Can Urban Greening Construction Improve the Corporate Preventive Environmental Investment? Evidence from China

Abstract

Preventive environmental investment can enhance corporate environmental pollution management at the source and facilitate green transformation development. As a form of government of green investment behavior, urban greening construction exhibits a “demonstration effect” and “innovation effect” on corporate preventive environmental investment. To investigate this, the present study utilizes Chinese listed company and city-level data from 2011 to 2020 to analyze the influence, mechanism, and heterogeneity of urban greening construction on corporate environmental preventive investment. The findings indicate that urban green construction significantly encourages corporate preventive environmental investments by increasing enterprises’ willingness to participate in environmental regulation and advancing their green technology innovation. Furthermore, the environmental investment impact of urban greening construction exhibits considerable regional and corporate heterogeneity. Specifically, this effect is more pronounced in areas with lower marketability degrees and environmental regulation levels. It plays a more substantial role for state-owned enterprises and enterprises with lower agency costs.

1. Introduction

In recent years, environmental pollution has emerged as a growing menace to human health and economic growth. It is also widely acknowledged that fostering a green, low-carbon economy is the essential path to resolving the conflict between economic development and the resource environment. Enhancing corporate preventive environmental investment and promoting enterprises’ green transformation are crucial to achieving a country’s successful green growth [1]. Nonetheless, under financing constraints, the expansion of corporate environmental investment will inevitably displace production investment, and the private benefits of corporate environmental investment fall short of the personal costs, resulting in a situation where corporate environmental investment is inadequate [2]. To mitigate the market failure of enterprise environmental investment and boost preventive environmental investment, it is necessary to advance the establishment of a more rational incentive and restraint system.

China has consistently emphasized the significance of urban greening construction. In 1992, the Ministry of Housing and Urban-Rural Development initiated the issuance of the National Garden City selection criteria, motivating local governments to enhance urban greening efforts. In 2012, the report presented at the 18th National Congress of the Communist Party of China (NPC) introduced the concept of building a beautiful China for the first time, concentrating on reinforcing the central government’s evaluation and assessment of local governments’ environmental protection performance. Notably, the degree of urban green construction serves as a crucial indicator in assessing local government environmental performance. In general, the environmental performance objectives set by the government inevitably influence the environmental performance objectives of enterprises, leading to changes in their environmental regulatory behaviors [3]. Concurrently, urban greening construction represents a vital public environmental investment activity undertaken by the government, and an increase in local government environmental investment undoubtedly encourages enterprises to enhance their green innovation levels to satisfy government environmental investment requirements [4]. This situation raises an inevitable question: Can urban greening construction boost enterprises’ preventive environmental investment by altering their environmental supervision behavior and strengthening their green technology innovation? Regrettably, existing research on the spillover effect of urban greening construction primarily focuses on the macro level [5,6,7], with no literature systematically addressing the impact of urban greening construction on corporate preventive environmental investment to date. This gap is incongruent with the reality that major cities worldwide are increasingly prioritizing environmental governance.

The extant literature on the determinants of firms’ environmental investments can be categorized into two dimensions. The first dimension emphasizes internal factors, encompassing corporate environmental and social responsibility [8], attributes of top executives [9,10], and the enhancement of internal control and governance structures [11,12,13]. Nevertheless, these internal drivers often struggle to genuinely address the cost compensation and capital dilemma encountered by firms when increasing environmental protection investments. The second dimension concentrates on external factors, comprising various forms of compulsory environmental regulations [14,15,16] and incentive-based environmental regulations [17]. However, during the enforcement of mandatory environmental regulations, not only might there be incomplete execution, data fabrication [18], collusion between the government and enterprises, and other transgressions that undermine the policy’s efficacy, but it may also unreasonably exacerbate the production burden on firms, as evidenced by the “constraint hypothesis” and “pollution haven hypothesis”. Moreover, the majority of incentive-based environmental measures primarily target end-of-pipe pollution control. Such “pollution first, treatment later” approaches are scarcely effective in enhancing firms’ proactive environmental investments.

More significantly, disparities in ownership and agency costs emerge as crucial factors influencing the internal governance of Chinese enterprises. Concurrently, the degree of marketability and the level of environmental regulation independently determine the societal incentive for enterprise environmental protection and the intensity of government-imposed penalties for enterprise environmental pollution. Thus, the question arises: will regional marketability degree, environmental regulation level, ownership, and agency cost differences further impact the relationship between urban greening construction and enterprises’ preventive environmental investment?

The overarching objective of this paper is to investigate the relationship between urban greening construction and the environmental preventive investment of enterprises. Three specific aims are pursued: first, to analyze whether urban greening construction fosters environmental preventive investment of enterprises; second, to delve into the inner mechanism or influence path of urban green construction affecting enterprises’ environmental preventive investment; and third, to explore the heterogeneity in the aforementioned relations. The remainder of this paper is structured as follows: Section 2 encompasses a literature review and hypothesis development. Section 3 details the methodology and data. Section 4 presents the empirical results and analysis. Section 5 involves mechanism verification. Section 6 addresses heterogeneity analysis, and the final section concludes the study.

