
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12411-5
10.1016/j.heliyon.2024.e36380
e36380
Research Article
Shareholder heterogeneity, financing constraints, and organizational resilience: Mixed-ownership reform in Chinese private enterprises
Zhang Jiruo
Cai Longli
Gao Yu gylyj1108@163.com
⁎
Department of Accounting, Qingdao University, Qingdao, China
⁎ Corresponding author. gylyj1108@163.com
16 8 2024
30 8 2024
16 8 2024
10 16 e363802 11 2023
3 8 2024
14 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Private enterprise development encounters numerous challenges. China encourages state-owned enterprises to acquire equity stakes in private enterprises, thereby facilitating development of private enterprises through reverse mixed-ownership reform. To test the effectiveness of this approach, we focus on the impact of state-owned equity on the organizational resilience of private enterprises. Using empirical research methods and data from A-share listed Chinese companies from 2009 to 2022, we find that reverse mixed-ownership reform is significantly and positively correlated with the organizational resilience of private enterprises. Further analysis reveals that involvement of shareholders from state-owned enterprises can bolster the organizational resilience of private enterprises by mitigating their financing constraints. This paper extends the research on the mechanism by which a heterogeneous ownership structure can impact the organizational resilience of private enterprises and offers insights for private enterprises on how to bolster their organizational resilience through mixed-ownership reform.

Keywords

State-owned capital
private enterprises
Shareholder heterogeneity
Organizational resilience
Financing constraints
==== Body
pmc1 Introduction

The private sector of the Chinese economy has experienced rapid growth; more than 50 million privately-owned enterprises were operating in China as of May 2023. These enterprises contribute over 50 % of tax revenue and account for 60 % of the country's GDP, 70 % of its technological innovation, 80 % of its urban employment, and an impressive 80 % of its growth in foreign trade. The pivotal role of the private sector in China's economic landscape is evident. Despite China's active support for the development of non-state-owned enterprises, private enterprises still encounter challenges in securing financing, overcoming industry barriers, and transforming their production operations [1]. These issues limit the resilience of Chinese private enterprises in facing crises and adapting to rapid changes in the external economic landscape.

To foster the advancement of private enterprises, the Chinese government proposes active cultivation of a mixed-ownership economy and support of private enterprises through various means, including state-owned capital. Organizational resilience of private enterprises can be enhanced through integration of equity from diverse sources, thereby promoting their development. Organizational resilience is a measure of an organization's capacity to effectively navigate VUCA (volatility, uncertainty, complexity, and ambiguity) environments in familiar and unfamiliar scenarios [2]. Organizational resilience encompasses anti-fragility, adaptability, and capacity to recover. These capabilities are instrumental in ensuring the long-term survival of an enterprise [3]. In turbulent operating environments where unexpected events may occur, organizational resilience can ensure sustainable development and growth [4,5]. For example, during the COVID-19 pandemic, the most widespread and impactful exogenous adverse event in recent years, over 40 % of Chinese enterprises suffered losses in the initial stages. In contrast to state-owned enterprises, private enterprises lacked government support during this time, so they were unable to cope with unexpected events and recover, in contrast to those with government support. In this study, we investigate the mechanism through which state-owned capital influences the organizational resilience of private enterprises.

Financing constraints restrict the development of private enterprises, which encounter greater challenges in securing financing compared to state-owned enterprises. With the implementation of China's mixed-ownership economy, many enterprises have acquired state-owned equity to alleviate financing constraints and access more debt financing through the information effect and government-business links [6,7]. Therefore, in this paper, we utilize financing constraints as the mediating variable to study the extent to which (partial) state ownership can alleviate such constraints and increase the organizational resilience of private enterprises.

Using data from A-share listed private enterprises in China between 2009 and 2022, we investigate how state-owned equity influences the resilience of private enterprises. We conclude that state-owned equity can mitigate financial volatility in private enterprises, enhance their long-term performance, improve their risk response capability, and improve organizational resilience by alleviating financing constraints.

This paper makes three main contributions: Firstly, previous research on mixed-ownership reform primarily focused on infusion of private equity into state-owned enterprises, but there remains a lack of comprehensive study regarding the impact of state-owned capital on private enterprises. This paper explores the impact of state capital on the organizational resilience of private enterprises, not only expanding upon relevant research concerning the economic consequences of mixed-ownership reform, but also providing empirical evidence for policy effects. Secondly, existing literature on organizational resilience focused on the relationship between firm attributes and the external economic environment [8]. Previous theoretical foundations for analyzing organizational resilience included resource orchestration theory [9,10] and basic intuition and capability evolution theory [11], among others. From the perspective of equity heterogeneity, this paper integrates resource-based theory and dynamic capability theory to examine the impact of state-owned capital on the organizational resilience of private enterprises. Our empirical research demonstrates the practicality of these theories. The findings of this study have significant theoretical implications for private enterprises wishing to enhance their resilience. Thirdly, China is vigorously pursuing mixed-ownership reform. The government encourages investment of state capital in non-state-owned enterprises in various ways to promote economic development. In the present study, we examine the mediating role of financing constraints in the relationship between state-owned equity and organizational resilience, considering the challenges and costs of access to financing. The present study advances research on the influence of heterogeneous ownership structures on the organizational resilience of private enterprises, offering practical suggestions and strategies for development in crisis scenarios in the Chinese context.

The subsequent sections of this paper are organized as follows: the second section provides a comprehensive literature review; the third section presents theoretical analysis and our research hypotheses; the fourth section discusses data sources and the research design; the fifth section analyzes the results of our empirical analysis; and finally, the sixth section draws conclusions and outlines policy implications.

2 Literature review

2.1 Benefits of organizational resilience

Organizational resilience is important for the success of enterprises in unstable and uncertain periods. To survive in uncertain environments and promote future development, enterprises must be able to deal with emergencies and overcome various disturbances, from minor adverse developments to major crises [12]. Studies have demonstrated that organizational resilience is evidenced by the anticipation, acceptance, and transformation of enterprises in response to adverse external environmental influences [13]. Resilient organizations can navigate effectively despite various disruptions and even thrive amidst external disturbances [14]. Such organizations reap multiple benefits both during regular operations and in times of unforeseen threats and changes [15]. Chen et al. (2021) contended that resilient organizations possess the capacity to adapt effectively to market fluctuations, take necessary measures, and respond rapidly to market changes [16]. Such enterprises can predict potential threats and learn from crisis events; in other words, they have dynamic capability, which not only enables them to thrive in a competitive and dynamic environment, but also empowers them to improve their core competitiveness and attain sustainable competitive advantages [12,17]. Resilience provides a crucial competitive advantage that can enhance performance, environmental adaptability, innovation capabilities, and overall development, particularly in small and medium-sized enterprises [14].

2.2 Economic implications of state capital infusion into privately-owned enterprises

The extant literature examined the economic implications of injecting state-owned capital into private enterprises from the vantage points of debt financing, resource and governance effects, as well as technological innovation.

With regard to debt financing, state-owned equity can facilitate private enterprises in establishing a symbiotic relationship with the government, thereby enhancing their reputation and enabling them to secure larger-scale and lower-cost debt financing in future [[18], [19], [20]]. State-owned capital investment in private enterprises represents the government's faith in these organizations, which sends positive signals to external stakeholders and increases their access to credit funds. It also reduces information asymmetry between lenders and borrowers, which helps to alleviate financing constraints [21,22].

Regarding resource and governance effects, an infusion of state-owned equity can safeguard private property rights and generate resource effects for enterprises [23,24]. The resulting enhanced operational performance helps firms to overcome the problem of insufficient market allocation, form heterogeneous equity structures, and leverage other positive effects of receiving state-owned equity [25]. In China specifically, mixed-ownership reform has the potential to mitigate agency conflicts, reduce equity mispricing, and enhance future stock market value returns [26]. Finally, the infusion of state-owned capital into private enterprises can enhance their organizational resilience by strengthening directorial relationships [27].

Looking at technological innovation, we see that an infusion of state-owned equity can enhance firms' inclination to invest in innovative activities and augment the resources available for such endeavors [28]. The optimal proportion of state-owned equity holdings within private enterprises can counterbalance the adverse effects of excessive regulation and foster increased investment in innovation, thereby effectively bolstering firms’ capacity for technological innovation in improving their bottom line [25,29].

2.3 Factors influencing organizational resilience in private enterprises

Numerous factors influence organizational resilience; these factors have been extensively analyzed and examined from diverse perspectives in the existing literature. Zhang et al. (2022) categorized the mechanisms driving organizational resilience in private Chinese listed enterprises as follows: those based on the relationship between resources and ability, those based on ability, and those based on resources [30]. Furthermore, they stated that having sufficient resources is a fundamental prerequisite for fostering organizational resilience in private enterprises. Ma and Zhang (2022) posited that organizational resilience is a consequence of numerous internal and external occurrences in which crisis management strategies are augmented through both passive and active coping mechanisms [31]. Examining enterprise characteristics, Feng et al. (2022) asserted that innovative endeavors can bolster organizational resilience and enhance anticipatory capabilities [11]. Considering the macro-environment, Li et al. (2022) argued that an enterprise's organizational resilience is influenced by its industry milieu. Technological advancements and market competition propel enterprises to build organizational resilience progressively in order to adapt to the environment; conversely, failure in market competition significantly undermines organizational resilience [32].

2.4 The impact of incorporation of state-owned equity on the organizational resilience of private enterprises

Organizational resilience pertains to the adaptability of enterprises. It enables them to respond promptly to shocks and recover gradually [33]. Hoa et al. (2023) defined organizational resilience as a conscious attempt to improve an organization's ability to cope with unexpected shocks and find ways to survive in adversity by identifying possible threats [34]. Private enterprises often seek assistance with specific resources; incorporating state-owned capital enables them to mitigate resource constraints and face risks with greater confidence. This resource effect fosters effective adaptation to market fluctuations, thus enhancing the organizational resilience of private enterprises [35].

In conclusion, the economic consequences of introducing state-owned capital into private enterprises have been extensively investigated, revealing its influence in terms of debt financing, resource allocation, and governance effects, as well as technological innovation. However, investigation is necessary of the impact on the organizational resilience of private enterprises of a heterogeneous equity structure comprising both private and state-owned equity, with consideration of resources, capabilities, and relationships. Therefore, this study explores the impact of state-owned equity on private enterprises and the mechanisms underlying organizational resilience. Given the significance of resources in shaping firms’ organizational resilience, we posit that an infusion of state-owned capital augments the debt financing capacity of private enterprises. The involvement of state-owned shareholders can also bolster the capabilities of private enterprises to respond to risks, manage their finances, and adapt to environmental changes. We posit that improvement of capabilities in private enterprises puts them in a better position to focus on innovation, which ultimately increases their resilience. Finally, relationships between these enterprises and the government can improve through infusion of state-owned capital; a type of symbiosis develops that contributes positively to organizational resilience.

3 Theoretical analysis and hypothesis development

Organizational resilience is essential for enterprises to confront economic and technological changes, proactively anticipate environmental crises, and thrive amidst adversity [11,36,37]. The greater the resilience of a firm, the better its capacity to identify and respond to crises [8]. With the rapid development of China's economy, private enterprises have emerged as crucial to the country's economic progress. Infusion of state-owned capital in non-state-owned enterprises can reshape existing organizational structures, effectively increasing the advantages of having a diverse shareholder portfolio and contributing to the competitiveness and dynamism of private enterprises [28]. The conceptual model has been shown on Fig. 1.Fig. 1 Conceptual model.

