Cross-Ownership System and Innovation Efficiency from a Corporate Sustainability Perspective

Abstract

In this study, the effects of horizontal and vertical cross-ownership on innovation are examined, along with the influence of controlling parties on innovation incentives in cross-ownership firms. Since state-owned enterprises (SOEs) have better resources, the focus question of the study is to understand if SOE-controlled cross-ownership firms have stronger innovation incentives and possess higher efficiency. By using regression methods to analyze the firms listed in Chinese market, the results show that horizontal cross-ownership increases innovation incentives, but vertical cross-ownership decreases them. When firms with cross-ownership are controlled by non-SOE institutions, investments in innovation decrease. However, the environmental protection score of such a firm is higher. Lower investment and greater environmental protection indicate greater efficiency, and cross-ownership provides greater synergy in terms of sustainability. When the firms are SOEs, there is no such effect, indicating a less efficient synergy. However, SOEs attract more research visits from financial institutions. This study provides significant value for understanding the cross-ownership business system in the Chinese market. It demonstrates that the controlling party of cross-ownership can impact the efficiency of joint research and innovation, which is crucial for transitioning from a push-based, digitalization-focused Industry and Society 4.0 to a more pull-based, human-centered Industry and Society 5.0 era. The results show that policymakers should consider initiating policy revisions to further support business sustainability and change SOEs’ leading business norms to support innovation.

1. Introduction

Cross-ownership in business systems is used by the shareholders to diversify their holdings and seek firm-level cooperation to strategically optimize production, adopt new technologies, minimize the cost associated with the latest technologies and share research-related risk. Cross-ownership could play a crucial role in transitioning from Industry and Society 4.0 to 5.0, a human-centered society where economic and social development are mutually compatible through a highly integrated system. The collaboration of firms and their stakeholders could transform science, technology, and innovation from a push-based to a pull-based approach [1]. The collaborative nature of cross-ownership integration among different firms could better meet market-oriented demand and create a more efficient and inclusive, human-centered business environment. Cross-ownership could be horizontal when cross-holding occurs in the same industry between rival firms [2]. It could also be vertical, sometimes referred to as common ownership [3], which is an upper or lower stream expansion seeking profitability [4]. Cross-ownership can also increase corporate governance, reducing potential conflicts of interest and agency costs [5].

The firm’s controlling party could set the firm’s long-term goal and operation strategies [6]. Different controlling parties of firms have different cross-holding purposes and strategies [7]. Within the same industry, horizontal cross-ownership largely changes the market structure and increases strategic collusion, which is traditionally believed to decrease consumer surplus and negatively contribute to consumer welfare [8]. However, cross-ownership can also create synergy, and when synergy is dominant, cross-ownership benefits consumers and improves business sustainability [9,10]. When the social impact of cross-ownership and its influence on environmental, governance and sustainability practices are analyzed, the types of cross-ownership, ownership concentration, and the controlling party should be considered [11,12]. Since all of those factors affect a firm’s innovation incentives, heterogeneous outcomes may exist when cross-ownership and firm-controlling party interactions are analyzed.

In this study, the Chinese market is selected as the study candidate. The market has a well-developed financial system and financial institutions to support firms’ development and innovation activities. The financial market experienced rapid growth alongside the Chinese economy and contributed to capital for economic growth [13,14]. The brokerage firms help firms list on the stock exchange to fund investments and new projects. Mutual fund managers manage investors’ assets and contribute to monitoring the firm’s risk-taking and financial market behavior. Both bonds and equity mutual funds experience significant growth. The banks play the largest role among financial institutions in the Chinese market. Commercial banks require firms to take appropriate risks and to emphasize risk management. The Chinese market is led by state-owned enterprises (SOEs), resulting in an emphasis on policy guidance rather than on being perfectly market-oriented [15,16] SOE managers have a strong incentive to follow green innovation policies, but they also hope that their firms will have good profitability performance. Such incentives provide a good opportunity to compare SOEs with non-SOE-controlled cross-ownership firms to understand the cross-ownership system, its mechanism and innovative investment efficiency.

Cross-ownership indicates strong institutional economic engagement. The key questions explored in this paper are as follows: When SOEs play an important role in the Chinese market relative to firms controlled by non-SOEs, do SOEs with cross-ownership invest more in innovation, research and development, particularly in the context of green innovation emphasized by the Chinese government? Moreover, if this investment is large, is it efficient, and does it increase environmental protection and business sustainability? Furthermore, from the social recognition aspect, particularly with respect to green innovation programs that need financial support, do cross-owned firms attract the interest of financial institutions?

Our findings suggest that horizontal cross-ownership increases the firm’s research and innovation investment, whereas vertical cross-ownership reduces it. Further, when SOEs control a cross-ownership firm, they increase innovation investment, but this investment does not improve the firm’s ESG score efficiently. When a non-SOE institution controls the cross-ownership firm, investment in research is lower, but the ESG environment score is higher, indicating higher innovation and research efficiency, thereby increasing sustainability. When a non-SOE institution controls the firm, it improves the firm’s earnings quality; when an SOE controls the firm, it reduces it. However, when SOEs control a firm, vertical cross-ownership mitigates the negative effect of SOEs on earnings quality, suggesting that SOEs have resources and connections to expand their operations across upstream and downstream segments. The firm visits conducted by financial institutions indicate they have less interest in cross-ownership overall. However, when the control party is an SOE, the cross-ownership firm could attract more financial institutions than non-SOE-controlled firms in both horizontal and vertical cross-ownership. Such results demonstrate the SOEs’ connections and the support they receive from financial institutions; even non-SOE-controlled firms exhibit better environmental awareness and higher research and innovation efficiency.

This paper makes the following contributions. First, unlike past studies that focus on different degrees of cross-ownership, our analysis separates horizontal and vertical cross-ownership and explores their different effects on research incentives. Furthermore, we focus on the controlling party of the firms to discover their R&D decisions and efficiency and to explore how the controlling party aligns with the financial institutions’ priorities. We show that the market structure is not the only concern of cross-ownership, that ownership structure matters, and that the controlling party of the firm can have significant effects on innovation incentives. Such results could help policy amendments and further implement green innovation strategies.