The primary contributions of this paper include the following: First, considering the substantial differences in the role and nature between corporate preventive and governance environmental investment, enterprises’ environmental investment is divided into preventive environmental investment and governance environmental investment, and an econometric model is constructed to test the factors influencing preventive environmental investment. Second, the urban greening construction level is incorporated into the research framework of corporate environmental investment, assessing the promotional effect of urban greening on enterprises’ preventive environmental investment, analyzing the mechanism of this promotional effect, and suggesting that urban greening construction can enhance corporate preventive environmental investment through the “demonstration effect” and “innovation effect.” Third, the heterogeneity effect of urban greening construction on corporate preventive environmental investment is appraised from the perspectives of regional marketability degree, environmental regulation level, corporate ownership difference, and agency costs difference, providing a reference for enhancing the level of urban greening construction and guiding enterprises to increase preventive environmental investment.

2. Literature Review and Hypothesis Presentation

2.1. Typical Facts

Cities exhibiting green coverage surpassing the median of the sample are classified as high-level green areas, while the remaining are categorized as low-level green areas. Subsequently, the association between urban greening construction and corporate preventive environmental investment is illustrated through total comparison and mean comparison, with the results displayed in Figure 1.

Figure 1 reflects the fluctuating trend of corporate preventive environmental protection investment under diverse urban greening levels. Upon comparison, it is observed that the magnitude and growth rate of the corporate preventive environmental investment in cities with elevated greening levels are considerably larger than those in regions with lower afforestation levels. Consequently, it is evident that as the urban greening construction level advances, the scope of enterprise preventive environmental investment will also be enhanced.

To further clarify whether a significant difference exists in the change of corporate preventive environmental investment under the grouping condition of urban greening level, a t-test was conducted based on this grouping variable. The results are presented in

Table 1. t-test results.

Indicators	High Green Level	Low Green Level	t
Preventive environmental investments	44.8606	27.5581	6.0424 ***

Note: *** represents 10% significance level.

.

The test results in Table 1 indicate that the mean value of corporate preventive environmental investment in regions with higher greening levels is significantly larger than that in regions with lower greening levels at the significance level of 1%. Thus, the following hypotheses is posited:

Hypothesis 1. 

Urban greening construction will promote corporate preventive environmental investment.

2.2. Analysis Based on “Demonstration Effect”

The urban greening investment signifies the local government’s commitment to participating in environmental governance. Under the government-led economic development model characterized by Chinese features, enterprise policy adherence can effectively bolster its capacity to communicate and negotiate with the government to acquire additional external resources for support [19]. As a result, urban greening aids in fostering enterprises’ willingness to partake in environmental investment. In addition, the “demonstration effect” of urban greening construction will also motivate more potential customers and investors to become “Green customers” and “Green investors”; this market shift has prompted companies to increasingly display their environmental image by actively engaging in environmental regulation, augmenting environmental investment to produce green products that satisfy the public’s growing environmental demands, and subsequently expanding the market share of enterprises [20]. Additionally, as urban greening construction continually improves, the public’s tolerance for negative external production behaviors will persistently decrease, and they will pay closer attention to the environmental protection information of the enterprises within their jurisdiction. To evade the increased social pressure and litigation risk, enterprises will also opt to take action to assume environmental responsibility [21]. The enhancement of proactivity in participating in environmental regulation will significantly boost the execution of corporate environmental investment, rapidly propelling the corporation to implement cleaner production through talent introduction, innovation promotion, production process improvement, and environmental equipment acquisition [22]. This will undoubtedly elevate corporate preventive environmental investment. Accordingly, the following hypothesis is put forth:

Hypothesis 2. 

Urban greening can promote corporate preventive environmental investment by improving the enterprise’s positiveness to participate in environmental regulation.

2.3. Analysis Based on Innovation Effect

Skilled professionals demonstrate a preference for working in areas with favorable environmental quality [23,24], and urban greening initiatives effectively enhance air quality. Consequently, elevated urban greening levels contribute to an increase in the influx of advanced labor factors and an improvement in urban human capital density. In addition, urban greening initiatives represent a significant non-monetary welfare, which can bolster a city’s comparative advantages in geographical environmental conditions, enticing domestic and international enterprises to establish operations within the city, thereby facilitating the enhancement of regional industrial agglomeration levels. Furthermore, the intra-industry spillover effect, inter-industry spillover effect, and competitive effect of urban human capital positively influence technological innovation within enterprises [25], and the augmentation of agglomeration levels will further intensify industrial correlations, decrease production expenses, yield higher returns, and expedite innovation [26]. Concurrently, urban greening initiatives heighten environmental awareness among the public, media, and enterprises, prompting polluting enterprises to undertake green technology innovation through three aspects: demand, stakeholder resource connections, and external supervisory pressures [27]. Studies by Oliva et al. [28], Singh et al. [29], and other researchers have demonstrated that green technology innovation assists enterprises in enhancing production and resource consumption patterns while reducing detrimental environmental behaviors, finally increasing the scope of corporate preventive environmental investments. Thus, the following hypothesis is proposed:

Hypothesis 3. 

Urban greening can increase corporate preventive environmental investment through promoting enterprise green technology innovation.

