Can Green Innovation Affect ESG Ratings and Financial Performance? Evidence from Chinese GEM Listed Companies
Abstract
:1. Introduction
1.1. Research Significance
1.2. Green Innovation of GEM Listed Companies
1.3. Main Contribution
2. Hypothesis Development and Research Design
2.1. Mediation Effect of ESG Performance
2.2. Moderating Effect of Political Connection and Regional Innovation
3. Methodology
3.1. Sample and Data Acquisition
3.2. Research Model
4. Empirical Results
4.1. Descriptive Statistics
4.2. Correlation Analysis of Variables
4.3. Mediation Effect of ESG Performance
4.4. Moderating Effect of Political Connection and Regional Innovation
5. Robustness Test
5.1. Replacing Variables
5.2. Endogeneity Analysis
5.3. Sobel-Goodman and Bootstrap Test
6. Conclusions
6.1. Policy Implications
6.2. Sustainable Development
6.3. Limitations and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Type | Factors | Variable Name | Symbol | Calculation Method |
---|---|---|---|---|
Dependent variable | Financial Performance | Return on Assets | ROA | Net Profit/Total Assets |
Independent variable | Green Innovation | Forward Citations of Green Patent | FCGP | Number of citations of green patents |
Mediating variable | Environment, Social, Governance Ratings | Environmental Indicator | SEC | Total Standard Energy Consumption of Industry GDP of Industry |
Corporate Social Responsibility | CSR | Collected CSR scores manually from HeXun Database | ||
Corporate Governance | CG | Principal component analysis from supervision, incentives and decision-making | ||
Moderating variable | Entrepreneurial Political Connection | Political Connection Strength | PCS | Obtain from CSMAR, filter by the highest level in the same firm |
Regional Differences | Regional Innovation Index | RII | Manually collate from “China Regional Innovation Capability Evaluation Report” | |
Control variable | Corporate Financial Indicators | Board Size | BS | The Natural Log of Board Size |
Independence Board | ID | The Proportion of Independent Directors | ||
Ownership Concentration | OC | The Ownership of the Largest Shareholder | ||
Corporation Characteristics | CC | Private Enterprise = 1, Else = 0 | ||
Firm Size | SIZE | The Natural Log of Total Assets | ||
Fixed Investment Growth Rate | FIGR | Growth Rate of Fixed Investment Newly Added to the Industry | ||
Asset Liability Ratio | ALR | Total Liabilities/Total Assets |
References
- Cao, T.; Zhang, C.; Yang, X. The Green Effect and Impact Mechanism of Green Credit Policy-Evidence Based on Green Patent Data of Chinese Listed Companies. Financ. Forum 2021, 26, 7–17. [Google Scholar]
- Busco, C.; Consolandi, C.; Eccles, R.G. A Preliminary Analysis of SASB Reporting: Disclosure Topics, Financial Relevance, and the Financial Intensity of ESG Materiality. J. Appl. Corp. Financ. 2020, 32, 117–125. [Google Scholar] [CrossRef]
- Parameswaran, M.; Whinston, A.B. Social computing: An overview. Commun. Assoc. Inf. Syst. 2007, 19, 37. [Google Scholar] [CrossRef] [Green Version]
- Jahn, J.; Brühl, R. How friedman’s view on individual freedom relates to stakeholder theory and social contract theory. J. Bus. Ethics 2018, 153, 41–52. [Google Scholar] [CrossRef]
- Gioia, D.A.; Corley, K.G. Being good versus looking good: Business school rankings and the circean transformation from substance to image. Acad. Manag. Learn. Educ. 2002, 1, 107–120. [Google Scholar] [CrossRef]
- Colquitt, L.L.; Hoyt, R.E. Determinants of corporate hedging behavior: Evidence from the life insurance industry. J. Risk Insur. 1997, 64, 649–671. [Google Scholar] [CrossRef]
- Xu, L.G. Earnings Information Transparency, Financing Constraints and Enterprise Technology Innovation. Friends Account. 2021, 1, 38–43. [Google Scholar]
- Lo, K.Y.; Kwan, C.L. The Effect of Environmental, Social, Governance and Sustainability Initiatives on Stock Value—Examining Market Response to Initiatives Undertaken by Listed Companies. Corp. Soc. Responsib. Environ. Manag. 2017, 24, 606–619. [Google Scholar] [CrossRef]
- Gu, L.; Wang, H. Social Trust, Financing Constraints and Enterprise Innovation. Economist 2020, 11, 39–50. [Google Scholar]
- Boyle, J.; Higgins, M.; Rhee, G.S. Stock Market Reaction to Ethical Initiatives of Defense Contractors: Theory and Evidence. Crit. Perspect. Account. 1997, 8, 541–561. [Google Scholar] [CrossRef]
- Drempetic, S.; Klein, C.; Zwergel, B. The influence of firm size on the ESG Score: Corporate sustainability ratings under review. J. Bus. Ethics 2019, 167, 333–360. [Google Scholar] [CrossRef]