2. Literature Review and Hypotheses

2.1. Market Structure and Impact

Firms and shareholder cross-ownership can be well explained by market structures and market power theory [17,18]. Firms and shareholders could use cross-ownership to collaborate or collude in service delivery and product pricing, reduce market competition, and form business coalitions [19]. In a weak market regulation environment, such behavior could exploit consumers and increase the firm’s profitability but weaken market competition [20]. Such monopoly behavior could reduce awareness and incentives to protect the environment and negatively contribute to business sustainability. There is evidence that cross-owners such as mutual funds tend to lower cross-ownership externalities to increase portfolio value [21]. Firms could focus on closer-term profit maximization [22]; when cross-ownership exists within the same industry, competitive pressure weakens, lowering firms’ incentives to invest in ethics, sustainability, innovation, and research—harming both consumers and the environment in the longer term [23], particularly when the degree of cross-ownership is high and when it has monopoly-like power [24].

2.2. Cooperative–Competitive Relationships

Cooperative–competitive relationships and strategies among firms can also be used to explain cross-ownership and firms’ innovation incentives [25]. In a more regulated environment, where monopoly is difficult, firms could use the cross-ownership of their shareholders to strategically cooperate and seek business synergies and increase profitability performance [26]. Some examples of this could include discovering a novel application of technology in the same industry and sharing patents. If cooperation is efficient, positive synergistic effects can positively contribute to business sustainability and social welfare; reduce research and innovation costs; and positively benefit firms, consumers and the environment [27,28,29].

Cross-ownership could reduce negative externalities and alleviate free-riding on innovation. Firms would lose the research incentive if successful research outcomes could be captured by other firms waiting for a free ride [30]. Further, cross-ownership could be used as a strategy to develop information sharing and dissemination, which not only benefits firms but also customers [31]. Much information is used as an important decision-making instrument, and by understanding customers’ needs, firms can redesign their products to better meet social demand. Moreover, firm cooperation could increase institutional shareholders’ engagement and improve monitoring, thereby enhancing corporate governance and sustainability.

2.3. Resource-Based View and Cross-Ownership

Cross-ownership, innovation impact and strategic alliances are also related to the resource-based view [32]. This view emphasizes the internal usage of a firm’s resources and increases the firm’s competitiveness through reorganization to improve the firm’s comparative advantage [33,34]. Cross-ownership allows firms to further acquire new technologies, enter new markets, and lower financial constraints or diversify their current products and services to further improve their profitability performance and sustainability [35,36]. It increases operating efficiency and reduces potential agency costs. Such cross-firm-level reorganization could be difficult for other competitors to replicate and implement.

Further, the firms could share their resources and networks. The firms could improve their market performance by receiving mutual benefits from strategic clustering and resource cooperation [37]. The firms’ cooperation in research and development is also a form of resource sharing from a human resources perspective [38], which effectively benefits firms that join the network and increases the likelihood of successful research, particularly in health and high-tech industries [39].

2.4. Cross-Ownership and RD Investment Incentives

When firms and shareholders have an interest in holding other firms’ shares, the behavior indicates positive expanding interests and is aligned with R&D incentives [40]. Firms may be able to expand the usage of their research and innovation outcomes and make the innovation internal with the cross-hold firm to prevent spillover effects [41]. Cross-ownership allows the internalization of innovation externalities and further improves business performance and sustainability [42]. Furthermore, as mentioned in earlier cooperative theory, firms could share innovation and lower research costs through cross-ownership. Economized research costs could increase a firm’s green innovation incentives, increase risk or increase R&D investments [43,44]; therefore, the firm becomes a beneficiary to consumers and the environment. Current evidence shows that cooperation and sharing could reduce information asymmetry and increase the quality of corporate governance [45]. However, the final controlling party of the firm and its cross-ownership structure could affect the level of cooperation between firms. In the Chinese market, SOEs emphasize social responsibility and obligation [46,47], and this political responsibility could increase when SOE-controlled firms have cross-ownership, increasing their investment in research and innovation.

H1a. 

Cross-ownership increases R&D investments when firms are controlled by SOEs.

H1b. 

Cross-ownership increases R&D investments when firms are controlled by non-SOE institutions.

2.5. Cross-Ownership and ESG Environment Score Efficiency

Although cross-ownership could be a market structure, it could also be used as a strategy to benefit from the firms’ social relationships [48]. The degree of cross-ownership becomes key, and firms have a positive attitude toward environmental protection when they cannot form monopolies, such as through collusion strategies [49]. SOEs with social obligations and large local connections and resources supported by the local government have large incentives to increase innovation and environmental protection to follow green policies [50,51]. However, cross-ownership of SOEs could be a strategy for expanding business instead of creating innovative synergies. Although cross-ownership between direct rivals could lead to more efficient innovation, SOE-controlled firms are less likely to implement such horizontal cross-ownership, instead favoring vertical cross-holding strategies aimed at expansion and improving reputational impact [52]. Furthermore, although SOEs are believed to make larger investments, many past studies indicate that SOEs experience more agency conflicts and a lower level of market orientation, preventing them from having higher management efficiency [53,54]. Managing innovation investment and planning may be similar, where cross-ownership may increase SOEs’ innovation investment, but high SOE-controlled cross-ownership may result in lower efficiency [55,56].

H2a. 

Cross-ownership increases environmental protection efficiency when firms are controlled by SOEs.

H2b. 

Cross-ownership increases environmental protection efficiency when firms are controlled by non-SOE institutions.

2.6. Cross-Ownership and External Recognition

Cross-ownership and innovation incentives could be affected by market recognition [57]. Any research and innovation that requires a large investment may require external support from economic policy and financial institutions [58,59]. Recent green loans and green bonds show significant recognition benefits. The green loans have a significant rate discount, and the green bond issuer enjoys the green premium by issuing the bond at lower coupon rates [60,61]. Economic policies, such as green credit and environmental taxes, motivate firms to innovate and produce green products [62,63]. SOEs have support from local governments and more vertical cross-holding aiming for profit; given that cross-ownership improves information disclosure [64], SOEs attract financial institutions seeking potentially better profitability performance. However, for the same industry, horizontal rivals engage in cross-holding; even though the aim of such cross-holding is innovation and synergy benefits, it is difficult for nondirect profit to attract the attention of financial institutions.

H3a. 

Cross-ownership increases financial institutions’ recognition when firms are controlled by SOEs.

H3b. 

Cross-ownership increases financial institutions’ recognition when firms are controlled by non-SOE institutions.

