Can the reform of green credit policy promote enterprise eco-innovation? A theoretical analysis

Sheng Wu; Liangpeng Wu; Xianglian Zhao

doi:10.3934/jimo.2021028

Article Contents

2022, Volume 18, Issue 2: 1451-1485. Doi: 10.3934/jimo.2021028

This issue Previous Article Optimizing micro-algae production in a raceway pond with variable depth Next Article Merging short-term and long-term planning problems in home health care under continuity of care and patterns for visits

Can the reform of green credit policy promote enterprise eco-innovation? A theoretical analysis

a.
College of Economic and Management, Nanjing University of Aeronautics, and Astronautics, Nanjing 211106, China
b.
College of Intelligent Manufacturing, TaiZhou Institute of Sci.& Tech., Njust, Taizhou 225300, China
c.
College of Management Engineering, Nanjing University of Information, Science & Technology, Nanjing, 210044, China

^* Corresponding author: 1017379408@qq.com
^* Corresponding author: 1017379408@qq.com

Received: August 2020

Revised: November 2020

Early access: February 2021

Published: March 2022

Abstract Full Text(HTML) Figure(10) / Table(4) Related Papers Cited by

Abstract

The weakness that China's traditional credit fails to effectively limit enterprise emissions has become increasingly evident. Although the industry-oriented green credit policy has achieved certain effects on environmental performance through the differentiated resource allocation of the industries, banking financial institutions have the ambiguity in the definition of the credit object and the characteristics of profit maximization, which cannot achieve the essential purpose of green credit sustainably. Hence, we propose a new eco-innovation-oriented green credit policy. We prove theoretically that the new green credit is feasible and can be used as an exogenous driver for improving enterprises' eco-innovation. Contrasting with traditional credit, the newly proposed credit policy is an expansionary monetary policy, which has the characteristics of expanding credit lines and differential interest rates. Utilizing evolutionary game theory, we calculate the evolution stability conditions of green credit and eco-innovation. The results show that the key to green credit to maintaining sustainable development is the return on investment due to eco-innovation. Our theoretical analysis also reveals that environmental benefit-cost ratios and adjustment cost parameters of different assets are the important factors for green credit.

Keywords:

Mathematics Subject Classification: 91B03.

Citation:

Full Text(HTML)

Figure 1. Path of credits to provide benefits

Download: Full-size image PowerPoint slide

Figure 2. Game matrix

Download: Full-size image PowerPoint slide

Figure 3. Impacts of $ \alpha $ and $ \beta $ on $ X_{2} $ when $ \varepsilon = J $. Evolution stability constraint $ X_{2} $ increases with the increase of the bank's environmental preference $ \alpha $ and the enterprise's environmental preference $ \beta $. The figure shows that some space remains where $ X_{2}>0 $ if $ \varepsilon>J $ with the increase in $ \alpha $ and $ \beta $

Download: Full-size image PowerPoint slide

Figure 4. Impacts of $ \alpha $ and $ \beta $ on $ r. $ The green surface denotes the optimal interest rate of EOGC, and the red surface denotes the optimal interest rate of the traditional credit. The figure shows the change in the optimal interest rate of different credits with respect to environmental preferences

Download: Full-size image PowerPoint slide

Figure 5. Impacts of $ \alpha $ and $ \beta $ on $ \frac{I}{K} . $ The green surface denotes the ratio of the optimal credit line to the enterprise capital under EOGC, $ \frac{I_{g}^{*}}{K}, $ and the red surface denotes the ratio of the optimal credit line to the enterprise capital under the traditional credit, $ \frac{I_{o}^{*}}{K} . $ The figure shows that the credit line of EOGC changes with the environmental preference, and the credit line of the traditional credit does not

Download: Full-size image PowerPoint slide

Figure 6. Impacts of $ \alpha $ and $ \beta $ on $ \frac{I_{ {ina}}^{*}}{I_{ {fia}}^{*}} . $ The green surface denotes the optimal eco-innovation investment ratio of intangible assets to fixed assets when $ \eta_{i n a} = 0.1, $ the red surface is the optimal ratio when $ \eta_{i n a} = 0.5, $ and the yellow surface is the optimal ratio when $ \eta_{i n a} = 0.8, $ with the condition of $ \eta_{fi a} = 0.3 . $ The figure shows that the impacts of $ \alpha $ and $ \beta $ on $ \frac{I_{ {ina}}^{*}}{I_{ {fia}}^{*}} $ change with the environmental benefit-cost ratio of intangible assets