- García, F.; González-Bueno, J.; Guijarro, F.; Oliver, J. Forecasting the Environmental, Social, and Governance Rating of Firms by Using Corporate Financial Performances: A Rough Set Approach. Sustainability 2020, 12, 3324. [Google Scholar] [CrossRef] [Green Version]
- Slager, R.; Gond, J.P.; Moon, J. Standardization As Institutional Work: The Regulatory Power of A Responsible Investment Standard. Organ. Stud. 2012, 33, 763–790. [Google Scholar] [CrossRef]
- Brooks, C.; Oikonomou, I. The effects of environment, social and governance disclosures and performance on firm value: A review of the literature in accounting and finance. Br. Account. Rev. 2018, 50, 1–15. [Google Scholar] [CrossRef]
- Dalal, K.K.; Thaker, N. ESG and Corporate Financial Performance: A Panel Study of Indian Companies. IUP J. Corp. Gov. 2019, 18, 44–59. [Google Scholar]
- Clementino, E.; Perkins, R. How Do Companies Respond to Environmental, Social and Governance (ESG) Ratings? Evidence from Italy. J. Bus. Ethics 2021, 171, 379–397. [Google Scholar] [CrossRef] [Green Version]
- Xie, J.; Nozawa, W.; Yagi, M.; Fujii, H.; Managi, S. Do Environmental, Social, and Governance Activities Improve Corporate Financial Performance? Bus. Strategy Environ. 2019, 28, 286–300. [Google Scholar] [CrossRef] [Green Version]
- Aras, G.; Crowther, D. Governance and Sustainability an Investigation into the Relationship between Corporate Governance and Corporate Sustainability. Manag. Decis. 2008, 46, 433–448. [Google Scholar] [CrossRef]
- Hagedoorn, J.; Cloodt, M. Measuring innovative performance: Is there an advantage in using multiple indicators? Res. Policy 2003, 32, 1365–1379. [Google Scholar] [CrossRef] [Green Version]
- Yu, G.; Rhee, S.Y. Effect of R&D collaboration with research organizations on innovation: The mediation effect of environmental performance. Sustainability 2015, 7, 11998–12016. [Google Scholar]
- Calik, E.; Bardudeen, F. A measurement scale to evaluate sustainable innovation performance in manufacturing organizations. Procedia CIRP 2016, 40, 449–454. [Google Scholar] [CrossRef] [Green Version]
- Gunarathne, N. Sustainable Innovation Measurement: Approaches and Challenges. Innov. Sustain. Bus. 2019, 1, 233–251. [Google Scholar]
- Qiao, Y.Z. Research on Influencing Factors of Patent Maintenance Time. Sci. Res. Manag. 2011, 32, 143–144. (In Chinese) [Google Scholar]
- Mansfield, E. R&D and Innovation: Some Empirical Findings; National Bureau of Economic Research: Cambridge, MA, USA, 1984. [Google Scholar]
- Lanjouw, J.O.; Putnam, P.J. How to Count Patents and Value Intellectual Property:The Uses of Patent Renewal and Application Data. J. Ind. Econ. 1998, 46, 405–432. [Google Scholar] [CrossRef]
- Schankerman, M.; Packes, A. Estimates of the Value of Patent Rights in European Countries During Thepost-1950 Period. Soc. Ence Electron. Publ. 1986, 96, 1052–1076. [Google Scholar]
- Feng, R.T. Analysis of Influencing Factors of Patent Maintenance Time Based on Patent Literature. J. Intell. 2020, 39, 202–207. (In Chinese) [Google Scholar]
- Hikkerova, L.; Kammoun, N.; Lantz, J.S. Patent Life Cycle: New Evidence. Technol. Forecast. Soc. Chang. 2014, 88, 313–324. [Google Scholar] [CrossRef]
- Dang, J.; Motohashi, K. Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality. China Econ. Rev. 2015, 35, 137–155. [Google Scholar] [CrossRef]
- Zhang, X.; Xu, B. R&D Internationalization and Green Innovation? Evidence from Chinese Resource Enterprises and Environmental Enterprises. Sustainability 2019, 11, 7225. [Google Scholar]
- Oltra, V.; Jean, M.S. Sectoral systems of environmental innovation: An application to the French automotive industry. Technol. Forecast. Soc. 2009, 76, 567–583. [Google Scholar] [CrossRef]
- Huang, X.; Hu, Z.; Fu, C.; Yu, D. The impact mechanism of green innovation strategy on corporate performance: Based on the mediating effect of green dynamic capabilities. Sci. Technol. Prog. Policy 2015, 32, 104–109. [Google Scholar]
- Ardito, L.; Messeni, A.; Pascucci, F.; Peruffo, E. Inter-firm R&D collaborations and green innovation value: Theroleoffamilyfirms’involvementandthemoderatingeffectsofproximitydimensions. Bus. Strategy Environ. 2019, 28, 185–197. [Google Scholar]
- Mazzucato, M.; Semieniuk, G. Public financing of innovation: New questions. Oxf. Rev. Econ. Policy 2017, 33, 24–48. [Google Scholar] [CrossRef]
- Driessen, P.H.; Hillebrand, B. Adoption and diffusion of green innovations. In Marketing for Sustainability: Towards Transactional Policy-Making; Ios Press Inc.: Amsterdam, The Netherlands, 2002; pp. 343–355. [Google Scholar]
