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5.03.889

Digital Transformation and

Corporate Environmental Green

Innovation Nexus: An Approach

towards Green Innovation

Improvement

Fenfen Ma, Shah Fahad, Shuxi Yan and Yapeng Zhang

Special Issue

Business Digital Transformation Processes toward Circular Economy and Sustainability

Edited by

Prof. Dr. Estrela Ferreira Cruz and Prof. Dr. António Miguel Rosado da Cruz

Article

https://doi.org/10.3390/su15076258

Citation: Ma, F.; Fahad, S.; Yan, S.;

Zhang, Y. Digital Transformation and

Corporate Environmental Green

Innovation Nexus: An Approach

towards Green Innovation

Improvement. Sustainability 2023,15,

6258. https://doi.org/10.3390/

su15076258

Academic Editors: Estrela Ferreira

Cruz and António Miguel Rosado da

Cruz

Received: 12 March 2023

Revised: 30 March 2023

Accepted: 3 April 2023

Published: 6 April 2023

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/).

sustainability

Article

Digital Transformation and Corporate Environmental

Green Innovation Nexus: An Approach towards Green

Innovation Improvement

Fenfen Ma 1, Shah Fahad 2,3,*, Shuxi Yan 1and Yapeng Zhang 1

1School of Management, Yulin University, Yulin 719000, China

2School of Management, Hainan University, Haikou 570228, China

3School of Economics and Management, Leshan Normal University, Leshan 614000, China

*Correspondence: shah.fahad@mail.xjtu.edu.cn

Abstract:

The impact of digital transformation on green innovation is widely discussed. However,

existing studies mainly focus on the impact of the digital transformation of enterprises and ﬁntech

company development on environmental green innovation, while ignoring the effect of the digital

transformation of commercial banks (DTCB) on corporate green innovation. Therefore, to ﬁll the re-

search gap, this paper explores the impact of DTCB on environmental green innovation in companies

based on the data of listed companies from 2010 to 2019. This study ﬁnds that DTCB has signiﬁcantly

promoted enterprises’ environmental green innovation. Mechanism analysis shows that DTCB can

promote green environmental innovation by increasing R&D expenditures and reducing agency costs.

The heterogeneity analysis indicates that DTCB can only promote the green environmental innovation

of private enterprises and enterprises with a high degree of digital transformation, but it cannot

promote the green environmental innovation of state-owned enterprises and enterprises with a low

degree of digital transformation. From the perspective of DTCB, this paper enriches the research

on the relationship between digital ﬁnance and enterprise environmental green innovation. The

government should promote the digital transformation of enterprises to utilize the green innovation

effect of DTCB.

Keywords: digital transformation; environmental green innovation; agency cost

1. Introduction

As China’s urbanization and industrialization continue to advance, green develop-

ment is being challenged. As an essential player in the market economy, enterprises are

responsible for coordinating economic growth with environmental protection [

]. Green

innovation can reduce pollution emissions in the production process [

], which is critical

to eliminating the conﬂict between China’s economic growth and environmental pollu-

tion [

]. However, the high risk of green innovation poses some challenges to itself. Green

technologies are more capital-intensive and risky than general innovations, making them

more challenging to ﬁnance [

]. Since commercial banks are the primary source of external

ﬁnancing for most companies in China, exploring how to increase the credit of commercial

banks for corporate green innovation is of great practical importance for developing a

green economy.