Fig. 1

3.1 Organizational resilience, state-owned equity, and the resource-based view

Resource-based theory posits that a firm is an assemblage of resources, and these resources are accumulated through the firm's activities. The resource-based perspective highlights that the risk response and resilience of enterprises are significantly influenced by resource constraints [30]. Unique and heterogeneous resources are the foundation for a firm's superior returns and competitive advantage; they also play a role in organizational resilience [38]. Compared to state-owned enterprises, lending restrictions are more stringent when it comes to financial institutions extending credit to private enterprises. The government plays a predominant role in resource allocation; thus, private enterprises, with their disadvantaged positions, must cultivate a robust rapport with the government [39]. As a valuable resource, this relationship can facilitate private enterprises in acquiring the necessary funding from both government and financial institutions [40], thereby mitigating financing constraints and enhancing their financial capabilities [41]. On one hand, government involvement in private enterprises can serve as a credible signal, fostering credit assurance and facilitating access to financial resources for private enterprises [42]. On the other hand, introducing state-owned equity into private enterprises can alleviate industrial restrictions imposed on private entities and help them overcome industry barriers, thereby mitigating highly monopolistic government policies regarding state-owned enterprises in certain industries [43]. Furthermore, the inclusion of state-owned private property rights in a corporate portfolio can aid in retaining high-quality resources [23,44]. Finally, government involvement can enable private enterprises to accumulate sufficient resources to address crises effectively, which increases their organizational resilience.

3.2 Organizational resilience, state-owned equity, and dynamic capability theory

Our research is based on dynamic capability theory, which is a further development of resource-based theory. This theory posits that in a complex and volatile business environment, organizations can enhance their ability to adapt to environmental changes and achieve developmental objectives by acquiring and integrating internal as well as external resources. Capability enhancement relies not only on acquisition of external knowledge, but also on adaptability to environmental changes [45,46]. The ability to adapt to external changes [47] drives enhancement of organizational resilience, which manifests as an organization's capacity to learn and progress despite unforeseen events and seize new opportunities through leveraging past experience [48]. Unsurprisingly, the capacity of enterprises to utilize internal and external resources effectively in response to fluctuations in the external environment significantly impacts their organizational resilience.

The theory of dynamic capability posits that enterprises can effectively navigate ever-changing market environments by strategically acquiring, integrating, and reconstructing internal and external resources [49]. This dynamic capability enables enterprises to attain crucial competitive advantages. Flexibility and adaptability in uncertain environments are essential in the processes of adapting, adjusting, and reconfiguring firm capabilities and resources [36,50].

3.3 Organizational resilience, state-owned equity, and innovation

Infusion of state-owned equity into private enterprises enhances their crisis response and technological innovation capabilities. Innovation, as a key driver of competitiveness, is intricately linked to market value and management of uncertainty. Innovation facilitates acquisition of market power and supernormal profits [51,52]. The survival of private enterprises is influenced by numerous uncertainties. State-owned equity can enhance the strategic risk-taking capacity of private enterprises by alleviating financing constraints; this effect is more pronounced as the degree of government support increases [22]. Moreover, state-owned capital can play a crucial role in encouraging private enterprises to engage actively in exploratory research, thereby significantly enhancing their capacity for independent innovation [39]. High proportions of state-owned shares can mitigate firm reliance on corporate governance and enhance innovative capacity [53]. A heterogeneous relationship between state-owned shareholders and private enterprises fosters a kind of symbiosis, which facilitates resource allocation and enhances efficiency [54].

3.4 Other benefits of state-owned equity for organizational resilience

Enterprises must consider the interests of multiple stakeholders when making decisions. They should not solely prioritize shareholders' interests, but rather strive to strike a balance among the diverse needs of different stakeholders and various social responsibilities [30]. Compared to state-owned enterprises, private enterprises have lower levels of information transparency; therefore, information asymmetry between enterprises and stakeholders may undermine investor interests. The participation of shareholders from state-owned enterprises in private enterprises can improve supervision, provide checks and balances, and enhance information transparency [20]. This involvement also safeguards the rights and interests of stakeholders, thereby bolstering the organizational resilience of private enterprises. Previous research indicated that an infusion of state-owned capital can enhance overall revenue and employee benefits in private enterprises. The introduction of state-owned shares into a corporation's portfolio can facilitate a Pareto improvement in income distribution and foster long-term cooperation among stakeholders [55].

Clearly, state-owned equity can significantly enhance organizational resilience. Building upon this premise, we propose Hypothesis 1 in this study.H1 Infusing state-owned capital into a private enterprise positively affects its organizational resilience.

3.5 Financing constraints and the relationship between state-owned capital and organizational resilience of private enterprises

The financing landscape in China's capital market is predominantly characterized by debt financing, which offers a cost advantage and serves as the primary funding source for many firms [56]. Having sufficient capital can alleviate financing constraints, thereby enabling private enterprises to seize development opportunities, enhance their innovation capabilities, and improve their business performance [35]. Information transparency is limited and operational risks associated with financing of private enterprises are high; therefore, financial institutions have historically exhibited a bias against private property rights and a reluctance to extend funding to such enterprises as a precautionary measure against potential risks [19,57]. The challenges associated with securing financing and the high costs involved in obtaining funding for private enterprises can potentially disrupt their capital flow, increase financial risks during emergencies, diminish risk management capabilities, and undermine the resilience of these enterprises [58]. To facilitate the development of private enterprises, China therefore encourages the infusion of state-owned capital into private enterprises to aid their synergistic integration into the marketplace.

3.5.1 State-owned equity and financing constraints

Financial participation of state-owned shareholders in private enterprises can send certain signals, enhance a company's reputation, and provide access to valuable resources. It can also facilitate expansion of debt financing for private enterprises, enabling them to diversify their funding sources and alleviate financing constraints [7,35].

Inclusion of state-owned capital in the financial mix of private enterprises can convey positive signals to creditors. The infusion of state-owned equity into private enterprises can enhance their access to financing opportunities through credit guarantees. In essence, state-owned equity is a form of government assistance to offset operational challenges and provide institutional credit guarantees for private enterprises in the market [59]. Involvement of state-owned shareholders enables supervision over private enterprises, provides balance, and conveys a signal of the quality of corporate information to creditors, thereby mitigating information asymmetry between private enterprises and creditors and reducing debt financing costs [60]. It can therefore be a viable solution to alleviate crises of trust between creditors and private enterprises. Increased trust has a positive effect on both debt financing for and the reputation of private enterprises. Fostering a strong relationship between government and private enterprises can improve corporate governance standards and increase commitment to social responsibilities. All these benefits alleviate the financing constraints faced by private enterprises [35].

3.5.2 Financing constraints and organizational resilience

Resources are important for organizational resilience. State-owned capital can increase convenience and provide a guarantee for debt financing for private enterprises by reducing financing costs and preventing credit discrimination. Financial constraints may lead companies to deviate from optimal investment levels, impeding their expansion and development, even potentially heightening the risk of bankruptcy [61]. Dynamic capability theory advocates developing appropriate capabilities and reallocating resources internally [36]. Expansion of the debt scale can alleviate financing constraints and promote implementation of various measures to address emergencies and pursue future plans. Adequate financial resources facilitate management of the impact of emergencies, gradual restoration of production and operations after an emergency, and enhancement of organizational resilience [58]. Financial stability enables private enterprises to sustain organizational operations during times of crisis, withstand various shocks, and swiftly restore the organization to its anticipated performance level [36,62]. Such dynamic organizational capabilities are developed by acquiring external resources such as debt financing. Government support helps organizations to adapt to crisis-induced changes and increase resilience through proactive coping strategies and adaptivity [37].

To summarize, involvement of state-owned shareholders in private enterprises can provide valuable resources and effectively alleviate the predicament presented by financing constraints. Adequate financial resources facilitate development of risk response and crisis recovery capabilities in private enterprises, thereby enabling them to adapt to economic and market changes and increase organizational resilience. We now present Hypothesis 2.H2 Infusion of state-owned capital positively affects the organizational resilience of private enterprises by alleviating financing constraints.

4 Materials and methods

4.1 Data and sample selection

This study utilizes data from Chinese A-share listed companies for the period 2009–2022. The dataset was sourced from the China Stock Market & Accounting Research (CSMAR) database. Regression analysis was conducted using Stata 18 software. The sample selection process was as follows: we included all Chinese A-share listed companies (i) excluding firms in the financial industry (due to the special structure of assets and liabilities in that industry, and the fact that its financial indicators and regulatory rules differ from those of other industries); (ii) excluding ST and *ST companies (Special Treatment, usually those public companies facing financial difficulties or other problems); (iii) excluding firms with missing data and abnormal or irrelevant data; (iv) excluding companies listed in the current year (whose short time on the market and limited available data prevent adequate analysis). In addition, we applied 1 % and 99 % tailing to all continuous variables in the model to reduce the impact of extreme values on the research results. Our final sample thus included unbalanced panel data of 20,510 firm-year observations.

Table 1, Table 2 present the industries and ages of listed firms in the sample, respectively.Table 1 Industries of the sample firms.

Table 1Industry Name	Numbers	
Agriculture, Forestry, Animal Husbandry and Fishery	298	
Mining industry	328	
Manufacturing industry	13,707	
Electricity, heat, gas and water production and supply industry	300	
Building industry	524	
Wholesale and retail trade	970	
Transportation, warehousing and postal services	270	
Accommodation and catering	27	
Information transmission, software and information technology services	1726	
Real estate industry	969	
Leasing and business services	294	
Scientific research and technical services	227	
Water, environment and utilities management	302	
Residential services, repairs and other services	14	
Education	31	
Hygiene	68	
Culture, sports and entertainment	251	
Public administration	204	
Total	20,510	

Table 2 Ages of the selected sample firms.

Table 2Firm Age (Years)	Numbers	
Less than 5	6388	
5–10	6074	
10–15	3719	
15–20	2355	
20–25	1558	
25–30	415	
Greater than 30	1	
Total	20,510	

4.2 Variables

4.2.1 Dependent variable

We use the measure of organizational resilience proposed by Ortize and Bansal (2016) [63] and Lv et al. (2019) [64] to assess the organizational resilience of private enterprises on two dimensions: financial volatility and growth ability. Financial volatility is quantified by calculating the standard deviation of monthly stock returns. The standard deviation for firm performance can serve as an indicator of an organization's ability to guarantee consistent performance (that is, how resilient it is). Growth ability is assessed based on the three-year cumulative rate of growth in sales revenue. This growth should be consistent and gradual, sustained over a period of time. In contrast to year-on-year growth, cumulative growth provides a more comprehensive measure of long-term expansion and effectively captures the sustained development of enterprises. Finally, the entropy method is employed to quantify organizational resilience comprehensively.

4.2.2 Independent variables

This paper refers to the work of Chen et al. [65] (2024) and Laeven and Levine [66] (2008) to assess the extent of state-owned shareholders’ involvement in private enterprises. Soeshare represents the cumulative shareholding ratio of major state-owned shareholders, while Dsoe indicates a significant influence of state-owned shareholders in privately-owned enterprises. The China Securities Regulatory Commission mandates that shareholders with a stake exceeding 5 % in the company must adhere to the requirement of obligatory disclosure. Therefore, in this study, we employ the binary variable Dsoe to ascertain the influence of significant state-owned shareholders in Chinese enterprises by determining whether the shareholding ratio of the top ten shareholders exceeds 5 %.

