The Impact of R&D Innovation Strategy on the Sustainable Development of Intelligent Manufacturing:evidence from a quasi-natural experiment in China

The Impact of R&D Innovation Strategy on the Sustainable Development of Intelligent Manufacturing:evidence from a quasi-natural experiment in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of R&D Innovation Strategy on the Sustainable Development of Intelligent Manufacturing:evidence from a quasi-natural experiment in China Mingli Chen, Han Xu, Fa Tian, Li Ji This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8410172/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Promoting the sustainable development of intelligent manufacturing enterprises is a key pathway to drive the green and efficient transformation of the manufacturing industry, and protecting the ecological environment. Based on the data of manufacturing enterprises listed in China, this paper empirically examines the impact of the policy of additional deduction for research and development (R&D) expenses on the sustainable development of intelligent manufacturing enterprises. The study finds that the R&D policy can significantly improve intelligent manufacturing enterprises’ sustainable development performance. The conclusion remains valid after a series of robustness tests, including parallel trend test, placebo test, propensity score matching, and replacement of enterprise sustainable development indicators. Mechanism tests reveal that R&D support policies improve the sustainable development performance by alleviating corporate financing constraints, enhancing the innovation level, and increasing the total factor productivity (TFP). Heterogeneity tests show that the R&D policy has a more significant impact on the enterprises that feature fast industry technology update speed, high capital intensity, non-state ownership, and large scale. The research conclusions of this paper provide valuable references to the development of intelligent manufacturing enterprises,providing Chinese experience for sustainable development in other countries and regions. Smart Manufacturing Innovation-Driven Financing Constraints Total Factor Productivity (TFP) Sustainable Development Figures Figure 1 Figure 2 Figure 3 1 Introduction The concept of sustainable development requires enterprises to move beyond mere scale expansion and instead shift toward an innovation-driven model, emphasizing green and low-carbon practices, achieving the coordinated integration of social responsibility and economic benefits(Krajnc and Glavič P, 2005;Groschl, Gabaldon, and Hahn,2019). When enterprises uphold the concept of sustainable development, they will focus on R&D investment, cultivate and attract innovative talents, which helps reduce energy and resource consumption and pollutant emissions.However, enterprises' increased investment in areas such as scientific and technological R&D and environmental compliance will significantly raise their economic burden(Bolton and Kacperczyk,2021༛Gantchev, Giannetti, and Li,2022༛Zhao and Zhang,2024). Therefore, how to achieve the coordination of economic benefits and environmental governance while practicing the concept of sustainable development has become an important issue that urgently needs to be solved at present. Intelligent manufacturing refers to the process of driving the comprehensive upgrading of the manufacturing industry by leveraging technologies such as artificial intelligence and digitalization.It is characterized by digitalization, intelligentization, business integration, and innovation(Qi and Xiao,2020). On one hand, through replacing manual labor with automated equipment and conducting precise data analysis, it enhances production efficiency, lowers operational costs(Mikalef,2020), improves innovation capabilities(Joshi et al.,2010), promotes enterprises' green technological innovation and improves ecological environment(Mahmudul Alam and Wahid Murad,2020;Shen and Zhang,2023;Bendig et al.,2023); on the other hand, it drives enterprises to transform from "product manufacturing" to "providing products + services", personalized customized production can also increase product added value(Muller and Voigt,2018༛Lü et al.,2023༛Huang et al.,2024). With the comprehensive advancement of enterprises' intelligent transformation, systematically exploring the sustainable development paths of intelligent manufacturing enterprises and the operational mechanisms will provide important policy references for China and other countries. Existing literature has extensively explored the influencing factors of corporate sustainable development performance from the external corporate environment perspectives(Shi and Xu,2018;Chen et al.,2021༛Song and Jin,2023༛Wu,2024) and internal corporate factors(Nayak and Venkatraman,2011༛Groschl, Gabaldon, and Hahn,2019༛Wang, Tan, and Li,2023༛Wei and Tian,2025). However, the review of existing studies reveals that no scholars have examined the impact of R&D support policies on intelligent manufacturing enterprises’ sustainable development performance. The most direct effect of China's policy of additional deduction for R&D expenses before tax, implemented in 2015, is to narrow the corporate income tax base. The policy can effectively reduce the corporate income tax burden and increase the operating cash flow. As the main force of innovation and the primary beneficiaries of the additional deduction policy for R&D expenses, intelligent manufacturing enterprises can leverage the policy to alleviate financing constraints, enhance R&D capabilities, improve total factor productivity, and promote sustainable development. Therefore, exploring how to improve intelligent manufacturing enterprises’ sustainable development performance and the underlying mechanism is conducive to driving industrial transformation and upgrading the sustainable development strategy. Against this backdrop, the study treats the policy of additional deduction for R&D expenses as a "quasi-natural experiment". Using data of Chinese A-share listed manufacturing enterprises from 2010 to 2020 as the sample, adopts the difference-in-differences (DID) method to explore the impact of the R&D policy on intelligent manufacturing enterprises’ sustainable development performance and underlying mechanism. The study finds that the R&D policy can significantly improve intelligent manufacturing enterprises’ sustainable development performance. The conclusion remains valid after a series of robustness tests, including parallel trend test, placebo test, propensity score matching, and replacement of enterprise sustainable development indicators. Mechanism tests reveal that R&D support policies improve the sustainable development performance by alleviating corporate financing constraints, enhancing the innovation level, and increasing the total factor productivity (TFP). Heterogeneity tests show that the R&D policy has a more significant impact on the enterprises that feature fast industry technology update speed, high capital intensity, non-state ownership, and large scale. Compared with existing studies, the potential contributions of this study are as follows: First, the study is first to focus on intelligent manufacturing enterprises’ sustainable development performance. Drawing on existing research (Xie and Zhu, 2021 ), the study uses comprehensive indicators of economic performance and environmental performance to measure the sustainable development performance. On the one hand, the performance model can reflect enterprises' operational financial performance and market competitiveness; on the other hand, it can reflect enterprises' fulfillment of social responsibilities in terms of external environmental performance, to better evaluate the external manifestation of enterprises' sustainable development. By integrating indicators of economic performance and environmental performance, the study conducts an in-depth analysis of the R&D policy on the sustainable development performance, expanding a new analytical dimension for relevant research. Second, on the basis of testing the alleviation of financing constraints serves as a mechanism, the study further explains whether the R&D policy promotes enterprises' sustainable development performance by advancing enterprises' innovation strategies and increasing total factor productivity (TFP). By focusing on the impact path of "the R&D policy – enhancing enterprises' innovation capabilities and TFP – enterprises' sustainable development performance", the study enriching the logical chain of how the R&D policy influences enterprises' sustainable development performance. Third, the study conducts an in-depth analysis of the heterogeneous impact of the R&D policy on the sustainable development performance in different industries. It reveals the differences of the policy's impact with varying technological update speeds, capital intensity, labor intensity, and enterprise scales. This provides theoretical support for intelligent manufacturing enterprises to vigorously promote sustainable development strategies. Fourth, it provides firm-level evidence from a major developing country. The research not only contributes to the literature on the dynamic determinants of corporate sustainable development (Jamal et al.,2021;Pedersen et al.,2021;DEL RÍO CASTRO et al.,2021),but also adds new content on the economic impacts of institutional reforms related to R&D expense-related tax incentives(Agrawal ,Rosell, and Simcoe,2020༛Ge and Zhong,2025), such as tax deductions and tax credits. The research conclusions can provide policy implications and reform references for other economies. 2. Theoretical Analysis and Research Hypotheses 2.1 Theoretical Analysis Sustainable development refers to a business philosophy and approach where enterprises pursuing optimal financial performance, focus on balancing three core needs: economic growth, environmental responsibility, and social contribution. In achieving business goals, enterprises should reduce environmental impact or create environmental benefits through product or service provision,realizing the long-term development, society, and the environment. Existing studies mostly focus on two aspects: the evaluation of corporate sustainable development performance and the factors influencing corporate sustainable development. (1) Literature related to the evaluation of corporate sustainable development performance. Van Marrewijk ( 2012 ) argues that corporate sustainability refers to addressing the needs of stakeholders while paying attention to the social and environmental impacts of corporate operations. Scholars have attempted to comprehensively evaluate corporate sustainability from three dimensions: economy, environment, and social responsibility (Krajnc and Glavič P, 2005; Steurer et al., 2005 ). Alexopoulos et al. ( 2018 ) ,Xie and Zhu ( 2021 ) measured corporate sustainable development performance using corporate financial performance and environmental-social responsibility performance. The indicator can reflect an enterprise’s profit-generating capacity, ensuring its long-term survival in the market; and it can reflect an enterprise’s production technology level, helping to reduce its burden on ecological environment. This enables a more comprehensive assessment of whether enterprise’s production complies with the requirements of sustainable development strategies. (2) Literature related to the factors influencing corporate sustainable development performance. From the perspective of external corporate factors, policy instruments such as green industry policies(Chen et al.,2021), central environmental inspection policies(Zhang and Ye,,2023), green credit policies(Jiang and Qin,2022), low-carbon city pilots(Wang and Wang,2022), the transformation of environmental protection fees into taxes(Mao,2024), and environmental regulations(Yu,Ramanathan, and Nath,2017)have all been proven to improve sustainable development performance. At the internal corporate factors level, including enterprise scale expansion(Nayak and Venkatraman,2011), executives' green awareness(Zou et al.,2019), CEO cognitive complexity(Groschl, Gabaldon, and Hahn,2019), the application of digital technologies(Wang, Tan, and Li,2023), and digital transformation have been confirmed to exert a positive impact on corporate sustainable development performance. Additionally, new-quality productive forces can enhance corporate sustainable development performance and have a positive effect on green innovation(Wang and Li,2025). In contrast, the misallocation of asset structure will significantly reduce corporate sustainable development performance(Wei and Tian,2025). The review of existing studies shows that most research is conducted from external environment perspectives or internal corporate characteristics. Few studies have discussed the influence of R&D support policies on intelligent manufacturing enterprises’ sustainable development. R&D support policies exert a crucial impact on enterprises' innovative behaviors. The implementation of innovation strategies, on one hand, encourages enterprises to adopt advanced technologies and methods,significantly enhances production efficiency; on the other hand, the application of high-end equipment and intelligent information devices can effectively reduce environmental pressure, improve total factor productivity (TFP), thus affect corporate sustainable development performance. The policy of additional deduction for R&D expenses may empower intelligent manufacturing enterprises’ sustainable development through the following channels: First, through tax deductions and supporting funds, it alleviates the pressure of internal and external resource constraints, improves the efficiency of corporate resource allocation, provides a capital channel for the sustainable development strategies. Second, the policy encourages enterprises to increase R&D investment, improve corporate capital investment and hardware resources required for innovation, enhance innovation level of corporate production, thereby providing innovation support for the sustainable development strategies. Third, by influencing R&D investment and innovation output,the R&D support policies can promote enterprises' TFP. The improvement of corporates’ TFP implies a reduction in resource consumption and an increase in production efficiency, which significantly enhances enterprises' market competitiveness and provides a driving foundation for corporate sustainable development. Based on the above analysis, this study proposes Hypothesis 1: The policy of additional deduction for R&D expenses is conducive to the improvement of intelligent manufacturing enterprises’ sustainable development performance. 2.2 Analysis of the Mechanism of Action (1) Financing Constraint Alleviation Channel: Capital Channel The resource allocation theory posits that by increasing support for enterprises' R&D investment, government guides more capital to flow into technological innovation and adjusts innovation resources to exert a resource allocation effect (Wen, Meng, and Zhang, 2018). Financing constraints not only reduce enterprises' market competitiveness but also hinder their innovative development(Gong,Lu, and Lin,2023), posing a threat to sustainable development. Limited internal resources of the company will be allocated to achieving corporate financial performance, while the fulfillment of social responsibilities and environmental obligations is neglected. The adversely affects enterprises' social and environmental performance, which in turn impacts sustainable development(Lai,Yue, and Chen,2021;Wei and Tian,2025). Facing financing constraints forces enterprises to bear higher capital costs(Wen, Wang, and Yu,2024), all these factors are detrimental to enterprises' sustainable development. The essence of financing constraints lies in the insufficiency of external capital supply or the restriction of internal capital accumulation, which results in the failure to fill the capital gap required for R&D and ultimately inhibits R&D investment either directly or indirectly. Compared with external financing that incurs higher capital costs, internal financing features lower capital costs. The R&D policy encourages enterprises to increase R&D investment and enhance innovation capabilities, which in turn attracts more attention from investors. For venture capitalists, they are more willing to invest in enterprises with innovative vitality and development potential. The innovation advantages demonstrated by intelligent manufacturing enterprises will make them high-quality targets in the eyes of investors, facilitating enterprises to obtain funds through equity financing. Furthermore, the government's policy support enables investors to perceive the promising prospects of industrial development, strengthens enterprises' ability to attract external investment (Yin and Li, 2022 ; Han et al., 2025 ), alleviates financing constraints. Through the R&D support policy, government demonstrates its supportive orientation toward intelligent manufacturing industry. Financial institutions will adjust their credit strategies in accordance with the policy orientation and allocate more financial resources to intelligent manufacturing enterprises (Tian, Xia, and Xu, 2022 ). As enterprises' innovation capabilities improve, their market competitiveness and profitability will also be enhanced. This enables enterprises to rely on better business prospects and expected returns, making it easier to gain recognition and financial support from financial institutions. Based on the above analysis, this study proposes Hypothesis 2: The policy of additional deduction for R&D expenses promotes the improvement of intelligent manufacturing enterprises' sustainable development performance by alleviating financing constraints. (2) R&D Capability Enhancement Channel: Innovation Channel R&D and innovation capability is a crucial factor influencing corporate sustainable development (Zhao et al., 2025 ). Technological progress is the outcome of R&D and innovation, the high-risk nature of R&D dictates sustained capital input is an important guarantee for innovation activities (Song and Liu, 2021 ). The capital supply effect of the R&D policy can alleviate intelligent manufacturing enterprises’ financing difficulties, prompting them to increase R&D investment and enhance innovation capabilities (Xu and Feng, 2024 ), thereby influencing enterprises' sustainable performance. R&D investment is characterized by high risk, high uncertainty, long cycles, and strong asset specificity(An, Wei, and Shu,2020),essentially, corporate R&D investment is a capital-intensive activity that requires continuous cash flow support.The government's active introduction of tax incentives for additional deduction of R&D expenses shares the R&D costs of enterprises and stimulates their enthusiasm for innovation. By leveraging innovation incentive policies to relax enterprises' resource constraint conditions, the government has effectively promoted corporate innovation in the short term (Bloom, Reenen, and Williams, 2019 ). Finally, the tax incentives guide enterprises to engage in innovation-aligned behaviors(Sun, Zhou, and Zhang,2021), attract more resources to converge toward enterprises, provide sound policy support for enterprises' R&D strategies. In terms of corporate human capital, high-skilled labor engaged in R&D and production can significantly promote enterprises' innovation output(Audia and Goncalo,2007;Kong,2025). To a certain extent, R&D support policies reduce the actual employment costs of technical personnel(Chen,Lin, and Zhang,2020), lowering the marginal costs of innovation activities. It gives enterprises greater incentive to hire high-education and high-quality skilled personnel,further enhances corporate sustainable development. Based on the above analysis, this study proposes Hypothesis 3: The policy of additional deduction for R&D expenses improves intelligent manufacturing enterprises’s sustainable