3. Methodology and Data

3.1. Model Specifications

To test H1, we specify the following empirical model:

$$PE{I}_{it}={\alpha }_0+{\alpha }_{1}CG{C}_{ct}+{{\displaystyle \sum }}^{ }{\alpha }_{\mathrm{h}}{\mathrm{Con}}_{it}+v_i+v_t+{\epsilon }_{ict}$$

(1)

i, c, and t represent the company, city, and year, respectively. Concurrently, city c is matched based on the administrative region of company i. $PE{I}_{it}$ represents the corporate preventive environmental investment, while $CG{C}_{ct}$ signifies the green coverage rate of urban built-up areas in t years, reflecting the overall urban greening level. The coefficient ${\alpha }_1$reflects the impact of urban greening construction level on the preventive environmental protection investment of regional enterprises. A significantly positive coefficient ${\alpha }_1$ suggests that urban greening construction can substantially enhance the scale of the preventive environmental protection investment of enterprises in the region. ${\mathrm{Con}}_{it}$ represents the control variables at the city and enterprise level; $v_i$ and $v_t$ are the firm and year fixed effects, respectively; and ${\epsilon }_{ict}$ is the random error term. To control for potential inter-group correlations, all empirical analyses below are aggregated at the industry level.

To test H2 and H3, the following empirical model is specified:

$$Mi{d}_{it}={\gamma }_0+{\gamma }_{1}CG{C}_{ct}+{{\displaystyle \sum }}^{ }{\sigma }_{\mathrm{m}}{\mathrm{Con}}_{it}+v_i+v_t+{\pi }_{ict}$$

(2)

$$PE{I}_{it}={\delta }_0+{\delta }_{1}Mid+{{\displaystyle \sum }}^{ }{\rho }_n{\mathrm{Con}}_{it}+v_i+v_t+{\mu }_{ict}$$

(3)

$$PE{I}_{it}={\partial }_0+{\partial }_{1}CG{C}_{ct}+{\partial }_{2}Mid+{{\displaystyle \sum }}^{ }{\vartheta }_d{\mathrm{Con}}_{it}+v_i+v_t+{ϵ}_{ict}$$

(4)

In this context, the method proposed by Baron and Kenny [30] is employed, taking the positiveness of enterprises to participate in environmental regulation and enterprise green technology innovation as the intermediary variables and constructing mediating effect models to test the influence mechanism. Firstly, the intermediary variables of the enterprises’ positiveness to participate in environmental regulation and enterprise green technology innovation are considered as the interpreted variables, and the $CG{C}_{ct}$ is utilized as a core explanatory variable to establish the empirical Model $\left(2\right)$. Secondly, the $PE{I}_{it}$ is taken as the explained variable, and the intermediary variables of the positiveness of enterprises to participate in environmental regulation and enterprise green technology innovation are employed as the explanatory variables to establish an empirical Model $\left(3\right)$. Finally, the corporate preventive environmental investment, the green coverage rate of urban built-up areas, and the intermediary variables are incorporated into the regression Model $\left(4\right)$ to observe whether the intermediary effect is valid. If coefficients ${\alpha }_1$,${\gamma }_1$, and ${\delta }_1$, are significant, and the coefficient ${\partial }_1$ either becomes smaller than ${\alpha }_1$ or becomes less significant, the mediating effect exists.

3.2. Variable Definitions

Dependent variables: Preventive environmental investment (PEI) encompasses environmental investments aimed at avoiding or preventing pollution at its source, thereby impacting the production process of an enterprise. This includes investments in clean production technology, environmental protection facilities purchases, and more. The primary data source for this variable is the “Construction in progress” accounts related to environmental protection investment found in financial statement notes.

Independent variable: Urban greening construction primarily utilizes the green coverage rate of urban built-up areas (CGC) as an index. This rate is calculated as the ratio of the green area within urban built-up regions to the administrative territorial entity area.

Mediating variables: (1) An enterprise’s proactivity in participating in environmental regulation (SP) is primarily indicated by whether the enterprise has obtained ISO 14001 [31] environmental certification. If firm i passes the certification in t year and the annual audit is normal, SP is assigned a value of 1; otherwise, it is assigned a value of 0. This is due to the ISO 14001 environmental management system being established by the International Organization for Standardization and audited by third-party independent auditors. It is widely accepted by Chinese industrial enterprises, making it a suitable indicator of Chinese enterprises’ willingness to engage in voluntary environmental regulation. (2) Enterprise green technology innovation (GPA) is primarily represented by the sum of green patent applications plus one logarithm. The data for this variable are primarily sourced from the Chinese Patent State Intellectual Property Office retrieval system and Chinese Research Data Services (CNRDS).

Other variables: The following control variables were selected based on factors influencing enterprise environmental investment: the growth rate of urban per capita gross domestic product (PGDP), reflecting regional economic development levels; industry gross profit rate (IGP), indicating the degree of industry competition; corporate size (Size), measured by the natural logarithm of total corporate assets; corporate growth (Growth), expressed by the growth rate of corporate operating revenue; return on net assets (ROE), controlling for profitability; capital intensity (GAP), calculated as the ratio of net fixed assets to total assets at the end of the period; and capital structure (ADR), represented as the ratio of total liabilities to total assets at the end of the period. Additionally, during the analysis of heterogeneity, samples were classified according to urban marketability level (MCP), environmental regulation intensity (ER), ownership nature (OWN), and agency costs (AC). Following the methodology of Sun et al. [32], 2010 was taken as the base period, and the marketability index of different cities was calculated from six aspects. Cities above the median sample were classified as having a high marketability group, while others were classified as having a low marketability group. Referring to the design of Tang et al. [33], the environmental regulation index of different cities was calculated from five aspects. Cities above the median sample were classified as having a high environmental regulation group, while others were classified as having a low environmental regulation group. For ownership, state-owned enterprises were assigned a value of 1, while other enterprises were assigned a value of 0. Finally, companies above the median sample were classified as having high agency costs, while others were classified as low agency costs companies.