3. Data and Methodology

3.1. Data

In this study, Chinese exchange-listed firm data for between 2013 and 2024 are collected. The cross-ownership information is collected from the China Stock Market and Accounting Research Database (CSMAR), which provides data on the cross-ownership of the top ten shareholders. Firms with foreign ownership, financial firms and financial firms that cross-hold other firms are excluded from the sample. Furthermore, the firm-level financial data are collected from the Choice data stream, where financially distressed firms and firms in the finance industry are excluded because of different exchange trading rules and different accounting treatments. Any firms listed on the stock exchange after 2013 are also not included in the sample. When the controlling party disclosed in the CSMAR dataset is selected, it is possible that one firm would have more than one controlling party or no controlling party; we have multiple entries included in the sample if the firm has more than one controlling party, and the entry is left empty if the firm has no significant controlling party. The data treatments are given in

Table 1. Variable definitions.

Variable	Symbol	Variable Treatment
Research and development investment	RD	Expenditure on research and development investment divided by total asset
Environmental score	ES	Environmental score observed from CSMAR ESG data
Environmental score ranking	ER	Environmental score ranking observed from CSMAR ESG data
Goss income percentage of total revenue	gross	Gross income/total revenue
Brokerage firm research visits	brokerv	Number of brokerage firms research visits
Mutual fund research visits	fundv	Number of mutual funds research visits
Bank research visits	bankv	Number of banks research visits
Number of top ten shareholders overlap in same industry	peer	Observed from CSMAR dataset
Number of top ten shareholders overlaps in different industries	npeer	Observed from CSMAR dataset
Number of directors sent to cross-ownership firms in same industry	dpeer	Observed from CSMAR dataset
Number of directors sent to cross-ownership firms in different industries	dnpeer	Observed from CSMAR dataset
Leverage ratio	Liab	Total liability/total asset
Current ratio	Current	Current asset/current liability
Book value per a share	BPS	Equity/number of shares
An individual person controls the firm with cross-ownership	cperson	Dummy variable, observed from CSMAR dataset
An non-SOE institute controls the firm with cross-ownership	cinst	Dummy variable, observed from CSMAR dataset
A cross-ownership firm controlled by state own firms or entities.	cSOE	Dummy variable, observed from CSMAR dataset

. The descriptive statistics are presented in

Table 2. Descriptive statistics.

Statistic	N	Mean	St. Dev.	Min	Max
RD	18,155	1.186	1.754	0.000	70.156
gross	18,154	26.249	17.684	−242.115	100.000
ES	16,459	20.872	19.826	0.000	97.025
ER	16,459	1395.848	1044.980	1	5309
brokerv	18,154	2.577	4.931	0	87
fundv	18,154	2.305	5.164	0	102
bankv	18,154	0.216	0.963	0	20
peer	18,155	0.385	1.231	0	20
npeer	18,155	3.263	5.377	0	61
dpeer	18,155	0.287	0.961	0	14
dnpeer	18,155	0.576	0.904	0	8
Liab	18,155	42.860	20.919	0.797	855.657
Current	18,155	2.368	3.567	0.000	144.000
BPS	18,155	4.629	4.585	−9.193	185.565
invturn	18,155	30.183	2183.625	0.000	205,580.500
cperson	12,361	0.003	0.055	0	1
cinst	12,361	0.603	0.489	0	1
cSOE	12,361	0.394	0.489	0	1

. The controlling party has significantly fewer observations than the other numbers because many firms do not have a significant number of controlling parties. The environmental scores and rankings are also lower because 2024 data were not available when data were collected. The number of firms listed in the exchange has significantly increased in recent years, resulting in a mean environmental ranking of 1395, but the maximum number (lowest ranking) was 5309 in later years. The only data with outlier values are those for inventory turnover and leverage ratio; however, considering that their mean values are reasonable, the number of outliers is not too high, and they are only control variables, no data smoothing or winsorizing was used to regularize the data. The data treatments are presented in Table 2.

3.2. Methodologies

The first set of tests target the baseline model and Hypothesis H1, the causal relationship between direct and indirect impacts of crow ownership on R&D. Equation (1) shows such a relationship. The term “cross” includes two variables: peer cross-ownership and nonpeer cross-ownership. Afterward, the controlling party is added and interacts with horizontal cross-ownership to show the effect of the controlling party’s incentive. The relationship is shown in Equation (2). The term “Control” refers to the three variables “cperson”, “cinst”, and “csoe”, and those three variables are used in the tests.

$${RD}_{i,t}={\beta }_0+{\beta }_1{Cross}_{1,t}+{\beta }_2{Liab}_{i,t}+{\beta }_3{Current}_{i,t}+{\beta }_4{BPS}_{i,t}+{\beta }_5{Invturn}_{i,t}+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(1)

$${RD}_{i,t}={\beta }_0+{\beta }_1{Peer}_{1,t}+{\beta }_2{Control}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Control}_{i,t}\ast {Peer}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(2)

The second set of tests are used to verify the hypothesis H2. The ESG environment score and rank are subsequently used as the dependent variables to show the heterogeneity in the innovation efficiency of horizontal and vertical cross-ownership. The variable “ENV” indicates the environmental score and ranking, which are regressed as the dependent variables. Firms controlled by non-SOE institutions and SOEs are intersected with horizontal and vertical cross-ownerships, respectively, to explore the control of heterogeneous effects on the environment. The two types of firms are represented by Equations (3) and (4), respectively:

$${ENV}_{i,t}={\beta }_0+{\beta }_1{Cross}_{1,t}+{\beta }_2{cinst}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Cross}_{i,t}\ast {cinst}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(3)

$${ENV}_{i,t}={\beta }_0+{\beta }_1{Cross}_{1,t}+{\beta }_2{csoe}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Cross}_{i,t}\ast {csoe}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(4)

Moreover, to understand the interaction effects of controlling parties and cross-ownership, Equations (5) and (6) explore the impact of these on earning quality and the gross return percentage of total revenue. Note that since testing when a firm is controlled by an individual person is less interesting, here, the variable “control” only refers to the “cinst” and “cSOE” variables. Finally, to verify the hypothesis H3, the focus shifts to the interests of financial institutions on cross-ownership and when it interacts with different controlling parties. Equation (7) checks the horizontal and vertical impact of cross-ownership on how these attract research visits performed by financial institutions. The term “visit” indicates the number of visits performed by brokerage firms, mutual funds, and banks. Equations (8) and (9) show the interaction of institutions with non-SOEs and SOEs to understand the heterogeneities of the impact when firms are controlled by institutions with different backgrounds.