- Li, C.; Liu, X.; Bai, X.; Umar, M. Financial Development and Environmental Regulations: The Two Pillars of Green Transformation in China. Int. J. Environ. Res. Public Health 2020, 17, 9242. [Google Scholar] [CrossRef]
- Runhaar, H.; Tigchelaar, C.; Vermeulen, W.J.V. Environmental Leaders: Making a Difference. A Typology of Environmental Leaders and Recommendations for a Differentiated Policy Approach. Bus. Strategy Environ. 2008, 17, 160–178. [Google Scholar] [CrossRef] [Green Version]
- Han, W.; Deng, Y.; Yang, J. How do startups build a connected portfolio to improve performance? A case study based on the “structure-resource” interaction process. Manag. World 2017, 10, 130–149. (In Chinese) [Google Scholar]
- Jiang, W.; Chai, H.; Shao, J. Green entrepreneurial orientation for enhancing firm performance: A dynamic capability perspective. J. Clean. Prod. 2018, 198, 1311–1323. [Google Scholar] [CrossRef]
- Ilias, A.; Kostas, K.; Dimitris, T. Environmental and Financial Performance. Is There a Win-win or a Win-loss Situation? Evidence From the Greek Manufacturing. J. Clean. Prod. 2018, 197, 1275–1283. [Google Scholar]
- Xie, X.M.; Zhu, Q.W. How to solve the problem of “harmonious symbiosis” in corporate green innovation practice? Manag. World 2021, 37, 128–149. (In Chinese) [Google Scholar]
- Qiu, M.; Yin, H. ESG performance and financing cost of enterprises under the background of ecological civilization construction. Quant. Econ. Technol. Econ. Res. 2019, 36, 108–123. (In Chinese) [Google Scholar]
- Zhang, Y.M. Enterprise ESG performance, financing constraints and green technology innovation. Commer. Account. 2021, 11, 33–39. [Google Scholar]
- Link, S.; Naveh, E. Standardization and Discretion: Does the Environmental Standard ISO 14001 Lead to Performance Benefits? IEEE Trans. Eng. Manag. 2006, 53, 508–519. [Google Scholar] [CrossRef]
- Caracuel, J.; Mandojana, N. Green Innovation and Financial Performance: An Institutional Approach. Organ. Environ. 2013, 26, 365–385. [Google Scholar] [CrossRef]
- Doran, J.; Ryan, G. The Importance of the Diverse Drivers and Types of Environmental Innovation for Firm Performance. Bus. Strategy Environ. 2014, 25, 665–667. [Google Scholar] [CrossRef]
- González-Blanco, J.; Coca-Pérez, J.L.; Guisado-González, M. The Contribution of Technological and Non-Technological Innovation to Environmental Performance. An Analysis with a Complementary Approach. Sustainability 2018, 10, 4014. [Google Scholar] [CrossRef] [Green Version]
- Stucki, T. Which Firms Benefit from Investments in Green Energy Technologies?—The Effect of Energy Costs. Res. Policy. 2019, 48, 546–555. [Google Scholar] [CrossRef]
- Zhou, Y.; Xu, Y.; Liu, C.; Fang, Z.; Fu, X.; He, M. The Threshold Effect of China’s Financial Development on Green Total Factor Productivity. Sustainability 2019, 11, 3776. [Google Scholar] [CrossRef] [Green Version]
- Wang, M.; Li, Y.M.; Wang, Z.T. Enterprise green technology innovation and performance under the dual uncertainty of technology and market. J. Syst. Manag. 2021, 30, 353–362. [Google Scholar]
- Porter, M.E.; Van Der Linde, C. Toward a New Conception of the Environment-Competitiveness Relationship. J. Econ. Perspect. 1995, 9, 97–118. [Google Scholar] [CrossRef] [Green Version]
- Fan, B.; Wang, W. The synergistic influence of environmental protection investment and green technological innovation of coal enterprises on financial performance. Chongqing Soc. Sci. 2019, 6, 70–82. (In Chinese) [Google Scholar]
- Tang, M.; Walsh, G.; Lerner, D.; Fitza, M.A.; Li, Q. Green Innovation, Managerial Concern and Firm Performance: An Empirical Study. Bus. Strategy Environ. 2018, 27, 39–51. [Google Scholar] [CrossRef]
- Verdolini, E.; Bak, C.; Ruet, J.; Venkatachalam, A. Innovative green-technology SMEs as an opportunity to promote financial de-risking. Economics 2018, 12, 2018-14. [Google Scholar] [CrossRef] [Green Version]
- Miroshnychenko, I.; Barontini, R.; Testa, F. Green practices and financial performance: A global outlook. J. Clean. Prod. 2017, 147, 340–351. [Google Scholar] [CrossRef] [Green Version]
- Marín-Vinuesa, L.M.; Scarpellini, S.; Portillo-Tarragona, P. The Impact of Eco-Innovation on Performance Through the Measurement of Financial Resources and Green Patents. Organ. Environ. 2018, 33, 285–310. [Google Scholar] [CrossRef] [Green Version]
- Xue, Q.; Li, G. The impact of GEM companies’ R&D investment on financial performance: The moderating effect of executive incentives. Financ. Account. Mon. 2015, 4, 123–128. [Google Scholar]
- Liu, X.; Zhang, M. R&D investment and corporate performance: Taking listed companies on the GEM as an example. Bus. Account. 2017, 4, 70–73. [Google Scholar]