4.2.3 Mediating variable

Referring to the work of Hadlock (2010) [67] and Ju et al. (2013) [68], we adopt the financing constraints index (SA) to measure the scale of debt financing. We calculate SA as follows: SA = - 0.737 * Size + 0.043 * Size2 - 0.040 * Age, where Size represents the natural logarithm of the total scale of assets of the enterprise, and Age represents the operating years of the enterprise, which is equal to the observation year (the current statistical deadline) minus the time of establishment of the enterprise (year). SA is negative, and the larger its value, the stronger the financing constraints of the enterprise.

4.2.4 Control variables

Referring to Xu et al. (2023) [69], Yan et al. (2023) [70], and Luo and Qin (2019) [28], we select the following two types of control variables. The first category comprises fundamental enterprise characteristics and essential financial variables, including Size, Lev, Roa, Cashflow, Ato, Ppe, Tang, Int, and Mfee. The second category represents the firm's ownership structure and governance level, encompassing variables such as Sep, Indep, and Balance Msalary. For effective management and analysis of the impact of political connections, we also include the political connections (PC) of private enterprises as a control variable. Variable definitions are presented in Table 3.Table 3 Variable definitions.

Table 3	Variable	Measurement	
Dependent Variable	Volatility	Standard deviation of stock returns for each month in a year	
Growth	Three-year cumulative growth in sales revenue	
Resilience	entropy method used to calculate	
Independent Variables	Soeshare	Among the top ten shareholders, the cumulative shareholding proportion of state-owned shareholders	
Dsoe	Among the top ten shareholders, if the state-owned shareholding ratio is above 5 %, the value is 1; otherwise, 0	
Mediating Variable	SA	Financing constraints, calculated as follows: SA = - 0.737 * Size +0.043 * Size2 - 0.040 * Age	
Control Variables	Size	Natural logarithm of the number of employees in a company	
Lev	Total liabilities/Total assets	
Odr	Operating liabilities/Total liabilities	
Roa	Net profit/Average total assets	
Cashflow	Net cash flow from operating activities/operating income	
Ato	Operating income/Average assets	
Ppe	Net fixed assets/Total assets	
Tang	Total tangible assets/Total assets	
Int	Total intangible assets/Total assets	
Mfee	Administrative expenses/Revenue	
Sep	Difference between control and ownership	
Indep	Percentage of independent directors on the board	
Balance	Sum of shares held by the second to fifth largest shareholders/shares held by the first largest shareholder	
Msalary	Total compensation of the top three directors, supervisors and managers	
PC	If either the chairman or manager of the enterprise is or has been a government official, the value is 1; otherwise zero	

4.3 Empirical model

To examine the influence of state-owned shareholders on the organizational resilience of private enterprises, we now employ ordinary least squares (OLS) regression analysis to obtain Model (1).(Model 1) Resiliencei,t=α0+α1Soesharei,t/Dsoei,t+α2Controlsi,t+∑Year+∑Ind+εi,t

The explained variables Volatility, Growth, and Resilience serve as metrics for assessing the organizational resilience of enterprises. The explanatory variables Soeshare and Dsoe are utilized to gauge the shareholding of state-owned shareholders. Model (1) incorporates year fixed effects and industry fixed effects as control variables.

To examine the mechanisms underlying the impact on the resilience of private enterprises of introducing state-owned capital, we establish a mechanism testing model, as depicted in Models (2) and (3). The variable Debt serves as an intermediary measure of the extent of debt financing in the sample. The remaining variables retain the same meaning as in Model (1).(Model 2) Debti,t=α0+α1Soesharei,t/Dsoei,t+α2Controlsi,t+∑Year+∑Ind+εi,t

(Model 3) Resiliencei,t=α0+α1Soesharei,t/Dsoei,t+α2Debti,t+α3Controlsi,t+∑Year+∑Ind+εi,t

5 Results

5.1 Descriptive statistics

The descriptive statistics for the main variables in this paper are presented in Table 4. We see that there is a wide range of values for Volatility among different private enterprises facing environmental changes (maximum value: 8.3316, minimum value: 0.0017). Moreover, it is noteworthy that the standard deviation is 0.141; this highlights the significant disparities in volatility levels among firms in the sample. The Growth variable demonstrates substantial heterogeneity across private enterprises, fluctuating and diverging considerably and reflecting significant variation in performance growth (maximum value: 29.7734, minimum value: 1.9363, standard deviation: 5.599). These findings underscore the previously identified pronounced variation in growth patterns. Values for the Resilience of different private enterprises also exhibit significant variations (maximum value: 0.9724, minimum value: 0.0515). The average value for Dsoe is 0.1120, indicating the presence of major state-owned shareholders (defined as holding at least 5 % of a company's shares) in 11.2 % of the observations in the sample, thereby suggesting that the overall proportion of private enterprises incorporating major state-owned shareholders is relatively modest. The mean value of Soeshare is 0.0187 and the maximum value is 0.4655, signifying that the significance of including state-owned shareholders within the equity structure of private enterprises is increasing, along with their potential impact on corporate governance and organizational resilience.Table 4 Descriptive statistics.

Table 4VarName	Obs	Mean	SD	Min	Median	Max	
Volatility	20510	0.1471	0.141	0.0017	0.1226	8.3316	
Growth	20510	3.3338	5.599	−1.9363	0.9808	29.7734	
Resilience	20510	0.8757	0.085	0.0515	0.8990	0.9724	
Soeshare	20510	0.0189	0.044	0.0000	0.0000	0.4655	
Dsoe	20510	0.1120	0.315	0.0000	0.0000	1.0000	
SA	20510	−3.7886	0.242	−5.6459	−3.7801	−2.8467	
Size	20510	7.3209	1.134	4.2341	7.2882	10.2717	
Lev	20510	0.3783	0.202	0.0453	0.3611	0.9492	
Odr	20510	0.6207	0.252	0.1142	0.6205	1.0000	
Roa	20510	0.0406	0.076	−0.3584	0.0456	0.2170	
Cashflow	20510	0.2481	0.453	−0.7618	0.1518	2.3518	
Ato	20510	0.5944	0.377	0.0622	0.5134	2.3044	
Ppe	20510	0.1879	0.133	0.0018	0.1647	0.5753	
Tang	20510	0.9221	0.091	0.5254	0.9539	1.0000	
Int	20510	0.0436	0.042	0.0000	0.0335	0.2657	
Mfee	20510	0.1000	0.091	0.0093	0.0765	0.6296	
Sep	20510	4.8614	7.322	0.0000	0.2497	29.0984	
Indep	20510	37.7757	5.216	33.3300	36.3600	57.1400	
Balance	20510	0.8472	0.623	0.0457	0.6917	2.9421	
Msalary	20510	14.4621	0.731	12.6411	14.4499	16.5281	
PC	20510	0.3191	0.466	0.0000	0.0000	1.0000	

5.2 Pearson correlation analysis

We now conduct a Pearson correlation analysis to examine correlations among variables. The corresponding results are presented in Table 5. These results demonstrate significant correlations between Soeshare and Volatility, Growth, and Resilience at the 1 % level. There is a significant negative association between Soeshare and Volatility, indicating that state-owned equity can significantly reduce volatility in private enterprises. There are significant positive correlations between Soeshare and Growth and Resilience, indicating that infusion of state-owned capital can significantly improve the long-term performance of private enterprises. Dsoe exhibits significant correlations with Volatility, Growth, and Resilience at the 1 % level. Specifically, its correlation with Volatility is negative, while its correlations with both Growth and Resilience are positive. These results show that infusion of state-owned capital can enhance the coping and recovery abilities of private enterprises in times of crisis by significantly reducing volatility in private enterprises and improving their long-term performance, thereby also enhancing their organizational resilience. Thus, Hypothesis 1 is verified.Table 5 Pearson correlation analysis.

Table 5	Volatility	Growth	Resilience	Soeshare	Dsoe	Size	Lev	Odr	Roa	Cashflow	
Volatility	1										
Growth	−0.044c	1									
Resilience	−0.450c	0.099c	1								
Growth	−0.017b	0.071c	0.030c	1							
Dsoe	−0.024c	0.055c	0.027c	0.736c	1						
Size	−0.099c	0.355c	0.105c	0.079c	0.058c	1					
Lev	−0.027c	0.290c	0.092c	0.204c	0.164c	0.306c	1				
Odr	0.046c	−0.101c	−0.069c	−0.088c	−0.096c	−0.152c	−0.426c	1			
Roa	0.011	0.014a	−0.035c	−0.040c	−0.055c	0.080c	−0.278c	0.171c	1		
Cashflow	0.014a	−0.041c	−0.044c	−0.037c	−0.037c	−0.039c	−0.326c	0.174c	0.216c	1	
Ato	−0.017b	0.244c	−0.002	−0.025c	−0.018b	0.218c	0.152c	0.075c	−0.006	−0.034c	
Ppe	−0.031c	0.006	0.061c	0.073c	0.066c	0.224c	0.079c	−0.315c	−0.043c	0.053c	
Tang	0.002	−0.054c	−0.110c	0.023c	0.012	−0.063c	0.022c	0.120c	0.067c	0.011	
Int	−0.01	−0.003	0.045c	0.042c	0.052c	0.039c	0.026c	−0.132c	−0.058c	0.017b	
Mfee	0	−0.009	−0.013a	−0.004	−0.002	−0.018b	0.002	−0.004	−0.045c	−0.027c	
Sep	−0.033c	0.090c	0.006	0.019b	0.021c	0.154c	0.114c	−0.054c	0.003	−0.022c	
Indep	0.011	0	0.005	−0.056c	−0.080c	−0.066c	−0.030c	0.013a	−0.015b	0.007	
Balance	0.024c	−0.020c	−0.028c	−0.034c	0.051c	−0.065c	−0.111c	0.063c	−0.01	0.034c	
Msalary	−0.053c	0.281c	0.060c	0.005	0.012	0.363c	0.124c	−0.012	0.079c	0.069c	
PC	−0.024c	−0.004	0.019b	0.006	0.024c	0.076c	0.027c	−0.076c	0.019c	−0.020c	
	Ato	Ppe	Tang	Int	Mfee	Sep	Indep	Balance	Msalary	PC	
Ato	1										
Ppe	0.054c	1									
Tang	0.098c	0.107c	1								
Int	−0.037c	0.129c	−0.529c	1							
Mfee	−0.025c	−0.008	0.003	0	1						
Sep	0.080c	0.075c	0.061c	−0.008	0	1					
Indep	−0.029c	−0.035c	−0.019b	−0.003	−0.004	−0.110c	1				
Balance	−0.033c	−0.073c	−0.096c	−0.01	−0.005	−0.195c	−0.037c	1			
Msalary	0.071c	−0.084c	−0.057c	−0.046c	0.012a	0.041c	0.002	0.082c	1		
PC	0.009	0.079c	0.005	0.041c	−0.009	0.029c	−0.034c	−0.021c	−0.061c	1	
p values in parentheses.

a p < 0.10.

b p < 0.05.

c p < 0.01.

To test for multicollinearity, we run the variance inflation factor (VIF) test. The VIF value of the dependent variable ranges from 1.01 to 1.86, and the mean VIF value is 1.27, which is less than 3, indicating that there is no multicollinearity problem.