development performance by enhancing their innovation capabilities. (3) Total Factor Productivity (TFP) Enhancement Channel: TFP Channel Corporate total factor productivity (TFP) is a key indicator of corporate development(Wong and Chen, 2023). It reflects changes in enterprises' technological innovation, management capabilities, labor quality, factor allocation efficiency, organizational effectiveness, and exerts a significant impact on corporate sustainable development. R&D investment and innovation output are the key factors determining a company’s TFP (Cao et al., 2022 ). An increase in TFP means that enterprises can achieve higher output with the same level of input, which can lead to lower costs and higher profits, enhance enterprises’ competitiveness, and lay a solid economic foundation for corporate sustainable development. Therefore, the impact of R&D support policy on corporates’ TFP is an important factor influencing corporate sustainable development. The policy affects enterprises’ TFP through the following two aspects: First, it enhances TFP by integrating into their R&D processes. The R&D policy incentivizes enterprises to increase R&D investment(Song and Liu,2021). The demand for high-quality human resources driven by R&D strategies encourages enterprises to recruit highly educated and high-skilled talents, which facilitates corporate knowledge accumulation and the optimization of human capital structure (Dai and Zhao, 2022 ). The improvement of knowledge stock not only helps enterprises absorb advanced technologies and strengthen independent innovation capabilities but also enables enterprises to identify technical bottlenecks and innovation opportunities,break through existing technological barriers. The upgrading of corporate human capital can also promote the integration of cross-departmental resources in R&D, management, and production, enhance R&D efficiency and innovation level, further drive the improvement of TFP. Second, it enhances TFP by integrating into manufacturing processes. In the manufacturing process, intelligent manufacturing enterprises mainly drive the improvement of TFP through approaches such as introducing high-end intelligent equipment (Shen, Qiao, and Lin,2024)and optimizing the human capital structure(Liang, Liang, and Qi,2024) to achieve a high level of collaborative production. The specific impact mechanism of R&D support policies is as follows: First, by alleviating financing constraints, the R&D policy encourages intelligent manufacturing enterprises to increase investment in intelligent software and hardware equipment. It enables enterprises to achieve accurate matching with enterprises in all links of the industrial chain during the production process,promotes TFP growth. Second, the policy's support incentivizes intelligent manufacturing enterprises to recruit highly educated and high-skilled talents. According to human capital theory, when workers' knowledge and skills match the job requirements, enterprises' production efficiency can be maximized. The employment of high-skilled talents reduces the demand for low-skilled and repetitive labor, realizes the accurate matching and efficient supply of production factors, optimizes overall resource allocation of enterprises(Jüttner and Wehrli,2011;Acemoglu et al,2020༛Yao, Zhang, and Guo,2024). Based on the above analysis, the study proposes Hypothesis 4: The policy of additional deduction for R&D expenses promotes improvement of intelligent manufacturing enterprises’ sustainable development performance by increasing total factor productivity (TFP). Building on the theoretical analysis,the direction and interaction of these mechanisms necessitate empirical validation. Figure 1 illustrates the conceptual framework linking the R&D Innovation Strategy to enterprise sustainable development. 3. Research Design 3.1 Specification of the Econometric Model To test the impact of the 2015 policy of additional deduction for R&D expenses on the sustainable development of intelligent manufacturing enterprises, we draw on the methodology of existing studies (Huang et al., 2023; Shen et al., 2024 ) and construct a difference-in-differences (DID) model for empirical regression analysis: \({\text{sustainD}}{{\text{e}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) Among them, the subscripts i and t represent the enterprise and year respectively. The explained variable sustainDe denotes the sustainable development of intelligent manufacturing enterprise i in year t. The core variable Treat is defined as follows: enterprises whose industry falls into the ten key supported fields specified in the Made in China 2025 industrial policy are identified as samples of intelligent manufacturing enterprises, in which case Treat equals 1; otherwise, it equals 0. Post equals 1 if the year is greater than or equal to 2015, and 0 otherwise. The policy variable of interest in this paper is the interaction term Treat×Post, where Treat is the treatment variable and Post is the policy shock variable. \(\theta\) is the regression coefficient that the paper focuses on primarily. If the estimated coefficient \(\theta\) is positive, it indicates that the implementation of the R&D policy is conducive to improving the sustainable development level. This paper also controls for a series of variables related to enterprise-level characteristics, as well as enterprise fixed effects ( \({\mu _{\text{i}}}\) ) and time fixed effects ( \({\gamma _{\text{t}}}\) ). 3.2 Variable Definition Corporate Sustainable Development Performance( \({\text{sustainDe}}\) ). Following existing studies (Chen, Li, and Lu, 2018 ; Xie and Zhu, 2021 ), we measure the level of corporate sustainable development from two dimensions: the financial dimension ( \({\text{Feco}}\) ) and the environmental dimension ( \({\text{Envro}}\) ). For the financial dimension, we use the enterprise’s Return on Total Assets ( \({\text{ROA}}\) ) for measurement; for the environmental dimension, referring to the research (Zhang and Yu, 2025 ), we use the environmental score item in the China Securities Index (CSI) ESG Index for measurement. We adopt Method \({{\text{Y}}^*}= Y-{\text{min}} / {\text{max}}-{\text{min}}\) to perform 0–1 standardization on Variables \({\text{Feco}}\) and \({\text{Envro}}\) , and then combine the standardized \({\text{Feco}}\) with \({\text{Envro}}\) to form the sustainable development performance indicator ( \({\text{sustainDe}}\) ), denoted as \({\text{sustain}}D{\text{e}}= 1-|F{\text{eco}}-E{\text{nvro}}| \times F{\text{eco}} \times E{\text{nvro}}/1\) . To account for the impact of other factors on the empirical results of this paper, we select a series of firm-level control variables. With reference to existing literature, the control variables we choose include: firm age (age), measured as the natural logarithm of the difference between the fiscal year and the firm's founding year; return on assets (roa), calculated as the ratio of net profit to total assets; firm leverage (lev), measured as the ratio of total liabilities at the end of the year to total assets; operating cash flow level (cash), calculated as the ratio of net cash flow from operating activities to total assets; firm growth (growth), measured by the annual growth rate of the firm's operating income; firm capital intensity (density), measured as the natural logarithm of the ratio of total fixed assets to total number of employees; firm value (tbq, Tobin's Q); management shareholding index (mshare), measured by the proportion of shares held by management; the shareholding ratio of the largest shareholder (bigholder), measured by the shareholding ratio of the largest shareholder; and firm financing constraint index (finan_bind, SA index). 3.3 Sample Selection and Descriptive Statistics of Variables This study uses data of manufacturing listed companies on the Shanghai and Shenzhen A-shares from 2010 to 2020. Firm-level characteristic data and financial data are mainly obtained from the WIND and CSMAR (China Stock Market & Accounting Research) databases. Two reasons are considered for the time range of the sample data: first, the Notice on the Policy of Additional Deduction for Enterprise R&D Expenses was officially implemented in 2015, and a 5-year time window before and after the policy implementation not only ensures the adequacy of the sample but also avoids the policy confusion effect caused by an excessively long time span; second, in consideration of the impact of the COVID-19 pandemic, the data is selected up to 2020. To ensure the rationality of data quality, consistent with existing studies, we conduct the following processing on the initial data: (1) This paper selects data of manufacturing listed companies and excludes irrelevant data of financial and other industries; (2) Delete data of companies with a short listing period and missing financial data; (3) To address the issue of outliers in the sample data, this paper conducts a 1% winsorization on continuous variables. The descriptive statistics results of the main variables in this paper are shown in Table 1 . Table 1 Descriptive Statistics of Main Variables Variable Sample Size Mean Standard Deviation Min Max sustainDe 15,956 0.040 0.135 0.000 1.000 ESG_Rate 16,725 22.827 14.840 -2.840 73.820 Environ_Rate 16,725 1.475 4.785 0.000 23.000 Social_Rate 16,725 3.938 3.438 -6.140 15.000 treat 16,846 0.702 0.457 0.000 1.000 post 16,846 0.660 0.474 0.000 1.000 age 16,846 2.840 0.329 1.792 3.466 roa 16,077 0.046 0.052 -0.148 0.196 lev 16,846 0.396 0.192 0.052 0.860 cash 16,077 0.051 0.065 -0.129 0.234 growth 16,077 11.422 25.731 -60.275 113.156 cdensity 15,578 12.610 0.842 10.355 14.726 tbq 16,516 2.126 1.299 0.891 8.357 mshare 16,506 12.999 19.817 0.000 68.596 bigholder 16,510 0.341 0.142 0.029 0.900 finan_bind 16,064 -3.783 0.229 -4.375 -3.223 soe 16,539 0.305 0.460 0.000 1.000 4. Empirical Results and Analysis 4.1 Impact of the R&D Policy on Corporate Sustainable Development: Baseline Regression We use the above Eq. (1) to test the impact of the 2015 R&D policy on the sustainable development of intelligent manufacturing enterprises. The baseline regression results are shown in Table 2 . In Column (1), we only include the interaction term( \({\text{Treat}} \times {\text{Post}}\) ). It can be found that the estimated coefficient of the interaction term ( \({\text{Treat}} \times {\text{Post}}\) )with corporate sustainable development performance ( \({\text{sustainDe}}\) ) is 0.021, it passes the significance test at the 1% level. This indicates that the 2015 R&D policy can significantly improve the sustainable development level of intelligent manufacturing enterprises, verifying the research hypothesis. Considering that Column (1) does not include sufficient control variables, we gradually add control variables in Columns (2), (3), and (4) to mitigate potential biases in the difference-in-differences (DID) estimation results. The regression coefficients of the interaction term ( \({\text{Treat}} \times {\text{Post}}\) ) and corporate sustainable development performance ( \({\text{sustainDe}}\) ) remain significantly positive and meet the significance level test. The results still support the research conclusions.Taking Column (3), where all control variables are included, as an example to explain the economic significance of the estimated coefficient of the interaction term( \({\text{Treat}} \times {\text{Post}}\) ): a coefficient of 0.018 means that the 2015 R&D policy increases the sustainable development performance of enterprises in the treatment group by 1.8% compared with those in the control group. Table 2 The Impact of the Additional Deduction Policy for R&D Expenses on Enterprise Sustainable Development: Baseline Regression Variables (1) (2) (3) (4) sustainDe sustainDe sustainDe sustainDe treat_post 0.021*** 0.018** 0.018** 0.015* (0.008) (0.008) (0.008) (0.008) age 0.148*** 0.125*** 0.088** (0.037) (0.038) (0.037) lev 0.026* 0.018 -0.007 (0.014) (0.014) (0.015) cash 0.012 0.013 -0.003 (0.020) (0.020) (0.020) cdensity 0.005 0.007* (0.004) (0.003) mshare -0.000*** -0.000** (0.000) (0.000) bigholder -0.069** -0.048 (0.029) (0.030) finan_bind -0.497*** (0.054) tbq 0.005*** (0.001) YEAR CONTROL CONTROL CONTROL CONTROL Constant 0.116*** -0.268*** -0.232** -1.944*** (0.005) (0.092) (0.104) (0.212) Observations 15,956 15,956 15,538 15,214 R-squared 0.155 0.160 0.162 0.188 Number of stkcd 2,389 2,389 2,324 2,322 5. Robustness Tests We further examine the robustness of the research conclusions of this paper from the perspectives of dynamic effect test, placebo test, propensity score matching (PSM), and replacement of corporate sustainable development performance indicators(ESG_Rate, Environ_Rate, Social_Rate). 5.1 Dynamic Effect Test A crucial assumption for the validity of the difference-in-differences (DID) model in application is that the treatment group and the control group satisfy the parallel trend assumption. Specifically, it means that the change trends of corporate sustainable development performance between the treatment group and the control group should remain parallel before the introduction of the 2015 R&D Policy. If the parallel trend assumption is not satisfied, the regression results of the DID model may be biased. To address this issue, we draw on the methods of Chen et al. ( 2018 ), Ye et al. (2023), and Shen et al. ( 2024 ), use an event study approach based on Eq. (1) to construct a more flexible dynamic regression. This regression is used to test the parallel trend and identify the specific timing when the R&D Policy begins to exert its policy effect: \({\text{sustainD}}{{\text{e}}_{it}}={\alpha _0}+\sum\nolimits_{{2010}}^{{2020}} {{\theta _t}} {\text{Trea}}{{\text{t}}_i} \times {\text{Yea}}{{\text{r}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) In the above formula, \({\text{Yea}}{{\text{r}}_t}\) represents the annual dummy variable; \({\theta _t}\) reflects the relative impact of the R&D policy on the corporate sustainable development performance in the experimental group in year t. If the parallel trend assumption is satisfied before the implementation of the policy, the change in the corporate sustainable development performance after 2015 is the policy effect. Figure 2 presents the regression coefficients of the interaction term. From the coefficients, it can be observed that the regression coefficient \({\theta _t}\) for the period 2010–2014 fails to pass the significance test, which verifies the corporate sustainable development performance in the experimental group and the control group exhibited a common parallel trend during the pre-policy implementation period. Additionally, the regression coefficients in Fig. 1 indicate that the R&D policy exerted a positive promotional effect on the corporate sustainable development performance in the experimental group in the very year when the policy was formally implemented. 5.2 Placebo Test Considering that external random factors may interfere with the baseline results, to further confirm the baseline regression results are not affected by other random events, the study draws on existing research (La Ferrara, Chong, and Duryea, 2012 ; Shen et al., 2024 ) to conduct a placebo test. By simulation, we artificially disrupt the corresponding relationship between the treatment group and the control group, randomly create a new treatment group and control group, constructing a false policy shock, and then re-conduct the regression based on the sample. Figure 3 depicts the probability density distribution of the estimated coefficients of false policy shocks from 500 random samples. As shown in Fig. 3 , most of the estimated coefficients obtained from the random sampling regression are distributed around zero and follow a normal distribution; however, the baseline regression estimated coefficient (0.015) is distributed on the right side of zero. This indicates that the randomly simulated policy shock has no significant impact on the level of corporate sustainable development.The placebo test shows that the policy shock effect is not caused by random events,the shock effect of the R&D support policy is indeed present. The above analysis can, to a certain extent, rule out the interference of non-time-varying confounding factors on the results, indicating that the positive impact on corporate sustainable development is real. 5.3 Propensity Score Matching (PSM) Before the implementation of the R&D policy, if there are significant characteristic differences between enterprises in the treatment group and the control group, it will interfere with the regression results of the difference-in-differences (DID) model. To verify the interference of such significant differences on the regression results, we adopt the Propensity Score Matching (PSM) method to identify the control group with similar characteristics. We use the control variable X as the covariate and adopt the 1:5 nearest neighbor matching method to select the control group. Column (2) in Table 3 below reports the matching results based on the Logit model, while Columns (3)-(6) present the balance test of covariates, which verifies the effectiveness of the PSM method. We conduct the DID test based on the data after PSM matching. From the regression results, we can find that the regression coefficient of Treat×Post remains positive and passes the significance test at the 1% level, which verifies the baseline regression results. Table 3 Regression Results of Propensity Score Matching (PSM) Panel A: PSM Process Panel B: DID Estimation Variables Logit Model Covariate Balance Test Variables sustainDe Matched Status Treatment Group Control Group Bias age -0.657*** NO 2.840 2.866 -8 Treat×Post 0.017*** (.139) YES 2.840 2.845 -1.5 (.0082) lev -0.318** NO 0.385 0.407 -11.2 Control Var YES (.106) YES 0.385 0.384 1 Year YES cash -3.144*** NO 0.048 0.058 -16.5 Firm YES (.297) YES 0.048 0.048 -0.1 Sample Size 13293 cdensity -0.146*** NO 12.571 12.709 -16 adj-R 2 0.196 (.022) YES 12.571 12.555 1.9 mshare 0.002 NO 13.818 11.898 9.7 (.001) YES 13.818 13.76 0.3 bigholder -1.025*** NO 0.333 0.358 -17.8 (.129) YES 0.333 0.331 1 growth 0.003*** NO 11.797 9.765 8.1 (.001) YES 11.797 11.218 2.3 finan_bind -0.505** NO -3.778 -3.788 4.6 (.191) YES -3.778 -3.784 2.9 tbq 0.105*** NO 2.131 1.974 12.7 (.018) YES 2.131 2.103 2.2 Constant Term 2.764*** (.530) Sample Size 15214 Pseudo R-Squared 0.023 5.4 Testing Using ESG_Rate, Environ_Rate, and Social_Rate Indicators The corporate Environmental, Social, and Governance (ESG) evaluation system covers the key performance dimensions of corporate sustainable development (Wang and Wang, 2022 ) and serves as a crucial indicator reflecting corporate social benefits. The study collects ESG performance data of listed companies from Hexun.com, specifically the overall ESG rating score of enterprises (ESG_Rate). A higher ESG rating indicator value indicates better sustainable development performance of the enterprise. The ESG rating is further divided into two sub-dimensions: Environmental Responsibility Score (Environ_Rate) and Social Responsibility Score (Social_Rate). In the regression results presented in Table 4 , Columns (1) to (6) report the regression outcomes for sustainable development based on the ESG evaluation system. It can be observed that the regression coefficients of the interaction term (Treat×Post) with the corporate sustainable development performance indicators (ESG_Rate, Environ_Rate, and Social_Rate) are all positive, all pass the significance level test. It indicates that the implementation of R&D support policies has a significant promoting effect on corporate sustainable development performance (ESG), the effect remains relatively significant when measured by environmental responsibility (Environ_Rate) and social responsibility (Social_Rate).It can be concluded that the implementation of the R&D policy not only improves corporate financial performance but also promotes corporate sustainable development performance. Table 4 Regression Results of Replacing Key Variables Variables (1) (2) (3) (4) (5) (6) ESG_Rate ESG_Rate Environ_Rate Environ_Rate Social_Rate Social_Rate treat_post 1.289* 1.538** 0.896*** 0.633** 0.105 0.238* (0.771) (0.750) (0.284) (0.274) (0.134) (0.139) age 8.939*** 2.639** 1.040* (3.323) (1.281) (0.578) lev -11.827*** 0.531 -1.895*** (1.490) (0.526) (0.320) cash 15.589*** -0.218 1.900*** (2.154) (0.726) (0.513) roa 34.010*** 0.570 2.052** (3.483) (1.132) (0.826) cdensity 0.355 0.249** 0.005 (0.328) (0.109) (0.079) mshare -0.008 -0.009*** 0.001 (0.009) (0.003) (0.002) bigholder 2.396 -1.234 1.216** (2.920) (1.010) (0.537) growth 0.069*** -0.000 0.012*** (0.004) (0.001) (0.001) finan_bind -41.125*** -16.344*** -19.364*** (5.034) (1.829) (1.959) tbq 0.358*** 0.161*** 0.178*** (0.130) (0.045) (0.072) YEAR CONTROL CONTROL CONTROL CONTROL CONTROL CONTROL Constant 28.850*** -144.740*** 3.593*** -64.237*** 4.415*** 1.536 (0.457) (19.213) (0.174) (7.051) (0.101) (1.712) Observations 16,725 15,217 16,725 15,217 16,725 15,542 R-squared 0.158 0.225 0.151 0.183 0.011 0.030 Number of stkcd 2,395 2,322 2,395 2,322 2,395 2,324 6.Mechanism Test of Action The regression results above confirm that the 2015 additional deduction policy for R&D expenses significantly improves the sustainable development performance of intelligent manufacturing enterprises.Therefore, this study will further examine the aforementioned mechanisms below. 