- Li, H.; Zhang, F. Research on the relationship between equity concentration, technological innovation and financial performance—Based on the empirical evidence of my country’s GEM manufacturing listed companies. Account. Res. 2020, 4, 40–46. [Google Scholar]
- Li, T.; Liao, G. The Heterogeneous Impact of Financial Development on Green Total Factor Productivity. Front. Energy Res. 2020, 8, 29. [Google Scholar] [CrossRef] [Green Version]
- Jensen, M.C.; Meckling, W.H. Theory of the firm: Managerial behavior, agency costs and ownership structure. J. Financ. Econ. 1976, 3, 305–360. [Google Scholar] [CrossRef]
- Friedman, M. The Social Responsibility of Business Is to Increase Its Profits; New York Times Magazine: New York, NY, USA, 2007; Volume 13, pp. 173–178. [Google Scholar]
- Peng, L.S.; Isa, M. Environmental, Social and Governance (ESG) Practices and Performance in Shariah Firms: Agency or Stakeholder Theory? Asian Acad. Manag. J. Account. Financ. 2020, 16, 1–34. [Google Scholar]
- Saunila, M.; Ukko, J.; Rantala, T. Sustainability as a driver of green innovation investment and exploitation. J. Clean. Prod. 2018, 179, 631–641. [Google Scholar] [CrossRef]
- Zhang, F.; Qin, X.; Liu, L. The Interaction Effect between ESG and Green Innovation and Its Impact on Firm Value from the Perspective of Information Disclosure. Sustainability 2020, 12, 1866. [Google Scholar] [CrossRef] [Green Version]
- Fombrun, C.; Shanley, M. What’s in A Name? Reputation Building and Corporate Strategy. Acad. Manag. J. 1990, 33, 233–258. [Google Scholar]
- Zhao, C.G.; Guo, Y.; Yuan, J.H.; Wu, M.Y.; Li, D.Y.; Zhou, Y.; Kang, J.G. ESG and Corporate Financial Performance: Empirical Evidence from China’s Listed Power Generation Companies. Sustainability 2018, 10, 2607. [Google Scholar] [CrossRef] [Green Version]
- Ahmad, N.; Mobarek, A.; Roni, N. Revisiting the impact of ESG on financial performance of FTSE350 UK firms: Static and dynamic panel data analysis. Cogent Bus. Manag. 2021, 8, 1900500. [Google Scholar] [CrossRef]
- De Lucia, C.; Pazienza, P.; Bartlett, M. Does Good ESG Lead to Better Financial Performances by Firms? Machine Learning and Logistic Regression Models of Public Enterprises in Europe. Sustainability 2020, 12, 5317. [Google Scholar] [CrossRef]
- Sang, K.; Li, Z.F. Understanding the Impact of ESG Practices in Corporate Finance. Sustainability 2021, 13, 3746. [Google Scholar]
- Wang, M.; Chen, Y. Does voluntary corporate social performance attract institutional investment? Evidence from China. Corp. Gov. Int. Rev. 2017, 25, 338–357. [Google Scholar] [CrossRef] [Green Version]
- Zhou, F.Z.; Pan, W.Y.; Fu, H. Listed Companies’ ESG Responsibility Performance and Institutional Investors’ Stockholding Preferences—Empirical Evidence from China’s A-Share Listed Companies. Sci. Decis. 2020, 11, 15–41. [Google Scholar]
- Li, X.; Xiao, X. System Escape or Innovation Driven? Institutional Constraints and Private Enterprises Foreign Direct Investment. Manag. World 2017, 10, 99–112. (In Chinese) [Google Scholar]
- Huang, L.; He, L. Executive Political Connections and Corporate Innovation Investment: An Empirical Study Based on GEM Listed Companies. Res. Dev. Manag. 2020, 32, 11–23. [Google Scholar]
- Chen, S.; Fu, F.; Jing, R. The Impact of Political Connections on R&D Investment: Promote or Suppress. Sci. Res. Manag. 2020, 41, 184–192. [Google Scholar]
- Dyer, J.H.; Hatch, N.W. Relation -specific capabilities and barriers to knowledge transfers: Creating advantage through network relationships. Strateg. Manag. J. 2006, 27, 701–719. [Google Scholar] [CrossRef]
- Engel, Y.; Kaandorp, M.; Elfring, T. Toward a dynamic process model of entrepreneurial networking under uncertainty. J. Bus. Ventur. 2017, 32, 35–51. [Google Scholar] [CrossRef] [Green Version]
- Luo, Z.; Qi, B. The industrial transfer and upgrading effect of environmental regulations and the synergistic development effect of banks: Evidence from the water pollution control of the Yangtze River Basin. Econ. Res. 2021, 56, 174–189. [Google Scholar]
- Sun, Z.; Chen, W.; Lan, Z. Research on Regional Green Innovation Capability Based on Entropy TOPSIS Method. Enterp. Econ. 2019, 38, 20–26. [Google Scholar]
- Asheim, B.T.; Coenen, L. Knowledge Bases and Regional Innovation Systems: Comparing Nordic Clusters. Res. Policy 2005, 34, 1173–1190. [Google Scholar] [CrossRef]
- Liu, B.; Zhu, J.; Zhou, Y.L. China’s Regional Economic Theory Evolution and Future Prospects. Manag. World 2020, 36, 182–194. (In Chinese) [Google Scholar]