The attitude of commercial banks toward corporate innovation has evolved from

aversion to tolerance. Early studies concluded that commercial banks have an aversion to

innovative corporate behavior [

]. On the one hand, commercial banks have an adversarial

attitude toward risk, while corporate technology innovation is inherently high risk. On

the other hand, commercial banks require companies to have stable cash ﬂow that can

repay principal and interest over a certain period, but technological innovation activities

require continuous cash investment. However, many subsequent studies have found that

Sustainability 2023,15, 6258. https://doi.org/10.3390/su15076258 https://www.mdpi.com/journal/sustainability

Sustainability 2023,15, 6258 2 of 15

commercial banks do indeed ﬁnance corporate innovation [

]. Commercial banks are

somewhat tolerant of this innovative behavior. In a fully competitive market environ-

ment, technological innovation becomes the key for enterprises to cultivate competitive

advantages and eliminate the “homogenization trap” of products [

]. Commercial banks

recognize that sustained growth through technological innovation is the only way for com-

panies to obtain sufﬁcient cash ﬂow to repay debt and interest [

]. Commercial banks can

identify with the practical logic of ‘technological innovation for business growth’, embrace

the risk of innovation, and lend to innovative enterprises [

]. The sustainable growth of

enterprises through technological innovation has become a common goal for banks and

enterprises. This ‘target binding effect’ provides sufﬁcient evolutionary motivation for the

commercial bank attitude to change from ‘innovation aversion’ to ‘innovation inclusion’. In

the current context of advocating green development, achieving the green development of

enterprises through green innovation has become a new common goal between enterprises

and commercial banks [

]. However, although commercial banks can accommodate the

innovative activities of enterprises, to some degree, many enterprises face credit rationing

due to information asymmetry and lack of collateral [10].

The digital transformation of commercial banks (DTCB) is conducive to improving

their ability to serve the real economy and can affect green innovation. DTCB refers to

the application of digital technologies, such as big data, cloud computing, blockchain

technology, the Internet of things, and artiﬁcial intelligence by commercial banks to realize

the online, intelligent, scenario-based, and platform-based banking business [

]. Currently,

commercial banks are beginning to implement digital transformation at a rapid pace [

National commercial banks implement digital transformation by setting up ﬁntech sub-

sidiaries, while urban and rural commercial banks implement digital transformation by

cooperating with ﬁntech companies [

]. DTCB can reduce information asymmetry and

increase credit supply to enterprises [

]. So, can DTCB promote green innovation by

increasing lending to enterprises? If DTCB can effectively promote the green innovation

of companies, exploring the effect of the green innovation of DTCB is vital to improving

the environment.

Studies have been conducted to explore the impact of digital transformation on green

innovation at both the macro and micro levels, respectively. At the macro level, ref. [

] and

ref. [

] have found that the development of the digital economy promotes green innova-

tion using data from the city panel at the prefecture level in China. Ref. [

] has discovered

that digital economy development can promote green innovation by promoting economic

openness, optimizing the industrial structure, and expanding the market potential. From

the micro level, ref. [

] has found that the digital transformation of enterprises promotes

green innovation by optimizing the human capital structure and strengthening the cooper-

ation between industry and academia. Ref. [

] has found that the digital transformation

of enterprises promotes green innovation by enhancing the level of information sharing

and resource allocation efﬁciency. Some studies focus on the green innovation effects

of the digital transformation of ﬁnancial institutions. Ref. [

] and ref. [

] have found

that the development of ﬁntech companies can signiﬁcantly improve green innovation.

The digital transformation of ﬁnancial institutions includes the development of ﬁntech

companies and DTCB. In fact, ﬁntech companies serve individual entrepreneurs and micro

and small enterprises [

] and engage less in green innovation. DTCB can increase lending

to enterprises, which may promote the green innovation of enterprises. However, the

existing research has mainly studied the relationship between ﬁntech companies and green

innovation, ignoring the relationship between DTCB and green innovation.

In summary, from the micro level, studies on the effects of digital transformation on

green innovation have mainly focused on exploring the impact of the digital transformation

of enterprises and ﬁntech companies on green innovation of enterprises, and little literature

has focused on the impact of DTCB on green innovation. Therefore, this paper ﬁlls this gap

by exploring the effect of DTCB on the green innovation of enterprises.