5.3 Regression analysis

To examine the impact of state-owned equity on the organizational resilience of private enterprises, we now conduct a regression analysis using Model (1), the corresponding results of which are presented in Table 6. Firstly, in terms of Volatility, the results in Columns (1) and (2) demonstrate that the coefficients of Soeshare and Dsoe indicate that these variables have significant negative effects at the 1 % level. This suggests that the involvement of state-owned shareholders can effectively mitigate the volatility experienced by private enterprises. Secondly, for the Growth variable, the results in Columns (3) and (4) demonstrate that the coefficients of Soeshare and Dsoe are significant and positive at the 1 % level, indicating that infusion of state-owned capital can substantially enhance the long-term performance of private enterprises. Regarding Resilience, the results in Column (5) reveal that the coefficient for Soeshare is positive and significant at the 5 % level, while Column (6) reveals that the coefficient of Dsoe is positive and significant at the 1 % level. These findings suggest that the involvement of state-owned shareholders increases the resilience of private enterprises.Table 6 Regression analysis.

Table 6	Volatility	Growth	Resilience	
(1)	(2)	(3)	(4)	(5)	(6)	
Soeshare	−0.0171c		16.6324c		0.0068b		
(-3.8182)		(6.4262)		(2.2633)		
Dsoe		−0.0052c		3.1012c		0.0023c	
	(-4.1815)		(4.3574)		(2.8322)	
Size	−0.0080c	−0.0081c	10.2971c	10.4117c	0.0042c	0.0042c	
(-16.6816)	(-16.8854)	(37.1390)	(37.6761)	(13.2028)	(13.3126)	
Lev	0.0046c	0.0046c	3.9962c	4.0360c	−0.0033c	−0.0033c	
(5.3453)	(5.3361)	(8.0819)	(8.1593)	(-5.7609)	(-5.7643)	
Odr	0.0049b	0.0047b	−7.1103c	−7.0358c	−0.0026a	−0.0025a	
(2.3968)	(2.2902)	(-6.0285)	(-5.9580)	(-1.9244)	(-1.8458)	
Roa	0.0061c	0.0061c	4.5460c	4.5806c	−0.0044c	−0.0044c	
(4.7019)	(4.7054)	(6.1191)	(6.1627)	(-5.1501)	(-5.1592)	
Cashflow	0.0003	0.0002	−0.7936a	−0.7895a	−0.0010a	−0.0010a	
(0.3488)	(0.3028)	(-1.8121)	(-1.8015)	(-1.9402)	(-1.9037)	
Ato	0.0032c	0.0033c	14.8387c	14.8048c	−0.0018c	−0.0018c	
(3.1545)	(3.1718)	(24.9971)	(24.9293)	(-2.6511)	(-2.6577)	
Ppe	−0.0049	−0.0050	−11.7642c	−11.4656c	0.0027	0.0027	
(-1.1984)	(-1.2236)	(-5.0084)	(-4.8805)	(0.9888)	(0.9926)	
Tang	−0.0009	−0.0009	−20.4393c	−20.1307c	−0.0166c	−0.0166c	
(-0.1367)	(-0.1394)	(-5.6185)	(-5.5315)	(-3.9441)	(-3.9538)	
Int	−0.0059	−0.0057	−12.8792b	−12.5718a	−0.0124a	−0.0126a	
(-0.5314)	(-0.5084)	(-2.0023)	(-1.9533)	(-1.6768)	(-1.7018)	
Mfee	−0.0000	−0.0000	0.0189	0.0189	0.0000	0.0000	
(-0.6220)	(-0.6277)	(1.0645)	(1.0609)	(0.6597)	(0.6648)	
Sep	−0.0002c	−0.0002b	0.1896c	0.1840c	0.0001	0.0001	
(-2.5854)	(-2.5053)	(5.2561)	(5.1006)	(1.6443)	(1.5993)	
Indep	0.0001	0.0001	0.1924c	0.1930c	0.0000	0.0000	
(1.3259)	(1.2091)	(3.9633)	(3.9693)	(0.2396)	(0.3314)	
Balance	0.0024c	0.0026c	−0.5011	−0.6542	−0.0019c	−0.0020c	
(3.1985)	(3.5248)	(-1.1805)	(-1.5358)	(-3.8509)	(-4.0658)	
Msalary	−0.0026c	−0.0026c	6.2502c	6.1823c	0.0010b	0.0010b	
(-3.5186)	(-3.4693)	(14.4400)	(14.2837)	(2.0429)	(2.0229)	
PC	−0.0028c	−0.0027c	−0.6855	−0.8073	0.0016b	0.0015b	
(-2.7904)	(-2.6965)	(-1.1882)	(-1.3998)	(2.3608)	(2.3122)	
Constant	0.2805c	0.2815c	−151.5371c	−151.5542c	0.5011c	0.5005c	
(19.8542)	(19.9188)	(-18.6143)	(-18.5961)	(53.3441)	(53.2553)	
Industry/Year	Yes	Yes	Yes	Yes	Yes	Yes	
N	20510	20510	20510	20510	20510	20510	
adj. R2	0.2379	0.2380	0.2266	0.2258	0.7447	0.7448	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01; heteroskedasticity-robust standard errors are used.

In sum, infusion of state-owned equity mitigates volatility in private enterprises and improves their long-term performance, thereby enhancing their capacity to navigate crises, that is, to become more resilient. In addition, high proportions of state-owned equity help Chinese private enterprises become more resilient. The results of the analysis described herein demonstrate that infusion of state-owned capital can significantly enhance the organizational resilience of private enterprises. Therefore, Hypothesis 1 is verified.

5.4 Mediating effect test

The results of the mechanism test with financing constraints as the mediating variable are shown in Table 7. Firstly, Columns (1) and (5) show that the coefficients of SA, Soeshare, and Dsoe are negative and significant at the 1 % level, indicating that infusion of state-owned capital helps private enterprises to alleviate financing constraints and obtain more debt financing. Secondly, Columns (2) and (6) show that the coefficients of SA and Volatility are positive and significant at the 1 % level, indicating that easing financing constraints can reduce volatility for private enterprises and thus enhance their organizational resilience. Columns (3), (4), (7), and (8) show that the coefficients of SA and Growth and Resilience are negative and significant at the 1 % level.Table 7 Mediation analysis.

Table 7	SA	Volatility	Growth	Resilience	SA	Volatility	Growth	Resilience	
(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	
Soeshare	−0.0028c	−0.0002c	0.0561c	0.0001c					
(-19.2199)	(-3.4366)	(16.9737)	(2.7496)					
Dsoe					−0.0805c	−0.0045c	1.4263c	0.0021c	
				(-20.2472)	(-3.6139)	(15.7171)	(2.9187)	
SA		0.0193c	−5.3359c	−0.0099c		0.0192c	−5.3437c	−0.0099c	
	(9.2210)	(-35.1374)	(-8.4029)		(9.1655)	(-35.1249)	(-8.3540)	
Size	−0.0179c	−0.0083c	0.4468c	0.0041c	−0.0190c	−0.0084c	0.4720c	0.0041c	
(-11.4031)	(-17.0273)	(12.5598)	(14.6992)	(-12.1397)	(-17.1929)	(13.2842)	(14.8329)	
Lev	−0.0357c	0.0230c	4.5294c	−0.0122c	−0.0381c	0.0229c	4.6237c	−0.0122c	
(-3.9675)	(8.2067)	(22.2740)	(-7.7360)	(-4.2473)	(8.1751)	(22.7679)	(-7.7161)	
Odr	0.0760c	0.0086c	−0.5198c	−0.0041c	0.0722c	0.0084c	−0.4423c	−0.0040c	
(10.8752)	(3.9248)	(-3.2822)	(-3.3109)	(10.3326)	(3.8306)	(-2.7920)	(-3.2357)	
Roa	−0.0151c	0.0025b	−0.1247a	−0.0015c	−0.0149c	0.0025b	−0.1251a	−0.0015c	
(-4.8572)	(2.5460)	(-1.7805)	(-2.8148)	(-4.8227)	(2.5514)	(-1.7844)	(-2.8194)	
Cashflow	0.0068c	0.0014a	−0.0941a	−0.0013c	0.0061b	0.0014a	−0.0807	−0.0012c	
(2.7149)	(1.8058)	(-1.6631)	(-2.8670)	(2.4517)	(1.7590)	(-1.4249)	(-2.8297)	
Ato	0.0144c	0.0021b	0.4807c	−0.0012b	0.0149c	0.0021b	0.4683c	−0.0012b	
(4.3374)	(2.0275)	(6.3873)	(-1.9974)	(4.4708)	(2.0527)	(6.2170)	(-2.0171)	
Ppe	−0.0265b	−0.0045	−2.4376c	0.0019	−0.0285b	−0.0046	−2.3781c	0.0019	
(-2.0268)	(-1.1011)	(-8.2625)	(0.8190)	(-2.1814)	(-1.1298)	(-8.0560)	(0.8411)	
Tang	0.0005c	−0.0000	0.0031	0.0000	0.0005c	−0.0000	0.0032	0.0000	
(5.4265)	(-0.8984)	(1.4103)	(0.8440)	(5.4126)	(-0.9000)	(1.4115)	(0.8454)	
Int	−0.0004b	−0.0002c	0.0542c	0.0001b	−0.0003a	−0.0002b	0.0524c	0.0001b	
(-2.0826)	(-2.6468)	(11.9661)	(2.1825)	(-1.6609)	(-2.5722)	(11.5632)	(2.1231)	
Mfee	0.1867c	−0.0134	2.7282c	−0.0049	0.1905c	−0.0132	2.6966c	−0.0050	
(5.2108)	(-1.2043)	(3.3692)	(-0.7847)	(5.3210)	(-1.1835)	(3.3267)	(-0.8019)	
Sep	0.0009c	0.0001	0.0150b	−0.0000	0.0008c	0.0001	0.0169c	−0.0000	
(3.5137)	(0.9636)	(2.4594)	(-0.5037)	(2.9903)	(0.8698)	(2.7710)	(-0.4272)	
Indep	0.1940c	−0.0064	−2.7941c	−0.0092b	0.1935c	−0.0065	−2.7569c	−0.0092b	
(9.5835)	(-1.0204)	(-6.0971)	(-2.5743)	(9.5652)	(-1.0226)	(-6.0109)	(-2.5738)	
Balance	0.0125c	0.0023c	−0.1357b	−0.0016c	0.0164c	0.0025c	−0.2037c	−0.0017c	
(5.3018)	(3.1471)	(-2.5424)	(-3.7444)	(6.9136)	(3.4294)	(-3.7983)	(-3.9681)	
Msalary	−0.0102c	−0.0023c	0.6380c	0.0009b	−0.0095c	−0.0023c	0.6217c	0.0009b	
(-4.2408)	(-3.1218)	(11.7287)	(2.1716)	(-3.9687)	(-3.0747)	(11.4251)	(2.1344)	
PC	−0.0096c	−0.0025b	−0.1871c	0.0015c	−0.0080b	−0.0024b	−0.2217c	0.0014b	
(-2.9828)	(-2.5420)	(-2.5816)	(2.6281)	(-2.4885)	(-2.4550)	(-3.0591)	(2.5594)	
Constant	−3.4672c	0.3425c	−27.901c	0.4696c	−3.4511c	0.3431c	−28.163c	0.4694c	
(-76.4831)	(21.5880)	(-24.2336)	(52.5233)	(-76.1571)	(21.6315)	(-24.4477)	(52.5163)	
Industry/Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	
N	20510	20510	20510	20510	20510	20510	20510	20510	
adj. R2	0.3317	0.2420	0.3350	0.8022	0.3329	0.2420	0.3337	0.8023	
Sobel-Goodman Mediation Tests	
Indirect effect	0.0006 (Z = 2.65)	0.0008 (Z = 3.43)	
Direct effect	0.0217 (Z = 10.50)	0.0215 (Z = 10.39)	
Total effect	0.0223 (Z = 10.87)	0.0223 (Z = 10.87)	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

We also conduct the Sobel-Goodman test in this study; the results reveal the significant presence of both direct and indirect effects, with financing constraints playing a partially mediating role. This shows that infusion of state-owned capital has a positive effect on alleviating the financing problems of private enterprises, providing them with sufficient funds for investment, innovation, and other activities, and thus improving their risk response ability and resilience. These results therefore verify Hypothesis 2.