3.3. Sample and Data

The analysis utilizes listed company and city-level data from 2011 to 2020. The data processing involves the following steps: (1) exclusion of financial listed companies, such as banks, insurance companies, securities, and futures companies with unique financial statement rules; (2) removal of ST, * ST with extreme outliers. Ultimately, balanced panel data for 4649 companies were obtained, totaling 46,490 observations. The primary data source is the China Stock Market & Accounting Research Database (CSMAR).

Table 2. Descriptive statistics.

Variables	Definition	Mean	S.D.	Min	Max
PEI	Corporate preventive environmental investment (LN)	1.9956	5.5063	0	27.0636
CGC	Green coverage rate of urban built-up area (%)	42.0028	4.3665	2	95.25
Size	Corporate total assets (LN)	21.5180	1.5855	14.4872	28.6364
Growth	(current period operating revenue—prior period operating revenue)/ prior period operating revenue (%)	24.8932	728.499	−96.197	330.294
ROE	Return on net assets (%)	10.5531	104.6315	−96.062	95.7079
GAP	capital intensity (%)	0.2107	0.1612	0.0001	0.9711
ADR	capital structure (%)	43.5422	94.6924	0.708	99.8124
PGDP	The growth rate of urban GDP per capital (%)	0.0731	0.0791	−0.4096	0.6007
IGP	Industry gross profit rate (%)	31.8986	5.4905	15.48	60.72
SP	=1 for a firm get certification from ISO; =0 otherwise	0.1649	0.3711	0	1
GPA	Corporate green patent applications plus one logarithm	0.2079	0.6171	0	6.8742
MCP	=1 for a city with high marketability level; =0 otherwise	11.7626	2.3994	4.9596	19.6944
ER	=1 for a city with high regulation; =0 otherwise	25.0812	10.4157	0.5455	68.232
OWN	=1 if a firm is state owned; =0 otherwise	0.3283	0.4696	0	1
AC	=1 for a firm with high agency costs; =0 otherwise	0.5663	0.4956	0	1

displays the summary statistics of the main variables.

4. Empirical Results and Analysis

4.1. Baseline Regression Analysis

Table 3. Baseline estimation results.

Variables	PEI
	(1)	(2)	(3)
CGC	0.0116 ** (0.0056)	0.0149 ** (0.0071)	0.0168 *** (0.0064)
Size		0.7218 *** (0.1609)	0.7450 *** (0.1623)
Growth		−0.00005 (0.00004)	−0.00005 (0.00004)
ROE		−0.0001 *** (0.00002)	−0.0002 *** (0.00002)
GAP		1.7195 ** (0.7029)	1.7053 ** (0.7319)
ADR		−0.0055 (0.0033)	−0.0053 (0.0034)
IGP			0.0315 (0.0507)
PGDP			0.3500 (0.3995)
_cons	0.7861 *** (0.2824)	−14.4786 *** (3.5872)	−16.0521 *** (2.8666)
Firm FE	Yes	Yes	Yes
Year FE	Yes	Yes	Yes
City FE	Yes	Yes	Yes
Observations	46040	37466	36924
R2	0.0255	0.1620	0.1538

Note: The empirical results are clustered at the industry level, and the robust standard errors are reported in parentheses, *** and ** represent different significance levels, indicating p < 0.01, p < 0.05 respectively.

reveals the fundamental results of urban greening construction and corporate preventive environmental investment. Columns (1)–(3) demonstrate the influence of urban greening construction on corporate preventive environmental investment by progressively incorporating control variables. The coefficients of urban greening construction (CGC) in Columns (1)–(3) are significantly positive, as shown in Table 3. These results suggest that as urban greening construction progresses, corporate preventive environmental investment increases, indicating that urban greening construction positively impacts the scale of corporate preventive environmental investment. Accordingly, H1 holds.

Regarding the control variables based on corporate characteristics, the regression coefficients of corporate size (Size) and capital intensity (GAP) in Columns (1)–(3) are significantly positive, suggesting that these variables positively affect corporate preventive environmental investment.

4.2. Other Robustness Tests

To further enhance the reliability of the baseline regression results, several robustness tests were conducted: (1) Excluding samples: To ascertain the stability of urban greening construction’s role in promoting corporate environmental investment across different research periods, the entire sample from 2011 to 2020 was replaced with sub-samples from 2017 to 2020. (2) Modifying estimations: Firm FE, City FE, and Industry clustering do not control the influence of unpredictable factors that change over time from the enterprise, city, and industry on corporate environmental investment. Therefore, “Firm*Year”, “City*Year”, and “Industry*Year” are generated and regressed to mitigate the potential issue of missing variables. (3) Eliminating extreme values: This test was performed due to the possibility of individual extreme values in the sample. To eliminate this interference, 5% and 10% tail reductions for all continuous variables were conducted, followed by regression according to the model. (4) Incorporating additional control variables: Variables affecting the estimation results at the city and firm levels, including public environmental attention (ADP) and equity concentration (EC), were added to the original ones.