- Liu, S.; Yu, Q.; Zhang, L.; Xu, J.; Jin, Z. Does Intellectual Capital Investment Improve Financial Competitiveness and Green Innovation Performance? Evidence from Renewable Energy Companies in China. Math. Probl. Eng. 2021, 13, 9929202. [Google Scholar] [CrossRef]
- Song, S. Research on China’s Regional Innovation Capability Evaluation. Technol. Econ. Manag. Res. 2020, 12, 118–123. [Google Scholar]
- Li, P.; Zhou, R.; Xiong, Y. Can ESG Performance Affect Bond Default Rate? Evidence from China. Sustainability 2020, 12, 2954. [Google Scholar] [CrossRef] [Green Version]
- Allison, H.L. A Climate for Change: Meeting Investor Demand for Climate and ESG Information at the SEC. 2021. Available online: https://www.sec.gov/news/speech/ (accessed on 12 November 2021).
- Freeman, R.E.; Wicks, A.C.; Parmar, B. Stakeholder theory and the corporate objective revisited. Organ. Sci. 2004, 15, 364–369. [Google Scholar] [CrossRef] [Green Version]
- Park, B.I.; Chidlow, A.; Choi, J. Corporate social responsibility: Stakeholders influence on MNEs’ activities. Int. Bus. Rev. 2014, 23, 966–980. [Google Scholar] [CrossRef]
- Gu, N.; Zhou, Y. Pre-Deterrence of Short Selling, Corporate Governance, and Corporate Financing Behavior-Based on Quasi-natural Experimental Test of Margin Trading System. Manag. World 2017, 2, 120–134. (In Chinese) [Google Scholar]
- Qi, S.; Lin, D.; Cui, J. Can the Environmental Rights Trading Market Induce Green Innovation? Evidence Based on the Green Patent Data of Listed Companies in my country. Econ. Res. 2018, 53, 129–143. [Google Scholar]
- Zhu, Y.H.; Zhou, X.; Zhang, Q.C. Private entrepreneurs’ political connections catalyze speculation or technological innovation. Sci. Res. Manag. 2016, 37, 77–84. [Google Scholar]
- Wen, Z.L.; Ye, B.J. Analysis of Mediation Effect: Method and Model Development. Adv. Psychol. Sci. 2014, 5, 731–745. (In Chinese) [Google Scholar] [CrossRef]
- Baron, R.M.; Kenny, D.A. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personal. Soc. Psychol. 1986, 51, 1173–1182. [Google Scholar] [CrossRef]
- Judd, C.M.; Kenny, D.A. Process analysis: Estimating mediation in treatment evaluations. Eval. Rev. 1981, 5, 602–619. [Google Scholar] [CrossRef]
- Wen, Z.L.; Zhang, L.; Hou, J.T.; Liu, H.G. Intermediary effect test procedure and its application. Chin. J. Psychol. 2004, 36, 614–620. (In Chinese) [Google Scholar]
- Hayes, A.F. Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Commun. Monogr. 2009, 76, 408–420. [Google Scholar] [CrossRef]
- MacKinnon, D.P.; Warsi, G.; Dwyer, J.H. A simulation study of mediated effect measures. Multivar. Behav. Res. 1995, 30, 41–62. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Preacher, K.J.; Hayes, A.F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 2008, 40, 879–891. [Google Scholar] [CrossRef] [PubMed]
- Iacobucci, D. Mediation Analysis; Sage: Thousand Oaks, CA, USA, 2008. [Google Scholar]
- Pituch, K.A.; Whittaker, T.A.; Stapleton, L.M. A comparison of methods to test for mediation in multisite experiments. Multivar. Behav. Res. 2005, 40, 1–23. [Google Scholar] [CrossRef] [PubMed]
- James, L.R.; Brett, J.M. Mediators, moderators, and tests for mediation. J. Appl. Psychol. 1984, 69, 307–321. [Google Scholar] [CrossRef]
- Fang, J.; Wen, Z.; Liang, D. Analysis of Moderating Effects Based on Multiple Regression. Psychol. Sci. 2015, 3, 715–720. [Google Scholar]
- Qiu, Y.; Shaukat, A.; Tharyan, R. Environmentaland social disclosures: Link with corporate financial performance. Br. Account. Rev. 2016, 48, 102–116. [Google Scholar] [CrossRef] [Green Version]
- Deng, X.; Cheng, X. Can ESG Indices Improve the Enterprises’ Stock Market Performance?—An Empirical Study from China. Sustainability 2019, 11, 4765. [Google Scholar] [CrossRef] [Green Version]
- Do, Y.; Kim, S. Do Higher-Rated or Enhancing ESG of Firms Enhance Their Long–Term Sustainability? Evidence from Market Returns in Korea. Sustainability 2020, 12, 2664. [Google Scholar] [CrossRef] [Green Version]
- Angrist, J.; Alan, K. Instrumental variables and the search for identification: From supply and demand to natural experiments. J. Econ. Perspect. 2001, 15, 69–85. [Google Scholar] [CrossRef] [Green Version]
- Roodman, D. How to Do Xtabond2: An Introduction to Difference and System GMM in Stata. Stata J. 2009, 9, 86–136. [Google Scholar] [CrossRef] [Green Version]
- Djebali, N.; Zaghdoudi, K. Testing the Governance-Performance Relationship for the Tunisian Banks: A GMM in System Analysis. Financ. Innov. 2020, 6, 23. [Google Scholar]