$${gross}_{i,t}={\beta }_0+{\beta }_1{peer}_{1,t}+{\beta }_2{Control}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Cross}_{i,t}\ast {peer}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(5)

$${gross}_{i,t}={\beta }_0+{\beta }_{1}n{peer}_{1,t}+{\beta }_2{Control}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Cross}_{i,t}\ast {npeer}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(6)

$${visit}_{i,t}={\beta }_0+{\beta }_1{Cross}_{1,t}+{\beta }_2{Liab}_{i,t}+{\beta }_3{Current}_{i,t}+{\beta }_4{BPS}_{i,t}+{\beta }_5{Invturn}_{i,t}+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(7)

$${visit}_{i,t}={\beta }_0+{\beta }_1{peer}_{1,t}+{\beta }_2{Control}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Control}_{i,t}\ast {peer}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(8)

$${visit}_{i,t}={\beta }_0+{\beta }_{1}n{peer}_{1,t}+{\beta }_2{Control}_{i,t}+{\beta }_3{Liab}_{i,t}+{\beta }_4{Current}_{i,t}+{\beta }_5{BPS}_{i,t}+{\beta }_6{Invturn}_{i,t}+{\beta }_7\left[{Control}_{i,t}\ast {npeer}_{i,t}\right]+\sum IND+\sum Year+{\epsilon }_{i,t}$$

(9)

The 2SLS tests and the PSM methods are used to show robustness and lower endogeneity concerns. The number of directors relates to both cross-ownerships. Since the sending director does not directly determine the firm’s R&D, it forms an exogenous condition. PSM is conducted by matching the return on equity (ROE) and firm size, which can affect the R&D incentive.

4. Results

The baseline results in Columns (1) and (2) of

Table 3. Cross-ownership and R&D.

	Dependent Variable
	RD
	(1)	(2)	(3)	(4)
peer	0.072 ***	0.018 **
	(0.008)	(0.008)
npeer			−0.006 ***	−0.006 ***
			(0.002)	(0.002)
Liab	−0.003 ***	−0.002 ***	−0.002 ***	−0.002 ***
	(0.001)	(0.001)	(0.001)	(0.001)
Current	−0.005	−0.011 ***	−0.005	−0.011 ***
	(0.003)	(0.003)	(0.003)	(0.003)
BPS	0.0001	0.006 **	0.001	0.006 ***
	(0.002)	(0.002)	(0.002)	(0.002)
Invturn	−0.00000	−0.00000	0.00000	−0.00000
	(0.00000)	(0.00000)	(0.00000)	(0.00000)
Constant	0.102 **	0.269 ***	0.112 **	0.271 ***
	(0.046)	(0.053)	(0.046)	(0.053)
IND	N	Y	N	Y
YEAR	Y	Y	Y	Y
Observations	18,155	18,155	18,155	18,155
R2	0.373	0.434	0.371	0.434
Adjusted R2	0.372	0.432	0.370	0.432
Residual Std. Error	1.390 (df = 18,138)	1.322 (df = 18,109)	1.392 (df = 18,138)	1.321 (df = 18,109)
F Statistic	673.733 *** (df = 16; 18,138)	308.140 *** (df = 45; 18,109)	667.384 *** (df = 16; 18,138)	308.348 *** (df = 45; 18,109)

Note: ***, ** denote statistical significance at the 1%, 5% levels, respectively, and standard errors are shown in parentheses.

show that when firms have cross-ownership in the same industry, it triggers them to increase their research and development investment to seek further innovation and firm competitiveness. However, Columns (3) and (4) show that when a firm owns significant shares of upper- or lower- stream firms rather than firms in the same industry, diversification reduces firm-level innovation investment. These results reflect that cross-ownership reflects a firm’s competition and development attitude. Diversification seeks expansion and avoids peer competition, but same-industry cross-ownership seeks synergy, market share and cooperation strategies.

The ownership of a firm could have a significant effect on its cross-ownership and innovation strategies. In

Table 4. Control and R&D.

	Dependent Variable
	RD
	(1)	(2)	(3)
peer	0.034 ***	0.053 ***	0.019
	(0.009)	(0.012)	(0.012)
cperson	0.153
	(0.199)
cinst		0.058 **
		(0.025)
cSOE			−0.061 **
			(0.025)
liab	−0.001 *	−0.001	−0.001
	(0.001)	(0.001)	(0.001)
Current	−0.008 **	−0.008 **	−0.008 **
	(0.004)	(0.004)	(0.004)
BPS	0.008 ***	0.009 ***	0.009 ***
	(0.002)	(0.002)	(0.002)
Invturn	−0.00000	−0.00000	−0.00000
	(0.00000)	(0.00000)	(0.00000)
Peer*cperson	−0.155
	(0.544)
Peer*cinst		−0.034 **
		(0.017)
Peer*cSOE			0.035 **
			(0.017)
Constant	0.172 ***	0.122 *	0.179 ***
	(0.059)	(0.063)	(0.059)
IND	Y	Y	Y
YEAR	Y	Y	Y
Observations	12,361	12,361	12,361
R2	0.467	0.467	0.467
Adjusted R2	0.465	0.465	0.465
Residual Std. Error (df = 12,314)	1.186	1.186	1.186
F Statistic (df = 46; 12,314)	234.244 ***	234.513 ***	234.533 ***

Note: ***, ** and * denote statistical significance at the 1%, 5% and 10% levels, respectively, and standard errors are shown in parentheses.

, further analysis of the controlling party reveals that when the major controlling party is an institution, this reduces investments in innovation; the results are shown by the interaction term in Column (2). However, state-owned enterprises show greater investment in innovation when they have higher cross-ownership in the same industry.

Table 5. ESG-E non-SOEs.