Download: Full-size image PowerPoint slide

Figure 7. Impacts of $ \eta_{ {ina}} $ and $ \eta_{ {fia}} $ on $ X_{2} $ when $ \varepsilon = J $. The green surface denotes the evolution stability constraint $ X_{2} $ when $ \beta = 0.7, $ the red surface denotes $ X_{2} $ when $ \beta = 0.5, $ and the yellow surface denotes $ X_{2} $ when $ \beta = 0.2, $ with the condition of $ \alpha = 0.3 . $ The figure shows that some space remains where $ X_{2}>0 $ if $ \varepsilon>J $ with the increase in $ \eta_{i n a} $ and $ \eta_{f i a}, $ and the impact of $ \eta_{ {ina}} $ is greater than that of $ \eta_{ {fia}} $

Download: Full-size image PowerPoint slide

Figure 8. Impacts of $ \eta_{i n a} $ and $ \eta_{fi a} $ on $ \frac{I_{i n a}^{*}}{I_{f i a}^{*}} . $ The green surface denotes the optimal eco-innovation investment ratio of intangible assets to fixed assets when $ \beta = 0.7, $ the red surface denotes the optimal investment ratio when $ \beta = 0.5, $ and the yellow surface denotes the optimal investment ratio when $ \beta = 0.2, $ with the condition of $ \alpha = 0.3 . $ The figure shows that the impacts of the environmental benefit-cost ratios on the optimal eco-innovation investment ratio of intangible assets to fixed assets change with the enterprise's environmental preference

Download: Full-size image PowerPoint slide

Figure 9. Impacts of EOGC on the bank's economic benefits. The green surface denotes the bank's economic benefits under EOGC, and the red surface denotes the bank's economic benefits under the traditional credit. The values of the bank's environmental preference $ \alpha $ and the enterprise's environmental preference $ \beta $ in the figure are 0.1, 0.3, and 0.6, respectively. The figure shows that the bank's economic benefits under EOGC change with the environmental preferences and differ from that of traditional credit

Download: Full-size image PowerPoint slide

Figure 10. Impacts of EOGC on the enterprise's economic benefits. The green surface denotes the enterprise's economic benefits growth caused by eco-innovation under EOGC, the red surface denotes the enterprise's economic benefits growth caused by the other activities under the traditional credit, and the yellow surface denotes the enterprise's economic benefits growth caused by eco-innovation under the traditional credit. The values of the bank's environmental preference $ \alpha $ and the enterprise's environmental preference $ \beta $ in the figure are 0.1, 0.3, and 0.6, respectively. The figure shows the change of the enterprise's economic benefits with the environmental preferences under EOGC

Download: Full-size image PowerPoint slide

Table 1. Comparison oftypes of credit

types		traditional credit		EOGC
characteristics		ordinary credit	IOGC	EOGC
credit object	pollution industries	√	×	√
	general industries	√	×	√
	green industries	√	√	√
guidance	market means	√	×	√
guidance	administrative means	×	√	×
credit standards	maximum economic benefits	√	√	×
credit standards	maximum comprehensive benefits	×	×	√
loans usage	activity with the greatest return on investment	√	√	×
loans usage	eco-innovation	×	×	√

| Show Table

DownLoad: CSV

Table 2. Variables and parameters

Notation		Definition
Variables	$ B $	comprehensive benefits of the bank
	$ R $	economic benefits of the bank
	$ F $	comprehensive benefits of the enterprise
	$ V $	economic benefits of the enterprise
	$ M $	environmental benefits
	$ I $	credit line
	$ r $	interest rate
Parameters	$ \alpha $	environmental preferences of the bank
	$ \beta $	environmental preferences of the enterprise
	$ \eta $	environmental benefit-cost ratio
	$ q $	Tobin's Q
	$ d $	credit risk
	$ \rho $	adjustment cost parameter
	$ J $	return on capital of eco-innovation
	$ \varepsilon $	return on capital of the other activities
	$ K $	enterprise capital
	$ \tau $	discount rate
Indexes	$ fna $	intangible assets of the enterprise
	$ fia $	fixed assets of the enterprise
	$ o $	traditional credits
	$ g $	EOGC
	$ t $	time

