligned with the mechanisms identified in this study. The research serves as a guide for accurately analyzing the impact of enterprise digital evolution on outbound investments, offering insights for policy formulation in the realms of enterprise digital evolution and foreign investments.

6. Limitations of the Study

On the basis of existing research, in terms of conclusions, it was found that the impact of enterprise digital evolution on outward investment can be achieved through two paths: improving the ESG performance and reducing the cost of debt financing COD1, as well as the finding that the older the firm, the stronger the positive impact of enterprise digital evolution on outward investment, and that the higher the cost of debt financing COD2, the more it suppresses the positive impact. In terms of theory, research on the theoretical aspects of enterprise digital evolution on enterprise outward investment is enriched. Existing research focuses on the theoretical study of technological progress, artificial intelligence and other outward investment of enterprises, and this paper studies the effect of the digital evolution of enterprises on the outward investment of enterprises, enriching the theoretical research related to the digital evolution of enterprises and outward investment of enterprises. In terms of methodology, a methodological test of the impact of extended enterprise digital transformation on corporate outward investment is presented. Previous studies have used the fixed effects model to test the relationship between the two, and this paper uses the mediating effect model and the moderating effect model for further testing, enriching the test of how enterprise digital evolution affects enterprise outward investment.

The research limitations of this paper are as follows: On one hand, this research explored the relationship between enterprise digital evolution and outward investment from the perspective of the enterprise, considering only internal factors while overlooking external economic conditions and other external factors. This approach has certain limitations. Future studies could conduct more comprehensive analyses by considering additional external factors based on actual conditions. On the other hand, this study directly investigated the impact of enterprise digital evolution on outward investment without exploring its effects on different types of investments, which poses certain limitations. Further research could delve deeper into this aspect in the future.