6.1 Financing Constraint Alleviation Channel: Capital Channel The study argues that the R&D policy alleviates enterprises’ financial pressure, provides more financial support for innovation activities to enhance innovation capabilities. Ultimately, the improvement of resource allocation efficiency and technological innovation capabilities is reflected in the improvement of corporate sustainable development performance. Following the practices of existing scholars (Ju, Lu, and Yu, 2013 ; Shen et al., 2024 ), this study uses the corporate financing constraint indices SA ( \({\text{finan\_bind}}\) ) and FC ( \({\text{FC}}\) ) to measure the level of corporate financial constraints. On the basis of Eq. (1), the following equations are constructed: \({\text{finan\_bin}}{{\text{d}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) \({\text{F}}{{\text{C}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) The regression results are presented in Columns (1), (2), (3), (5), (6), and (7) of Table 5 . Whether considering the regression coefficient of the corporate financing constraint index ( \({\text{finan\_bind}}\) ) with the interaction term ( \({\text{Treat}} \times {\text{Post}}\) ), or the regression coefficient of ( \({\text{FC}}\) ) with the interaction term ( \({\text{Treat}} \times {\text{Post}}\) ), both are negative and basically significant. It verifies the R&D policy has a significant effect on alleviating corporate financing constraints. Table 5 Mechanism Test: Capital Channel Variables (1) (2) (3) (4) (5) (6) (7) (8) finan_bind finan_bind finan_bind sustainDe FC FC FC sustainDe treat_post -0.010*** -0.006* -0.007* 0.015* -0.049*** -0.018** -0.020*** 0.018** (0.004) (0.003) (0.003) (0.008) (0.009) (0.007) (0.007) (0.008) age -0.091*** -0.075*** 0.088** -0.268*** -0.211*** 0.123*** finan_bind -0.498*** (0.054) FC -0.011 (0.011) (0.020) (0.021) (0.037) (0.038) (0.039) (0.039) lev -0.068*** -0.061*** -0.007 -0.669*** -0.653*** 0.014 (0.009) (0.008) (0.015) (0.021) (0.021) (0.016) cash -0.007 -0.016* -0.002 -0.042* -0.012 0.006 (0.008) (0.008) (0.020) (0.025) (0.025) (0.021) roa -0.039*** -0.062*** -0.0591*** -0.332*** -0.343*** -0.372*** (0.015) (0.014) (0.016) (0.036) (0.037) (0.039) cdensity 0.003* 0.003 0.007* -0.026*** -0.027*** 0.005 (0.002) (0.002) (0.003) (0.005) (0.005) (0.004) mshare 0.000*** -0.000** 0.001*** -0.000*** (0.000) (0.000) (0.000) (0.000) bigholder 0.042** -0.048 0.064* -0.067** (0.018) (0.030) (0.039) (0.031) growth -0.000*** -0.000 -0.000*** 0.000 (0.000) (0.000) (0.000) (0.000) tbq 0.006*** 0.005*** -0.014*** 0.002 (0.001) (0.001) (0.002) (0.001) YEAR YES YES YES YES YES YES YES YES Constant -3.567*** -3.351*** -3.424*** -1.946*** 0.648*** 1.876*** 1.726*** -0.219** (0.002) (0.055) (0.059) (0.213) (0.006) (0.110) (0.115) (0.106) Observations 16,064 15,567 15,244 15,214 16,496 15,252 15,244 15,214 R-squared 0.886 0.895 0.901 0.188 0.146 0.365 0.384 0.164 Number of stkcd 2,422 2,349 2,348 2,322 2,424 2,348 2,348 2,322 6.2 Channel for Enhancing R&D Capabilities: Innovation Channel To examine the impact of the R&D policy on the innovation level of smart manufacturing enterprises, this paper constructs the following equation using the aforementioned Formula (1). For the measurement of enterprise innovation indicators, we draw on existing research (Shen et al., 2024 ) and use R&D investment intensity (rd_invest) and enterprise innovation outputs (total_patent) as the explained variables.R&D investment intensity is measured by the ratio of an enterprise’s total annual R&D investment to its operating income.The enterprise innovation output indicator is measured by taking the logarithm of the number of patent applications filed by the enterprise. \({\text{rd\_inves}}{{\text{t}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) \({\text{total\_paten}}{{\text{t}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) The regression results are shown in Table 2 . In columns (1) and (5), we only added the interaction term (Treat × Post), we found that the estimated coefficients of the interaction term (Treat ×Post) with R&D investment intensity (rd_invest) and enterprise innovation achievement (total_patent) were 0.402 and 0.128, respectively, both passed the significance test at the 1% level. It indicates that the 2015 R&D policy can significantly improve the innovation level of intelligent manufacturing enterprises. To avoid bias caused by omitted variables in the double difference estimation results, we gradually added control variables in columns (2), (3), and (6), (7). It can be observed that with the addition of control variables, the regression results of the interaction term (Treat × Post) with the coefficients of R&D investment intensity (rd_invest) and enterprise innovation achievement (total_patent) are both positive and significant, basically meeting the significance level of 1%. The regression results support that the 2015 R&D policy can significantly improve the innovation level of intelligent manufacturing enterprises. Table 6 Mechanism Test: Innovation Channel Variables (1) (2) (3) (4) (5) (6) (7) (8) rd_invest rd_invest rd_invest sustainDe total_patent total_patent total_patent sustainDe treat_post 0.402*** 0.411*** 0.410*** 0.015* 0.128*** 0.101*** 0.099** 0.017** (0.101) (0.104) (0.104) (0.008) (0.042) (0.039) (0.039) (0.008) rd_invest 0.000 (0.001) total_patent 0.002 (0.004) age -1.741*** -1.799*** 0.106*** 0.626*** 0.596*** 0.096** (0.559) (0.573) (0.038) (0.176) (0.179) (0.038) lev -0.897*** -0.988*** -0.001 0.358*** 0.375*** -0.008 (0.289) (0.284) (0.015) (0.084) (0.087) (0.015) cash -1.938*** -1.929*** -0.006 0.096 0.080 -0.001 (0.372) (0.375) (0.021) (0.089) (0.090) (0.020) roa -1.817*** -1.783*** -1.767*** 0.315** 0.347** 0.368** (0.608) (0.610) (0.549) (0.141) (0.142) (0.151) cdensity 0.087 0.005 0.015 0.006* (0.069) (0.003) (0.021) (0.003) mshare 0.000 -0.000** -0.000 -0.000** (0.002) (0.000) (0.001) (0.000) bigholder -0.160 -0.059* -0.223 -0.049 (0.565) (0.031) (0.197) (0.031) growth -0.015*** -0.015*** -0.000 0.000 0.000 -0.000 (0.001) (0.001) (0.000) (0.000) (0.000) (0.000) finan_bind -0.184 -0.071 -0.459*** 0.547* 0.632* -0.502*** (0.792) (0.818) (0.055) (0.308) (0.324) (0.055) tbq -0.051* -0.049* 0.004*** -0.029*** -0.029*** 0.005*** (0.029) (0.029) (0.001) (0.007) (0.007) (0.001) YEAR CONTROL CONTROL CONTROL CONTROL CONTROL CONTROL CONTROL CONTROL Constant 3.901*** 8.479*** 8.037** -1.844*** 3.347*** 3.878*** 4.160*** -1.977*** (0.150) (3.101) (3.425) (0.216) (0.031) (1.089) (1.167) (0.214) Observations 14,677 14,199 14,073 14,044 16,561 15,520 15,039 15,009 R-squared 0.031 0.095 0.097 0.179 0.704 0.702 0.703 0.191 Number of stkcd 2,331 2,329 2,299 2,273 2,406 2,399 2,329 2,303 6.3 Improving Total Factor Productivity Channel: Total Factor Productivity Channel To test whether the impact of the 2015 R&D support policy on the sustainable development performance is through the channel of improving the total factor productivity, this paper constructs the following equation to perform regression testing on the sample data. For the measurement of total factor productivity of enterprises, consistent with the practices of most scholars, this article uses LP and OP methods to calculate the total factor productivity of enterprises. Meanwhile, the green total factor productivity of enterprises is a comprehensive reflection of production efficiency and environmental performance, and an important manifestation of sustainable development. Therefore, using green total factor productivity is more comprehensive compared to total factor productivity (Xie and Zhu, 2021 ). We used the Luenberger productivity indicator (LPI) method to measure the green total factor productivity (Green_TFP) at the enterprise level. \({\text{TFP\_L}}{{\text{P}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) \({\text{TFP\_O}}{{\text{P}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) \({\text{Green\_TF}}{{\text{P}}_{it}}={\alpha _0}+\theta {\text{Trea}}{{\text{t}}_i} \times {\text{Pos}}{{\text{t}}_t}+\beta {{\text{X}}_{it}}+{\mu _i}+{\gamma _t}+{\varepsilon _{it}}\) The regression results are shown in Table 7 . In the regression of columns (1) to (4), we gradually added control variables and found that the regression coefficients between the interaction term (Treat×Post) and the total factor productivity (TFP_LP, TFP_OP) were positive, basically passed the significance level test. It indicates that the R&D policy in 2015 can significantly improve the total factor productivity of intelligent manufacturing enterprises. In the regression results of columns (5) to (6), we found that the regression coefficients between the interaction term (Treat×Post) and the green total factor productivity (Green_TFP) were both positive and passed the 5% significance level test. This once again confirms that R&D support policies promote the improvement of total factor productivity and green total factor productivity, drive sustainable development of enterprises. Table 7 Mechanism Test: Channel of Improving Total Factor Productivity (TFP) Variables (1) (2) (3) (4) (5) (6) TFP_LP TFP_LP TFP_OP TFP_OP Green_TFP Green_TFP treat_post 0.072*** 0.080*** 0.030 0.037* 0.002** 0.002** (0.022) (0.022) (0.020) (0.020) (0.001) (0.001) age 0.592*** 0.599*** 0.391*** 0.401*** 0.014*** 0.013** (0.101) (0.107) (0.089) (0.093) (0.005) (0.005) lev 0.894*** 0.759*** 0.597*** 0.486*** -0.017*** -0.021*** (0.070) (0.066) (0.063) (0.060) (0.003) (0.004) cash 0.793*** 0.682*** 0.783*** 0.667*** 0.049*** 0.042*** (0.072) (0.065) (0.070) (0.064) (0.006) (0.006) roa 1.783*** 1.922*** 1.570*** 1.676*** -0.121*** -0.123*** (0.118) (0.120) (0.112) (0.113) (0.010) (0.010) cdensity -0.194*** -0.177*** -0.025 -0.010 -0.006*** -0.005*** (0.016) (0.015) (0.016) (0.015) (0.001) (0.001) mshare -0.001*** -0.000 -0.000 (0.000) (0.000) (0.000) bigholder -0.157 -0.196** 0.006 (0.104) (0.089) (0.005) growth 0.005*** 0.004*** 0.000*** (0.000) (0.000) (0.000) finan_bind -0.330 -0.217 -0.023*** (0.202) (0.153) (0.008) tbq -0.014*** -0.003 0.001*** (0.005) (0.004) (0.000) YEAR CONTROL CONTROL CONTROL CONTROL CONTROL CONTROL Constant 8.399*** 7.061*** 5.297*** 4.362*** 0.041** -0.046 (0.320) (0.737) (0.300) (0.575) (0.018) (0.032) Observations 15,578 15,244 15,578 15,244 13,431 13,172 R-squared 0.401 0.501 0.349 0.451 0.088 0.100 Number of stkcd 2,350 2,348 2,350 2,348 2,087 2,086 7. Further Discussion 7.1 Regional differences: Eastern region vs. Central region vs. Western region There are differences in economic foundation, policy environment, and resource endowment among the eastern, central, and western regions of China, which have different impacts on the sustainable development of enterprises. The well-established market system and developed financial market in the eastern region have integrated the concept of sustainable development into production and operation process of enterprises earlier. As the core region of China's economic development, the eastern region focuses on supporting technology research and development, green and low-carbon, high-end industries in the development layout of intelligent manufacturing enterprises. Due to relatively lagging economic development compared to the eastern region, the central and western regions have slower market-oriented mechanisms and processes. Relying on the advantages of "low cost, abundant resources, and policy support for industrial transfer", they focus on laying out labor-intensive, resource-based, and other types of enterprises. The industrial characteristics of "resource dependence" and "environmental upgrading" in the central and western regions make the sustainable development strategy particularly urgent, and the impact of R&D support policies on the sustainable development of enterprises in the central and western regions may be more significant. 7.2 Differences in Enterprise Scale: Large Scale vs. Small Scale The scale of a company often reflects its economic strength. The size of the enterprise directly affects the impact of the R&D policy on the sustainable development performance of the enterprise. The sustainable development of enterprises requires the support of technological innovation, the investment of resources such as talent and high-end equipment. The scale of enterprises directly determines the ability to acquire resources and the intensity of investment, which is the core root of the impact on the sustainable development of different scales. Large scale enterprises have relatively mature management mechanisms and comprehensive innovation incentive mechanisms. Their high operational management efficiency and mature R&D innovation system occupy a favorable position in market competition. Large scale enterprises often lead industry development concepts, their high R&D level and environmental protection technology are more conducive to environmental (E) performance and social (S) responsibility fulfillment. Compared to small and medium-sized enterprises, large-scale enterprises are better able to digest and absorb the policy dividends. In the measurement of large-scale enterprises, we draw on the classification standards of the National Bureau of Statistics to define whether the enterprise's operating income exceeds 400 million yuan(about 56.72 million US dollars), and set a dummy variable scale. The regression results are shown in Table 8 . In the regression results, we can find that the promotion effect of the R&D policy on the sustainable development performance is more significant in the central and western regions and large-scale enterprises. It indicates that while pursuing economic development in the central and western regions, it is necessary to balance economic profitability, environmental compliance, and social responsibility. The comparative advantages of large-scale enterprises in technology and funding can better utilize the positive effects brought by the R&D policy and obtain policy support. Table 8 Regression Results of Regional Heterogeneity and Scale Heterogeneity Variables (1) (2) (3) (4) (5) sustainDe sustainDe sustainDe sustainDe sustainDe Enterprise's location region Enterprise Scale Eastern China Central China Western China Large-Scale Small-Scale treat_post 0.007 0.054*** 0.002* 0.014* 0.003 (0.009) (0.019) (0.021) (0.008) (0.018) age 0.085* 0.106 0.159 0.092** -0.155 (0.043) (0.094) (0.130) (0.040) (0.099) lev 0.010 -0.027 0.012 0.025 0.002 (0.019) (0.040) (0.032) (0.017) (0.021) cash 0.027 -0.094* -0.013 -0.001 -0.026 (0.023) (0.050) (0.050) (0.022) (0.059) roa 0.134*** 0.202*** 0.184** 0.210*** -0.006 (0.042) (0.077) (0.072) (0.037) (0.037) cdensity 0.007* 0.007 0.013 0.008** 0.004 (0.004) (0.008) (0.010) (0.004) (0.004) mshare -0.000** -0.001** -0.000 -0.000** -0.000* (0.000) (0.000) (0.000) (0.000) (0.000) bigholder -0.029 -0.174** -0.014 -0.063* 0.022 (0.037) (0.077) (0.069) (0.033) (0.050) growth -0.000 0.000 -0.000 -0.000 -0.000 (0.000) (0.000) (0.000) (0.000) (0.000) tbq 0.004** 0.003 0.008** 0.004** 0.000 (0.002) (0.003) (0.003) (0.002) (0.002) finan_bind -0.546*** -0.287** -0.450*** -0.558*** 0.015 (0.065) (0.120) (0.121) (0.065) (0.052) YEAR CONTROL CONTROL CONTROL CONTROL CONTROL Constant -2.122*** -1.224** -2.100*** -2.207*** 0.429 (0.253) (0.474) (0.565) (0.248) (0.277) Observations 10,233 2,925 2,056 13,811 1,403 R-squared 0.195 0.186 0.211 0.206 0.036 Number of stkcd 1,637 415 286 2,212 486 7.3 Capital intensity difference: high capital intensity vs. low capital intensity Capital intensity is a core indicator for measuring the ratio of capital input to labor input in enterprise production and operation, usually measured by the ratio of fixed assets to the number of employees or the ratio of enterprise capital to output. High capital intensive enterprises rely on large-scale investment in equipment, factories, technology research and development to drive production, while low capital intensive enterprises rely more on human resources and light asset operations. The core of sustainable development is to achieve long-term value growth under the three-dimensional goals of "economic benefits, environmental responsibility, and social responsibility", while capital intensity profoundly shapes the sustainable development path of enterprises by affecting their cost structure, innovation ability, risk resistance, and resource utilization efficiency. Capital intensity provides "hard support" for the sustainable development of enterprises by consolidating the production foundation, promoting technological upgrading and resource optimization. Compared with the production activities of enterprises with low capital intensity, which focus more on the investment of human capital, the policy should have a greater impact on improving the sustainable development performance with high capital intensity. To verify the theoretical inference, we measure the capital intensity of a company by the ratio of its total fixed assets to the number of employees, and rank this value. Companies above the median are defined as high capital intensity types, while those below the median are defined as low capital intensity types, and a dummy variable (cintency) is set. Table 9 reports the grouped regression results based on the height of enterprise capital intensity. It can be observed that the estimated coefficient of the interaction term (Treat × Post) is significantly positive in the sample group with high capital intensity, but not significant in the sample group with low capital intensity. The regression results indicate that the R&D policy has a stronger effect on improving the sustainable development performance in capital intensive enterprises. 