| Show Table

DownLoad: CSV

Table 3. Evolutionary stability conditions

Scenarios	Points	$ \operatorname{det} T $	$ \operatorname{tr} T $	Equilibrium results	Stability conditions
I	(0, 0)	$ + $	$ + $	instability point
	(0, 1)	$ - $	$ \pm $	saddle point	$ B_{1}>B_{2} $
	(1, 0)	$ - $	$ \pm $	saddle point	$ F_{1}>F_{3} $
	(1, 1)	$ + $	$ - $	ESS
II	(0, 0)	$ - $	$ \pm $	saddle point
	(0, 1)	$ + $	$ - $	ESS	$ B_{2}>B_{1} $
	(1, 0)	$ + $	$ + $	instability point	$ F_{2}>F_{4} $
	(1, 1)	$ - $	$ \pm $	saddle point
III	(0, 0)	$ - $	$ \pm $	saddle point
	(0, 1)	$ + $	$ + $	instability point	$ B_{3}>B_{4} $
	(1, 0)	$ + $	$ - $	ESS	$ F_{3}>F_{1} $
	(1, 1)	$ - $	$ \pm $	saddle point
IV	(0, 0)	$ + $	$ - $	ESS
	(0, 1)	$ - $	$ \pm $	saddle point	$ B_{4}>B_{3} $
	(1, 0)	$ - $	$ \pm $	saddle point	$ F_{4}>F_{2} $
	(1, 1)	$ + $	$ + $	instability point

| Show Table

DownLoad: CSV

Table 4. Optimal interest rates and credit lines

Scenarios	Optimal interest rates	Optimal credit lines
I	$ \frac{1}{2}(q+d)+\frac{\tau\left(\eta_{{ina}} \rho_{\text {fia}}+\eta_{{fia}} \rho_{{ina}}\right)}{2\left(\rho_{{ina}}+\rho_{{fia}}\right)}\left(\frac{\beta}{1-\beta}-\frac{\alpha}{1-\alpha}\right) $	$ \frac{K\left(\rho_{{ina}}+\rho_{{fia}}\right)}{2 \rho_{{ina}} \rho_{ {fia}}}(q-d)+\frac{\tau K\left(\eta_{ {ina}} \rho_{{fia}}+\eta_{ {fia}} \rho_{ {ina}}\right)}{2 \rho_{ {ina}} \rho_{ {fia}}}\left(\frac{\alpha}{1-\alpha}+\frac{\beta}{1-\beta}\right) $
II	$ \frac{1}{2}(q+d)+\frac{\tau\left(\eta_{{ina}} \rho_{{fia}}+\eta_{{fia}} \rho_{{ina}}\right) \beta}{2\left(\rho_{{ina}}+\rho_{{fia}}\right)(1-\beta)} $	$ \frac{K\left(\rho_{{ina}}+\rho_{{fia}}\right)}{2 \rho_{{ina}} \rho_{ {fia}}}(q-d)+\frac{\tau K\left(\eta_{ {ina}} \rho_{{fia}}+\eta_{{fia}} \rho_{ {ina}}\right) \beta}{2 \rho_{{ina}} \rho_{{fia}}(1-\beta)} $
III	$ \frac{1}{2}(q+d)-\frac{\tau\left(\eta_{{ina}} \rho_{{fia}}+\eta_{{fia}} \rho_{{ina}}\right) \alpha}{2\left(\rho_{{ina}}+\rho_{{fia}}\right)(1-\alpha)} $	$ \frac{K\left(\rho_{{ina}}+\rho_{ {fia}}\right)}{2 \rho_{ {ina}} \rho_{ {fia}}}(q-d)+\frac{\tau K\left(\eta_{ {ina}} \rho_{ {fia}}+\eta_{ {fia}} \rho_{ {ina}}\right) \alpha}{2 \rho_{ {ina}} \rho_{ {fia}}(1-\alpha)} $
IV	$ \frac{1}{2}(q+d) $	$ \frac{K\left(\rho_{ {ina}}+\rho_{ {fia}}\right)}{2 \rho_{ {ina}} \rho_{ {fia}}}(q-d) $