5.5 Endogeneity tests

5.5.1 Heckman two-step method

Although the above results of the regression analysis show that reverse mixed-ownership reform can significantly enhance the organizational resilience of private enterprises, there may also be reverse causality between the two constructs. The selection of private enterprises for investment by state-owned shareholders in the process of reverse mixed-ownership reform may not be random, but rather a self-selection behavior based on comprehensive consideration of their own development goals and the economic characteristics of the enterprises in which they choose to invest. To mitigate such endogeneity concerns, we employ the Heckman two-step method to re-examine the data.

In the first stage, we construct the probit regression model. We calculate the inverse Mills ratio (IMR) to test whether the characteristics of private enterprises affect state-owned equity participation. The probit model of the first stage is shown in Model 4.(Model 4) Probit(Stateifit) = η0+η1Controlsit+μit

In this model, Stateif indicates whether private enterprises received an investment in the form of state-owned equity in a certain year, and Controls is a set of characteristic variables of private enterprises.

In the second stage, we add IMR to Model (1) as a control variable to determine the presence of endogeneity in the form of sample selection bias. The regression results, presented in Table 8, demonstrate that the estimated coefficient of IMR is significant for Resilience, Volatility, and Growth at the 1 % level. This indicates that the results of the aforementioned model are not affected by endogeneity issues such as sample selection bias. After adding IMR, we see that the estimated coefficient symbols and significance levels of Resilience, Volatility, and Growth by Soeshare have not changed. Thus, the results of this analysis are basically consistent with the main regression results, indicating that the research results in this paper are robust.Table 8 Heckman two-step method.

Table 8	Resilience	Volatility	Resilience	
(1)	(2)	(3)	(4)	(5)	(6)	
Soeshare	0.0167b		−0.0448c		1.1998c		
(2.1928)		(-3.7823)		(3.8579)		
Dsoe		0.0011		−0.0032b		0.1573c	
	(1.0446)		(-2.0003)		(3.7200)	
Size	0.0097c	0.0098c	−0.0278c	−0.0281c	−0.2024b	−0.1986b	
(4.8793)	(4.9429)	(-9.0249)	(-9.1265)	(-2.5007)	(-2.4540)	
Lev	−0.0016b	−0.0016b	0.0001	0.0000	0.0039	0.0054	
(-2.2806)	(-2.2355)	(0.1125)	(0.0371)	(0.1359)	(0.1870)	
Odr	−0.0027	−0.0028a	0.0049a	0.0050a	−0.1430b	−0.1451b	
(-1.6284)	(-1.6727)	(1.8760)	(1.9469)	(-2.1020)	(-2.1331)	
Roa	−0.0012	−0.0012	−0.0012	−0.0013	0.1923c	0.1941c	
(-1.1317)	(-1.0928)	(-0.7048)	(-0.7689)	(4.4001)	(4.4413)	
Cashflow	0.0004	0.0004	−0.0029b	−0.0029b	−0.0847b	−0.0840b	
(0.4268)	(0.4159)	(-2.0004)	(-1.9847)	(-2.1983)	(-2.1808)	
Ato	−0.0055c	−0.0056c	0.0172c	0.0174c	0.5334c	0.5320c	
(-3.6064)	(-3.6442)	(7.2318)	(7.2909)	(8.5142)	(8.4923)	
Ppe	0.0071a	0.0072a	−0.0296c	−0.0300c	−0.4134b	−0.4077b	
(1.7778)	(1.8245)	(-4.7995)	(-4.8744)	(-2.5516)	(-2.5173)	
Tang	0.0093	0.0099	−0.0753c	−0.0767c	−2.6788c	−2.6622c	
(1.1195)	(1.1908)	(-5.8035)	(-5.9188)	(-7.8580)	(-7.8129)	
Int	0.0263a	0.0270a	−0.1289c	−0.1306c	−2.6875c	−2.6830c	
(1.8218)	(1.8705)	(-5.7380)	(-5.8124)	(-4.5513)	(-4.5436)	
Mfee	−0.0002b	−0.0002c	0.0007c	0.0007c	0.0088c	0.0086c	
(-2.5641)	(-2.6158)	(6.1508)	(6.2340)	(3.0167)	(2.9765)	
Sep	0.0004c	0.0004c	−0.0014c	−0.0014c	−0.0176c	−0.0172c	
(3.3627)	(3.4542)	(-7.0248)	(-7.1751)	(-3.4082)	(-3.3239)	
Indep	−0.0002b	−0.0002b	0.0009c	0.0009c	0.0163c	0.0162c	
(-2.3595)	(-2.4260)	(5.8699)	(5.9732)	(4.2284)	(4.2097)	
Balance	−0.0028c	−0.0027c	0.0062c	0.0060c	−0.0679c	−0.0668c	
(-4.5599)	(-4.4362)	(6.4389)	(6.2423)	(-2.6855)	(-2.6443)	
Msalary	0.0040c	0.0041c	−0.0136c	−0.0138c	−0.1279b	−0.1246b	
(3.2112)	(3.2704)	(-6.9846)	(-7.0816)	(-2.4922)	(-2.4296)	
PC	0.0014b	0.0014b	−0.0036c	−0.0036c	−0.0336	−0.0348	
(1.9688)	(1.9647)	(-3.1210)	(-3.1096)	(-1.1168)	(-1.1584)	
IMR	0.0508c	0.0517c	−0.1810c	−0.1832c	−3.3773c	−3.3476c	
(2.8727)	(2.9242)	(-6.5883)	(-6.6709)	(-4.6776)	(-4.6377)	
Constant	0.3795c	0.3773c	0.7042c	0.7099c	5.8817c	5.7847c	
(8.8844)	(8.8349)	(10.6111)	(10.6966)	(3.3718)	(3.3173)	
Year/Industry	Yes	Yes	Yes	Yes	Yes	Yes	
N	20371	20371	20371	20371	20371	20371	
adj. R2	0.7652	0.7651	0.2516	0.2511	0.0848	0.0847	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

5.5.2 Propensity score matching method

To address the possible endogeneity problem arising from missing firm variables, we employ the propensity score matching method and a 1:1 nearest-neighbor matching approach with a caliper of 0.05. In selecting matching variables, we consider three types of indicators. The first type comprises micro-characteristics at the company level, including firm size, leverage ratio, cash flow, return on assets, and other relevant metrics. The second category encompasses governance factors at the enterprise level, such as the separation of ownership and control rights, equity balance, and other pertinent indicators. Lastly, the third category incorporates the risk associated with a firm's stock price collapse and its political connections. Model (1) is regressed using the matched samples; the results are presented in Table 9. Columns (1), (3), and (5) demonstrate that the coefficients of Soeshare and Volatility are negative and significant at a level of 1 %, while those of Soeshare, Growth, and Resilience are positive and significant at a level of 1 %. The coefficients of Dsoe and Volatility in Columns (2), (4), and (6) are negative and significant at the 1 % level, while those of Dsoe and Growth as well as Resilience are positive and significant at the 5 % and 1 % levels, respectively. These test results demonstrate that, even after accounting for variations in observable variables at the enterprise level, our findings remain consistent with those of previous research, thereby affirming the robustness of the conclusions presented in this paper.Table 9 Propensity score matching.

Table 9	Violatility	Growth	Resilience	
(1)	(2)	(3)	(4)	(5)	(6)	
Soeshare	−0.0484c		13.7197c		0.0132c		
(-3.7200)		(3.7912)		(3.3983)		
Dsoe		−0.0100c		2.1980b		0.0031c	
	(-2.9584)		(2.3347)		(3.0941)	
Size	−0.0098c	−0.0100c	8.7412c	8.7944c	0.0037c	0.0037c	
(-6.8777)	(-7.0119)	(21.9862)	(22.1231)	(8.6247)	(8.7506)	
Lev	0.0389c	0.0375c	30.9513c	31.4110c	−0.0127c	−0.0123c	
(4.5903)	(4.4307)	(13.1359)	(13.3529)	(-5.0014)	(-4.8705)	
Odr	0.0211c	0.0201c	−2.4856	−2.2203	−0.0050c	−0.0047b	
(3.3334)	(3.1840)	(-1.4155)	(-1.2647)	(-2.6499)	(-2.5114)	
Roa	0.0330a	0.0333a	37.2728c	37.0907c	−0.0043	−0.0043	
(1.6746)	(1.6879)	(6.7965)	(6.7605)	(-0.7290)	(-0.7319)	
Cashflow	−0.0029	−0.0032	1.1120	1.1664	0.0006	0.0007	
(-0.8732)	(-0.9436)	(1.1862)	(1.2434)	(0.6107)	(0.6845)	
Ato	0.0012	0.0016	21.1989c	21.0901c	−0.0020	−0.0021a	
(0.2778)	(0.3732)	(17.7742)	(17.6773)	(-1.5739)	(-1.6656)	
Ppe	−0.0105	−0.0114	−9.1838c	−8.9370c	0.0056	0.0058	
(-0.8842)	(-0.9567)	(-2.7808)	(-2.7056)	(1.5660)	(1.6318)	
Tang	0.0326a	0.0320a	−28.4108c	−28.1387c	−0.0153c	−0.0152c	
(1.7535)	(1.7199)	(-5.4935)	(-5.4393)	(-2.7482)	(-2.7281)	
Int	0.0148	0.0132	−29.8262c	−29.2608c	−0.0117	−0.0113	
(0.3858)	(0.3432)	(-2.7906)	(-2.7370)	(-1.0197)	(-0.9856)	
Mfee	−0.0054	−0.0037	16.7856c	16.3381c	−0.0036	−0.0041	
(-0.3315)	(-0.2293)	(3.7342)	(3.6333)	(-0.7496)	(-0.8491)	
Sep	−0.0004b	−0.0003a	0.1433c	0.1355c	0.0001b	0.0001b	
(-1.9619)	(-1.8354)	(2.8602)	(2.7068)	(2.5495)	(2.4503)	
Indep	−0.0002	−0.0002	0.2636c	0.2662c	−0.0000	0.0000	
(-0.6962)	(-0.7584)	(3.8331)	(3.8666)	(-0.0505)	(0.0230)	
Balance	0.0012	0.0018	0.5302	0.4130	−0.0009	−0.0011a	
(0.5807)	(0.8355)	(0.8901)	(0.6898)	(-1.4203)	(-1.6868)	
Msalary	−0.0032	−0.0031	4.8428c	4.8075c	0.0017c	0.0017c	
(-1.4588)	(-1.4226)	(7.8773)	(7.8179)	(2.6037)	(2.5823)	
PC	−0.0002	0.0001	−0.6274	−0.7189	0.0011	0.0010	
(-0.0824)	(0.0314)	(-0.8010)	(-0.9179)	(1.2555)	(1.1529)	
Constant	0.2591c	0.2613c	−137.953c	−138.158c	0.4942c	0.4933c	
(6.4666)	(6.5128)	(-12.3905)	(-12.3900)	(41.1988)	(41.0769)	
Industry/Year	Yes	Yes	Yes	Yes	Yes	Yes	
N	10460	10460	10460	10460	10460	10460	
adj. R2	0.0962	0.0958	0.2355	0.2349	0.7795	0.7795	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01; heteroskedasticity-robust standard errors are used.