	Dependent Variable
	ES	ER	ES	ER
	(1)	(2)	(3)	(4)
peer	0.322 *	−26.152 **
	(0.174)	(10.191)
npeer			0.001	−2.326
			(0.037)	(2.171)
cinst	−1.962 ***	147.242 ***	−2.220 ***	145.034 ***
	(0.338)	(19.805)	(0.380)	(22.260)
Liab	0.007	−0.602	0.007	−0.629
	(0.009)	(0.499)	(0.009)	(0.500)
Current	−0.170 ***	11.275 ***	−0.172 ***	11.456 ***
	(0.047)	(2.741)	(0.047)	(2.746)
BPS	0.154 ***	−13.701 ***	0.162 ***	−14.232 ***
	(0.032)	(1.859)	(0.032)	(1.862)
Invturn	−0.00004	0.012	−0.00005	0.013
	(0.0003)	(0.020)	(0.0003)	(0.020)
Peer*cinst	0.399 *	−30.286 **
	(0.239)	(13.995)
npeer*cinst			0.104 *	−1.453
			(0.055)	(3.238)
Constant	8.797 ***	1024.353 ***	8.857 ***	1031.468 ***
	(0.847)	(49.619)	(0.855)	(50.127)
IND	Y	Y	Y	Y
YEAR	Y	Y	Y	Y
Observations	11,253	11,253	11,253	11,253
R2	0.439	0.260	0.438	0.257
Adjusted R2	0.436	0.257	0.436	0.254
Residual Std. Error (df = 11,207)	15.258	893.324	15.267	894.673
F Statistic (df = 45; 11,207)	194.600 ***	87.363 ***	194.034 ***	86.349 ***

Note: ***, ** and * denote statistical significance at the 1%, 5% and 10% levels, respectively, and standard errors are shown in parentheses.

and

Table 6. ESG-E SOEs.

	Dependent Variable
	ES	ER	ES	ER
	(1)	(2)	(3)	(4)
peer	0.705 ***	−56.328 ***
	(0.171)	(9.997)
npeer			0.093 **	−3.631
			(0.042)	(2.445)
cSOE	1.660 ***	−143.956 ***	1.833 ***	−140.840 ***
	(0.339)	(19.858)	(0.381)	(22.336)
Liab	0.007	−0.593	0.008	−0.621
	(0.009)	(0.500)	(0.009)	(0.501)
Current	−0.170 ***	11.253 ***	−0.172 ***	11.436 ***
	(0.047)	(2.742)	(0.047)	(2.746)
BPS	0.157 ***	−13.736 ***	0.165 ***	−14.267 ***
	(0.032)	(1.860)	(0.032)	(1.863)
Invturn	−0.00004	0.012	−0.0001	0.013
	(0.0003)	(0.020)	(0.0003)	(0.020)
peer*cSOE	−0.342	29.841 **
	(0.239)	(14.000)
npeer*cSOE			−0.075	1.160
			(0.055)	(3.240)
Constant	6.869 ***	1169.268 ***	6.706 ***	1173.853 ***
	(0.782)	(45.768)	(0.786)	(46.047)
IND	Y	Y	Y	Y
YEAR	Y	Y	Y	Y
Observations	11,253	11,253	11,253	11,253
R2	0.438	0.260	0.437	0.257
Adjusted R2	0.436	0.257	0.435	0.254
Residual Std. Error (df = 11,207)	15.264	893.432	15.275	894.785
F Statistic (df = 45; 11,207)	194.215 ***	87.282 ***	193.597 ***	86.265 ***

Note: ***, ** denote statistical significance at the 1%, 5% levels, respectively, and standard errors are shown in parentheses.

show the effects of cross-ownership on the environment, social factors and governance (ESG). These results help us further understand innovation efficiency. The results in Table 5 show that when the controlling party is an institution, cross-ownership generally increases ESG. However, the results in Table 6 show that when SOEs are the controlling party, cross-ownership has an insignificant but negative effect on the ESG score and significantly increases the ESG ranking (a higher number of rankings is negative). These results are surprising since the previous results show that SOEs are motivated to invest in research and development when same-industry cross-ownership is high.

Table 7. Earning quality, horizontal cross-ownership, and controlling party.

	Dependent Variable
	Gross
	(1)	(2)	(3)
peer	−0.411 ***	−0.049	−0.171
	(0.081)	(0.130)	(0.130)
cinst		3.935 ***
		(0.268)
cSOE			−4.057 ***
			(0.268)
Liab	−0.203 ***	−0.183 ***	−0.182 ***
	(0.005)	(0.007)	(0.007)
Current	0.114 ***	0.008	0.007
	(0.030)	(0.038)	(0.038)
BPS	0.393 ***	0.480 ***	0.481 ***
	(0.022)	(0.024)	(0.024)
Invturn	−0.0001 *	−0.0001 *	−0.0001 *
	(0.00004)	(0.00004)	(0.00004)
peer*cinst		−0.118
		(0.180)
peer*cSOE			0.137
			(0.180)
Constant	30.544 ***	26.399 ***	30.277 ***
	(0.517)	(0.677)	(0.626)
IND	Y	Y	Y
YEAR	Y	Y	Y
Observations	18,154	12,361	12,361
R2	0.474	0.498	0.499
Adjusted R2	0.473	0.496	0.497
Residual Std. Error	12.842 (df = 18,108)	12.670 (df = 12,314)	12.663 (df = 12,314)
F Statistic	362.536 *** (df = 45; 18,108)	265.649 *** (df = 46; 12,314)	266.213 *** (df = 46; 12,314)

Note: *** and * denote statistical significance at the 1% and 10% levels, respectively, and standard errors are shown in parentheses.

and

Table 8. Earning quality, vertical cross-ownership and controlling party.

	Dependent Variable
	Gross
	(1)	(2)	(3)
npeer	−0.201 ***	−0.080 ***	−0.210 ***
	(0.018)	(0.028)	(0.032)
cinst		4.102 ***
		(0.300)
cSOE			−4.247 ***
			(0.301)
Liab	−0.201 ***	−0.181 ***	−0.180 ***
	(0.005)	(0.007)	(0.007)
Current	0.118 ***	0.009	0.009
	(0.030)	(0.038)	(0.038)
BPS	0.384 ***	0.473 ***	0.474 ***
	(0.022)	(0.024)	(0.024)
Invturn	−0.0001 *	−0.0001 *	−0.0001 *
	(0.00004)	(0.00004)	(0.00004)
npeer*cinst		−0.128 ***
		(0.042)
npeer*cSOE			0.136 ***
			(0.042)
Constant	30.725 ***	26.495 ***	30.546 ***
	(0.516)	(0.681)	(0.628)
IND	Y	Y	Y
YEAR	Y	Y	Y
Observations	18,154	12,361	12,361
R2	0.477	0.500	0.501
Adjusted R2	0.475	0.498	0.499
Residual Std. Error	12.809 (df = 18,108)	12.646 (df = 12,314)	12.639 (df = 12,314)
F Statistic	366.556 *** (df = 45; 18,108)	267.712 *** (df = 46; 12,314)	268.270 *** (df = 46; 12,314)

Note: *** and * denote statistical significance at the 1% and 10% levels, respectively, and standard errors are shown in parentheses.

report the results of earning quality as the indicator of the earning performance of cross-ownership. In both cases (Column (2) in both tables), we see that when the controlling party is an institution, it increases earning performance, and in Column (3) of both tables, SOEs reduce earning performance. When cross-ownership is horizontal in the same industry, the interactions in Table 7 have no significant effect, regardless of the controlling party. However, in the results of vertical cross-ownership in Table 8, the cross-ownership of different industries and institutional ownership significantly negatively contribute to earnings performance, but SOEs have a positive interactive effect on earnings. These results demonstrate that SOEs can better manage different resources because of their government background, making it easier for SOEs to make versatile profits by diversifying their business.