| Show Table

DownLoad: CSV

Related Papers

Cited by

References

[1]	A. B. Abel, The effects of q and cash flow on investment in the presence of measurement error, J. Financ. Econ., 128 (2018), 363-377. doi: 10.1016/j.jfineco.2018.02.005.
[2]	A. B. Abel and J. C. Eberly, A unified model of investment under uncertainty, Am. Econ. Rev., 84 (1994), 1369-1384. doi: 10.3386/w4296.
[3]	I. Alexopoulos, K. Kounetas and D. Tzelepis, Environmental and financial performance. Is there a win-win or a win-loss situation? Evidence from the Greek manufacturing, J. Clean Prod., 197 (2018), 1275-1283. doi: 10.1016/j.jclepro.2018.06.302.
[4]	M. D. Amore, C. Schneider and A. Žaldokas, Credit supply and corporate innovation, J. Financ. Econ., 109 (2013), 835-855.
[5]	D. Andrei, W. Mann and N. Moyen, Why did the q theory of investment start working?, J. Financ. Econ., 133 (2019), 251-272.
[6]	M. G. Arnold and K. Hockerts, The greening Dutchman: Philips' process of green flagging to drive sustainable innovations, Bus. Strateg. Environ., 20 (2011), 394-407. doi: 10.1002/bse.700.
[7]	J. Atanassov, V. Nanda and A. Seru, Finance and innovation: The case of publicly listed firms, Unpublished working paper. University of Oregon, Georgia State of Technology, and University of Chicago.
[8]	R. Baeriswyl and C. Cornand, The distortionary effect of monetary policy: Credit expansion vs. lump-sum transfers in the lab, B. E. J. Macroecono., 18 (2018), 1-30.
[9]	J. Barney, Firm resources and sustained competitive advantage, J. Manag., 17 (1991), 99-120. doi: 10.1016/S0742-3322(00)17018-4.
[10]	F. Basrawi, T. K. Ibrahim, K. Habib and T. Yamada, Effect of operation strategies on the economic and environmental performance of a micro gas turbine trigeneration system in a tropical region, Energy, 97 (2016), 262-272. doi: 10.1016/j.energy.2015.12.117.
[11]	W. J. Baumol, The Free-Market Innovation Machine: Analyzing the Growth Miracle of Capitalism, Princeton University Press, 2002. doi: 10.1515/9781400851638.
[12]	L. Benfratello, F. Schiantarelli and A. Sembenelli, Banks and innovation: Microeconometric evidence on Italian firms, J. Financ. Econ., 90 (2008), 197-217. doi: 10.1016/j.jfineco.2008.01.001.
[13]	P. Berrone, A. Fosfuri, L. Gelabert and L. R. Gomez-Mejia, Necessity as the mother of "green" inventions: Institutional pressures and environmental innovations, Strateg. Manage. J., 34 (2013), 891-909. doi: 10.1002/smj.2041.
[14]	A. Bitat, Environmental regulation and eco-innovation: The porter hypothesis refined, Eurasian Bus. Rev., 8 (2018), 299-321. doi: 10.1007/s40821-017-0084-6.
[15]	P. Bolton, H. Chen and N. Wang, A unified theory of Tobin's q, corporate investment, financing, and risk management, J. Financ., 66 (2011), 1545-1578. doi: 10.3386/w14845.
[16]	M. B. Bossle, M. D. de Barcellos, L. M. Vieira and L. Sauvée, The drivers for adoption of eco-innovation, J. Clean Prod., 113 (2016), 861-872. doi: 10.1016/j.jclepro.2015.11.033.
[17]	W. Cai and G. Li, The drivers of eco-innovation and its impact on performance: Evidence from China, J. Clean Prod., 176 (2018), 110-118. doi: 10.1016/j.jclepro.2017.12.109.
[18]	W. Cai and X. Zhou, On the drivers of eco-innovation: Empirical evidence from China, J. Clean Prod., 79 (2014), 239-248. doi: 10.1016/j.jclepro.2014.05.035.
[19]	L. M. Campos, D. A. de Melo Heizen, M. A. Verdinelli and P. A. C. Miguel, Environmental performance indicators: A study on iso 14001 certified companies, J. Clean Prod., 99 (2015), 286-296. doi: 10.1016/j.jclepro.2015.03.019.
[20]	J. Carrillo-Hermosilla, P. Del Río and T. Könnölä, Diversity of eco-innovations: Reflections from selected case studies, J. Clean Prod., 18 (2010), 1073-1083. doi: 10.1016/j.jclepro.2010.02.014.