/16

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5.03.889DigitalTransformationandCorporateEnvironmentalGreenInnovationNexus:AnApproachtowardsGreenInnovationImprovementFenfenMa,ShahFahad,ShuxiYanandYapengZhangSpecialIssueBusinessDigitalTransformationProcessestowardCircularEconomyandSustainabilityEditedbyProf.Dr.EstrelaFerreiraCruzandProf.Dr.AntónioMiguelRosadodaCruzArticlehttps://doi.org/10.3390/su15076258Citation:Ma,F.;Fahad,S.;Yan,S.;Zhang,Y.DigitalTransformationandCorporateEnvironmentalGreenInnovationNexus:AnApproachtowardsGreenInnovationImprovement.Sustainability2023,15,6258.https://doi.org/10.3390/su15076258AcademicEditors:EstrelaFerreiraCruzandAntónioMiguelRosadodaCruzReceived:12March2023Revised:30March2023Accepted:3April2023Published:6April2023Copyright:©2023bytheauthors.LicenseeMDPI,Basel,Switzerland.ThisarticleisanopenaccessarticledistributedunderthetermsandconditionsoftheCreativeCommonsAttribution(CCBY)license(https://creativecommons.org/licenses/by/4.0/).sustainabilityArticleDigitalTransformationandCorporateEnvironmentalGreenInnovationNexus:AnApproachtowardsGreenInnovationImprovementFenfenMa1,ShahFahad2,3,,ShuxiYan1andYapengZhang11SchoolofManagement,YulinUniversity,Yulin719000,China2SchoolofManagement,HainanUniversity,Haikou570228,China3SchoolofEconomicsandManagement,LeshanNormalUniversity,Leshan614000,ChinaCorrespondence:shah.fahad@mail.xjtu.edu.cnAbstract:Theimpactofdigitaltransformationongreeninnovationiswidelydiscussed.However,existingstudiesmainlyfocusontheimpactofthedigitaltransformationofenterprisesandﬁntechcompanydevelopmentonenvironmentalgreeninnovation,whileignoringtheeffectofthedigitaltransformationofcommercialbanks(DTCB)oncorporategreeninnovation.Therefore,toﬁllthere-searchgap,thispaperexplorestheimpactofDTCBonenvironmentalgreeninnovationincompaniesbasedonthedataoflistedcompaniesfrom2010to2019.ThisstudyﬁndsthatDTCBhassigniﬁcantlypromotedenterprises’environmentalgreeninnovation.MechanismanalysisshowsthatDTCBcanpromotegreenenvironmentalinnovationbyincreasingR&Dexpendituresandreducingagencycosts.TheheterogeneityanalysisindicatesthatDTCBcanonlypromotethegreenenvironmentalinnovationofprivateenterprisesandenterpriseswithahighdegreeofdigitaltransformation,butitcannotpromotethegreenenvironmentalinnovationofstate-ownedenterprisesandenterpriseswithalowdegreeofdigitaltransformation.FromtheperspectiveofDTCB,thispaperenrichestheresearchontherelationshipbetweendigitalﬁnanceandenterpriseenvironmentalgreeninnovation.ThegovernmentshouldpromotethedigitaltransformationofenterprisestoutilizethegreeninnovationeffectofDTCB.Keywords:digitaltransformation;environmentalgreeninnovation;agencycost1.IntroductionAsChina’surbanizationandindustrializationcontinuetoadvance,greendevelop-mentisbeingchallenged.Asanessentialplayerinthemarketeconomy,enterprisesareresponsibleforcoordinatingeconomicgrowthwithenvironmentalprotection[1].Greeninnovationcanreducepollutionemissionsintheproductionprocess[2],whichiscriticaltoeliminatingtheconﬂictbetweenChina’seconomicgrowthandenvironmentalpollu-tion[3].However,thehighriskofgreeninnovationposessomechallengestoitself.Greentechnologiesaremorecapital-intensiveandriskythangeneralinnovations,makingthemmorechallengingtoﬁnance[4].SincecommercialbanksaretheprimarysourceofexternalﬁnancingformostcompaniesinChina,exploringhowtoincreasethecreditofcommercialbanksforcorporategreeninnovationisofgreatpracticalimportancefordevelopingagreeneconomy.Theattitudeofcommercialbankstowardcorporateinnovationhasevolvedfromaversiontotolerance.Earlystudiesconcludedthatcommercialbankshaveanaversiontoinnovativecorporatebehavior[5].Ontheonehand,commercialbankshaveanadversarialattitudetowardrisk,whilecorporatetechnologyinnovationisinherentlyhighrisk.Ontheotherhand,commercialbanksrequirecompaniestohavestablecashﬂowthatcanrepayprincipalandinterestoveracertainperiod,buttechnologicalinnovationactivitiesrequirecontinuouscashinvestment.However,manysubsequentstudieshavefoundthatSustainability2023,15,6258.https://doi.org/10.3390/su15076258https://www.mdpi.com/journal/sustainabilitySustainability2023,15,62582of15commercialbanksdoindeedﬁnancecorporateinnovation[6].Commercialbanksaresomewhattolerantofthisinnovativebehavior.Inafullycompetitivemarketenviron-ment,technologicalinnovationbecomesthekeyforenterprisestocultivatecompetitiveadvantagesandeliminatethe“homogenizationtrap”ofproducts[7].Commercialbanksrecognizethatsustainedgrowththroughtechnologicalinnovationistheonlywayforcom-paniestoobtainsufﬁcientcashﬂowtorepaydebtandinterest[8].Commercialbankscanidentifywiththepracticallogicof‘technologicalinnovationforbusinessgrowth’,embracetheriskofinnovation,andlendtoinnovativeenterprises[6].Thesustainablegrowthofenterprisesthroughtechnologicalinnovationhasbecomeacommongoalforbanksandenterprises.This‘targetbindingeffect’providessufﬁcientevolutionarymotivationforthecommercialbankattitudetochangefrom‘innovationaversion’to‘innovationinclusion’.Inthecurrentcontextofadvocatinggreendevelopment,achievingthegreendevelopmentofenterprisesthroughgreeninnovationhasbecomeanewcommongoalbetweenenterprisesandcommercialbanks[9].However,althoughcommercialbankscanaccommodatetheinnovativeactivitiesofenterprises,tosomedegree,manyenterprisesfacecreditrationingduetoinformationasymmetryandlackofcollateral[10].Thedigitaltransformationofcommercialbanks(DTCB)isconducivetoimprovingtheirabilitytoservetherealeconomyandcanaffectgreeninnovation.DTCBreferstotheapplicationofdigitaltechnologies,suchasbigdata,cloudcomputing,blockchaintechnology,theInternetofthings,andartiﬁcialintelligencebycommercialbankstorealizetheonline,intelligent,scenario-based,andplatform-basedbankingbusiness[11].Currently,commercialbanksarebeginningtoimplementdigitaltransformationatarapidpace[12].Nationalcommercialbanksimplementdigitaltransformationbysettingupﬁntechsub-sidiaries,whileurbanandruralcommercialbanksimplementdigitaltransformationbycooperatingwithﬁntechcompanies[13].DTCBcanreduceinformationasymmetryandincreasecreditsupplytoenterprises[14].So,canDTCBpromotegreeninnovationbyincreasinglendingtoenterprises?IfDTCBcaneffectivelypromotethegreeninnovationofcompanies,exploringtheeffectofthegreeninnovationofDTCBisvitaltoimprovingtheenvironment.Studieshavebeenconductedtoexploretheimpactofdigitaltransformationongreeninnovationatboththemacroandmicrolevels,respectively.Atthemacrolevel,ref.[15]andref.[16]havefoundthatthedevelopmentofthedigitaleconomypromotesgreeninnova-tionusingdatafromthecitypanelattheprefecturelevelinChina.Ref.