7.4 Industry technology update speed difference: fast technology update speed vs. slow technology update speed The speed of technological change reflects the exposure to cutting-edge new technologies. For enterprises in industries with fast technological change rates, the R&D policy has a more significant role in promoting innovation, and may have a greater impact on the total factor productivity, thereby having a more significant impact on their sustainable development. The reason is that enterprises in these industries need to timely grasp market changes and technological progress information of peers, in order to improve production and operation efficiency to cope with more intense market competition. Therefore, the R&D policy has brought about improvements in the sustainable development performance of enterprises, its impact on enterprises with different technological update speeds is relatively different. Following the approach of Shen et al. ( 2024 ), we consider manufacturing industries such as computers, communications, other electronic devices, and electrical machinery, as companies with fast technological changes in the industry, while other manufacturing enterprises are considered as companies with slow technological changes, and represent them as dummy variables (techupdate). The specific regression results are shown in Table 9 . As expected, the results indicate that the R&D policy has a greater promoting effect on the sustainable development performance (sustainDe) in industries with rapid technological change. It indicates that companies in industries with fast technological changes are more sensitive to research and development innovation, promote innovation strategies, and enhance the sustainable development performance of enterprises. Table 9 Regression Results of Heterogeneity in Capital Intensity, Labor Intensity, and Industry Technological Change Speed Variables (1) (2) (3) (4) (5) (6) sustainDe sustainDe sustainDe sustainDe sustainDe sustainDe Capital Intensity Labor Intensity Industry Technology Update Speed High Low High Low Fast Slow treat_post 0.024** -0.005 -0.004 0.028** 0.022* 0.014 (0.012) (0.012) (0.012) (0.011) (0.040) (0.009) age 0.134** 0.039 0.053 0.113** 0.096 0.080* (0.059) (0.055) (0.053) (0.057) (0.063) (0.047) lev 0.003 -0.002 -0.002 -0.002 -0.031 0.015 (0.020) (0.023) (0.023) (0.021) (0.032) (0.018) cash 0.000 -0.021 -0.014 -0.001 0.115*** -0.047** (0.030) (0.028) (0.028) (0.030) (0.038) (0.023) roa 0.220** 0.191*** 0.125** 0.146*** 0.120** 0.181*** (0.034) (0.042) (0.051) (0.032) (0.057) (0.040) cdensity 0.006 0.007 0.011* 0.010 0.006 0.008* (0.008) (0.006) (0.006) (0.007) (0.006) (0.004) mshare -0.000* -0.000*** -0.000*** -0.000 -0.000** -0.000* (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) bigholder -0.077* -0.043 -0.030 -0.070 -0.089 -0.049 (0.043) (0.046) (0.046) (0.043) (0.068) (0.034) growth 0.000 -0.000*** -0.000*** 0.000 -0.000 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) finan_bind -0.413*** -0.623*** -0.609*** -0.443*** -0.505*** -0.503*** (0.081) (0.078) (0.077) (0.082) (0.100) (0.065) tbq 0.005** 0.004* 0.003 0.006*** 0.004 0.005*** (0.002) (0.002) (0.002) (0.002) (0.003) (0.002) YEAR CONTROL CONTROL CONTROL CONTROL CONTROL CONTROL Constant -1.733*** -2.275*** -2.306*** -1.852*** -1.964*** -1.981*** (0.333) (0.304) (0.304) (0.328) (0.383) (0.256) Observations 7,507 7,707 7,591 7,623 3,943 11,271 R-squared 0.218 0.165 0.166 0.217 0.176 0.198 Number of stkcd 1,511 1,672 1,640 1,502 649 1,743 8 Research Conclusions and Policy Recommendations The R&D innovation strategy helps enterprises improve production efficiency, enhance market competitiveness, promote green production, assist enterprises in developing energy-saving and emission reduction technologies,promote enterprises’ development towards green manufacturing. This is the key to achieving sustainable development. Continuous research and development innovation can enable enterprises to keep up with market trends.This article uses a sample of Chinese listed manufacturing companies from 2010 to 2020 to identify policy effects through a difference in differences model, and explores the impact and mechanism of R&D support policies on sustainable development of enterprises. The study finds that the R&D policy can significantly improve intelligent manufacturing enterprises’ sustainable development performance. The conclusion remains valid after a series of robustness tests, including parallel trend test, placebo test, propensity score matching, and replacement of enterprise sustainable development indicators. Mechanism tests reveal that R&D support policies improve the sustainable development performance by alleviating corporate financing constraints, enhancing the innovation level, and increasing the total factor productivity (TFP). Heterogeneity tests show that the R&D policy has a more significant impact on the enterprises that feature fast industry technology update speed, high capital intensity, non-state ownership, and large scale. The research conclusions of this paper provide valuable references to the development of intelligent manufacturing enterprises,providing Chinese experience for sustainable development in other countries and regions. Based on the above research conclusions, the article proposes the following policy recommendations: (1)Increase research and development funding support. The government should explore the establishment of a special research and development fund for intelligent manufacturing, focusing on supporting enterprises to carry out core technology research and development, providing high funding for eligible projects, and alleviating the financial pressure on enterprise research and development. Implement tax preferential policies and additional deduction policies for R&D investment of intelligent manufacturing enterprises, encourage enterprises to increase R&D investment, and explore import tariff reduction and exemption support for intelligent manufacturing R&D equipment purchased. (2)Promote innovation and application of key technologies. In response to the bottleneck technologies in the field of intelligent manufacturing, such as high-end sensors, industrial software, organize and implement national science and technology major projects, concentrate the advantageous forces of universities, research institutions, and enterprises to jointly tackle and accelerate the localization process of core technologies. Encourage enterprises to deeply integrate new technologies such as artificial intelligence, big data,the Internet of Things with manufacturing technology, and promote the integration and application of new technologies. Support enterprises to carry out innovation application scenarios based on new technologies, and provide financial rewards and policy support for related demonstration projects. (3)Strengthen research and innovation in green manufacturing. Support enterprises to carry out green technology research and development, establish a special project for green manufacturing research and development, support the development of energy-saving, consumption reducing, resource recycling technologies, provide subsidies and support to enterprises whose research and development achievements have reached the international advanced level. Develop standards and specifications related to green design, promote the concept of green design, guide enterprises to fully consider environmental factors in product design, give priority support to government procurement for products certified by green design, and improve market recognition of green products. This paper has several limitations. First, the research sample is restricted to listed smart manufacturing enterprises in China, the conclusions drawn may not be fully generalizable to the broader population of Chinese smart manufacturing enterprises, especially small and medium-sized non-listed firms.Second, the measurement of key variables, particularly the sustainable development of enterprise, relies on secondary data from listed company financial reports, it may not fully capture the nuanced dimensions of these constructs. This reliance on quantitative secondary data may limit the depth of understanding regarding the mechanisms linking R&D policy.Third, the study does not explore the long-term dynamic effects of the R&D policy. It remains unclear whether this effect persists, diminishes, or evolves over time. Long-term tracking of enterprises’ sustainable development trajectories post-policy implementation would be necessary to assess the policy’s sustained effectiveness.Therefore, subsequent studies can focus on an in-depth analysis of the relationship between the strategy with the changes in intelligent manufacturing enterprises’ sustainable development. Disclosure statement No potential conflict of interest was reported by the author(s). Declarations Funding This work was supported by the Major Program of the National Social Science Foundation of China under Grant No. 24BJY047. Data availability statement The data underlying this study are available from the CSMAR, WIND, and CNRDS databases. Readers can access these datasets through the following websites: https://www.gtarsc.com/ ., https://www.wind.com.cn/ ., and https://www.cnrds.com/ . References Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy , 128 (6), 2188–2244. 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A study on the impact of senior executives'green cognition and enterprises'green behavior on enterprises'green performance: An empirical analysis based on data of light industry enterprises in Shandong. East China Economic Management , 33 (12), 35–41. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8410172","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585432129,"identity":"6b7dcee2-9b63-4217-9b81-b83a0b89cf48","order_by":0,"name":"Mingli Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYDACZiB+YMDAA2QdOPDhB7FaEgwMgFrYEg/O7CHWpgQGAyDJY3yYg40I1brtvIdfJBT8kTG4kfPhMNB98vxiB/BrMTvMl2YBcpjBjdwNhwssGAxnzk4gpIXHzACuZQYP0F+3ideS8+AwDxtxWowfQLUwEK3FDKjMmEfyzDMDYCBLEOGX82eMP3z4I2fPdzz58YcPP2zk+aUJaAECNgkQqXAAzJEgqBwEmD+ASPkGohSPglEwCkbBSAQAwDxEzuRCf80AAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0000-8168-7710","institution":"Jiangsu College of Engineering and Technology","correspondingAuthor":true,"prefix":"","firstName":"Mingli","middleName":"","lastName":"Chen","suffix":""},{"id":585432130,"identity":"fd50636d-e88e-407e-9a02-b435344a8fe8","order_by":1,"name":"Han Xu","email":"","orcid":"","institution":"Jiangsu College of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Han","middleName":"","lastName":"Xu","suffix":""},{"id":585432131,"identity":"0fe7b784-7db1-42ef-bb90-093a06a5c706","order_by":2,"name":"Fa Tian","email":"","orcid":"","institution":"University of Shanghai for Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Fa","middleName":"","lastName":"Tian","suffix":""},{"id":585432132,"identity":"27fd58e7-fd23-4d69-968c-a51da44a14fe","order_by":3,"name":"Li Ji","email":"","orcid":"","institution":"University of Shanghai for Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Ji","suffix":""}],"badges":[],"createdAt":"2025-12-20 07:08:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8410172/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8410172/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102044681,"identity":"ca24928f-183b-4264-ae7f-c9f2597b6d74","added_by":"auto","created_at":"2026-02-06 13:42:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30753,"visible":true,"origin":"","legend":"\u003cp\u003eMechanism framework:the conceptual framework linking the R\u0026amp;D Innovation Strategy to enterprise sustainable development.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8410172/v1/41726670651740507d9acff5.png"},{"id":102044764,"identity":"a8b1f696-84e7-47d3-9b4b-3fca03f809a6","added_by":"auto","created_at":"2026-02-06 13:42:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79578,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParallel Trend Test\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8410172/v1/b80fc6d9e3816591a9dde0c8.png"},{"id":102044705,"identity":"b8169f03-edaa-4454-a001-a55480dd69a5","added_by":"auto","created_at":"2026-02-06 13:42:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":53737,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePlacebo Test\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8410172/v1/24f132cc6546c93a268f89ad.png"},{"id":106728054,"identity":"39ca57a2-83c4-47ee-9515-d0bde652c80d","added_by":"auto","created_at":"2026-04-12 18:41:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2905764,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8410172/v1/3bd450eb-c990-40ed-b1f9-9c92fbca866f.pdf"}],"financialInterests":"","formattedTitle":"The Impact of R\u0026amp;D Innovation Strategy on the Sustainable Development of Intelligent Manufacturing:evidence from a quasi-natural experiment in China","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe concept of sustainable development requires enterprises to move beyond mere scale expansion and instead shift toward an innovation-driven model, emphasizing green and low-carbon practices, achieving the coordinated integration of social responsibility and economic benefits(Krajnc and Glavič P, 2005;Groschl, Gabaldon, and Hahn,2019). When enterprises uphold the concept of sustainable development, they will focus on R\u0026amp;D investment, cultivate and attract innovative talents, which helps reduce energy and resource consumption and pollutant emissions.However, enterprises' increased investment in areas such as scientific and technological R\u0026amp;D and environmental compliance will significantly raise their economic burden(Bolton and Kacperczyk,2021༛Gantchev, Giannetti, and Li,2022༛Zhao and Zhang,2024). Therefore, how to achieve the coordination of economic benefits and environmental governance while practicing the concept of sustainable development has become an important issue that urgently needs to be solved at present.\u003c/p\u003e \u003cp\u003eIntelligent manufacturing refers to the process of driving the comprehensive upgrading of the manufacturing industry by leveraging technologies such as artificial intelligence and digitalization.It is characterized by digitalization, intelligentization, business integration, and innovation(Qi and Xiao,2020). On one hand, through replacing manual labor with automated equipment and conducting precise data analysis, it enhances production efficiency, lowers operational costs(Mikalef,2020), improves innovation capabilities(Joshi et al.,2010), promotes enterprises' green technological innovation and improves ecological environment(Mahmudul Alam and Wahid Murad,2020;Shen and Zhang,2023;Bendig et al.,2023); on the other hand, it drives enterprises to transform from \"product manufacturing\" to \"providing products\u0026thinsp;+\u0026thinsp;services\", personalized customized production can also increase product added value(Muller and Voigt,2018༛L\u0026uuml; et al.,2023༛Huang et al.,2024). With the comprehensive advancement of enterprises' intelligent transformation, systematically exploring the sustainable development paths of intelligent manufacturing enterprises and the operational mechanisms will provide important policy references for China and other countries.\u003c/p\u003e \u003cp\u003eExisting literature has extensively explored the influencing factors of corporate sustainable development performance from the external corporate environment perspectives(Shi and Xu,2018;Chen et al.,2021༛Song and Jin,2023༛Wu,2024) and internal corporate factors(Nayak and Venkatraman,2011༛Groschl, Gabaldon, and Hahn,2019༛Wang, Tan, and Li,2023༛Wei and Tian,2025). However, the review of existing studies reveals that no scholars have examined the impact of R\u0026amp;D support policies on intelligent manufacturing enterprises\u0026rsquo; sustainable development performance.\u003c/p\u003e \u003cp\u003eThe most direct effect of China's policy of additional deduction for R\u0026amp;D expenses before tax, implemented in 2015, is to narrow the corporate income tax base. The policy can effectively reduce the corporate income tax burden and increase the operating cash flow. As the main force of innovation and the primary beneficiaries of the additional deduction policy for R\u0026amp;D expenses, intelligent manufacturing enterprises can leverage the policy to alleviate financing constraints, enhance R\u0026amp;D capabilities, improve total factor productivity, and promote sustainable development. Therefore, exploring how to improve intelligent manufacturing enterprises\u0026rsquo; sustainable development performance and the underlying mechanism is conducive to driving industrial transformation and upgrading the sustainable development strategy.\u003c/p\u003e \u003cp\u003eAgainst this backdrop, the study treats the policy of additional deduction for R\u0026amp;D expenses as a \"quasi-natural experiment\". Using data of Chinese A-share listed manufacturing enterprises from 2010 to 2020 as the sample, adopts the difference-in-differences (DID) method to explore the impact of the R\u0026amp;D policy on intelligent manufacturing enterprises\u0026rsquo; sustainable development performance and underlying mechanism. The study finds that the R\u0026amp;D policy can significantly improve intelligent manufacturing enterprises\u0026rsquo; sustainable development performance. The conclusion remains valid after a series of robustness tests, including parallel trend test, placebo test, propensity score matching, and replacement of enterprise sustainable development indicators. Mechanism tests reveal that R\u0026amp;D support policies improve the sustainable development performance by alleviating corporate financing constraints, enhancing the innovation level, and increasing the total factor productivity (TFP). Heterogeneity tests show that the R\u0026amp;D policy has a more significant impact on the enterprises that feature fast industry technology update speed, high capital intensity, non-state ownership, and large scale.\u003c/p\u003e \u003cp\u003eCompared with existing studies, the potential contributions of this study are as follows: First, the study is first to focus on intelligent manufacturing enterprises\u0026rsquo; sustainable development performance. Drawing on existing research (Xie and Zhu, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the study uses comprehensive indicators of economic performance and environmental performance to measure the sustainable development performance. On the one hand, the performance model can reflect enterprises' operational financial performance and market competitiveness; on the other hand, it can reflect enterprises' fulfillment of social responsibilities in terms of external environmental performance, to better evaluate the external manifestation of enterprises' sustainable development. By integrating indicators of economic performance and environmental performance, the study conducts an in-depth analysis of the R\u0026amp;D policy on the sustainable development performance, expanding a new analytical dimension for relevant research.\u003c/p\u003e \u003cp\u003eSecond, on the basis of testing the alleviation of financing constraints serves as a mechanism, the study further explains whether the R\u0026amp;D policy promotes enterprises' sustainable development performance by advancing enterprises' innovation strategies and increasing total factor productivity (TFP). By focusing on the impact path of \"the R\u0026amp;D policy \u0026ndash; enhancing enterprises' innovation capabilities and TFP \u0026ndash; enterprises' sustainable development performance\", the study enriching the logical chain of how the R\u0026amp;D policy influences enterprises' sustainable development performance.\u003c/p\u003e \u003cp\u003eThird, the study conducts an in-depth analysis of the heterogeneous impact of the R\u0026amp;D policy on the sustainable development performance in different industries. It reveals the differences of the policy's impact with varying technological update speeds, capital intensity, labor intensity, and enterprise scales. This provides theoretical support for intelligent manufacturing enterprises to vigorously promote sustainable development strategies.\u003c/p\u003e \u003cp\u003eFourth, it provides firm-level evidence from a major developing country. The research not only contributes to the literature on the dynamic determinants of corporate sustainable development (Jamal et al.,2021;Pedersen et al.,2021;DEL R\u0026Iacute;O CASTRO et al.,2021),but also adds new content on the economic impacts of institutional reforms related to R\u0026amp;D expense-related tax incentives(Agrawal ,Rosell, and Simcoe,2020༛Ge and Zhong,2025), such as tax deductions and tax credits. The research conclusions can provide policy implications and reform references for other economies.