- Zhao, X.; Lynch, J.G., Jr.; Chen, Q. Reconsidering Baron and Kenny: Myths and truths about mediation analysis. J. Consum. Res. 2010, 37, 197–206. [Google Scholar] [CrossRef]
- Edwards, J.R.; Lambert, L.S. Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychol. Methods 2007, 12, 1–22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sobel, M.E. Asymptotic confidence intervals for indirect effects in structural equation models. In Sociological Methodology; Leinhardt, S., Ed.; American Sociological Association: Washington, DC, USA, 1982; pp. 290–312. [Google Scholar]
- Fritz, M.S.; MacKinnon, D.P. Required sample size to detect the mediated effect. Psychol. Sci. 2007, 18, 233–239. [Google Scholar] [CrossRef] [Green Version]
- Fang, J.; Zhang, M. Point and Interval Estimation of Mediation Effect: Multiplication Integral distribution method, non-parametric Bootstrap and MCMC method. Psychol. Bull. 2012, 44, 1408–1420. [Google Scholar]
- Sun, Z.; Hou, Y. Multi-perspective observation and policy response to my country’s regional unbalanced development. Manag. World 2019, 35, 1–8. (In Chinese) [Google Scholar]
- Wu, H.; Qu, Y. How Do Firms Promote Green Innovation through International Mergers and Acquisitions: The Moderating Role of Green Image and Green Subsidy. Int. J. Environ. Res. Public Health 2021, 18, 7333. [Google Scholar] [CrossRef]
- Yang, J.Y.; Roh, T. Open for Green Innovation: From the Perspective of Green Process and Green Consumer Innovation. Sustainability 2019, 11, 3234. [Google Scholar] [CrossRef] [Green Version]
- Gunnar, F.; Timo, B.; Alexander, B. ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. J. Sustain. Fin. Inv. 2015, 5, 210–233. [Google Scholar]
- Daniel, R.; Jochen, M.; Frank, W.G.; Lea, F. Why carbon pricing is not sufficient to mitigate climate change—And how “sustainability transition policy” can help. Proc. Natl. Acad. Sci. USA 2020, 117, 8664–8668. [Google Scholar]
- Chen, L.F.; Ye, Z.X.; Jin, S.Y. A Security, Privacy and Trust Methodology for IIoT. Tech. Gaz. 2021, 28, 898–906. [Google Scholar]
- Cao, Y.; Sun, L.; Wu, W. Customer concentration, internal control quality and corporate tax avoidance. Audit Res. 2018, 01, 120–128. [Google Scholar]
- Escrig-Olmedo, E.; Fernandez-Izquierdo, M.A.; Ferrero-Ferrero, I.; Rivera-Lirio, J.M.; Muñoz-Torres, M.J. Rating the raters: Evaluating how ESG rating agencies integrate sustainability principles. Sustainability 2019, 11, 915. [Google Scholar] [CrossRef] [Green Version]
Variable | Obs. | Mean | Std. | Min. | Max. |
---|---|---|---|---|---|
ROA | 3100 | 0.034 | 0.092 | −0.549 | 0.205 |
FCGP | 3100 | 2.528 | 8.382 | 0.000 | 150.000 |
SEC | 3100 | 0.464 | 0.546 | 0.080 | 2.187 |
CSR | 3100 | 20.497 | 10.317 | −19.750 | 83.960 |
CG | 3100 | 0.790 | 0.895 | −1.985 | 3.402 |
PCS | 3100 | 3.083 | 7.743 | 0.000 | 5.000 |
RII | 3100 | 5.885 | 6.033 | 1.000 | 31.000 |
BS | 3100 | 7.907 | 1.438 | 4.000 | 13.000 |
OC | 3100 | 29.552 | 12.155 | 3.003 | 81.104 |
ID | 3100 | 0.384 | 0.056 | 0.000 | 0.750 |
CC | 3100 | 0.771 | 0.420 | 0.000 | 1.000 |
SIZE | 3100 | 21.453 | 0.814 | 19.555 | 25.342 |
ALR | 3100 | 21.453 | 0.814 | 19.555 | 25.342 |
FIGR | 3100 | 0.497 | 2.758 | −0.986 | 1.687 |
Variable | ROA | FCGP | SEC | CSR | CG | PCS | RII | BS | OC | ID | SIZE | ALR | FIGR |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ROA | 1.00 | ||||||||||||
FCGP | 0.01 *** | 1.00 | |||||||||||
SEC | 0.05 *** | 0.02 ** | 1.00 | ||||||||||
CSR | 0.48 *** | 0.05 *** | 0.04 *** | 1.00 | |||||||||
CG | −0.01 *** | 0.02 ** | −0.03 *** | −0.04 *** | 1.00 | ||||||||
PCS | 0.06 *** | 0.69 *** | −0.02 *** | 0.06 *** | 0.02 *** | 1.00 | |||||||
RII | −0.01 *** | 0.04 *** | 0.03 ** | −0.02 *** | −0.09 *** | −0.07 *** | 1.00 | ||||||
BS | 0.04 *** | −0.06 *** | 0.06 *** | 0.06 | −0.59 *** | −0.03 | 0.09 *** | 1.00 | |||||
OC | 0.16 *** | 0.01 *** | 0.02 *** | 0.08 ** | −0.06 ** | 0.01 ** | −0.01 *** | −0.11 *** | 1.00 | ||||
ID | −0.03 *** | 0.08 *** | −0.07 | −0.05 *** | 0.54 *** | 0.04 *** | −0.06 *** | −0.66 | 0.08 *** | 1.00 | |||
SIZE | −0.07 *** | 0.16 *** | −0.04 | 0.05 *** | −0.30 *** | 0.09 *** | −0.04 *** | 0.13 *** | −0.14 *** | 0.04 *** | 1.00 | ||
ALR | −0.36 *** | 0.12 *** | −0.01 *** | −0.11 *** | 0.03 *** | −0.03 *** | 0.04 *** | −0.04 *** | −0.01 ** | −0.11 *** | 0.42 *** | 1.00 | |
FIGR | 0.02 *** | 0.01 *** | −0.02 *** | 0.04 *** | 0.04 *** | 0.02 *** | −0.01 *** | −0.02 *** | −0.02 *** | −0.01 *** | −0.01 *** | 0.01 * | 1.00 |
KERRYPNX | M 1 | M 2 | |||
---|---|---|---|---|---|
Var. | ROA | SEC | CSR | CG | ESG |
FCGP | 0.001 *** | 0.001 ** | 0.123 *** | 0.003 ** | 0.002 *** |
(2.59) | (2.53) | (4.35) | (2.52) | (14.77) | |