The last focus is on market reaction to cross-ownership.

Table 9. External focus and horizontal cross-ownership.

	Dependent Variable
	Brokerv	Fundv	Bankv
	(1)	(2)	(3)
peer	−0.121 ***	−0.132 ***	−0.015 **
	(0.031)	(0.032)	(0.006)
Liab	−0.012 ***	−0.011 ***	0.001 ***
	(0.002)	(0.002)	(0.0004)
Current	−0.020 *	−0.011	−0.002
	(0.011)	(0.012)	(0.002)
BPS	0.117 ***	0.111 ***	0.022 ***
	(0.008)	(0.008)	(0.002)
Invturn	−0.00002	−0.00001	−0.00000
	(0.00002)	(0.00002)	(0.00000)
Constant	3.233 ***	3.275 ***	−0.013
	(0.194)	(0.203)	(0.038)
IND	Y	Y	Y
YEAR	Y	Y	Y
Observations	18,154	18,154	18,154
R2	0.044	0.047	0.030
Adjusted R2	0.042	0.045	0.028
Residual Std. Error (df = 18,108)	4.827	5.047	0.949
F Statistic (df = 45; 18,108)	18.562 ***	19.876 ***	12.614 ***

Note: ***, ** and * denote statistical significance at the 1%, 5% and 10% levels, respectively, and standard errors are shown in parentheses.

and

Table 10. External focus, horizontal cross-ownership and controlling party.

	Dependent Variable
	Brokerev	Fundv	Bankv	Brokerv	Fundv	Bankv
	(1)	(2)	(3)	(4)	(5)	(6)
peer	0.129 ***	0.099 **	0.005	−0.130 ***	−0.119 **	−0.005
	(0.047)	(0.049)	(0.010)	(0.047)	(0.049)	(0.010)
cinst	0.515 ***	0.527 ***	0.035 *
	(0.096)	(0.101)	(0.020)
cSOE				−0.561 ***	−0.555 ***	−0.034 *
				(0.096)	(0.101)	(0.020)
Liab	−0.012 ***	−0.010 ***	0.0004	−0.012 ***	−0.010 ***	0.0004
	(0.002)	(0.003)	(0.0005)	(0.002)	(0.003)	(0.0005)
Current	−0.015	0.008	−0.0002	−0.015	0.008	−0.0002
	(0.014)	(0.014)	(0.003)	(0.014)	(0.014)	(0.003)
BPS	0.085 ***	0.088 ***	0.016 ***	0.085 ***	0.088 ***	0.016 ***
	(0.009)	(0.009)	(0.002)	(0.009)	(0.009)	(0.002)
Invturn	−0.00001	−0.00001	−0.00000	−0.00001	−0.00001	−0.00000
	(0.00002)	(0.00002)	(0.00000)	(0.00002)	(0.00002)	(0.00000)
peer*cinst	−0.257 ***	−0.216 ***	−0.010
	(0.065)	(0.068)	(0.013)
peer*cSOE				0.265 ***	0.221 ***	0.010
				(0.065)	(0.068)	(0.013)
Constant	2.499 ***	2.492 ***	−0.001	3.007 ***	3.012 ***	0.033
	(0.244)	(0.255)	(0.050)	(0.225)	(0.236)	(0.046)
IND	Y	Y	Y	Y	Y	Y
YEAR	Y	Y	Y	Y	Y	Y
Observations	12,361	12,361	12,361	12,361	12,361	12,361
R2	0.043	0.043	0.030	0.043	0.043	0.030
Adjusted R2	0.039	0.039	0.027	0.040	0.039	0.027
Residual Std. Error (df = 12,314)	4.560	4.765	0.931	4.559	4.765	0.931
F Statistic (df = 46; 12,314)	11.955 ***	11.917 ***	8.356 ***	12.068 ***	11.981 ***	8.354 ***

Note: ***, ** and * denote statistical significance at the 1%, 5% and 10% levels, respectively, and standard errors are shown in parentheses.

report the brokerage, mutual fund and bank firm visits and use the visits as an indication of the market interest in the firm and a reaction to cross-ownership. The results in Table 9 show that all the financial institutions are negatively interested in horizontal cross-ownership. The results in Table 10 show that institutionally controlled firms attract more visits, but SOEs attract fewer visits. However, an institutionally controlled firm with the same industry cross-ownership has a decreased number of visits, whereas an SOE-controlled firm has an increase in visits by financial institutions when same industry cross-ownership occurs.

Furthermore, we investigated the interest of financial institutions in visiting firms with vertical cross-ownership. The results are shown in

Table 11. External focus and vertical cross-ownership.

	Dependent Variable
	Brokerv	Fundv	Bankv
	(1)	(2)	(3)
npeer	−0.073 ***	−0.072 ***	−0.009 ***
	(0.007)	(0.007)	(0.001)
Liab	−0.011 ***	−0.011 ***	0.001 ***
	(0.002)	(0.002)	(0.0004)
Current	−0.018	−0.010	−0.002
	(0.011)	(0.012)	(0.002)
BPS	0.114 ***	0.109 ***	0.022 ***
	(0.008)	(0.008)	(0.002)
Invturn	−0.00002	−0.00001	−0.00000
	(0.00002)	(0.00002)	(0.00000)
Constant	3.295 ***	3.338 ***	−0.005
	(0.194)	(0.203)	(0.038)
IND	Y	Y	Y
YEAR	Y	Y	Y
Observations	18,154	18,154	18,154
R2	0.049	0.051	0.033
Adjusted R2	0.047	0.049	0.030
Residual Std. Error (df = 18,108)	4.814	5.036	0.948
F Statistic (df = 45; 18,108)	20.827 ***	21.820 ***	13.532 ***

Note: *** denote statistical significance at the 1% levels, respectively, and standard errors are shown in parentheses.

and

Table 12. External focus, vertical cooperation and controlling party.