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"2. Theoretical Analysis and Research Hypotheses","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Theoretical Analysis\u003c/h2\u003e \u003cp\u003eSustainable development refers to a business philosophy and approach where enterprises pursuing optimal financial performance, focus on balancing three core needs: economic growth, environmental responsibility, and social contribution. In achieving business goals, enterprises should reduce environmental impact or create environmental benefits through product or service provision,realizing the long-term development, society, and the environment. Existing studies mostly focus on two aspects: the evaluation of corporate sustainable development performance and the factors influencing corporate sustainable development.\u003c/p\u003e \u003cp\u003e(1) Literature related to the evaluation of corporate sustainable development performance. Van Marrewijk (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) argues that corporate sustainability refers to addressing the needs of stakeholders while paying attention to the social and environmental impacts of corporate operations. Scholars have attempted to comprehensively evaluate corporate sustainability from three dimensions: economy, environment, and social responsibility (Krajnc and Glavič P, 2005; Steurer et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Alexopoulos et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) ,Xie and Zhu (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) measured corporate sustainable development performance using corporate financial performance and environmental-social responsibility performance. The indicator can reflect an enterprise\u0026rsquo;s profit-generating capacity, ensuring its long-term survival in the market; and it can reflect an enterprise\u0026rsquo;s production technology level, helping to reduce its burden on ecological environment. This enables a more comprehensive assessment of whether enterprise\u0026rsquo;s production complies with the requirements of sustainable development strategies.\u003c/p\u003e \u003cp\u003e(2) Literature related to the factors influencing corporate sustainable development performance. From the perspective of external corporate factors, policy instruments such as green industry policies(Chen et al.,2021), central environmental inspection policies(Zhang and Ye,,2023), green credit policies(Jiang and Qin,2022), low-carbon city pilots(Wang and Wang,2022), the transformation of environmental protection fees into taxes(Mao,2024), and environmental regulations(Yu,Ramanathan, and Nath,2017)have all been proven to improve sustainable development performance.\u003c/p\u003e \u003cp\u003eAt the internal corporate factors level, including enterprise scale expansion(Nayak and Venkatraman,2011), executives' green awareness(Zou et al.,2019), CEO cognitive complexity(Groschl, Gabaldon, and Hahn,2019), the application of digital technologies(Wang, Tan, and Li,2023), and digital transformation have been confirmed to exert a positive impact on corporate sustainable development performance. Additionally, new-quality productive forces can enhance corporate sustainable development performance and have a positive effect on green innovation(Wang and Li,2025). In contrast, the misallocation of asset structure will significantly reduce corporate sustainable development performance(Wei and Tian,2025).\u003c/p\u003e \u003cp\u003eThe review of existing studies shows that most research is conducted from external environment perspectives or internal corporate characteristics. Few studies have discussed the influence of R\u0026amp;D support policies on intelligent manufacturing enterprises\u0026rsquo; sustainable development. R\u0026amp;D support policies exert a crucial impact on enterprises' innovative behaviors. The implementation of innovation strategies, on one hand, encourages enterprises to adopt advanced technologies and methods,significantly enhances production efficiency; on the other hand, the application of high-end equipment and intelligent information devices can effectively reduce environmental pressure, improve total factor productivity (TFP), thus affect corporate sustainable development performance.\u003c/p\u003e \u003cp\u003eThe policy of additional deduction for R\u0026amp;D expenses may empower intelligent manufacturing enterprises\u0026rsquo; sustainable development through the following channels: First, through tax deductions and supporting funds, it alleviates the pressure of internal and external resource constraints, improves the efficiency of corporate resource allocation, provides a capital channel for the sustainable development strategies. Second, the policy encourages enterprises to increase R\u0026amp;D investment, improve corporate capital investment and hardware resources required for innovation, enhance innovation level of corporate production, thereby providing innovation support for the sustainable development strategies. Third, by influencing R\u0026amp;D investment and innovation output,the R\u0026amp;D support policies can promote enterprises' TFP. The improvement of corporates\u0026rsquo; TFP implies a reduction in resource consumption and an increase in production efficiency, which significantly enhances enterprises' market competitiveness and provides a driving foundation for corporate sustainable development.\u003c/p\u003e \u003cp\u003eBased on the above analysis, this study proposes \u003cb\u003eHypothesis 1: The policy of additional deduction for R\u0026amp;D expenses is conducive to the improvement of intelligent manufacturing enterprises\u0026rsquo; sustainable development performance.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Analysis of the Mechanism of Action\u003c/h2\u003e \u003cp\u003e(1) Financing Constraint Alleviation Channel: Capital Channel\u003c/p\u003e \u003cp\u003eThe resource allocation theory posits that by increasing support for enterprises' R\u0026amp;D investment, government guides more capital to flow into technological innovation and adjusts innovation resources to exert a resource allocation effect (Wen, Meng, and Zhang, 2018). Financing constraints not only reduce enterprises' market competitiveness but also hinder their innovative development(Gong,Lu, and Lin,2023), posing a threat to sustainable development. Limited internal resources of the company will be allocated to achieving corporate financial performance, while the fulfillment of social responsibilities and environmental obligations is neglected. The adversely affects enterprises' social and environmental performance, which in turn impacts sustainable development(Lai,Yue, and Chen,2021;Wei and Tian,2025). Facing financing constraints forces enterprises to bear higher capital costs(Wen, Wang, and Yu,2024), all these factors are detrimental to enterprises' sustainable development.\u003c/p\u003e \u003cp\u003eThe essence of financing constraints lies in the insufficiency of external capital supply or the restriction of internal capital accumulation, which results in the failure to fill the capital gap required for R\u0026amp;D and ultimately inhibits R\u0026amp;D investment either directly or indirectly. Compared with external financing that incurs higher capital costs, internal financing features lower capital costs. The R\u0026amp;D policy encourages enterprises to increase R\u0026amp;D investment and enhance innovation capabilities, which in turn attracts more attention from investors. For venture capitalists, they are more willing to invest in enterprises with innovative vitality and development potential. The innovation advantages demonstrated by intelligent manufacturing enterprises will make them high-quality targets in the eyes of investors, facilitating enterprises to obtain funds through equity financing. Furthermore, the government's policy support enables investors to perceive the promising prospects of industrial development, strengthens enterprises' ability to attract external investment (Yin and Li, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Han et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), alleviates financing constraints.\u003c/p\u003e \u003cp\u003eThrough the R\u0026amp;D support policy, government demonstrates its supportive orientation toward intelligent manufacturing industry. Financial institutions will adjust their credit strategies in accordance with the policy orientation and allocate more financial resources to intelligent manufacturing enterprises (Tian, Xia, and Xu, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As enterprises' innovation capabilities improve, their market competitiveness and profitability will also be enhanced. This enables enterprises to rely on better business prospects and expected returns, making it easier to gain recognition and financial support from financial institutions.\u003c/p\u003e \u003cp\u003eBased on the above analysis, this study proposes \u003cb\u003eHypothesis 2: The policy of additional deduction for R\u0026amp;D expenses promotes the improvement of intelligent manufacturing enterprises' sustainable development performance by alleviating financing constraints.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(2) R\u0026amp;D Capability Enhancement Channel: Innovation Channel\u003c/p\u003e \u003cp\u003eR\u0026amp;D and innovation capability is a crucial factor influencing corporate sustainable development (Zhao et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Technological progress is the outcome of R\u0026amp;D and innovation, the high-risk nature of R\u0026amp;D dictates sustained capital input is an important guarantee for innovation activities (Song and Liu, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The capital supply effect of the R\u0026amp;D policy can alleviate intelligent manufacturing enterprises\u0026rsquo; financing difficulties, prompting them to increase R\u0026amp;D investment and enhance innovation capabilities (Xu and Feng, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), thereby influencing enterprises' sustainable performance.\u003c/p\u003e \u003cp\u003eR\u0026amp;D investment is characterized by high risk, high uncertainty, long cycles, and strong asset specificity(An, Wei, and Shu,2020),essentially, corporate R\u0026amp;D investment is a capital-intensive activity that requires continuous cash flow support.The government's active introduction of tax incentives for additional deduction of R\u0026amp;D expenses shares the R\u0026amp;D costs of enterprises and stimulates their enthusiasm for innovation. By leveraging innovation incentive policies to relax enterprises' resource constraint conditions, the government has effectively promoted corporate innovation in the short term (Bloom, Reenen, and Williams, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Finally, the tax incentives guide enterprises to engage in innovation-aligned behaviors(Sun, Zhou, and Zhang,2021), attract more resources to converge toward enterprises, provide sound policy support for enterprises' R\u0026amp;D strategies.\u003c/p\u003e \u003cp\u003eIn terms of corporate human capital, high-skilled labor engaged in R\u0026amp;D and production can significantly promote enterprises' innovation output(Audia and Goncalo,2007;Kong,2025). To a certain extent, R\u0026amp;D support policies reduce the actual employment costs of technical personnel(Chen,Lin, and Zhang,2020), lowering the marginal costs of innovation activities. It gives enterprises greater incentive to hire high-education and high-quality skilled personnel,further enhances corporate sustainable development.\u003c/p\u003e \u003cp\u003eBased on the above analysis, this study proposes \u003cb\u003eHypothesis 3: The policy of additional deduction for R\u0026amp;D expenses improves intelligent manufacturing enterprises\u0026rsquo;s sustainable development performance by enhancing their innovation capabilities.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(3) Total Factor Productivity (TFP) Enhancement Channel: TFP Channel\u003c/p\u003e \u003cp\u003eCorporate total factor productivity (TFP) is a key indicator of corporate development(Wong and Chen, 2023). It reflects changes in enterprises' technological innovation, management capabilities, labor quality, factor allocation efficiency, organizational effectiveness, and exerts a significant impact on corporate sustainable development. R\u0026amp;D investment and innovation output are the key factors determining a company\u0026rsquo;s TFP (Cao et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). An increase in TFP means that enterprises can achieve higher output with the same level of input, which can lead to lower costs and higher profits, enhance enterprises\u0026rsquo; competitiveness, and lay a solid economic foundation for corporate sustainable development. Therefore, the impact of R\u0026amp;D support policy on corporates\u0026rsquo; TFP is an important factor influencing corporate sustainable development. The policy affects enterprises\u0026rsquo; TFP through the following two aspects:\u003c/p\u003e \u003cp\u003eFirst, it enhances TFP by integrating into their R\u0026amp;D processes. The R\u0026amp;D policy incentivizes enterprises to increase R\u0026amp;D investment(Song and Liu,2021). The demand for high-quality human resources driven by R\u0026amp;D strategies encourages enterprises to recruit highly educated and high-skilled talents, which facilitates corporate knowledge accumulation and the optimization of human capital structure (Dai and Zhao, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The improvement of knowledge stock not only helps enterprises absorb advanced technologies and strengthen independent innovation capabilities but also enables enterprises to identify technical bottlenecks and innovation opportunities,break through existing technological barriers. The upgrading of corporate human capital can also promote the integration of cross-departmental resources in R\u0026amp;D, management, and production, enhance R\u0026amp;D efficiency and innovation level, further drive the improvement of TFP.\u003c/p\u003e \u003cp\u003eSecond, it enhances TFP by integrating into manufacturing processes. In the manufacturing process, intelligent manufacturing enterprises mainly drive the improvement of TFP through approaches such as introducing high-end intelligent equipment (Shen, Qiao, and Lin,2024)and optimizing the human capital structure(Liang, Liang, and Qi,2024) to achieve a high level of collaborative production. The specific impact mechanism of R\u0026amp;D support policies is as follows: First, by alleviating financing constraints, the R\u0026amp;D policy encourages intelligent manufacturing enterprises to increase investment in intelligent software and hardware equipment. It enables enterprises to achieve accurate matching with enterprises in all links of the industrial chain during the production process,promotes TFP growth. Second, the policy's support incentivizes intelligent manufacturing enterprises to recruit highly educated and high-skilled talents. According to human capital theory, when workers' knowledge and skills match the job requirements, enterprises' production efficiency can be maximized. The employment of high-skilled talents reduces the demand for low-skilled and repetitive labor, realizes the accurate matching and efficient supply of production factors, optimizes overall resource allocation of enterprises(J\u0026uuml;ttner and Wehrli,2011;Acemoglu et al,2020༛Yao, Zhang, and Guo,2024).\u003c/p\u003e \u003cp\u003eBased on the above analysis, the study proposes \u003cb\u003eHypothesis 4: The policy of additional deduction for R\u0026amp;D expenses promotes improvement of intelligent manufacturing enterprises\u0026rsquo; sustainable development performance by increasing total factor productivity (TFP).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBuilding on the theoretical analysis,the direction and interaction of these mechanisms necessitate empirical validation. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the conceptual framework linking the R\u0026amp;D Innovation Strategy to enterprise sustainable development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Research Design","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Specification of the Econometric Model\u003c/h2\u003e \u003cp\u003eTo test the impact of the 2015 policy of additional deduction for R\u0026amp;D expenses on the sustainable development of intelligent manufacturing enterprises, we draw on the methodology of existing studies (Huang et al., 2023; Shen et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and construct a difference-in-differences (DID) model for empirical regression analysis:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{sustainD}}{{\\text{e}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003eAmong them, the subscripts i and t represent the enterprise and year respectively. The explained variable sustainDe denotes the sustainable development of intelligent manufacturing enterprise i in year t. The core variable Treat is defined as follows: enterprises whose industry falls into the ten key supported fields specified in the Made in China 2025 industrial policy are identified as samples of intelligent manufacturing enterprises, in which case Treat equals 1; otherwise, it equals 0. Post equals 1 if the year is greater than or equal to 2015, and 0 otherwise. The policy variable of interest in this paper is the interaction term Treat\u0026times;Post, where Treat is the treatment variable and Post is the policy shock variable. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\theta\\)\u003c/span\u003e\u003c/span\u003e is the regression coefficient that the paper focuses on primarily. If the estimated coefficient \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\theta\\)\u003c/span\u003e\u003c/span\u003e is positive, it indicates that the implementation of the R\u0026amp;D policy is conducive to improving the sustainable development level. This paper also controls for a series of variables related to enterprise-level characteristics, as well as enterprise fixed effects (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mu _{\\text{i}}}\\)\u003c/span\u003e\u003c/span\u003e) and time fixed effects (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\gamma _{\\text{t}}}\\)\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Variable Definition\u003c/h2\u003e \u003cp\u003eCorporate Sustainable Development Performance(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{sustainDe}}\\)\u003c/span\u003e\u003c/span\u003e). Following existing studies (Chen, Li, and Lu, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Xie and Zhu, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we measure the level of corporate sustainable development from two dimensions: the financial dimension (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Feco}}\\)\u003c/span\u003e\u003c/span\u003e) and the environmental dimension (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Envro}}\\)\u003c/span\u003e\u003c/span\u003e). For the financial dimension, we use the enterprise\u0026rsquo;s Return on Total Assets (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{ROA}}\\)\u003c/span\u003e\u003c/span\u003e) for measurement; for the environmental dimension, referring to the research (Zhang and Yu, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), we use the environmental score item in the China Securities Index (CSI) ESG Index for measurement.