Table 4. Other robustness estimation results.

Variables	PEI
	Excluding Samples	Changing Estimations	Eliminating Extreme Values		Adding Control Variables
	2017–2020	2016–2020	5%	10%	ADP	EC
	(1)	(2)	(3)	(4)	(5)	(6)
CGC	0.0426 ** (0.0185)	0.0160 *** (0.0060)	0.0230 ** (0.0093)	0.0173 * (0.0093)	0.0153 ** (0.0064)	0.0209 *** (0.0072)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
ADP					0.7457 ** (0.3055)
EC						−0.0116 ** (0.0048)
_cons	−24.5566 *** (4.8138)	−296.301 *** (156.3819)	−16.4185 *** (2.7427)	−15.1862 *** (2.3181)	−15.9965 *** (2.8646)	−16.9755 *** (3.3130)
Firm FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes	Yes	Yes
Firm∗ear		Yes
City∗year		Yes
Industry∗Year		Yes
Observations	17,559	36,924	36,924	36,924	36,924	31345
R2	0.1242	0.0347	0.1617	0.1640	0.1512	0.1400

Note: The empirical results are clustered at the industry level, and the robust standard errors are reported in parentheses, ***, **, and * represent different significance levels, indicating p < 0.01, p < 0.05, and p < 0.1, respectively.

lists the regression results after conducting these tests, with the main findings remaining fundamentally unchanged.

4.3. Endogenous Tests

Notwithstanding that a low possibility of inverse causality exists between the green coverage rate at the city level and preventive environmental protection at the enterprise level, potential endogenous problems, such as missing variables and common influencing factors, remain. To further address these issues, two instrumental variables are adopted, and the two-stage least squares method is employed to test the estimates. (1) IV1: annual average precipitation (YRQ). On one hand, annual average precipitation (YRQ) as an instrumental variable satisfies the relevance condition. Abundant precipitation aids plant cultivation and maintenance, reduces greening costs, and increases urban greening areas. On the other hand, annual average precipitation (YRQ) as an instrumental variable satisfies the exogenous condition: as a natural phenomenon variable, annual average precipitation is unrelated to economic and social factors and does not affect corporate production, confirming its exogeneity. (2) IV2: the area ratio of roads and bridges (RBR). The rationale behind this selection is that roads, bridges, and urban greening are all components of the government’s public investment. An increase in investment in roads and bridges may crowd out part of the investment in greening under the control of the total amount of public expenditure, and road and bridge greening are more complex, potentially occupying part of the greening area. In addition, little evidence supports the notion that road and bridge area is directly linked to corporate preventive environmental investments, ensuring that the variable satisfies the relevance and exogeneity criteria for instrumental variables. The estimation results in

Table 5. Endogenous estimation results.

Variables	IV1:(YRQ)		IV2:(RBR)
	First-Stage	Second-Stage	First-Stage	Second-Stage
	CGC	PEI	CGC	PEI
	(1)	(2)	(4)	(5)
IV1	128.4075 ***
IV2			1.7468 ***
CGC		0.2133 ***		0.2566 ***
Control variables	Yes	Yes	Yes	Yes
_cons	41.5929 ***	−24.3368 ***	38.8717 ***	−25.9932 ***
Firm FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes
F value	16.08		15.74
Observations	36,924	36,924	36,924	36,924
R2	0.0531	0.0915	0.0683	0.0788

Note: The empirical results are clustered at the industry level, and the robust standard errors are reported in parentheses. *** represents 10% significance level.

demonstrate that the conclusion that urban greening construction promotes corporate preventive environment investment is robust.

5. Mechanism Verification

The basic regression results in Table 3 indicate that the coefficient of urban greening construction on corporate preventive environmental investment is significantly positive, meeting the precondition of the intermediary effect test. Consequently, this section concentrates on testing the intermediary effect Models (2) to (4).

5.1. Mediating Test of Demonstration Effect

The results of urban greening through the mediation of the enterprise’s willingness to participate in environmental regulation are presented in

Table 6. The mediating test results of the demonstration effect.

Variables	No Adding Control Variables			Adding Control Variables
	SP	PEI	PEI	SP	PEI	PEI
	(1)	(2)	(3)	(4)	(5)	(6)
SP		0.4946 *** (0.0696)	0.5011 *** (0.0721)		0.4080 *** (0.0774)	0.4073 *** (0.0774)
CGC	0.0121 *** (0.0033)		0.0115 ** (0.0055)	0.0079 *** (0.0033)		0.0166 ** (0.0064)
Control variables	No	No	No	Yes	Yes	Yes
_cons	−1.8959 *** (0.1436)	1.2284 *** (0.0993)	0.7289 *** (0.2836)	−4.6981 *** (0.3601)	−15.1958 *** (2.7040)	−15.8950 *** (2.8312)
Firm FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes	Yes	Yes
Observations	30,155	46,490	46,040	29,374	36,924	36,924
R2		0.0268	0.0266		0.1641	0.1624

Note: The results in Columns (1) and (4) are not clustered; others are clustered at the industry level. The standard errors are reported in parentheses in Columns (1) and (4), and the robust standard errors are reported in parentheses in other columns. ***, ** represent different significance levels, indicating p < 0.01, p < 0.05, respectively.