5.6 Robustness checks

5.6.1 Dependent variable lagged by one period

In the present study, we posit that the impact of introducing state-owned equity on the resilience of private enterprises may not be immediately obvious in the current period due to the potential causal relationship between these two constructs. Hence, in this study, we lag the explanatory variables Soeshare and Dsoe by one period to examine the relationship between infusion of state-owned capital and the organizational resilience of private enterprises. The findings are presented in Table 10, where we see that all results remain robust, except for the change from a 1 % positive correlation to a 5 % positive correlation between L.Soeshare and Resilience, as well as between L.Dsoe and Growth. These outcomes effectively validate the hypotheses presented in this paper.Table 10 Dependent variable lagged by one period.

Table 10	Volatility	Growth	Resilience	
(1)	(2)	(3)	(4)	(5)	(6)	
L.Soeshare	−0.0118c		7.3345c		0.0049b		
(-2.9949)		(2.7233)		(2.4650)		
L.Dsoe		−0.0030c		1.6989b		0.0014c	
	(-2.7927)		(2.2838)		(2.5980)	
Size	−0.0054c	−0.0054c	9.7738c	9.8038c	0.0024c	0.0024c	
(-12.1150)	(-12.2303)	(32.1356)	(32.2923)	(10.8326)	(10.9132)	
Lev	0.0237c	0.0235c	25.5672c	25.7519c	−0.0132c	−0.0131c	
(9.5136)	(9.4473)	(15.0012)	(15.1488)	(-10.5151)	(-10.4981)	
Odr	0.0059c	0.0057c	−1.3194	−1.2085	−0.0027c	−0.0026c	
(3.0398)	(2.9495)	(-0.9901)	(-0.9073)	(-2.7274)	(-2.6533)	
Roa	−0.0001	−0.0000	1.4861b	1.4846b	0.0005	0.0005	
(-0.0587)	(-0.0515)	(2.4535)	(2.4508)	(1.0926)	(1.0818)	
Cashflow	0.0007	0.0007	0.5924	0.5990	−0.0007b	−0.0007b	
(0.9681)	(0.9562)	(1.2052)	(1.2184)	(-2.0040)	(-1.9971)	
Ato	0.0013	0.0014	21.2179c	21.1605c	−0.0008	−0.0008	
(0.9747)	(1.0386)	(22.9350)	(22.8841)	(-1.1712)	(-1.2188)	
Ppe	0.0009	0.0007	−16.2785c	−16.1675c	−0.0005	−0.0004	
(0.2379)	(0.1951)	(-6.6305)	(-6.5874)	(-0.2556)	(-0.2278)	
Tang	−0.0469c	−0.0469c	−17.4129c	−17.3652c	0.0173c	0.0172c	
(-8.5597)	(-8.5623)	(-4.6525)	(-4.6392)	(6.2815)	(6.2727)	
Int	−0.0485c	−0.0484c	−17.2659c	−17.2433c	0.0197c	0.0196c	
(-4.9631)	(-4.9593)	(-2.5852)	(-2.5815)	(4.0145)	(4.0041)	
Mfee	0.0356c	0.0362c	8.7502c	8.4115b	−0.0148c	−0.0151c	
(7.3106)	(7.4275)	(2.6287)	(2.5244)	(-6.0735)	(-6.1830)	
Sep	−0.0002c	−0.0002c	0.1750c	0.1729c	0.0001c	0.0001c	
(-2.8144)	(-2.7574)	(4.6486)	(4.5952)	(2.7188)	(2.6748)	
Indep	0.0002b	0.0002b	0.1890c	0.1915c	−0.0001b	−0.0001b	
(2.5078)	(2.4286)	(3.7294)	(3.7717)	(-2.2705)	(-2.1831)	
Balance	0.0001	0.0002	0.3439	0.2673	−0.0002	−0.0002	
(0.1651)	(0.3710)	(0.7662)	(0.5942)	(-0.5046)	(-0.6936)	
Msalary	−0.0014b	−0.0013b	6.2860c	6.2584c	0.0006a	0.0006a	
(-2.0992)	(-2.0376)	(13.9091)	(13.8544)	(1.9488)	(1.9032)	
PC	−0.0015a	−0.0014	−0.4058	−0.4598	0.0007	0.0006	
(-1.7095)	(-1.6161)	(-0.6816)	(-0.7730)	(1.5366)	(1.4651)	
Constant	0.2243c	0.2246c	−165.6125c	−165.7702c	0.7599c	0.7597c	
(18.0687)	(18.0919)	(-19.5138)	(-19.5259)	(121.9479)	(121.8845)	
Industry/Year	Yes	Yes	Yes	Yes	Yes	Yes	
N	18603	18603	18603	18603	18603	18603	
adj. R2	0.2715	0.2715	0.2532	0.2531	0.7770	0.7770	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01; heteroskedasticity-robust standard errors are used.

5.6.2 Alternative independent variables

In accordance with the study conducted by Ren et al. (2023) [27], we employ a 10 % threshold to measure the number of shares owned by significant state-owned shareholders (Dsoe10). Specifically, we consider the cumulative shareholding ratio of the top ten Chinese shareholders; if this ratio exceeds 10 %, a value of 1 is assigned; otherwise, it is recorded as 0. Model (1) is now re-estimated incorporating Dsoe10 as an independent variable; the corresponding test results are presented in Table 11. After changing the independent variables, we see that the results in Column (1) indicate that Dsoe10 is significantly and negatively associated with Volatility at a 1 % level, while it is significantly and positively associated with Growth at a 5 % level. Additionally, Resilience shows a significant positive correlation with resilience at a 1 % level. The test results demonstrate that even with the use of alternative independent variables, the influence of state-owned capital on the resilience of private enterprises remains significant.Table 11 Alternative independent variables.

Table 11	Volatility	Growth	Resilience	
(1)	(2)	(3)	
Dsoe10	−0.0070c	1.7640b	0.0030c	
(-4.6660)	(2.0573)	(2.9819)	
Size	−0.0088c	10.4580c	0.0046c	
(-18.0064)	(37.8457)	(14.2311)	
Lev	0.0221c	4.0571c	−0.0123c	
(7.8832)	(8.1982)	(-6.6270)	
Odr	0.0098c	−7.1630c	−0.0052c	
(4.4903)	(-6.0649)	(-3.5842)	
Roa	0.0022b	4.6065c	−0.0015b	
(2.2548)	(6.1948)	(-2.3647)	
Cashflow	0.0015b	−0.8257a	−0.0017c	
(1.9606)	(-1.8839)	(-3.1836)	
Ato	0.0025b	14.7701c	−0.0014b	
(2.4079)	(24.8636)	(-2.0839)	
Ppe	−0.0051	−11.3224c	0.0028	
(-1.2404)	(-4.8169)	(1.0287)	
Tang	−0.0029	−19.8395c	−0.0155c	
(-0.4653)	(-5.4505)	(-3.6923)	
Int	−0.0101	−11.9805a	−0.0106	
(-0.8998)	(-1.8613)	(-1.4284)	
Mfee	−0.0000	0.0187	0.0000	
(-0.5603)	(1.0486)	(0.5115)	
Sep	−0.0002c	0.1841c	0.0001a	
(-2.7118)	(5.1022)	(1.7518)	
Indep	0.0001	0.1836c	0.0000	
(1.1583)	(3.7778)	(0.3722)	
Balance	0.0028c	−0.5640	−0.0021c	
(3.7577)	(-1.3254)	(-4.2454)	
Msalary	−0.0025c	6.1694c	0.0010a	
(-3.3764)	(14.2420)	(1.9251)	
PC	−0.0027c	−0.8169	0.0015b	
(-2.6576)	(-1.4155)	(2.2957)	
Constant	0.2766c	−150.6582c	0.5031c	
(19.5563)	(-18.4814)	(53.4714)	
Industry/Year	Yes	Yes	Yes	
N	20510	20510	20510	
adj. R2	0.2391	0.2253	0.7449	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01; heteroskedasticity-robust standard errors are used.

5.6.3 Additional control variables

In addition to the above control variables, we now add control variables to reflect the business risks of enterprises; we do this to solve the self-selection problem caused by omission of these important variables. Stock price crash risk [71] and the risk coefficient beta are chosen as additional control variables. The risk of stock price crash is due to the agency problem caused by the separation of quantitative and qualitative rights, and the management tendency to hide negative information for various reasons [72,73]. The risk coefficient beta is a relative measure of systematic risk [74] used to measure the price volatility of individual stocks or stock funds relative to the overall stock market. The higher the value of beta, the greater the volatility of the stock relative to the performance evaluation benchmark.

The results of the regression are shown in Table 12. After controlling for business risks, we see that in terms of Volatility, the coefficients of Soeshare and Dsoe in Columns (1) and Column (2) are still negative and significant at the 1 % level. For the Growth variable, Columns (3) and (4) respectively show that the coefficients of Soeshare and Dsoe are still positive and significant at the 1 % level, indicating that infusion of state-owned capital can significantly improve the long-term performance of private enterprises. In terms of Resilience, Column (5) shows that the coefficient of Soeshare is positive and significant at the 5 % level, and Column (6) shows that the coefficient of Dsoe is positive and significant at the 1 % level. As for the newly added control variables, Risk is negatively correlated with Volatility and significant at the 1 % level, positively correlated with Growth and significant at the 10 % level, and positively correlated with Resilience and significant at the 1 % level. Beta is positively correlated with Volatility and significant at the 1 % level, and negatively correlated with Growth and Resilience and significant at the 1 % level. Therefore, the selected control variables pass the robustness test, proving that the conclusions in this paper are robust, and indicating that the previously presented benchmark regression results are reliable.Table 12 Additional control variables.