\u003c/p\u003e \u003cp\u003eWe adopt Method \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({{\\text{Y}}^*}= Y-{\\text{min}} / {\\text{max}}-{\\text{min}}\\)\u003c/span\u003e\u003c/span\u003e to perform 0\u0026ndash;1 standardization on Variables \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Feco}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Envro}}\\)\u003c/span\u003e\u003c/span\u003e, and then combine the standardized \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Feco}}\\)\u003c/span\u003e\u003c/span\u003e with \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Envro}}\\)\u003c/span\u003e\u003c/span\u003e to form the sustainable development performance indicator (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{sustainDe}}\\)\u003c/span\u003e\u003c/span\u003e), denoted as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{sustain}}D{\\text{e}}= 1-|F{\\text{eco}}-E{\\text{nvro}}| \\times F{\\text{eco}} \\times E{\\text{nvro}}/1\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTo account for the impact of other factors on the empirical results of this paper, we select a series of firm-level control variables. With reference to existing literature, the control variables we choose include: firm age (age), measured as the natural logarithm of the difference between the fiscal year and the firm's founding year; return on assets (roa), calculated as the ratio of net profit to total assets; firm leverage (lev), measured as the ratio of total liabilities at the end of the year to total assets; operating cash flow level (cash), calculated as the ratio of net cash flow from operating activities to total assets; firm growth (growth), measured by the annual growth rate of the firm's operating income; firm capital intensity (density), measured as the natural logarithm of the ratio of total fixed assets to total number of employees; firm value (tbq, Tobin's Q); management shareholding index (mshare), measured by the proportion of shares held by management; the shareholding ratio of the largest shareholder (bigholder), measured by the shareholding ratio of the largest shareholder; and firm financing constraint index (finan_bind, SA index).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sample Selection and Descriptive Statistics of Variables\u003c/h2\u003e \u003cp\u003eThis study uses data of manufacturing listed companies on the Shanghai and Shenzhen A-shares from 2010 to 2020. Firm-level characteristic data and financial data are mainly obtained from the WIND and CSMAR (China Stock Market \u0026amp; Accounting Research) databases. Two reasons are considered for the time range of the sample data: first, the Notice on the Policy of Additional Deduction for Enterprise R\u0026amp;D Expenses was officially implemented in 2015, and a 5-year time window before and after the policy implementation not only ensures the adequacy of the sample but also avoids the policy confusion effect caused by an excessively long time span; second, in consideration of the impact of the COVID-19 pandemic, the data is selected up to 2020. To ensure the rationality of data quality, consistent with existing studies, we conduct the following processing on the initial data: (1) This paper selects data of manufacturing listed companies and excludes irrelevant data of financial and other industries; (2) Delete data of companies with a short listing period and missing financial data; (3) To address the issue of outliers in the sample data, this paper conducts a 1% winsorization on continuous variables. The descriptive statistics results of the main variables in this paper are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics of Main Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESG_Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e73.820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnviron_Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial_Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-6.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eroa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-60.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e113.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.726\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emshare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68.596\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-3.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esoe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Empirical Results and Analysis","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Impact of the R\u0026amp;D Policy on Corporate Sustainable Development: Baseline Regression\u003c/h2\u003e \u003cp\u003eWe use the above Eq.\u0026nbsp;(1) to test the impact of the 2015 R\u0026amp;D policy on the sustainable development of intelligent manufacturing enterprises. The baseline regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In Column (1), we only include the interaction term(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Treat}} \\times {\\text{Post}}\\)\u003c/span\u003e\u003c/span\u003e). It can be found that the estimated coefficient of the interaction term (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Treat}} \\times {\\text{Post}}\\)\u003c/span\u003e\u003c/span\u003e)with corporate sustainable development performance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{sustainDe}}\\)\u003c/span\u003e\u003c/span\u003e) is 0.021, it passes the significance test at the 1% level. This indicates that the 2015 R\u0026amp;D policy can significantly improve the sustainable development level of intelligent manufacturing enterprises, verifying the research hypothesis.\u003c/p\u003e \u003cp\u003eConsidering that Column (1) does not include sufficient control variables, we gradually add control variables in Columns (2), (3), and (4) to mitigate potential biases in the difference-in-differences (DID) estimation results. The regression coefficients of the interaction term (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Treat}} \\times {\\text{Post}}\\)\u003c/span\u003e\u003c/span\u003e) and corporate sustainable development performance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{sustainDe}}\\)\u003c/span\u003e\u003c/span\u003e) remain significantly positive and meet the significance level test. The results still support the research conclusions.Taking Column (3), where all control variables are included, as an example to explain the economic significance of the estimated coefficient of the interaction term(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Treat}} \\times {\\text{Post}}\\)\u003c/span\u003e\u003c/span\u003e): a coefficient of 0.018 means that the 2015 R\u0026amp;D policy increases the sustainable development performance of enterprises in the treatment group by 1.8% compared with those in the control group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe Impact of the Additional Deduction Policy for R\u0026amp;D Expenses on Enterprise Sustainable Development: Baseline Regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.021***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.148***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.125***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.088**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.026*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emshare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.069**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.497***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.054)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.116***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.268***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.232**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.944***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.092)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.212)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15,214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Robustness Tests","content":"\u003cp\u003eWe further examine the robustness of the research conclusions of this paper from the perspectives of dynamic effect test, placebo test, propensity score matching (PSM), and replacement of corporate sustainable development performance indicators(ESG_Rate, Environ_Rate, Social_Rate).\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e5.1\u003c/b\u003e Dynamic Effect Test\u003c/h2\u003e \u003cp\u003eA crucial assumption for the validity of the difference-in-differences (DID) model in application is that the treatment group and the control group satisfy the parallel trend assumption. Specifically, it means that the change trends of corporate sustainable development performance between the treatment group and the control group should remain parallel before the introduction of the 2015 R\u0026amp;D Policy. If the parallel trend assumption is not satisfied, the regression results of the DID model may be biased.\u003c/p\u003e \u003cp\u003eTo address this issue, we draw on the methods of Chen et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Ye et al. (2023), and Shen et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), use an event study approach based on Eq.\u0026nbsp;(1) to construct a more flexible dynamic regression. This regression is used to test the parallel trend and identify the specific timing when the R\u0026amp;D Policy begins to exert its policy effect:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{sustainD}}{{\\text{e}}_{it}}={\\alpha _0}+\\sum\\nolimits_{{2010}}^{{2020}} {{\\theta _t}} {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Yea}}{{\\text{r}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003eIn the above formula, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Yea}}{{\\text{r}}_t}\\)\u003c/span\u003e\u003c/span\u003e represents the annual dummy variable; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\theta _t}\\)\u003c/span\u003e\u003c/span\u003e reflects the relative impact of the R\u0026amp;D policy on the corporate sustainable development performance in the experimental group in year t. If the parallel trend assumption is satisfied before the implementation of the policy, the change in the corporate sustainable development performance after 2015 is the policy effect.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the regression coefficients of the interaction term. From the coefficients, it can be observed that the regression coefficient \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\theta _t}\\)\u003c/span\u003e\u003c/span\u003e for the period 2010\u0026ndash;2014 fails to pass the significance test, which verifies the corporate sustainable development performance in the experimental group and the control group exhibited a common parallel trend during the pre-policy implementation period. Additionally, the regression coefficients in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicate that the R\u0026amp;D policy exerted a positive promotional effect on the corporate sustainable development performance in the experimental group in the very year when the policy was formally implemented.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e5.2\u003c/b\u003e Placebo Test\u003c/h2\u003e \u003cp\u003eConsidering that external random factors may interfere with the baseline results, to further confirm the baseline regression results are not affected by other random events, the study draws on existing research (La Ferrara, Chong, and Duryea, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Shen et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) to conduct a placebo test. By simulation, we artificially disrupt the corresponding relationship between the treatment group and the control group, randomly create a new treatment group and control group, constructing a false policy shock, and then re-conduct the regression based on the sample.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e depicts the probability density distribution of the estimated coefficients of false policy shocks from 500 random samples. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, most of the estimated coefficients obtained from the random sampling regression are distributed around zero and follow a normal distribution; however, the baseline regression estimated coefficient (0.015) is distributed on the right side of zero. This indicates that the randomly simulated policy shock has no significant impact on the level of corporate sustainable development.The placebo test shows that the policy shock effect is not caused by random events,the shock effect of the R\u0026amp;D support policy is indeed present. The above analysis can, to a certain extent, rule out the interference of non-time-varying confounding factors on the results, indicating that the positive impact on corporate sustainable development is real.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e5.3\u003c/b\u003e Propensity Score Matching (PSM)\u003c/h2\u003e \u003cp\u003eBefore the implementation of the R\u0026amp;D policy, if there are significant characteristic differences between enterprises in the treatment group and the control group, it will interfere with the regression results of the difference-in-differences (DID) model. To verify the interference of such significant differences on the regression results, we adopt the Propensity Score Matching (PSM) method to identify the control group with similar characteristics. We use the control variable X as the covariate and adopt the 1:5 nearest neighbor matching method to select the control group.\u003c/p\u003e \u003cp\u003eColumn (2) in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below reports the matching results based on the Logit model, while Columns (3)-(6) present the balance test of covariates, which verifies the effectiveness of the PSM method. We conduct the DID test based on the data after PSM matching. From the regression results, we can find that the regression coefficient of Treat\u0026times;Post remains positive and passes the significance test at the 1% level, which verifies the baseline regression results.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Results of Propensity Score Matching (PSM)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ePanel A: PSM Process\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003ePanel B: DID Estimation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLogit Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eCovariate Balance Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatched Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTreatment Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBias\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.657***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreat\u0026times;Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.017***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.139)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(.0082)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.318**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eControl Var\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ecash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.144***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFirm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.297)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.146***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eadj-R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003emshare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.025***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.505**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.105***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant Term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.764***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.530)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudo R-Squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Testing Using ESG_Rate, Environ_Rate, and Social_Rate Indicators\u003c/h2\u003e \u003cp\u003eThe corporate Environmental, Social, and Governance (ESG) evaluation system covers the key performance dimensions of corporate sustainable development (Wang and Wang, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and serves as a crucial indicator reflecting corporate social benefits. The study collects ESG performance data of listed companies from Hexun.com, specifically the overall ESG rating score of enterprises (ESG_Rate). A higher ESG rating indicator value indicates better sustainable development performance of the enterprise. The ESG rating is further divided into two sub-dimensions: Environmental Responsibility Score (Environ_Rate) and Social Responsibility Score (Social_Rate).\u003c/p\u003e \u003cp\u003eIn the regression results presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Columns (1) to (6) report the regression outcomes for sustainable development based on the ESG evaluation system. It can be observed that the regression coefficients of the interaction term (Treat\u0026times;Post) with the corporate sustainable development performance indicators (ESG_Rate, Environ_Rate, and Social_Rate) are all positive, all pass the significance level test. It indicates that the implementation of R\u0026amp;D support policies has a significant promoting effect on corporate sustainable development performance (ESG), the effect remains relatively significant when measured by environmental responsibility (Environ_Rate) and social responsibility (Social_Rate).It can be concluded that the implementation of the R\u0026amp;D policy not only improves corporate financial performance but also promotes corporate sustainable development performance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Results of Replacing Key Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESG_Rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eESG_Rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnviron_Rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEnviron_Rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSocial_Rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSocial_Rate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.289*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.538**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.896***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.633**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.238*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.771)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.274)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.139)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.939***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.639**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.040*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.281)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.578)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-11.827***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.895***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.490)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.526)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.320)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.589***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.900***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.726)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.513)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eroa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.010***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.052**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.483)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.132)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.826)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.249**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.328)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.079)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emshare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.009***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.216**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.920)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.537)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.012***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-41.125***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-16.344***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-19.364***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(5.034)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.829)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(1.959)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.358***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.161***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.178***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.072)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.850***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-144.740***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.593***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-64.237***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.415***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.457)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(19.213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.174)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(7.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(1.712)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15,217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"6.Mechanism Test of Action","content":"\u003cp\u003eThe regression results above confirm that the 2015 additional deduction policy for R\u0026amp;D expenses significantly improves the sustainable development performance of intelligent manufacturing enterprises.Therefore, this study will further examine the aforementioned mechanisms below.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Financing Constraint Alleviation Channel: Capital Channel\u003c/h2\u003e \u003cp\u003eThe study argues that the R\u0026amp;D policy alleviates enterprises\u0026rsquo; financial pressure, provides more financial support for innovation activities to enhance innovation capabilities. Ultimately, the improvement of resource allocation efficiency and technological innovation capabilities is reflected in the improvement of corporate sustainable development performance.\u003c/p\u003e \u003cp\u003eFollowing the practices of existing scholars (Ju, Lu, and Yu, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Shen et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), this study uses the corporate financing constraint indices SA (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{finan\\_bind}}\\)\u003c/span\u003e\u003c/span\u003e) and FC (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{FC}}\\)\u003c/span\u003e\u003c/span\u003e) to measure the level of corporate financial constraints. On the basis of Eq.\u0026nbsp;(1), the following equations are constructed:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{finan\\_bin}}{{\\text{d}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{F}}{{\\text{C}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe regression results are presented in Columns (1), (2), (3), (5), (6), and (7) of Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Whether considering the regression coefficient of the corporate financing constraint index (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{finan\\_bind}}\\)\u003c/span\u003e\u003c/span\u003e) with the interaction term (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Treat}} \\times {\\text{Post}}\\)\u003c/span\u003e\u003c/span\u003e), or the regression coefficient of (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{FC}}\\)\u003c/span\u003e\u003c/span\u003e) with the interaction term (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{Treat}} \\times {\\text{Post}}\\)\u003c/span\u003e\u003c/span\u003e), both are negative and basically significant. It verifies the R\u0026amp;D policy has a significant effect on alleviating corporate financing constraints.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMechanism Test: Capital Channel\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.010***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.006*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.007*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.049***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.018**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.020***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.018**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.091***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.075***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.088**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.268***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.211***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.123***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.498***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.068***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.061***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.669***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.653***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.567***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.351***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.424***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.946***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.648***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.876***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.726***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.219**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.106)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15,214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16,496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15,244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15,214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2,322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Channel for Enhancing R\u0026amp;D Capabilities: Innovation Channel\u003c/h2\u003e \u003cp\u003eTo examine the impact of the R\u0026amp;D policy on the innovation level of smart manufacturing enterprises, this paper constructs the following equation using the aforementioned Formula (1). For the measurement of enterprise innovation indicators, we draw on existing research (Shen et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and use R\u0026amp;D investment intensity (rd_invest) and enterprise innovation outputs (total_patent) as the explained variables.R\u0026amp;D investment intensity is measured by the ratio of an enterprise\u0026rsquo;s total annual R\u0026amp;D investment to its operating income.The enterprise innovation output indicator is measured by taking the logarithm of the number of patent applications filed by the enterprise.\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{rd\\_inves}}{{\\text{t}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{total\\_paten}}{{\\text{t}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In columns (1) and (5), we only added the interaction term (Treat \u0026times; Post), we found that the estimated coefficients of the interaction term (Treat \u0026times;Post) with R\u0026amp;D investment intensity (rd_invest) and enterprise innovation achievement (total_patent) were 0.402 and 0.128, respectively, both passed the significance test at the 1% level. It indicates that the 2015 R\u0026amp;D policy can significantly improve the innovation level of intelligent manufacturing enterprises.\u003c/p\u003e \u003cp\u003eTo avoid bias caused by omitted variables in the double difference estimation results, we gradually added control variables in columns (2), (3), and (6), (7). It can be observed that with the addition of control variables, the regression results of the interaction term (Treat \u0026times; Post) with the coefficients of R\u0026amp;D investment intensity (rd_invest) and enterprise innovation achievement (total_patent) are both positive and significant, basically meeting the significance level of 1%. The regression results support that the 2015 R\u0026amp;D policy can significantly improve the innovation level of intelligent manufacturing enterprises.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMechanism Test: Innovation Channel\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003erd_invest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003erd_invest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003erd_invest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003etotal_patent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003etotal_patent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003etotal_patent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.402***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.411***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.410***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.128***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.101***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.099**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.017**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erd_invest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etotal_patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.741***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.799***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.106***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.626***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.596***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.096**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.559)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.459***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.547*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.632*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.502***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.818)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.324)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.051*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.049*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.029***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.029***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.005***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.901***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.479***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.037**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.844***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.347***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.878***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.160***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.977***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.216)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(1.089)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(1.167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.214)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14,044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16,561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15,009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2,303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e6.3 Improving Total Factor Productivity Channel: Total Factor Productivity Channel\u003c/h2\u003e \u003cp\u003eTo test whether the impact of the 2015 R\u0026amp;D support policy on the sustainable development performance is through the channel of improving the total factor productivity, this paper constructs the following equation to perform regression testing on the sample data. For the measurement of total factor productivity of enterprises, consistent with the practices of most scholars, this article uses LP and OP methods to calculate the total factor productivity of enterprises.\u003c/p\u003e \u003cp\u003eMeanwhile, the green total factor productivity of enterprises is a comprehensive reflection of production efficiency and environmental performance, and an important manifestation of sustainable development. Therefore, using green total factor productivity is more comprehensive compared to total factor productivity (Xie and Zhu, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We used the Luenberger productivity indicator (LPI) method to measure the green total factor productivity (Green_TFP) at the enterprise level.\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{TFP\\_L}}{{\\text{P}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{TFP\\_O}}{{\\text{P}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\text{Green\\_TF}}{{\\text{P}}_{it}}={\\alpha _0}+\\theta {\\text{Trea}}{{\\text{t}}_i} \\times {\\text{Pos}}{{\\text{t}}_t}+\\beta {{\\text{X}}_{it}}+{\\mu _i}+{\\gamma _t}+{\\varepsilon _{it}}\\)\u003c/span\u003e \u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. In the regression of columns (1) to (4), we gradually added control variables and found that the regression coefficients between the interaction term (Treat\u0026times;Post) and the total factor productivity (TFP_LP, TFP_OP) were positive, basically passed the significance level test. It indicates that the R\u0026amp;D policy in 2015 can significantly improve the total factor productivity of intelligent manufacturing enterprises.\u003c/p\u003e \u003cp\u003eIn the regression results of columns (5) to (6), we found that the regression coefficients between the interaction term (Treat\u0026times;Post) and the green total factor productivity (Green_TFP) were both positive and passed the 5% significance level test. This once again confirms that R\u0026amp;D support policies promote the improvement of total factor productivity and green total factor productivity, drive sustainable development of enterprises.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMechanism Test: Channel of Improving Total Factor Productivity (TFP)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTFP_LP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTFP_LP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTFP_OP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTFP_OP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGreen_TFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGreen_TFP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.072***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.080***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.037*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.592***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.599***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.391***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.401***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.014***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.013**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e 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align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.112)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.010)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.194***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.177***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.006***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.005***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e 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colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.196**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.089)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004***\u003c/p\u003e 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align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.023***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.014***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.399***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.061***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.297***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.362***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.041**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.737)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.032)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15,244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13,431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13,172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"7. Further Discussion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e7.1 Regional differences: Eastern region vs. Central region vs. Western region\u003c/h2\u003e \u003cp\u003eThere are differences in economic foundation, policy environment, and resource endowment among the eastern, central, and western regions of China, which have different impacts on the sustainable development of enterprises. The well-established market system and developed financial market in the eastern region have integrated the concept of sustainable development into production and operation process of enterprises earlier. As the core region of China's economic development, the eastern region focuses on supporting technology research and development, green and low-carbon, high-end industries in the development layout of intelligent manufacturing enterprises. Due to relatively lagging economic development compared to the eastern region, the central and western regions have slower market-oriented mechanisms and processes. Relying on the advantages of \"low cost, abundant resources, and policy support for industrial transfer\", they focus on laying out labor-intensive, resource-based, and other types of enterprises. The industrial characteristics of \"resource dependence\" and \"environmental upgrading\" in the central and western regions make the sustainable development strategy particularly urgent, and the impact of R\u0026amp;D support policies on the sustainable development of enterprises in the central and western regions may be more significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e7.2 Differences in Enterprise Scale: Large Scale vs. Small Scale\u003c/h2\u003e \u003cp\u003eThe scale of a company often reflects its economic strength. The size of the enterprise directly affects the impact of the R\u0026amp;D policy on the sustainable development performance of the enterprise. The sustainable development of enterprises requires the support of technological innovation, the investment of resources such as talent and high-end equipment. The scale of enterprises directly determines the ability to acquire resources and the intensity of investment, which is the core root of the impact on the sustainable development of different scales.\u003c/p\u003e \u003cp\u003eLarge scale enterprises have relatively mature management mechanisms and comprehensive innovation incentive mechanisms. Their high operational management efficiency and mature R\u0026amp;D innovation system occupy a favorable position in market competition. Large scale enterprises often lead industry development concepts, their high R\u0026amp;D level and environmental protection technology are more conducive to environmental (E) performance and social (S) responsibility fulfillment. Compared to small and medium-sized enterprises, large-scale enterprises are better able to digest and absorb the policy dividends. In the measurement of large-scale enterprises, we draw on the classification standards of the National Bureau of Statistics to define whether the enterprise's operating income exceeds 400\u0026nbsp;million yuan(about 56.72\u0026nbsp;million US dollars), and set a dummy variable scale.\u003c/p\u003e \u003cp\u003eThe regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. In the regression results, we can find that the promotion effect of the R\u0026amp;D policy on the sustainable development performance is more significant in the central and western regions and large-scale enterprises. It indicates that while pursuing economic development in the central and western regions, it is necessary to balance economic profitability, environmental compliance, and social responsibility. The comparative advantages of large-scale enterprises in technology and funding can better utilize the positive effects brought by the R\u0026amp;D policy and obtain policy support.