[21]	W. Chen and Z. Hu, Using evolutionary game theory to study governments and manufacturers' behavioral strategies under various carbon taxes and subsidies, J. Clean Prod., 201 (2018), 123-141. doi: 10.1016/j.jclepro.2018.08.007.
[22]	C. Cheng, Y. Hua and D. Tan, Spatial dynamics and determinants of sustainable finance: Evidence from venture capital investment in China, J. Clean Prod., 232 (2019), 1148-1157. doi: 10.1016/j.jclepro.2019.05.360.
[23]	C. C. Cheng, C. Yang and C. Sheu, The link between eco-innovation and business performance: A Taiwanese industry context, J. Clean Prod., 64 (2014), 81-90. doi: 10.1016/j.jclepro.2013.09.050.
[24]	G. Contreras, J. W. Bos and S. Kleimeier, Self-regulation in sustainable finance: The adoption of the equator principles, World Dev., 122 (2019), 306-324. doi: 10.1016/j.worlddev.2019.05.030.
[25]	M. C. Cuerva, Á. Triguero-Cano and D. Córcoles, Drivers of green and non-green innovation: Empirical evidence in low-tech smes, J. Clean Prod., 68 (2014), 104-113. doi: 10.1016/j.jclepro.2013.10.049.
[26]	S. R. Das, The surprise element: Jumps in interest rates, J. Econom., 106 (2002), 27-65. doi: 10.1016/S0304-4076(01)00085-9.
[27]	M. D. Delis and G. P. Kouretas, Interest rates and bank risk-taking, J. Bank Financ., 35 (2011), 840-855. doi: 10.1016/j.jbankfin.2010.09.032.
[28]	M. Finger, I. Gavious and R. Manos, Environmental risk management and financial performance in the banking industry: A cross-country comparison, J. Int. Financ. Mark. Institut. Money, 52 (2018), 240-261. doi: 10.1016/j.intfin.2017.09.019.
[29]	D. Friedman, Evolutionary games in economics, Econometrica, 59 (1991), 637-666. doi: 10.2307/2938222.
[30]	D. Friedman, On economic applications of evolutionary game theory, J. Evol. Econ., 8 (1998), 15-43. doi: 10.1007/s001910050054.
[31]	C. Fussler and P. James, Eco-innovation: A breakthrough discipline for innovation and sustainability, Pitman: London, 1996.
[32]	E. M. García-Granero, L. Piedra-Muñoz and E. Galdeano-Gómez, Eco-innovation measurement: A review of firm performance indicators, J. Clean Prod., 191 (2018), 304-317.
[33]	C. Ghisetti and K. Rennings, Environmental innovations and profitability: How does it pay to be green? An empirical analysis on the German innovation survey, J. Clean Prod., 75 (2014), 106-117. doi: 10.1016/j.jclepro.2014.03.097.
[34]	F. He, X. Miao, C. W. Wong and S. Lee, Contemporary corporate eco-innovation research: A systematic review, J. Clean Prod., 174 (2018), 502-526. doi: 10.1016/j.jclepro.2017.10.314.
[35]	L. He, L. Zhang, Z. Zhong, D. Wang and F. Wang, Green credit, renewable energy investment and green economy development: Empirical analysis based on 150 listed companies of China, J. Clean Prod., 208 (2019), 363-372. doi: 10.1016/j.jclepro.2018.10.119.
[36]	A. M. Herrera and R. Minetti, Informed finance and technological change: Evidence from credit relationships, J. Financ. Econ., 83 (2007), 223-269. doi: 10.2139/ssrn.539782.
[37]	J. Hojnik and M. Ruzzier, The driving forces of process eco-innovation and its impact on performance: Insights from Slovenia, J. Clean Prod., 133 (2016), 812-825. doi: 10.1016/j.jclepro.2016.06.002.
[38]	P. Hsu, X. Tian and Y. Xu, Financial development and innovation: Cross-country evidence, J. Financ. Econ., 112 (2014), 116-135.
[39]	O. Jaeggi, G. W. Ziero, J. Tobin-de la Puente and J. F. Kölbel, Understanding sustainable finance, Positive Impact Investing, Springer, 2018, 39-63. doi: 10.1007/978-3-319-10118-7_3.
[40]	K. Jiang, D. You, R. Merrill and Z. Li, Implementation of a multi-agent environmental regulation strategy under Chinese fiscal decentralization: An evolutionary game theoretical approach, J. Clean Prod., 214 (2019), 902-915. doi: 10.1016/j.jclepro.2018.12.252.