. Columns (1) to (3) exclude control variables, while Columns (4) to (6) include them.

The regression coefficients of urban greening construction (CGC) in Columns (1) and (4) are 0.0121 and 0.0079, respectively, and both are significantly positive at the 1% significance level. This suggests that urban greening notably enhances the willingness of enterprises to participate in environmental regulation. In Columns (2) and (5), the coefficients of enterprise positiveness to participate in environmental regulation (SP) on corporate preventive environmental investment (PEI) are 0.4946 and 0.4080, respectively. Both are significantly positive at the 1% significance level, demonstrating that the improvement in enterprise participation in environmental regulation positiveness leads to an increase in corporate preventive environmental investment. In Columns (3) and (6), both the urban greening (CGC) and enterprise positiveness participants in environmental regulation (SP) variables are incorporated into the regression model. The coefficients of urban greening construction are 0.0115 and 0.0166, which are relatively smaller than those when the intermediate variable is not included in the model (in Table 3). This confirms the presence of the mediating effect of the enterprise’s positiveness to participate in environmental regulation and indicates that urban greening construction boosts corporate preventive environmental investment by promoting enterprise positiveness to participate in environmental regulation. The rationale behind this finding is as follows: the urban greening behavior of local governments effectively guides the decision-making of enterprises’ environmental investment and significantly enhances the enterprise’s positivity to participate in environmental regulation. In turn, enterprises’ environmental responsibility can enable corporations to attract talent, improve production processes, acquire environmental equipment, etc., thereby increasing the scale of corporate preventive environmental investment.

5.2. Mediating Test of Innovation Effect

Another pathway through which urban greening construction can impact corporate preventive environmental investment is enterprise green technology innovation. The regression results of this mediating effect are displayed in Columns (1) to (6) of

Table 7. The mediating test results of innovation effect.

Variables	No Adding Control Variables			Adding Control Variables
	GPA	PEI	PEI	GPA	PEI	PEI
	(1)	(2)	(3)	(4)	(5)	(6)
GPA		0.3389 *** (0.0800)	0.3329 *** (0.0818)		0.2677 *** (0.0709)	0.2668 *** (0.0707)
CGC	0.0014 ** (0.0007)		0.0111 ** (0.0054)	0.0015 ** (0.0006)		0.0164 ** (0.0063)
Control variables	No	No	No	Yes	Yes	Yes
_cons	0.0928 *** (0.0317)	1.2350 *** (0.1045)	0.7552 *** (0.2820)	−1.4102 *** (0.2860)	−14.9849 *** (2.6971)	−15.6759 *** (2.8191)
Firm FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes	Yes	Yes
Observations	46,040	46,490	46,040	36,924	36,924	36,924
R2	0.0349	0.0675	0.0596	0.1130	0.1661	0.1643

Note: The empirical results are clustered at the industry level, and the robust standard errors are reported in parentheses. ***, ** represent different significance levels, indicating p < 0.01, p < 0.05,, respectively.

. Among them, Columns (1) to (3) do not include control variables, while Columns (4) to (6) do.

The regression coefficients of greening construction (CGC) in Columns (1) and (4) are 0.0014 and 0.0015, respectively, and are statistically significant. This implies that urban greening construction substantially enhances the level of enterprise green technology innovation. In Columns (2) and (5), the regression coefficients of enterprise green technology innovation (GPA) on corporate preventive environmental investment (PEI) are 0.3389 and 0.2677, respectively. Both are significantly positive at the 1% significance level, signifying that the improvement in enterprise green technology innovation can elevate corporate preventive environmental investment. In Columns (3) and (6), both the urban greening construction (CGC) and enterprise green technology innovation (GPA) variables are incorporated into the regression model. The regression coefficients of urban greening are 0.0111 and 0.0164, respectively, which are relatively smaller than those when the intermediate variable is not included in the model (in Table 3). This verifies the presence of the mediating effect of enterprise green technology innovation and suggests that urban greening construction can enhance corporate preventive environmental investment by promoting the level of enterprise green technology innovation.

6. Heterogeneity Analysis

6.1. Regression Analysis of Differences in Marketability Level

In regions with a higher degree of marketability, the congestion of government expenditure is more pronounced [34], potentially crowding out funds allocated for urban greening and subsequently affecting the promotional effect of urban greening construction on corporate preventive environmental investment. Consequently, this section will explore the varying impacts of greening construction on corporate preventive environmental investment in the context of different marketability levels.

Cities are categorized into high-marketability and low-marketability groups, with the results of the group test displayed in Columns (1) and (2) of

Table 8. Effect heterogeneity based on regional characteristics.