Table 12	Volatility	Growth	Resilience	
(1)	(2)	(3)	(4)	(5)	(6)	
Soeshare	−0.0149c		0.0112c		0.0062c		
(-3.8217)		(3.5265)		(2.7930)		
Dsoe		−0.0038c		0.1185c		0.0015b	
	(-3.5173)		(2.7419)		(2.5199)	
Size	−0.0064c	−0.0065c	0.1910c	0.1921c	0.0031c	0.0032c	
(-15.1671)	(-15.4117)	(12.9187)	(12.9970)	(13.0158)	(13.2059)	
Lev	0.0045c	0.0045c	0.0934c	0.0942c	−0.0028c	−0.0028c	
(5.8690)	(5.8321)	(3.6262)	(3.6577)	(-6.5283)	(-6.5010)	
Odr	0.0038b	0.0037b	−0.4704c	−0.4735c	−0.0015	−0.0015	
(2.1040)	(2.0205)	(-7.6738)	(-7.7248)	(-1.4863)	(-1.4272)	
Roa	0.0037c	0.0036c	0.3204c	0.3212c	−0.0023c	−0.0023c	
(3.0089)	(2.9839)	(7.8897)	(7.9096)	(-3.3051)	(-3.2864)	
Cashflow	−0.0006	−0.0006	−0.0731c	−0.0726c	0.0000	0.0000	
(-0.9192)	(-0.9431)	(-3.1674)	(-3.1439)	(0.0936)	(0.1100)	
Ato	0.0022b	0.0022b	0.2784c	0.2789c	−0.0013b	−0.0013b	
(2.3758)	(2.4020)	(8.9855)	(9.0019)	(-2.4984)	(-2.5181)	
Ppe	−0.0024	−0.0025	0.1860	0.1871	0.0008	0.0009	
(-0.6556)	(-0.7030)	(1.4835)	(1.4920)	(0.3994)	(0.4355)	
Tang	−0.0269c	−0.0269c	−1.4612c	−1.4520c	0.0057a	0.0057a	
(-4.8242)	(-4.8397)	(-7.8083)	(-7.7603)	(1.7974)	(1.8104)	
Int	−0.0170a	−0.0170a	−0.6742b	−0.6794b	−0.0011	−0.0011	
(-1.7398)	(-1.7329)	(-1.9788)	(-1.9933)	(-0.1953)	(-0.1986)	
Mfee	−0.0000	−0.0000	−0.0043c	−0.0043c	0.0000	0.0000	
(-0.4069)	(-0.4095)	(-4.9511)	(-4.9565)	(0.5004)	(0.5020)	
Sep	−0.0001a	−0.0001a	0.0052c	0.0055c	0.0000	0.0000	
(-1.7639)	(-1.6855)	(2.7659)	(2.9000)	(0.6626)	(0.6044)	
Indep	0.0002b	0.0002b	0.0010	0.0010	−0.0001	−0.0001	
(2.1063)	(2.0315)	(0.3973)	(0.3855)	(-1.4044)	(-1.3533)	
Balance	0.0019c	0.0021c	−0.1215c	−0.1188c	−0.0013c	−0.0013c	
(2.8597)	(3.1400)	(-5.4470)	(-5.3319)	(-3.4031)	(-3.5997)	
Msalary	−0.0021c	−0.0021c	0.0599c	0.0609c	0.0007a	0.0007a	
(-3.1890)	(-3.1115)	(2.6151)	(2.6619)	(1.8568)	(1.7986)	
PC	−0.0033c	−0.0032c	0.0161	0.0151	0.0020c	0.0019c	
(-3.7553)	(-3.6500)	(0.5378)	(0.5063)	(3.9663)	(3.8894)	
Risk	−0.0088c	−0.0088c	0.0337a	0.0336a	0.0042c	0.0042c	
(-17.4196)	(-17.3787)	(1.9525)	(1.9463)	(14.8433)	(14.8133)	
Beta	0.0412c	0.0412c	−0.1375c	−0.1402c	−0.0202c	−0.0202c	
(32.5859)	(32.5786)	(-3.2387)	(-3.3011)	(-28.3359)	(-28.3321)	
Constant	0.2368c	0.2372c	−1.4419c	−1.4556c	0.5127c	0.5125c	
(19.0708)	(19.0959)	(-3.3888)	(-3.4192)	(73.1036)	(73.0349)	
Year/Industry	Yes	Yes	Yes	Yes	Yes	Yes	
N	19039	19039	19039	19039	19039	19039	
adj. R2	0.3181	0.3180	0.0921	0.0919	0.8528	0.8528	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

5.6.4 Alternative dependent variable

We now use the financial distress - MertonDD model to measure volatility. The volatile values for equity, debt, and assets in the model all reflect to some extent the financial volatility of a given enterprise; however, the interactions among these multiple variables complicate the analysis. Therefore, we employ principal component analysis to reduce dimensionality and obtain a principal factor (Volatility_N) as an alternative measure of financial volatility. Then, we replace the measure of growth potential in Model (1) with the growth rate of revenue (Growth_N) and re-estimate the model. The regression results are shown in Table 13. The results show that our conclusions remain robust after adjusting for the measurement errors of the explanatory variables.Table 13 Alternative dependent variable.

Table 13	Volatility_N	Growth_N	
(1)	(2)	(3)	(4)	
Soeshare	−0.0129c		0.0517c		
(-4.6001)		(3.8817)		
Dsoe		−0.1581c		0.6567c	
	(-4.1256)		(3.6419)	
Size	−0.1872c	−0.1877c	−0.2510c	−0.2502c	
(-13.1167)	(-13.1492)	(-3.6881)	(-3.6752)	
Lev	−0.1759b	−0.1834b	2.2182c	2.2433c	
(-2.0821)	(-2.1717)	(5.1406)	(5.1996)	
Odr	0.1511b	0.1522b	0.2796	0.2734	
(2.3674)	(2.3840)	(0.9223)	(0.9020)	
Roa	0.6353c	0.6273c	39.3126c	39.3498c	
(4.8694)	(4.8071)	(51.6505)	(51.6975)	
Cashflow	0.0076	0.0071	−0.8107c	−0.8073c	
(0.2071)	(0.1916)	(-4.5996)	(-4.5797)	
Ato	0.0146	0.0140	−0.0300	−0.0248	
(0.5413)	(0.5171)	(-0.2290)	(-0.1890)	
Ppe	−0.0551	−0.0583	−0.0082	0.0050	
(-0.4866)	(-0.5145)	(-0.0151)	(0.0093)	
Tang	−0.8355c	−0.8406c	−1.6835b	−1.6634b	
(-5.0914)	(-5.1219)	(-2.2152)	(-2.1889)	
Int	−0.8462c	−0.8285c	−0.7004	−0.7993	
(-2.6490)	(-2.5919)	(-0.4546)	(-0.5186)	
Mfee	0.0009	0.0009	−0.0038	0.0109	
(0.2366)	(0.2410)	(-0.0068)	(0.0196)	
Sep	−0.0107c	−0.0110c	0.0150a	0.0159b	
(-6.3491)	(-6.5200)	(1.9182)	(2.0347)	
Indep	0.0000	0.0000	−0.0109	−0.0107	
(0.0147)	(0.0127)	(-1.0007)	(-0.9816)	
Balance	0.0173	0.0146	0.0053	0.0140	
(0.8436)	(0.7169)	(0.0552)	(0.1469)	
Msalary	−0.0060	−0.0075	−0.2181b	−0.2112b	
(-0.2907)	(-0.3643)	(-2.2310)	(-2.1611)	
PC	−0.0175	−0.0160	0.0472	0.0432	
(-0.6593)	(-0.6042)	(0.3819)	(0.3498)	
Constant	4.9263c	4.9549c	0.6376	0.4900	
(12.9240)	(12.9942)	(0.2973)	(0.2285)	
Year/Industry	Yes	Yes	Yes	Yes	
N	15610	15610	13685	13685	
adj. R2	0.3102	0.3100	0.2051	0.2050	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

5.7 Cross-sectional tests

5.7.1 Environmental uncertainty

Environmental uncertainty refers to the rate of change or variability of the external environment of a given organization, requiring managers to adapt to the operating environment [75]. Changes in the environment cause variability in the company's business activities, ultimately leading to fluctuations in the company's operating income [76]. Referring to Peng et al. (2022) [77] and Chen et al. (2023) [76], we adopt a variable representing environmental uncertainty to represent fluctuations in a company's operating income. We use the standard deviation of operating income in the past five years to measure environmental uncertainty. For accuracy, we eliminate the stable growth portion of operating revenue; that is, we conduct an OLS regression on the data of each company in the past five years. The specific model is as follows.(Model 5) Sale = φ0 +φ1Year +ε

Sale represents operating income, while Year denotes the annual variable. We employ the median of EU as the benchmark in this study to categorize the sample into weaker and stronger groups based on environmental uncertainty; the regression outcomes are presented in Table 14. The test results show that when environment uncertainty is high, the value of Soeshare is significant for Volatility and Resilience at a level of 5 %, and significant for Growth at a level of 10 %. In the sample of firms with low environmental uncertainty, the regression coefficients of Soeshare on Growth and Resilience are not significant. The results of this regression show that the organizational resilience of private enterprises must be enhanced when environmental uncertainty is high. Therefore, infusing state-owned equity into private enterprises can improve their organizational resilience, enabling them to cope with crises despite uncertainty.Table 14 Environmental uncertainty test.

Table 14	Volatility	Growth	Resilience	
(1)
High EU	(2)
Low EU	(3)
High EU	(4)
Low EU	(5)
High EU	(6)
Low EU	
Soeshare	−0.0428b	−0.0567c	1.1559c	0.6362	0.0272b	0.0091	
(-2.4100)	(-3.3889)	(2.8357)	(1.4102)	(2.3571)	(0.8325)	
Size	−0.0066c	−0.0094c	0.1372c	0.2265c	0.0033c	0.0054c	
(-7.6341)	(-10.8998)	(6.9494)	(9.7229)	(5.8952)	(9.5742)	
Lev	0.0204c	0.0049b	−0.0386	0.2646c	−0.0117c	−0.0075c	
(6.3143)	(2.2563)	(-0.5198)	(4.5567)	(-5.5488)	(-5.3465)	
Odr	0.0084b	0.0075b	−0.3291c	0.0821	−0.0055b	−0.0042a	
(2.1397)	(1.9859)	(-3.6603)	(0.8090)	(-2.1684)	(-1.6947)	
Roa	0.0181c	0.0231a	0.3837c	−0.9763c	−0.0100c	−0.0175b	
(5.2428)	(1.7879)	(4.8518)	(-2.8028)	(-4.4698)	(-2.0853)	
Cashflow	0.0007	−0.0064c	−0.0680	0.0959	−0.0003	0.0011	
(0.3320)	(-2.5844)	(-1.4822)	(1.4387)	(-0.2358)	(0.6996)	
Ato	0.0019	0.0040b	0.2599c	0.2841c	−0.0005	−0.0018	
(1.3243)	(2.0136)	(7.7721)	(5.2464)	(-0.5552)	(-1.3692)	
Ppe	−0.0070	0.0080	0.0813	0.1448	0.0052	−0.0098b	
(-1.0304)	(1.1582)	(0.5186)	(0.7745)	(1.1625)	(-2.1801)	
Tang	−0.0154a	0.0060	−0.9630c	−1.5315c	−0.0058	−0.0117	
(-1.6745)	(0.4860)	(-4.5713)	(-4.6289)	(-0.9760)	(-1.4673)	
Int	−0.0206	−0.0004	−0.9228b	−0.4914	−0.0068	−0.0046	
(-1.0883)	(-0.0162)	(-2.1189)	(-0.8197)	(-0.5511)	(-0.3171)	
Mfee	−0.0001a	−0.0092a	−0.0039c	−0.5726c	0.0000	0.0164c	
(-1.7464)	(-1.7237)	(-5.5206)	(-3.9714)	(1.6349)	(4.7100)	
Sep	−0.0001	−0.0002a	0.0014	0.0058b	0.0001	0.0001	
(-0.9393)	(-1.8964)	(0.5809)	(2.1101)	(0.8584)	(1.5741)	
Indep	0.0002	−0.0000	−0.0004	0.0038	−0.0000	0.0001	
(1.4000)	(-0.1389)	(-0.1075)	(1.0034)	(-0.5237)	(0.8734)	
Balance	0.0008	0.0060c	−0.1536c	−0.0830b	−0.0006	−0.0034c	
(0.6230)	(4.8579)	(-5.2229)	(-2.4941)	(-0.6845)	(-4.2575)	
Msalary	−0.0013	−0.0036c	0.1007c	0.0590a	0.0005	0.0016a	
(-1.0429)	(-2.7686)	(3.4642)	(1.6971)	(0.5966)	(1.8804)	
PC	−0.0007	−0.0042c	0.0495	−0.0089	0.0010	0.0012	
(-0.4284)	(-2.5891)	(1.2954)	(-0.2059)	(0.9295)	(1.1634)	
Constant	0.2711c	0.2923c	−1.5073c	−2.0047c	0.5040c	0.4831c	
(10.9863)	(12.2206)	(-2.6613)	(-3.1085)	(31.4186)	(31.0296)	
Year/Industry	Yes	Yes	Yes	Yes	Yes	Yes	
N	9505	9769	9505	9769	9505	9769	
adj. R2	0.2569	0.2552	0.0877	0.1016	0.7498	0.7499	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

5.7.2 Regional heterogeneity test

Due to differences in policy environment, market demand, and infrastructure among different regions, the impact of reverse mixed-ownership reform on the organizational resilience of enterprises may also vary in terms of intensity and scope. In general, economic conditions and the market environment are better in the eastern and central regions of China, where the innovation ecosystem, infrastructure, and development platforms are more mature. In these regions, private enterprises are better positioned to enhance their organizational resilience through reverse mixed-ownership reform. The concentration of private enterprises in the western region is more inclined towards traditional industries and low-end manufacturing; in these regions, organizational resilience is less important. In allocating resources, these firms tend to prioritize immediate production and operational activities rather than long-term capacity and organizational resilience. Consequently, reverse mixed-ownership reform may not have a significant impact on the organizational resilience of enterprises in the western region.