	Dependent Variable
	Brokerv	Fundv	Bankv	Brokerv	Fundv	Bankv
	(1)	(2)	(3)	(4)	(5)	(6)
npeer	−0.020 *	−0.015	−0.004 *	−0.089 ***	−0.092 ***	−0.012 ***
	(0.010)	(0.011)	(0.002)	(0.011)	(0.012)	(0.002)
cinst	0.538 ***	0.605 ***	0.046 **
	(0.108)	(0.113)	(0.022)
cSOE				−0.594 ***	−0.640 ***	−0.045 **
				(0.108)	(0.113)	(0.022)
Liab	−0.012 ***	−0.010 ***	0.001	−0.011 ***	−0.009 ***	0.001
	(0.002)	(0.003)	(0.0005)	(0.002)	(0.003)	(0.0005)
Current	−0.015	0.009	−0.0001	−0.015	0.009	−0.0001
	(0.014)	(0.014)	(0.003)	(0.014)	(0.014)	(0.003)
BPS	0.082 ***	0.086 ***	0.016 ***	0.083 ***	0.086 ***	0.016 ***
	(0.008)	(0.009)	(0.002)	(0.008)	(0.009)	(0.002)
Invturn	−0.00001	−0.00001	−0.00000	−0.00001	−0.00001	−0.00000
	(0.00002)	(0.00002)	(0.00000)	(0.00002)	(0.00002)	(0.00000)
npeer*cinst	−0.068 ***	−0.076 ***	−0.009 ***
	(0.015)	(0.016)	(0.003)
npeer*cSOE				0.072 ***	0.079 ***	0.008 ***
				(0.015)	(0.016)	(0.003)
Constant	2.566 ***	2.524 ***	0.003	3.100 ***	3.123 ***	0.048
	(0.245)	(0.256)	(0.050)	(0.226)	(0.236)	(0.046)
IND	Y	Y	Y	Y	Y	Y
YEAR	Y	Y	Y	Y	Y	Y
Observations	12,361	12,361	12,361	12,361	12,361	12,361
R2	0.046	0.046	0.033	0.047	0.047	0.033
Adjusted R2	0.043	0.043	0.029	0.043	0.043	0.029
Residual Std. Error (df = 12,314)	4.551	4.756	0.930	4.550	4.755	0.930
F Statistic (df = 46; 12,314)	12.997 ***	13.039 ***	9.014 ***	13.115 ***	13.110 ***	9.010 ***

Note: ***, ** and * denote statistical significance at the 1%, 5% and 10% levels, respectively, and standard errors are shown in parentheses.

. The results are similar to those for horizontal cross-ownership. SOEs attract increased visits when they have greater cross-ownership, but cross-ownership decreases the interest of financial institutions if the firm is controlled by regular institutions. Such differences in interest are attributed to background differences, and SOEs are believed to succeed more easily because of support from the local government.

Table 13. Instrumental Variable.

	Dependent Variable
	Peer	RD		ES	ER	ES	ER
	OLS	Instrumental		Instrumental	Instrumental	Instrumental	Instrumental
		Variable		Variable	Variable	Variable	Variable
	(1)	(2)	(3)	(4)	(5)	(6)	(7)
dpeer	0.651 ***
	(0.008)
peer		0.091 ***	0.106 **	1.187 ***	−72.982 ***	2.734 ***	−163.300 ***
		(0.026)	(0.054)	(0.371)	(21.735)	(0.768)	(44.884)
cinst		0.082 ***		−1.434 ***	118.639 ***
		(0.029)		(0.393)	(23.031)
cSOE			−0.035			2.244 ***	−174.786 ***
			(0.030)			(0.404)	(23.608)
Liab		−0.001 *	−0.001 *	0.006	−0.558	0.006	−0.512
		(0.001)	(0.001)	(0.009)	(0.500)	(0.009)	(0.504)
Current		−0.008 **	−0.007 **	−0.170 ***	11.283 ***	−0.165 ***	10.995 ***
		(0.004)	(0.004)	(0.047)	(2.744)	(0.047)	(2.758)
BPS		0.008 ***	0.008 ***	0.149 ***	−13.413 ***	0.148 ***	−13.266 ***
		(0.002)	(0.002)	(0.032)	(1.865)	(0.032)	(1.879)
Invturn		−0.00000	−0.00000	−0.00003	0.011	−0.00001	0.010
		(0.00000)	(0.00000)	(0.0003)	(0.020)	(0.0003)	(0.020)
peer*cinst		−0.070 **		−0.433	14.749
		(0.027)		(0.396)	(23.171)
peer*cSOE			−0.048			−2.290 ***	132.558 ***
			(0.053)			(0.758)	(44.299)
Constant	0.198 ***	0.106 *	0.172 ***	8.459 ***	1042.670 ***	6.721 ***	1177.075 ***
	(0.008)	(0.064)	(0.059)	(0.858)	(50.229)	(0.789)	(46.111)
IND		Y	Y	Y	Y	Y	Y
Year		Y	Y	Y	Y	Y	Y
Observations	18,155	12,361	12,361	11,253	11,253	11,253	11,253
R2	0.258	0.467	0.465	0.437	0.258	0.431	0.252
Adjusted R2	0.258	0.465	0.463	0.435	0.255	0.429	0.249
Residual Std. Error	1.061 (df = 18,153)	1.187 (df = 12,314)	1.189 (df = 12,314)	15.275 (df = 11,207)	894.165 (df = 11,207)	15.360 (df = 11,207)	897.985 (df = 11,207)
F Statistic	6314.640 *** (df = 1; 18,153)

Note: ***, ** and * denote statistical significance at the 1%, 5% and 10% levels, respectively, and standard errors are shown in parentheses.

and

Table 14. PSM, external focus horizontal cross-corporate and controlling party.