Variables	PEI
	High Marketability	Low Marketability	High Regulations	Low Regulations
	(1)	(2)	(3)	(4)
CGC	−0.0243 *** (0.0086)	0.0431 *** (0.0101)	0.0115 (0.0103)	0.0192 *** (0.0070)
Control variables	Yes	Yes	Yes	Yes
_cons	−16.2595 *** (3.0010)	−14.9988 *** (3.8894)	−16.9071 *** (2.9802)	−16.0976 *** (5.5412)
Firm FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes
Observations	19,800	17,124	19,827	17,097
R2	0.1507	0.1125	0.1377	0.1163

Note: The empirical results are clustered at the industry level, and the robust standard errors are reported in parentheses, *** represents 10% significance level.

. The findings indicate that in the high-marketability group, urban greening construction exhibited a significantly negative impact on corporate preventive environmental investment. Conversely, in the low-marketability group, urban greening construction demonstrated a significantly positive effect on corporate preventive environmental investment. Moreover, the absolute value of the regression coefficient of urban greening in the low-marketability group surpasses that of the high-marketability group. This comparison implies that the corporate preventive environmental effect of urban greening construction is considerably more substantial in areas with low marketization. A plausible explanation for this phenomenon is that in regions with a higher degree of marketability, government intervention expenditure is reduced, while the development of the non-state-owned economy is elevated [35]. As a result, local governments’ urban greening investment is relatively limited, and enterprises’ environmental investment willingness is generally low. In such circumstances, guided by local government greening investment behavior, enterprises are more inclined to adopt increased preventive environmental investment in areas with lower marketability.

6.2. Regression Analysis of Differences in Environmental Regulations

When the intensity of regional environmental regulations falls within the enterprise tolerance range, enterprises will enhance their environmental investment, either to comply with legal requirements or as a means to “show goodwill” to the government [36]. However, when the cost of adhering to regional environmental regulations becomes excessively high, it negatively impacts enterprise environmental investment [37,38]. Therefore, the variation in regional environmental regulation intensity may influence the promotional effect of urban greening on corporate preventive environmental investment.

Based on the aforementioned analysis, the samples were divided into high and low environmental regulation cities. Subsequently, the heterogeneity of corporate preventive environmental investment behavior was compared due to differences in regional environmental regulation intensity, according to the firms’ locations. The test results can be observed in Columns (3) and (4) of Table 8. The findings reveal that in the high environmental regulations group, the coefficient of urban greening construction is not significant. Conversely, the coefficient of urban greening construction is significant, indicating that urban greening in promoting corporate preventive environmental investment is more pronounced in areas with low-intensity environmental regulation. The probable explanation is that urban greening, as a public environmental governance behavior, and low environmental regulation, as an appropriate environmental protection policy, form a joint policy in promoting corporate preventive environmental investment, which substantially alleviates the market failure in enterprise environmental investment.

6.3. Regression Analysis of Differences in Ownership

Significant differences are present between state-owned and non-state-owned enterprises in goal pursuit, financial support, and government intervention. Consequently, when faced with different types of policy impacts, enterprises with varying ownership forms will exhibit distinct behaviors to cope with them [39]. Generally, state-owned enterprises prioritize the maximization of social welfare, while non-state-owned enterprises tend to pursue profit maximization. In light of this perspective, under the backdrop of a local government prioritizing urban greening construction, state-owned enterprises with strong political connections will have greater incentives to make environmental investments to enhance regional environmental performance than non-state-owned enterprises [40,41].

In this light, the companies were categorized into a state-owned group and a non-state-owned group to examine the behavioral differences. The group test results can be found in Columns (1) and (2) of

Table 9. Effect heterogeneity based on firm characteristics.

Variables	PEI
	State-Owned	Non-State-Owned	High Agency Costs	Low Agency Costs
	(1)	(2)	(3)	(4)
CGC	0.0348 * (0.0184)	0.0078 (0.0113)	0.0131 (0.0099)	0.0207 * (0.0103)
Control variables	Yes	Yes	Yes	Yes
_cons	−17.1580 * (8.7042)	−17.4486 *** (4.9863)	−12.98 *** (2.8613)	−24.6393 *** (4.6180)
Firm FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes
Observations	9493	19,881	18,278	18,646
R2	0.0906	0.0820	0.0963	0.1407

Note: The empirical results are clustered at the industry level, and the robust standard errors are reported in parentheses. *** and * represent different significance levels, indicating p < 0.01 and p < 0.1, respectively.

. Column (1) in Table 9 considers state-owned enterprises as the research sample; within it, the coefficient of urban greening construction is statistically significant. This result suggests that urban greening construction behavior induced preventive environmental investment in state-owned enterprises. Column (2) in Table 9 presents the results with non-state-owned enterprises as the research sample. However, the coefficient of urban greening is not significant. This finding suggests that urban greening construction cannot enhance non-state-owned enterprises’ preventive environmental investment. The rationale is that non-state-owned enterprises generally possess relatively low political connections and are not sensitive to non-mandatory environmental policies. In this context, increasing political correlation holds considerable importance for improving the promoting effect of urban greening on corporate preventive environmental investment.