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Results of Regional Heterogeneity and Scale Heterogeneity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEnterprise's location region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eEnterprise Scale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWestern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLarge-Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSmall-Scale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.054***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.085*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.092**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.094)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.099)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.021)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.094*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.059)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eroa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.134***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.202***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.184**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.210***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.077)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emshare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.174**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.063*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.077)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.069)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.050)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.546***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.287**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.450***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.558***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.121)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.052)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.122***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.224**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.100***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.207***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.474)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.565)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.248)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.277)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,403\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e7.3 Capital intensity difference: high capital intensity vs. low capital intensity\u003c/h2\u003e \u003cp\u003eCapital intensity is a core indicator for measuring the ratio of capital input to labor input in enterprise production and operation, usually measured by the ratio of fixed assets to the number of employees or the ratio of enterprise capital to output. High capital intensive enterprises rely on large-scale investment in equipment, factories, technology research and development to drive production, while low capital intensive enterprises rely more on human resources and light asset operations. The core of sustainable development is to achieve long-term value growth under the three-dimensional goals of \"economic benefits, environmental responsibility, and social responsibility\", while capital intensity profoundly shapes the sustainable development path of enterprises by affecting their cost structure, innovation ability, risk resistance, and resource utilization efficiency. Capital intensity provides \"hard support\" for the sustainable development of enterprises by consolidating the production foundation, promoting technological upgrading and resource optimization. Compared with the production activities of enterprises with low capital intensity, which focus more on the investment of human capital, the policy should have a greater impact on improving the sustainable development performance with high capital intensity.\u003c/p\u003e \u003cp\u003eTo verify the theoretical inference, we measure the capital intensity of a company by the ratio of its total fixed assets to the number of employees, and rank this value. Companies above the median are defined as high capital intensity types, while those below the median are defined as low capital intensity types, and a dummy variable (cintency) is set. Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e reports the grouped regression results based on the height of enterprise capital intensity. It can be observed that the estimated coefficient of the interaction term (Treat \u0026times; Post) is significantly positive in the sample group with high capital intensity, but not significant in the sample group with low capital intensity. The regression results indicate that the R\u0026amp;D policy has a stronger effect on improving the sustainable development performance in capital intensive enterprises.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e7.4 Industry technology update speed difference: fast technology update speed vs. slow technology update speed\u003c/h2\u003e \u003cp\u003eThe speed of technological change reflects the exposure to cutting-edge new technologies. For enterprises in industries with fast technological change rates, the R\u0026amp;D policy has a more significant role in promoting innovation, and may have a greater impact on the total factor productivity, thereby having a more significant impact on their sustainable development. The reason is that enterprises in these industries need to timely grasp market changes and technological progress information of peers, in order to improve production and operation efficiency to cope with more intense market competition. Therefore, the R\u0026amp;D policy has brought about improvements in the sustainable development performance of enterprises, its impact on enterprises with different technological update speeds is relatively different.\u003c/p\u003e \u003cp\u003eFollowing the approach of Shen et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), we consider manufacturing industries such as computers, communications, other electronic devices, and electrical machinery, as companies with fast technological changes in the industry, while other manufacturing enterprises are considered as companies with slow technological changes, and represent them as dummy variables (techupdate). The specific regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. As expected, the results indicate that the R\u0026amp;D policy has a greater promoting effect on the sustainable development performance (sustainDe) in industries with rapid technological change. It indicates that companies in industries with fast technological changes are more sensitive to research and development innovation, promote innovation strategies, and enhance the sustainable development performance of enterprises.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Results of Heterogeneity in Capital Intensity, Labor Intensity, and Industry Technological Change Speed\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003esustainDe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCapital Intensity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLabor Intensity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eIndustry Technology Update Speed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSlow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etreat_post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.024**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.009)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.134**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.113**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.080*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.055)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.053)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.057)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.063)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.047)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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\u003cp\u003e0.146***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.120**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.181***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.034)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.057)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecdensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emshare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebigholder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.077*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.043\u003c/p\u003e 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align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.034)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinan_bind\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.413***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.623***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.609***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.443***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.505***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.503***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.078)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.077)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.065)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etbq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.005**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.733***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.275***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.306***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.852***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.964***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.981***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.333)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.304)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.304)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.328)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.256)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,271\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stkcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"8 Research Conclusions and Policy Recommendations","content":"\u003cp\u003eThe R\u0026amp;D innovation strategy helps enterprises improve production efficiency, enhance market competitiveness, promote green production, assist enterprises in developing energy-saving and emission reduction technologies,promote enterprises\u0026rsquo; development towards green manufacturing. This is the key to achieving sustainable development. Continuous research and development innovation can enable enterprises to keep up with market trends.This article uses a sample of Chinese listed manufacturing companies from 2010 to 2020 to identify policy effects through a difference in differences model, and explores the impact and mechanism of R\u0026amp;D support policies on sustainable development of enterprises.\u003c/p\u003e \u003cp\u003eThe study finds that the R\u0026amp;D policy can significantly improve intelligent manufacturing enterprises\u0026rsquo; sustainable development performance. The conclusion remains valid after a series of robustness tests, including parallel trend test, placebo test, propensity score matching, and replacement of enterprise sustainable development indicators. Mechanism tests reveal that R\u0026amp;D support policies improve the sustainable development performance by alleviating corporate financing constraints, enhancing the innovation level, and increasing the total factor productivity (TFP). Heterogeneity tests show that the R\u0026amp;D policy has a more significant impact on the enterprises that feature fast industry technology update speed, high capital intensity, non-state ownership, and large scale. The research conclusions of this paper provide valuable references to the development of intelligent manufacturing enterprises,providing Chinese experience for sustainable development in other countries and regions.\u003c/p\u003e \u003cp\u003eBased on the above research conclusions, the article proposes the following policy recommendations:\u003c/p\u003e \u003cp\u003e(1)Increase research and development funding support. The government should explore the establishment of a special research and development fund for intelligent manufacturing, focusing on supporting enterprises to carry out core technology research and development, providing high funding for eligible projects, and alleviating the financial pressure on enterprise research and development. Implement tax preferential policies and additional deduction policies for R\u0026amp;D investment of intelligent manufacturing enterprises, encourage enterprises to increase R\u0026amp;D investment, and explore import tariff reduction and exemption support for intelligent manufacturing R\u0026amp;D equipment purchased.\u003c/p\u003e \u003cp\u003e(2)Promote innovation and application of key technologies. In response to the bottleneck technologies in the field of intelligent manufacturing, such as high-end sensors, industrial software, organize and implement national science and technology major projects, concentrate the advantageous forces of universities, research institutions, and enterprises to jointly tackle and accelerate the localization process of core technologies. Encourage enterprises to deeply integrate new technologies such as artificial intelligence, big data,the Internet of Things with manufacturing technology, and promote the integration and application of new technologies. Support enterprises to carry out innovation application scenarios based on new technologies, and provide financial rewards and policy support for related demonstration projects.\u003c/p\u003e \u003cp\u003e(3)Strengthen research and innovation in green manufacturing. Support enterprises to carry out green technology research and development, establish a special project for green manufacturing research and development, support the development of energy-saving, consumption reducing, resource recycling technologies, provide subsidies and support to enterprises whose research and development achievements have reached the international advanced level. Develop standards and specifications related to green design, promote the concept of green design, guide enterprises to fully consider environmental factors in product design, give priority support to government procurement for products certified by green design, and improve market recognition of green products.\u003c/p\u003e \u003cp\u003eThis paper has several limitations. First, the research sample is restricted to listed smart manufacturing enterprises in China, the conclusions drawn may not be fully generalizable to the broader population of Chinese smart manufacturing enterprises, especially small and medium-sized non-listed firms.Second, the measurement of key variables, particularly the sustainable development of enterprise, relies on secondary data from listed company financial reports, it may not fully capture the nuanced dimensions of these constructs. This reliance on quantitative secondary data may limit the depth of understanding regarding the mechanisms linking R\u0026amp;D policy.Third, the study does not explore the long-term dynamic effects of the R\u0026amp;D policy. It remains unclear whether this effect persists, diminishes, or evolves over time. Long-term tracking of enterprises\u0026rsquo; sustainable development trajectories post-policy implementation would be necessary to assess the policy\u0026rsquo;s sustained effectiveness.Therefore, subsequent studies can focus on an in-depth analysis of the relationship between the strategy with the changes in intelligent manufacturing enterprises\u0026rsquo; sustainable development.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDisclosure\u003c/strong\u003e \u003cp\u003e \u003cb\u003estatement\u003c/b\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003eNo potential conflict of interest was reported by the author(s).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Major Program of the National Social Science Foundation of China under Grant No. 24BJY047.\u003c/p\u003e\u003ch2\u003eData availability statement\u003c/h2\u003e \u003cp\u003eThe data underlying this study are available from the CSMAR, WIND, and CNRDS databases. Readers can access these datasets through the following websites: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gtarsc.com/\u003c/span\u003e\u003cspan address=\"https://www.gtarsc.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e., \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wind.com.cn/\u003c/span\u003e\u003cspan address=\"https://www.wind.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e., and \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cnrds.com/\u003c/span\u003e\u003cspan address=\"https://www.cnrds.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcemoglu, D., \u0026amp; Restrepo, P. (2020). 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A study on the impact of senior executives'green cognition and enterprises'green behavior on enterprises'green performance: An empirical analysis based on data of light industry enterprises in Shandong. \u003cem\u003eEast China Economic Management\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(12), 35\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Smart Manufacturing, Innovation-Driven, Financing Constraints, Total Factor Productivity (TFP), Sustainable Development","lastPublishedDoi":"10.21203/rs.3.rs-8410172/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8410172/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePromoting the sustainable development of intelligent manufacturing enterprises is a key pathway to drive the green and efficient transformation of the manufacturing industry, and protecting the ecological environment. Based on the data of manufacturing enterprises listed in China, this paper empirically examines the impact of the policy of additional deduction for research and development (R\u0026amp;D) expenses on the sustainable development of intelligent manufacturing enterprises. The study finds that the R\u0026amp;D policy can significantly improve intelligent manufacturing enterprises\u0026rsquo; sustainable development performance. The conclusion remains valid after a series of robustness tests, including parallel trend test, placebo test, propensity score matching, and replacement of enterprise sustainable development indicators. Mechanism tests reveal that R\u0026amp;D support policies improve the sustainable development performance by alleviating corporate financing constraints, enhancing the innovation level, and increasing the total factor productivity (TFP). Heterogeneity tests show that the R\u0026amp;D policy has a more significant impact on the enterprises that feature fast industry technology update speed, high capital intensity, non-state ownership, and large scale. The research conclusions of this paper provide valuable references to the development of intelligent manufacturing enterprises,providing Chinese experience for sustainable development in other countries and regions.\u003c/p\u003e","manuscriptTitle":"The Impact of R\u0026amp;D Innovation Strategy on the Sustainable Development of Intelligent Manufacturing:evidence from a quasi-natural experiment in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-06 13:40:56","doi":"10.21203/rs.3.rs-8410172/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b4c92ca-e585-4a6a-8000-2579d9b04dc8","owner":[],"postedDate":"February 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-11T21:48:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-06 13:40:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8410172","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8410172","identity":"rs-8410172","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}