[41]	D. Jin and N. Mengqi, The paradox of green credit in China, Energy Procedia, 5 (2011), 1979-1986. doi: 10.1016/j.egypro.2011.03.340.
[42]	E. Karakaya, A. Hidalgo and C. Nuur, Diffusion of eco-innovations: A review, Renew. Sust. Energ. Rev., 33 (2014), 392-399. doi: 10.1016/j.rser.2014.01.083.
[43]	R. Kemp and M. Volpi, The diffusion of clean technologies: A review with suggestions for future diffusion analysis, J. Clean Prod., 16 (2008), 14-21. doi: 10.1016/j.jclepro.2007.10.019.
[44]	T. Kuo and S. Smith, A systematic review of technologies involving eco-innovation for enterprises moving towards sustainability, J. Clean Prod., 192 (2018), 207-220. doi: 10.1016/j.jclepro.2018.04.212.
[45]	L. Laeven, R. Levine and S. Michalopoulos, Financial innovation and endogenous growth, J. Financ. Intermed., 24 (2015), 1-24.
[46]	T. Lagoarde-Segot, Diversifying finance research: From financialization to sustainability, Int. Rev. Financ. Anal., 39 (2015), 1-6. doi: 10.1016/j.irfa.2015.01.004.
[47]	T. Lagoarde-Segot, Sustainable finance. A critical realist perspective, Res. Int. Bus. Financ., 47 (2019), 1-9. doi: 10.1016/j.ribaf.2018.04.010.
[48]	A. Laschi, E. Marchi and S. González-García, Environmental performance of wood pellets' production through life cycle analysis, Energy, 103 (2016), 469-480. doi: 10.1016/j.energy.2016.02.165.
[49]	J. Lerner, M. Sorensen and P. Strömberg, Private equity and long-run investment: The case of innovation, J. Financ., 66 (2011), 445-477. doi: 10.3386/w14623.
[50]	C. Li, F. Zhang, C. Cao, Y. Liu and T. Qu, Organizational coordination in sustainable humanitarian supply chain: An evolutionary game approach, J. Clean Prod., 219 (2019), 291-303. doi: 10.1016/j.jclepro.2019.01.233.
[51]	R. Li and R. Ramanathan, Exploring the relationships between different types of environmental regulations and environmental performance: Evidence from China, J. Clean Prod., 196 (2018), 1329-1340. doi: 10.1016/j.jclepro.2018.06.132.
[52]	J. Liu, Y. Xia, Y. Fan, S. Lin and J. Wu, Assessment of a green credit policy aimed at energy-intensive industries in china based on a financial cge model, J. Clean Prod., 163 (2017), 293-302. doi: 10.1016/j.jclepro.2015.10.111.
[53]	X. Liu, E. Wang and D. Cai, Green credit policy, property rights and debt financing: Quasi-natural experimental evidence from China, Financ. Res. Lett., 29 (2019), 129-135. doi: 10.1016/j.frl.2019.03.014.
[54]	A. Marcon, J. F. de Medeiros and J. L. D. Ribeiro, Innovation and environmentally sustainable economy: Identifying the best practices developed by multinationals in Brazil, J. Clean Prod., 160 (2017), 83-97. doi: 10.1016/j.jclepro.2017.02.101.
[55]	J. Murphy and A. Gouldson, Environmental policy and industrial innovation: Integrating environment and economy through ecological modernisation, Geoforum, 31 (2000), 33-44. doi: 10.1016/S0016-7185(99)00042-1.
[56]	Y. Nakao, A. Amano, K. Matsumura, K. Genba and M. Nakano, Relationship between environmental performance and financial performance: An empirical analysis of japanese corporations, Bus. Strateg. Environ., 16 (2007), 106-118. doi: 10.1002/bse.476.
[57]	R. Nidumolu, C. K. Prahalad and M. R. Rangaswami, Why sustainability is now the key driver of innovation, Harv. Bus. Rev., 87 (2009), 57-64.
[58]	X. Peng and Y. Liu, Behind eco-innovation: Managerial environmental awareness and external resource acquisition, J. Clean Prod., 139 (2016), 347-360. doi: 10.1016/j.jclepro.2016.08.051.
[59]	R. H. Peters and L. A. Taylor, Intangible capital and the investment-q relation, J. Financ. Econ., 123 (2017), 251-272.
[60]	M. Prokopczuk, S. T. Rachev, G. Schindlmayr and S. Trück, Quantifying risk in the electricity business: A raroc-based approach, Energy Econ., 29 (2007), 1033-1049. doi: 10.1016/j.eneco.2006.08.006.