According to the Beijing Macroeconomic and Social Development Basic Database, the regions of Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Guangxi, and Hainan are classified as belonging to the Eastern Region, while Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, and Hunan are classified as the Central Region. The remaining areas are categorized as the Western Region for the purposes of our regression analysis. The results of this analysis can be found in Table 15.Table 15 Regional heterogeneity test.

Table 15	Volatility	Growth	Resilience	
	(1)	(2)	(3)	(4)	(5)	(6)	
Eastern and Central	West	Eastern and Central	West	Eastern and Central	West	
Soeshare	−0.0429c	−0.0448	1.0088c	0.2225	0.0011c	0.0010	
(-3.2534)	(-1.2748)	(2.8515)	(0.2684)	(5.1464)	(1.3279)	
Size	0.0081c	−0.0069c	0.1937c	−0.0765	0.0041c	0.0037c	
(-12.8176)	(-3.2296)	(11.3800)	(-1.5224)	(10.0717)	(2.6360)	
Lev	0.0037c	0.0140a	0.0732c	0.3655b	−0.0029c	−0.0081	
(3.6527)	(1.7896)	(2.6617)	(1.9809)	(-4.4017)	(-1.5835)	
Odr	0.0068b	0.0085	−0.1239a	−0.4669a	−0.0029	−0.0053	
(2.4125)	(0.8295)	(-1.6476)	(-1.9362)	(-1.6156)	(-0.7954)	
Roa	0.0018	0.0184a	0.4230c	0.5771b	−0.0017	−0.0107	
(0.9876)	(1.7767)	(8.6171)	(2.3663)	(-1.4421)	(-1.5862)	
Cashflow	−0.0020	−0.0019	−0.1036b	0.1346	0.0002	0.0005	
(-1.2653)	(-0.3914)	(-2.4127)	(1.2053)	(0.2270)	(0.1487)	
Ato	0.0028b	0.0065	0.2669c	0.6392c	−0.0014a	−0.0062	
(2.3796)	(1.0924)	(8.3227)	(4.5688)	(-1.8285)	(-1.5927)	
Ppe	0.0029	−0.0252a	0.0680	0.6552a	−0.0037	0.0132	
(0.5618)	(-1.7736)	(0.4895)	(1.9550)	(-1.1186)	(1.4340)	
Tang	−0.0094	−0.0100	−1.2550c	−2.1139c	−0.0055	−0.0055	
(-1.2175)	(-0.3210)	(-6.0479)	(-2.8684)	(-1.1103)	(-0.2706)	
Int	−0.0165	−0.0147	−0.3020	−1.5577	−0.0051	0.0011	
(-1.1011)	(-0.3230)	(-0.7516)	(-1.4561)	(-0.5309)	(0.0367)	
Mfee	−0.0004	−0.0000	−0.1030c	−0.0051c	0.0007	0.0000	
(-0.4210)	(-1.1167)	(-4.4489)	(-6.1676)	(1.2653)	(1.1964)	
Sep	−0.0001a	−0.0002	0.0042b	0.0125a	0.0001	0.0001	
(-1.7193)	(-0.7565)	(2.0360)	(1.8231)	(1.2964)	(0.5496)	
Indep	0.0001	0.0003	0.0021	0.0154a	−0.0000	−0.0001	
(0.9218)	(0.6792)	(0.7615)	(1.6683)	(-0.2148)	(-0.4624)	
Balance	0.0036c	0.0060a	−0.1371c	0.0150	−0.0018c	−0.0019	
(3.7270)	(1.9494)	(-5.3144)	(0.2049)	(-2.9744)	(-0.9414)	
Msalary	−0.0016	−0.0042	0.0759c	0.1233a	0.0004	0.0031	
(-1.6335)	(-1.4068)	(2.9342)	(1.7355)	(0.5737)	(1.5765)	
PC	−0.0018	−0.0028	0.0044	−0.1922a	0.0009	0.0005	
(-1.4418)	(-0.6623)	(0.1349)	(-1.9313)	(1.2097)	(0.1648)	
Constant	0.2689c	0.3695c	−2.1188c	−0.4563	0.5035c	0.4581c	
(15.2000)	(6.5052)	(-4.4672)	(-0.3406)	(44.6159)	(12.3861)	
Year/Industry	Yes	Yes	Yes	Yes	Yes	Yes	
N	13372	1455	13372	1455	13372	1455	
adj. R2	0.2514	0.1904	0.0966	0.1508	0.7721	0.7793	
t statistics in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

According to Tables 15 and in the East-Central region, there is a negative correlation between Soeshare and Volatility that is significant at the 1 % level, while these variables are positively correlated with Growth and Resilience at the same significance level. However, in the Western region, the regression coefficients of Soeshare for Volatility, Growth, and Resilience are not statistically significant. The regression results indicate that the impact of state-owned capital infusion on organizational resilience of private enterprises varies significantly across regions. Specifically, this impact in the East-Central region is significantly greater than that in the West.

6 Conclusion and discussion

6.1 Conclusion

Private enterprises play a pivotal role in driving China's economic development. As fluctuations in the global economy increase, private enterprises are confronted with challenges posed by the VUCA environment, rendering their survival increasingly tenuous. Especially in recent years, the COVID-19 pandemic has had a huge impact on the Chinese economy. Despite various risks, private enterprises must enhance their organizational resilience and improve their ability to withstand risks. Government infusion of state-owned equity into private enterprises can establish a robust symbiotic relationship between them and the Chinese government, allowing them to leverage the institutional advantages of state-owned capital alongside the market advantages of private capital. This can enhance organizational resilience and improve the recovery capabilities of private enterprises in times of crisis.

This study demonstrates that infusion of state-owned capital can bolster the capacity of private enterprises to respond and recover swiftly from shocks in the areas of resources, capabilities, and relationships, thereby strengthening their resilience. In addition, state-owned equity alleviates the financing constraints of private enterprises, allowing them to expand the scale of debt financing and benefit from signaling effects, improved corporate reputation, and better access to resources. Finally, reverse mixed-ownership reform can provide private enterprises with resource advantages, bolster their adaptability and resilience during crises, and ultimately foster their development.

6.2 Theoretical implications

Our findings have the following theoretical implications. Firstly, this paper contributes to the research on the impact of shareholder heterogeneity on the organizational resilience of private enterprises. Through empirical analysis, we examine how an infusion of state-owned equity affects the organizational resilience of private enterprises in terms of resources, capabilities, and relationships. Cardinale (2021) [78] studied the effects of market liberalization and private equity entry on organizational resilience and vulnerability in state-owned enterprises. In this paper, we study the effects on organizational resilience of the entry of state-owned equity in private enterprises from the perspective of reverse mixed-ownership reform. This paper enriches our understanding of the influence of state-owned equity on the organizational resilience of private enterprises, elucidating the economic consequences of shareholder heterogeneity. Secondly, in this paper, we integrate resource-based theory and dynamic capability theory, broadening the research scope and application of both theories and enhancing their practicality. Finally, we study financing constraints as an intermediary variable to clarify the relationship between state-owned equity and organizational resilience. He et al. (2022) [20] focused on debt financing and examined how the infusion of state-owned capital into private enterprises can effectively reduce the cost of debt financing for these enterprises while simultaneously facilitating expansion of their debt financing capacity. In this paper, we use debt financing as a mediating variable to learn about the influence of state-owned enterprises on the organizational resilience of private enterprises in terms of debt financing.

6.3 Practical implications

From the perspective of shareholder heterogeneity, we provide new ideas for the improvement of the organizational resilience of private enterprises. Based on the theoretical analysis and empirical testing conducted herein, we now put forward the following policy recommendations.

Firstly, China's policy on reverse mixed-ownership reform must be actively promoted. There are problems with reverse mixed-ownership reform, such as only mixing without reforming, not reforming enough, and not being able to reap the advantages of different ownership types. Private enterprises should leverage the advantages of receiving state-owned capital to minimize losses caused by external shocks while avoiding the pitfalls related to the short-term impact of state-owned equity. In this way, resources may be effectively allocated, and firms may achieve their goals.

Secondly, reverse mixed-ownership reform should be effectively utilized to enhance the organizational resilience of private enterprises. Organizational resilience is crucial to manage risks and navigate changes; it enables enterprises to leverage the impact of receiving state-owned equity fully in order to drive firm operations and development. It empowers them to adapt to fluctuations in the external environment and acquire key competitive advantages.

Finally, the Chinese government and regulatory bodies should implement policies conducive to facilitating private enterprises in their development efforts. The report of the 20th CPC National Congress explicitly emphasized the imperative to “facilitate the development and expansion of private enterprises.” Active participation by private enterprises in mixed-ownership reform must be proactively encouraged through government initiatives such as establishing a dedicated fund for reverse mixed-ownership reform, providing tax incentives, and establishing specialized institutions to facilitate this reform at the firm level.

6.4 Research limitations and prospects

The present study investigates the influence of state-owned equity on the organizational resilience of private enterprises, while also examining the mediating role played by financing constraints. Our conclusions have theoretical and practical significance, but there are still some problems that need to be addressed. Firstly, the sample for this study comprises data for all available mixed-ownership private enterprises. Future research could focus more specifically on the nature of individual firms and investigate the influence of state-owned equity on organizational resilience across various industries. Secondly, this paper categorizes organizational resilience into three dimensions: resources, capabilities, and relationships. However, due to space limitations, it is not feasible to thoroughly examine all dimensions of organizational resilience. In the future, researchers can explore additional dimensions of organizational resilience. Finally, only the role of financing constraints as an intermediary variable is studied in this paper. In future research, other mediating variables may be found to mediate the impact of state-owned equity on the organizational resilience of private enterprises.

Data availability statement

Data associated with our study has been deposited into a publicly available repository, the CSMAR Database.

Funding

This work was supported by Shandong Province 10.13039/501100020487 Nature Science Foundation, China (ZR2023QG043 ) and Shandong Province Social Science Foundation, China (22DGLJO4 ).

CRediT authorship contribution statement

Jiruo Zhang: Writing – review & editing, Writing – original draft, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization. Longli Cai: Writing – original draft. Yu Gao: Writing – review & editing, Supervision.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Jiruo Zhang reports financial support was provided by 10.13039/501100020487 Nature Science Foundation of Shandong Province . If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

We thank our colleagues for their valuable comments, which improved the manuscript.
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