BS | 0.009 *** | 0.003 | 0.827 *** | −0.221 *** | −0.010 *** |
(3.78) | (0.67) | (2.99) | (−21.94) | (−6.11) | |
OC | 0.004 *** | −0.001 | 0.198 *** | 0.003 | 0.001 *** |
(9.80) | (-0.07) | (4.59) | (1.93) | (3.25) | |
ID | 0.061 | −0.051 | −5.108 | 3.949 *** | 0.169 *** |
(1.09) | (−0.60) | (−0.82) | (17.38) | (4.77) | |
CC | 0.027 *** | −0.002 | 1.318 ** | 0.091 *** | 0.008 *** |
(5.65) | (−0.23) | (2.47) | (4.69) | (2.68) | |
SIZE | 0.045 *** | −0.025 *** | 2.487 *** | −0.185 *** | 0.001 |
(10.48) | (−3.83) | (5.24) | (−10.71) | (0.38) | |
ALR | −0.339 *** | −0.022 | −17.265 *** | −0.108 | −0.041 *** |
(−20.53) | (−0.88) | (−9.38) | (−1.61) | (−3.91) | |
FIGR | 0.001 * | 0.001 | 0.207 *** | 0.009 *** | 0.001 *** |
(1.78) | (1.00) | (3.54) | (4.41) | (2.76) | |
Con. | −1.043 *** | 0.997 *** | −39.011 *** | 4.848 *** | 0.550 *** |
Obs. | 3100 | 3100 | 3100 | 3100 | 3100 |
Adj. R2 | 0.23 | 0.01 | 0.08 | 0.48 | 0.16 |
F | 86.76 | 4.26 | 24.21 | 274.38 | 56.39 |
Var. | ROA | |||
---|---|---|---|---|
SEC | 0.038 *** | |||
(2.80) | ||||
CSR | 0.003 *** | |||
(15.02) | ||||
CG | 0.011 ** | |||
(2.13) | ||||
ESG | 0.259 *** | |||
(8.44) | ||||
BS | 0.009 *** | 0.007 *** | 0.012 *** | 0.012 *** |
(3.69) | (3.00) | (4.27) | (4.80) | |
OC | 0.004 *** | 0.003 *** | 0.004 *** | 0.004 *** |
(9.77) | (8.77) | (9.66) | (9.37) | |
ID | 0.069 | 0.078 | 0.024 | 0.018 |
(1.23) | (1.45) | (0.41) | (0.32) | |
CC | 0.027 *** | 0.023 *** | 0.026 *** | 0.025 *** |
(5.67) | (5.14) | (5.43) | (5.28) | |
SIZE | 0.045 *** | 0.037 *** | 0.046 *** | 0.044 *** |
(10.54) | (9.23) | (10.55) | (10.57) | |
ALR | −0.338 *** | −0.293 *** | −0.338 *** | −0.328 *** |
(−20.51) | (−18.25) | (−20.47) | (−20.10) | |
FIGR | 0.001 * | 0.001 | 0.001 | 0.001 |
(1.76) | (0.79) | (1.62) | (1.35) | |
Con. | −1.066 *** | −0.932 *** | −1.080 *** | −1.185 *** |
Obs. | 3100 | 3100 | 3100 | 3100 |
Adj. R2 | 0.23 | 0.29 | 0.23 | 0.16 |
F | 86.94 | 122.03 | 86.40 | 56.39 |
Var. | ROA | |||
---|---|---|---|---|
SEC | 0.036 *** | |||
(2.67) | ||||
CSR | 0.003 *** | |||
(14.84) | ||||
CG | 0.010 ** | |||
(2.59) | ||||
ESG | 0.258 *** | |||
(8.02) | ||||
FCGP | 0.001 *** | 0.001 | 0.001 ** | 0.001 |
(2.45) | (1.38) | (2.49) | (0.18) | |
BS | 0.009 *** | 0.007 *** | 0.012 *** | 0.012 *** |
(3.71) | (3.02) | (4.47) | (4.81) | |
OC | 0.004 *** | 0.003 *** | 0.004 *** | 0.004 *** |
(9.83) | (8.82) | (9.68) | (9.41) | |
ID | 0.070 | 0.079 | 0.021 | 0.019 |
(1.25) | (1.47) | (0.35) | (0.35) | |
CC | 0.027 *** | 0.023 *** | 0.026 *** | 0.025 *** |
(5.59) | (5.08) | (5.37) | (5.23) | |
SIZE | 0.045 *** | 0.038 *** | 0.046 *** | 0.045 *** |
(10.66) | (9.32) | (10.75) | (10.64) | |
ALR | −0.338 *** | −0.293 *** | −0.337 *** | −0.328 *** |
(−20.52) | (−18.26) | (−20.41) | (−20.11) | |
FIGR | 0.001 * | 0.001 | 0.001 | 0.001 |
(1.68) | (0.78) | (1.54) | (1.34) | |
Con. | −1.079 *** | −0.941 *** | −1.092 *** | −1.185 *** |
Obs. | 3100 | 3100 | 3100 | 3100 |
Adj. R2 | 0.23 | 0.29 | 0.23 | 0.25 |
F | 78.11 | 108.72 | 77.66 | 86.34 |
Var. | M 4 | M 5 |
---|---|---|
FCGP | −0.001 | 0.001 *** |
(−0.11) | (3.36) | |
PCS | 0.003 *** | |
(6.62) | ||
FCGP × PCS | −0.001 *** | |
(−3.08) | ||
RII | −0.001 | |
(−0.80) | ||
FCG × PRII | −0.001 ** | |
(−2.45) | ||
BS | 0.009 *** | 0.009 *** |
(3.70) | (3.75) | |
OC | 0.004 *** | 0.004 *** |
(9.47) | (9.78) | |
ID | 0.064 | 0.065 |
(1.15) | (1.16) | |
CC | 0.023 *** | 0.027 *** |
(4.89) | (5.58) | |
SIZE | 0.049 *** | 0.044 *** |
(11.52) | (10.46) | |
ALR | −0.329 *** | −0.340 *** |
(−20.07) | (−20.60) | |
FIGR | 0.001 | 0.001 * |
(1.60) | (1.79) | |
Con. | −1.141 *** | −1.036 *** |
Obs. | 3100 | 3100 |
Adj. R2 | 0.24 | 0.23 |
F | 75.27 | 70.38 |
Var. | M 1 | M 2 | |||
---|---|---|---|---|---|
ROA | SEC | CSR | CG | ESG | |
GPQ | 0.002 *** | −0.001 | 0.168 *** | 0.015 *** | 0.001 *** |
(3.54) | (−0.12) | (3.12) | (7.14) | (3.15) | |
BS | 0.009 *** | 0.003 | 0.806 *** | −0.221 *** | −0.010 *** |
(3.74) | (0.76) | (2.90) | (−20.87) | (−6.14) | |
OC | 0.004 *** | −0.001 | 0.197 *** | 0.004 ** | 0.001 *** |
(9.80) | (−0.10) | (4.54) | (2.42) | (2.91) | |
ID | 0.070 | −0.024 | −3.651 | 3.877 *** | 0.193 *** |
(1.25) | (−0.28) | (−0.58) | (16.23) | (5.24) | |
CC | 0.028 *** | −0.002 | 1.382 *** | 0.081 *** | 0.009 *** |
(5.78) | (−0.29) | (2.58) | (3.96) | (2.71) | |
SIZE | 0.043 *** | −0.026 *** | 2.267 *** | −0.174 *** | −0.002 |
(10.13) | (−3.94) | (4.77) | (−9.57) | (−0.73) | |
ALR | −0.341 *** | −0.021 | −17.559 *** | −0.195 *** | −0.043 *** |
(−20.70) | (−0.83) | (−9.51) | (−2.76) | (−4.00) | |
FIGR | 0.001 * | 0.002 ** | 0.211 *** | 0.011 *** | 0.001 *** |