6.4. Regression Analysis of Differences in Agency Costs

The extant literature demonstrates a close relationship between agency conflict issues and a company’s investment decisions. Richardson [42] established a positive correlation between agency costs and over-investment. Lin et al. [43] further suggested that higher agency costs lead to greater over-investment in production and R&D, which inevitably crowds out enterprises’ environmental investments. The primary reason for this discrepancy lies in the differing perceptions of green investment held by shareholders and management. Shareholders view environmental investment as a means to cultivate competitive advantages, reduce environmental compliance costs, and contribute positively to the long-term development of enterprises. Conversely, management tends to prioritize short-term income, with the social benefits of environmental investment outweighing the economic benefits [44]. As a result, agency conflict influences the impact of urban greening on corporate preventive environmental investment.

According to the aforementioned analysis, companies were divided into high agency cost and low agency cost groups to test the heterogeneous effects of agency costs. The estimation results are presented in Columns (3) and (4) of Table 9. The coefficient of urban greening construction in Column (3) is not significant, indicating that urban greening construction does not significantly enhance preventive environmental investment for companies with high agency costs. In contrast, the coefficient in Column (4) is statistically significant, suggesting that urban greening can improve preventive environmental investment for companies with low agency costs. The primary explanation for this finding is that severe agency conflicts may diminish enterprises’ willingness to comply with government policies.

7. Discussion

This paper not only confirmed the promotional effect of urban greening on corporate preventive environmental investment but also identified the limitations of this effect. To further enhance the positive impact of urban greening, four key areas can be considered.

Firstly, the demonstration effect of urban greening construction relies on the continuous increase in market demand for environmental protection, public attention, and media supervision. Consequently, local governments should not only actively engage in urban greening construction but also intensify environmental publicity and heighten environmental protection awareness among the public.

Secondly, the innovation effect of urban greening construction depends on whether local governments can enhance the environmental stickiness of high-quality talents and attract more clean production enterprises to settle in, among other factors. This necessitates further strengthening of local government intervention and regulation in public environmental governance.

Thirdly, high-intensity environmental regulations may adversely impact corporate environmental investment, counteracting the positive effect of urban greening construction. This necessitates local governments not only to bolster green investment but also to avoid adopting a “one-size-fits-all” approach in environmental law enforcement.

Fourthly, local governments should proactively fortify communications and connections with non-state-owned enterprises to further amplify the promoting effect of urban greening on the preventive environmental investment of non-state-owned enterprises. Additionally, they should expedite the development of intermediary organizations, enhance the external supervision mechanism, and reduce the agency costs of local enterprises.

Nevertheless, this study is not without certain limitations that can be addressed in subsequent studies. (1) The analysis only considered the influence of urban greening on corporate preventive environmental investment, neglecting the impact of urban greening construction on corporate governance environmental investment and the differences between them. (2) Diverse environmental regulation policies and green investment behaviors are crucial environmental protection strategies. Investigating the complementarity and substitution of heterogeneous environmental regulation tools and local government green investment behaviors in promoting corporate environmental investment is also essential. (3) While local governments in China have played a pivotal role in accelerating urban greening and implementing various environmental regulations, this may not be applicable to all countries.

8. Conclusions

Drawing from relevant studies, this research utilizes Chinese-listed company and city-level data from 2011 to 2020, primarily examining the influence, mechanism, and heterogeneity of urban greening on corporate preventive environmental investment. The main research conclusions are as follows:

(1) Urban greening substantially enhances corporate preventive environmental investment, remaining reliable after numerous robustness tests and diverse endogeneity treatments. (2) Urban greening fosters corporate preventive environmental investment through demonstration and innovation effects. Specifically, urban greening bolsters enterprises’ willingness to engage in environmental regulation, modifies resource consumption patterns, and elevates the degree of green technology innovation within enterprises, thereby providing a technical foundation for cleaner production implementation. (3) The promotional impact of urban greening on corporate preventive environmental investment exhibits notable regional and firm heterogeneity. In particular, this effect is more pronounced in areas with lower marketability degrees and environmental regulation levels. It exerts a more significant influence on state-owned enterprises and enterprises with lower agency costs.

Compared with prior research, this study advances in the following three aspects:

Firstly, existing studies have concentrated on the effects of environmental regulation measures and firm heterogeneity on corporate environmental investment, while greater emphasis should be placed on the impact of local government environmental protection pressure and environmental investment behavior amid changes in environmental performance assessment objectives. Utilizing the green coverage index of urban built-up areas, this study primarily investigates the influence of environmental performance assessment objectives or shifts in public environmental investment on corporate preventive environmental investment and the transmission mechanism under the local government competition model.

Secondly, the existing literature lacks a uniform conclusion regarding the impact of marketability and environmental regulation levels on enterprise environmental investment. Some argue for the positive effect of high marketability and environmental regulation levels, while others challenge this view. The heterogeneity analysis results reveal that not only “Prevention” measures, such as introducing various environmental regulation policies, but also “Governance” measures, e.g., strengthening urban greening construction, can motivate corporations to increase preventive environmental investment and encourage green transformation. In addition, it is essential to reasonably delineate the boundary between the government and market and promote coordinated governance between the two entities.

Thirdly, previous studies typically employed the same econometric model to analyze the heterogeneity of enterprise preventive and governance environmental investment. Considering the heterogeneity of corporate preventive environmental investment and governance investment, this study establishes a specific econometric model to explore the influence and mechanism of urban greening construction, regional and corporate heterogeneity, and other factors on corporate preventive environmental investment, rendering the research conclusions more precise.