[61]	J. Qian, P. E. Strahan and Z. Yang, The impact of incentives and communication costs on information production and use: Evidence from bank lending, J. Financ., 70 (2015), 1457-1493. doi: 10.1111/jofi.12251.
[62]	M. Raberto, B. Ozel, L. Ponta, A. Teglio and S. Cincotti, From financial instability to green finance: The role of banking and credit market regulation in the eurace model, J. Evol. Econ., 29 (2019), 429-465. doi: 10.1007/s00191-018-0568-2.
[63]	K. Rennings, Redefining innovation-Eco-innovation research and the contribution from ecological economics, Ecol. Econ., 32 (2000), 319-332. doi: 10.1016/S0921-8009(99)00112-3.
[64]	S. Scarpellini, L. M. Marín-Vinuesa, P. Portillo-Tarragona and J. M. Moneva, Defining and measuring different dimensions of financial resources for business eco-innovation and the influence of the firms' capabilities, J. Clean Prod., 204 (2018), 258-269. doi: 10.1016/j.jclepro.2018.08.320.
[65]	B. Scholtens and L. Dam, Banking on the equator. Are banks that adopted the equator principles different from non-adopters?, World Dev., 35 (2007), 1307-1328. doi: 10.1016/j.worlddev.2006.10.013.
[66]	A. Smith, P. Voss Jan and J. Grin, Innovation studies and sustainability transitions: The allure of the multi-level perspective and its challenges, Res. Policy, 39 (2010), 435-448. doi: 10.1016/j.respol.2010.01.023.
[67]	N. M. Stoughton and J. Zechner, Optimal capital allocation using raroc(tm) and eva, J. Financ. Intermed., 16 (2007), 312-342.
[68]	Q. Sun and M. Z. Xiaolan, Financing intangible capital, J. Financ. Intermed., 133 (2019), 564-588.
[69]	D. D. Thomakos and T. A. Alexopoulos, Carbon intensity as a proxy for environmental performance and the informational content of the epi, Energy Policy, 94 (2016), 179-190. doi: 10.1016/j.enpol.2016.03.030.
[70]	P. Tian and B. Lin, Impact of financing constraints on firm's environmental performance: Evidence from China with survey data, J. Clean Prod., 217 (2019), 432-439. doi: 10.1016/j.jclepro.2019.01.209.
[71]	C. Trumpp, J. Endrikat, C. Zopf and E. Guenther, Definition, conceptualization, and measurement of corporate environmental performance: A critical examination of a multidimensional construct, J. Bus. Ethics, 126 (2015), 185-204. doi: 10.1007/s10551-013-1931-8.
[72]	M. Tseng, R. Wang, A. S. Chiu, Y. Geng and Y. H. Lin, Improving performance of green innovation practices under uncertainty, J. Clean Prod., 40 (2013), 71-82. doi: 10.1016/j.jclepro.2011.10.009.
[73]	C. Tumelero, R. Sbragia and S. Evans, Cooperation in r & d and eco-innovations: The role in companies' socioeconomic performance, J. Clean Prod., 207 (2019), 1138-1149. doi: 10.1016/j.jclepro.2018.09.146.
[74]	C. Wang, P. Nie, D. Peng and Z. Li, Green insurance subsidy for promoting clean production innovation, J. Clean Prod., 148 (2017), 111-117. doi: 10.1016/j.jclepro.2017.01.145.
[75]	M. Warusawitharana, Research and development, profits, and firm value: A structural estimation, Quant. Econ., 6 (2015), 531-565. doi: 10.3982/QE282.
[76]	A. F. Xavier, R. M. Naveiro, A. Aoussat and T. Reyes, Systematic literature review of eco-innovation models: Opportunities and recommendations for future research, J. Clean Prod., 149 (2017), 1278-1302. doi: 10.1016/j.jclepro.2017.02.145.
[77]	D. Yang, Z. Chen, Y. Yang and P. Nie, Green financial policies and capital flows, Physica A, 522 (2019), 135-146. doi: 10.1016/j.physa.2019.01.126.
[78]	B. Zhang, Y. Yang and J. Bi, Tracking the implementation of green credit policy in China: Top-down perspective and bottom-up reform, J. Environ. Manage., 92 (2011), 1321-1327. doi: 10.1016/j.jenvman.2010.12.019.