(1.81) | (2.06) | (3.59) | (4.76) | (2.86) | |
Con. | −1.012 *** | 1.011 *** | −34.537 *** | 4.633 *** | 0.550 *** |
Obs. | 3100 | 3100 | 3100 | 3100 | 3100 |
Adj. R2 | 0.23 | 0.01 | 0.07 | 0.45 | 0.09 |
F | 87.69 | 3.69 | 22.99 | 244.69 | 27.99 |
M 2 | M 3 | ||||
---|---|---|---|---|---|
Var. | TobinQ | ||||
FCGP | 0.053 *** | ||||
(12.29) | |||||
SEC | −0.473 ** | ||||
(−1.97) | |||||
CSR | 0.020 *** | ||||
(6.13) | |||||
CG | −0.666 *** | ||||
(−7.54) | |||||
ESG | 0.918 * | ||||
(1.67) | |||||
BS | −0.043 | −0.053 | −0.070 | −0.202 *** | −0.045 |
(−1.02) | (−1.21) | (−1.61) | (−4.25) | (−1.02) | |
OC | 0.006 | 0.004 | 0.001 | 0.006 | 0.004 |
(0.83) | (0.61) | (0.05) | (0.91) | (0.52) | |
ID | −0.740 | −0.244 | −0.148 | 2.421 ** | −0.401 |
(−0.77) | (−0.25) | (−0.15) | (2.33) | (−0.40) | |
CC | 0.035 | 0.037 | 0.011 | 0.098 | 0.030 |
(0.42) | (0.43) | (0.13) | (1.17) | (0.35) | |
SIZE | −1.085 *** | −1.154 *** | −1.189 *** | −1.267 *** | −1.141 *** |
(−14.88) | (−15.35) | (−15.89) | (−16.68) | (−15.22) | |
ALR | −0.690 ** | −0.736 ** | −0.383 | −0.798 *** | −0.686 ** |
(−2.44) | (−2.53) | (−1.30) | (−2.77) | (−2.35) | |
FIGR | 0.007 | 0.009 | 0.004 | 0.015 | 0.008 |
(0.75) | (0.96) | (0.47) | (1.61) | (0.82) | |
Con. | 26.369 *** | 28.161 *** | 28.387 *** | 30.948 *** | 27.120 *** |
Obs. | 3100 | 3100 | 3100 | 3100 | 3100 |
Adj. R2 | 0.19 | 0.14 | 0.29 | 0.23 | 0.14 |
F | 70.23 | 48.83 | 122.03 | 86.40 | 48.67 |
KERRYPNX | 2SLS Test Results | GMM Test Results | ||
---|---|---|---|---|
Var. | M 4 | M 5 | M 4 | M 5 |
FCGP | 0.001 | 0.002 ** | −0.003 ** | 0.001 |
(1.64) | (2.51)) | (−2.38) | (1.01) | |
PCS | 0.001 | 0.006 *** | ||
(1.51) | (4.51) | |||
FCGP × PCS | −0.001 * | −0.001 | ||
(−1.79) | (−1.21) | |||
IV-PCS | −0.008 *** | |||
(−3.51) | ||||
IV-PCS × FCGP | −0.001 * | |||
(1.66) | ||||
RII | 0.001 | −0.001 | ||
(0.76) | (1.05) | |||
FCGP × RII | −0.001 * | −0.001 | ||
(−1.82) | (−1.08) | |||
IV-RII | −0.002 * | |||
(−1.78) | ||||
IV-RII × FCGP | −0.001 | |||
(0.16) | ||||
BS | 0.004 *** | 0.004 ** | −0.005 | −0.001 *** |
(2.85) | (2.42) | (−0.95) | (−0.21) | |
OC | 0.001 *** | 0.001 *** | 0.002 *** | 0.001 * |
(9.70) | (9.43) | (2.75) | (1.84) | |
ID | 0.001 | 0.003 | −0.123 | −0.076 |
(0.02) | (0.09) | (−0.95) | (−0.51) | |
CC | 0.020 *** | 0.019 *** | −0.006 | 0.008 |
(4.72) | (4.15) | (−0.59) | (0.93) | |
SIZE | 0.013 *** | 0.013 *** | 0.038 | 0.003 |
(5.44) | (5.38) | (1.14) | (0.66) | |
ALR | −0.201 *** | −0.200 *** | −0.034 | −0.114 *** |
(−12.61) | (−12.44) | (−0.86) | ||
FIGR | −0.001 * | 0.001 * | −0.002 | 0.001 |
(1.83) | (1.79) | (−0.66) | (0.30) | |
Obs. | 3100 | 3100 | 2311 | 2311 |
AR (1) | 0.000 | 0.000 | ||
AR (2) | 0.112 | 0.053 | ||
Hansen Test | 0.086 | 0.033 |
Variable | Obs. | Coef. | Std. Err. | Z Score | P > Z |
---|---|---|---|---|---|
Soble | 3100 | 0.000056 | 0.000024 | 2.368 | 0.018 |
Goodman-1 | 3100 | 0.000056 | 0.000024 | 2.339 | 0.019 |
Goodman-2 | 3100 | 0.000056 | 0.000024 | 2.399 | 0.016 |
a coefficient | 3100 | 0.000476 | 0.000183 | 2.602 | 0.009 |
b coefficient | 3100 | 0.118743 | 0.020767 | 5.718 | 0.001 |
Indirect effect | 3100 | 0.000056 | 0.000024 | 2.368 | 0.018 |
Direct effect | 3100 | 0.001603 | 0.000211 | 7.586 | 0.001 |
Total effect | 3100 | 0.001659 | 0.000212 | 7.822 | 0.001 |
Proportion of total effect that is mediated | 3.40% |
Variable | Obs. | Coef. | Bias. | Std. Err. | 95% Conf. Interval |
---|---|---|---|---|---|
Indirect effect (P) | 3100 | 0.000056 | 0.000001 | 0.000017 | (0.0000259, 0.0000904) |
Indirect effect (BC) | 3100 | 0.000056 | 0.000001 | 0.000017 | (0.0000281, 0.0000911) |
Direct effect (P) | 3100 | 0.001603 | 0.000017 | 0.000311 | (0.0010192, 0.0022461) |
Direct effect (BC) | 3100 | 0.001603 | 0.000017 | 0.000311 | (0.0009986, 0.0022380) |
Proportion of total effect that is mediated | 3.40% |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zheng, J.; Khurram, M.U.; Chen, L. Can Green Innovation Affect ESG Ratings and Financial Performance? Evidence from Chinese GEM Listed Companies. Sustainability 2022, 14, 8677. https://doi.org/10.3390/su14148677
Zheng J, Khurram MU, Chen L. Can Green Innovation Affect ESG Ratings and Financial Performance? Evidence from Chinese GEM Listed Companies. Sustainability. 2022; 14(14):8677. https://doi.org/10.3390/su14148677
Chicago/Turabian StyleZheng, Jianzhuang, Muhammad Usman Khurram, and Lifeng Chen. 2022. "Can Green Innovation Affect ESG Ratings and Financial Performance? Evidence from Chinese GEM Listed Companies" Sustainability 14, no. 14: 8677. https://doi.org/10.3390/su14148677