	Dependent Variable
	Brokerv	Fundv	Brokerv	Fundv
	(1)	(2)	(3)	(4)
peer	0.130 ***	0.100 **	−0.127 ***	−0.116 **
	(0.047)	(0.049)	(0.047)	(0.049)
cinst	0.523 ***	0.536 ***
	(0.096)	(0.101)
cSOE			−0.569 ***	−0.564 ***
			(0.097)	(0.101)
Liab	−0.012 ***	−0.010 ***	−0.012 ***	−0.010 ***
	(0.002)	(0.003)	(0.002)	(0.003)
Current	−0.015	0.008	−0.015	0.008
	(0.014)	(0.014)	(0.014)	(0.014)
BPS	0.087 ***	0.090 ***	0.087 ***	0.090 ***
	(0.009)	(0.009)	(0.009)	(0.009)
Invturn	−0.00001	−0.00001	−0.00001	−0.00001
	(0.00002)	(0.00002)	(0.00002)	(0.00002)
peer*cinst	−0.255 ***	−0.215 ***
	(0.065)	(0.068)
peer*cSOE			0.262 ***	0.220 ***
			(0.065)	(0.068)
Constant	2.486 ***	2.481 ***	3.001 ***	3.009 ***
	(0.244)	(0.255)	(0.225)	(0.236)
IND	Y	Y	Y	Y
YEAR	Y	Y	Y	Y
Observations	12,339	12,339	12,339	12,339
R2	0.043	0.043	0.043	0.043
Adjusted R2	0.039	0.039	0.040	0.039
Residual Std. Error (df = 12,292)	4.555	4.761	4.554	4.760
F Statistic (df = 46; 12,292)	12.006 ***	11.932 ***	12.122 ***	11.997 ***

Note: ***, ** denote statistical significance at the 1%, 5% levels, respectively, and standard errors are shown in parentheses.

use the instrumental-variable 2-stage least squares (2SLS) and the propensity score matching (PSM) methods to demonstrate the reliability of the results. In Table 13, whether sending a director to a horizontal cross-owned firm is used as the instrumental variable to measure the impact of cross-ownership on R&D and environmental protection. The first column shows that director sending is a qualified instrument variable. The interactive terms in Columns (2) and (3) show that the institutionally controlled cross-ownership firms have lower R&D investment than SOE-controlled cross-ownership firms do; however, the environmental score and ranking from Columns (4) to (7) show the opposite results. SOEs cross-ownership firms with larger R&D investments but suffer lower scores and rankings. Table 14 shows the results of financial institution visits when the firm size and ROE are matched. The interactive terms show that when the firm is controlled by institutions, horizontal cross-ownership decreases visits, but when it is controlled by SOEs, horizontal cross-ownership increases visits. Both the 2SLS and the PSM results are similar to our original results above and are reliable. The results and the hypotheses validation are summarized in

Table 15. Summary of findings.

Hypotheses	Validation
H1a. Cross-ownership increases R&D investments when firms are controlled by SOEs.	Support
H1b. Cross-ownership increases R&D investments when firms are controlled by non-SOE institutions.	Reject
H2a. Cross-ownership increases environmental protection efficiency when firms are controlled by SOEs.	Reject
H2b. Cross-ownership increases environmental protection efficiency when firms are controlled by non-SOE institutions.	Support
H3a. Cross-ownership increases financial institutions’ recognition when firms are controlled by SOEs.	Support
H3b. Cross-ownership increases financial institutions’ recognition when firms are controlled by non-SOE institutions.	Reject

.

When a firm is controlled by non-SOE institutions with horizontal cross-ownership, the innovation cost decreases significantly, but the level of environmental protection significantly increases. Such results show synergy from firm cooperation in horizontal cross-ownership. The results do not support the traditional market-structure view, which points to mergers as increasing the market power of firms, resulting in higher prices with more monopoly power and reduced innovative incentives [65,66].

The results are in line with cost-reduction, strategic cooperation, and social welfare improvement theories [67]. Cross-ownership could benefit society and improve sustainability by offering a wider range of products and greater efficiency. The results show that SOEs experience lower corporate governance quality under double-principal agency problems. However, the non-SOEs are more market-oriented and make research and development decisions to maximize investment efficiency by utilizing limited resources. Cross-ownership provides a platform for participating non-SOEs to share and exchange their knowledge with other firms with common shareholders, contributing to more efficient research and development [68] and significantly increasing their ESG scores with less investment. Cross-ownership, particularly when it occurs horizontally, also provides insight into monitoring by the more engaged common shareholder with superior industrial knowledge [69], thereby significantly improving corporate governance.

Furthermore, the results show that, even though there is an improvement in environmental protection, financial institutions show little interest in such cooperation. This constraint reflects the financial institution’s focus on earning performance and quality. SOEs could attract financial institutions’ visits because they have good relationships with financial institutions and local government support. Additionally, SOEs that participate in vertical cross-ownership show significant improvements in earnings quality, even if environmental protection is worsened. Such outcomes call for policy revision to support non-SOE institutions when their cross-firm cooperation benefits the environment. Additionally, even though this research does not reveal features such as collusion with greater market power, which usually reduces innovation incentives, it is important to adopt regulations to prevent such cases. These policies should also encourage financial institutions to focus more on ESG and corporate governance rather than merely the financial and earning status of the firms.

5. Conclusions

In this study, we use empirical data from the Chinese market to demonstrate that horizontal cross-ownership could increase innovation incentives. SOEs prefer to increase their investment in innovation, but their efficiency is low. Non-SOEs with horizontal cross-ownership have lower R&D investments; however, they have higher environmental scores and rankings. Such outcomes indicate that cross-ownership increases firm research sharing and decreases research costs among non-SOEs. Furthermore, SOEs with cross-ownership show better earnings performance and quality and successfully attract the interest of financial institutions. However, non-SOEs with environmental protection improvements, cost reduction and higher cooperation synergy are ignored, and financial institutions show little interest. Financial support is needed for green innovation, and such outcomes call for policy revisions.

The current research has several limitations. Firstly, it does not cover the common ownership owned by mutual funds. There are academic arguments questioning mutual funds’ levels of engagement in corporate and strategic management; their common ownership across rivals in the same industry may significantly affect industry behavior and, in turn, the individual firms’ decisions. Further, internal monitoring, supervision, and firm-level comparative advantage are not well considered. Some evidence suggests that cultural diversity can improve innovation, suggesting that cross-geographical cross-ownership is more efficient, allowing firms to leverage their comparative advantages.

Future research could conduct individual projects to understand the impact of horizontal cross-firm ownership held by mutual funds by designing a model to estimate the level of collective power across industries and to measure whether higher collective power and cross-ownership increase mutual funds’ engagement and whether such engagement improves business sustainability. From a cultural diversification perspective, the research could test whether cross-ownership by more internationally oriented firms significantly increases research and development efficiency.