[17]hasdiscoveredthatdigitaleconomydevelopmentcanpromotegreeninnovationbypromotingeconomicopenness,optimizingtheindustrialstructure,andexpandingthemarketpotential.Fromthemicrolevel,ref.[18]hasfoundthatthedigitaltransformationofenterprisespromotesgreeninnovationbyoptimizingthehumancapitalstructureandstrengtheningthecooper-ationbetweenindustryandacademia.Ref.[19]hasfoundthatthedigitaltransformationofenterprisespromotesgreeninnovationbyenhancingthelevelofinformationsharingandresourceallocationefﬁciency.Somestudiesfocusonthegreeninnovationeffectsofthedigitaltransformationofﬁnancialinstitutions.Ref.[20]andref.[21]havefoundthatthedevelopmentofﬁntechcompaniescansigniﬁcantlyimprovegreeninnovation.ThedigitaltransformationofﬁnancialinstitutionsincludesthedevelopmentofﬁntechcompaniesandDTCB.Infact,ﬁntechcompaniesserveindividualentrepreneursandmicroandsmallenterprises[22]andengagelessingreeninnovation.DTCBcanincreaselendingtoenterprises,whichmaypromotethegreeninnovationofenterprises.However,theexistingresearchhasmainlystudiedtherelationshipbetweenﬁntechcompaniesandgreeninnovation,ignoringtherelationshipbetweenDTCBandgreeninnovation.Insummary,fromthemicrolevel,studiesontheeffectsofdigitaltransformationongreeninnovationhavemainlyfocusedonexploringtheimpactofthedigitaltransformationofenterprisesandﬁntechcompaniesongreeninnovationofenterprises,andlittleliteraturehasfocusedontheimpactofDTCBongreeninnovation.Therefore,thispaperﬁllsthisgapbyexploringtheeffectofDTCBonthegreeninnovationofenterprises.Sustainability2023,15,62583of15Themarginalcontributionsofthisstudyareasfollows.First,theresearchobjectofdigitalﬁnanceisextendedtothebankingsystem,enrichingtheresearchontheeffectofdigitalﬁnanceongreeninnovation.Currentresearchfocusesonexploringtheeffectofﬁntechcompaniesongreeninnovation,whiletheimpactofDTCBongreeninnovationisyettobestudied.UnderChina’sbank-basedﬁnancialsystem,ignoringtheeffectofDTCBongreeninnovationwillmakeitdifﬁculttoclarifytheeffectofdigitalﬁnanceongreeninnovation.Second,itexpandstheresearchontheeconomicconsequencesofDTCB.TheexistingliteraturehasmainlyexploredtheimpactofDTCBonthecreditscaleandcreditstructure,andtheimpactofDTCBongreeninnovationisyettobestudied.Hence,thispaperfurtherexpandstheeconomicconsequencesofDTCB.Third,theheterogeneityofDTCBaffectinggreeninnovationisexplored.WehavefoundthatDTCBcanonlypromotethegreeninnovationofenterpriseswithahighdegreeofdigitaltransformation,whichprovidesabasisforgovernmentdepartmentstofurtherpromotethedigitaltransformationofenterprisestofacilitatetheirgreendevelopment.2.LiteratureReviewandResearchHypothesis2.1.ImpactMechanismofDTCBonGreenInnovation2.1.1.AnalysisofInnovationResourcesMechanismFinancingconstraintsleadtoinsufﬁcientinvestmentofcompaniesininnovativeresources[23].Thereasonwhygreeninnovationbycorporationsoftenfacesﬁnancingconstraintsisasfollows.First,thetraditionallendingprocessiscumbersome,whichmayresultininnovativeprojectsmissingthebestresearchanddevelopmentperiodduetothelackoftimelyﬁnancing.Second,companiesareoftenreluctanttorevealspeciﬁcdetailsrelatedtotheirinnovativeprojectstoavoidrevealingtradesecrets,whichexacerbatesinformationasymmetry,andfurtherunderminesthewillingnessofcommercialbankstolendtothesecompanies[24].Third,manyinnovativeenterpriseshavefewerﬁxedassetsandlackcollateral,makingitdifﬁculttoobtainexternalﬁnancingintraditionallendingmodelsthatvaluecollateral.Next,theeffectofDTCBonﬁnancingforgreeninnovationisanalyzedfromtheperspectiveoftheabovethreeexplanations.First,DTCBhassimpliﬁedthecreditapprovalprocessandreducedthepossibilityofinnovativeprojectsmissingthebestresearchanddevelopmentperiodbecausetheycannotobtainﬁnancingintime.Thetraditionalcreditapprovalprocessrequirescreditapprovalpersonneltovisittheenterprisetoconducton-siteduediligenceresearch.Itincludesexplicitlyassessingthebusinessstatusoftheenterprise,verifyingthecollateralandguarantors,etc.Thewholeprocessislong.Commercialbankshavechangedthecredit-grantingmodel,usingbigdataandartiﬁcialintelligence.Commercialbankshaveimplementedonlinelendingoperationsbasedonﬁrm-relatedinformationsearchedinmanychannelsandintelligentriskcontrolmodels[25].Companiescanapplyforloansusingtheon-lineplatformsofcommercialbanks,avoidingthecumbersomeapprovalprocessandreducingthetimeittakestoobtainloans.Second,theDTCBimprovesthelendingtechniquesofcommercialbanksbasedonsoftinformationandincreasesthelendingtoinnovativecorporateprojects.First,DTCBen-hancesthecapabilitiesofcommercialbankstosearchforandprocesssoftinformation.Softinformationreferstoqualitativeinformation,usuallytext,suchasthequalityofcompanymanagersandthecompetitivenessofenterpriseproducts[26].Thissoftinformationformsanimportantbasisforcommercialbankstograntloans[27].Asthedigitaleconomydevel-opsrapidly,e-commerce,socialnetworks,andcreditplatformsareaccumulatingalargeamountofcorporatedata,whichcancapturethefundamentalinformationofacompanyindetail.DTCBcanefﬁcientlyconnecttosuchdataplatforms,broadeninformationsources,andthusreducethecostofsoftinformationproduction[28].Atthesametime,digitaltechnologyallowscommercialbankstohandlesoftinformationmoreeffectively[29].Com-paredtothetraditionalmanualinformationprocessingmode,commercialbankscanapplybigdata,cloudcomputing,blockchaintechnology,andmathematicalandstatisticalmodelstoprocesssoftinformationmorerapidlyandeffectively[30].AmorecomprehensiverangeSustainability2023,15,62584of15ofsoftinformationsourcesandmoreefﬁcientsoftinformationprocessingtechniqueshaveenabledcommercialbankstoimprovetheirsoftinformation-basedlendingtechniques[31].Moreover,digitaltechnologyenablescommercialbankstoachieveremotemonitoringthroughtheInternetofthingsandblockchaintechnology,thussupervisingthegrantingofloanstoenterprisesmoreeffectively[32].Itavoidsthepossiblemoralhazardofenterprisesandimprovesthewillingnessofcommercialbankstoﬁnanceinnovativeprojects.2.1.2.AnalysisofDebtGovernanceMechanismsTheprincipalagentproblemsqueezesoutgreeninnovationactivities.Theseparationofoperationandownershipoftheenterprisecausestheprincipal–agentproblem.Inthecaseofbusinessandownershipseparation,managersoftenholdaportionofthecompany’sequity.Theutilityofmanagersdoesnotdependentirelyonthevalueandproﬁtofthecompany,givingmanagersanincentivetousetheresourcestheycontroltosatisfytheirpreferences[33].Managerialpreferencesareexpressedinthreeaspects.Theﬁrstisthesizepreferenceofmanagers.Inlargecompanies,managersarepaidmoreandhavemorepower,sotheytendtopursuegrowthinsizetobuildtheir‘economicempire’[34].Thesecondisthespendingpreferenceofmanagers.Someoftheexpendituresinthecompanycandirectlyorindirectlyimprovetheutilityofthemanager[35].Thethirdisthemanager’spreferenceforaquietlife.Managershaveonlypartialownershipofthecompany,makingthemreluctanttoengageinactivitiestheyﬁnddifﬁcult,suchasgreeninnovation[36].Thesizepreferenceandspendingpreferenceofmanagersleadtoaﬂowofresourcestoﬁxedassetinvestmentandtheconsumptionofmanagersonthejob,etc.,whichdirectlysqueezeoutgreeninnovationactivities.Thepreferenceofmanagerstoenjoyaquietlifealsoconﬂictswiththehighriskofgreeninnovationactivities.Therefore,thepreferencesofthethreetypesofmanagerssqueezeoutthegreeninnovationactivitiesofthecompany.Bankdebtgovernancealleviatestheprincipalagentproblem,andthusimprovesman-agers’effortstoimplementgreeninnovationactivities.Accordingtoorganizationalcontroltheory,theimportantroleofcorporategovernanceistoconstrainmanagers’preferencesandmakerationaluseoffundingresources,suchasinvestingingreeninnovation[37].Theeconomictheoryoftheagencyindicatesthatbankdebtgovernancemechanismscanallevi-atetheprincipalagentproblem,affectingcorporatemanagers’decision-makingbehaviorandresourceallocationefﬁciency[38].First,theexistenceofliabilitiesrequirescompaniestorepayprincipalandinteresttocreditorswithinaspeciﬁedperiod.Itreducesthecapitalavailabletomanagersattheirdiscretionandconstrainsmanagers’expansionandspendingpreferences.Second,intheeventthatthedebtorisunabletorepaytheloan,thecommercialbankcanrequestthedebtortotakeoutbankruptcythroughlegalprocedures.Bankruptcycausesmanagerstolosetheirjobsanddamagestheirreputations.Therefore,thethreatofbankruptcycanforcemanagerstoworkharder[39].Third,topreventdebtorsfrominvestingborrowedcapitalinriskyprojects,commercialbanksmonitortheuseofbor-rowedcapital,constrainingmanagers’privatepreferences[40].Inconclusion,commercialbanksreducethesizeandspendingpreferencesofmanagersbyexercisingcontractualrestrictionsandsupervision,etc.,andinducemanagerstoworkhardertoimplementgreeninnovationactivities.TheDTCBstrengthenstheroleofcommercialbanksindebtgovernance,thuspro-motingcorporategreeninnovation.First,theDTCBincreaseslendingtocompanies,thusstrengtheningthegovernanceroleofcontractualconstraints.Forcompanies,largerloansimplymorepressuretorepaydebtandagreaterthreatofbankruptcy,whichmotivatesmanagerstoreducetheirexpansionandspendingpreferencesandtoworkhardertoim-plementgreeninnovationactivities.Second,theDTCBstrengthensthesupervisionoftheusageofloans.Throughdigitaltransformation,commercialbankscanobtaininformationrelatedtoenterprisesinrealtimeandcross-verifytheinformationobtained[41],makingtheinformationobtainedbycommercialbanksmoretimely,accurate,extensive,anddifﬁculttomanipulate[42].Inthiscase,commercialbankscanmonitortheuseofloansmoreeffectively,limitingtheuseofloansforexpansionandspendingpreferences.Ingeneral,Sustainability2023,15,62585of15themechanismofDTCBaffectinggreeninnovationisshowninFigure1.Therefore,thefollowinghypothesesareproposed.Hypothesis1:DTCBcanpromotegreeninnovationinenterprises.Hypothesis2:DTCBpromotesgreeninnovationbyincreasingtheinnovationresourcesofenterprises.Hypothesis3:DTCBpromotesgreeninnovationbyenhancingthegovernanceofdebtbyenterprises.,reflectingtheenterprise’stecFigure1.ThemechanismofDTCBaffectinggreeninnovation.2.2.AnalysisofHeterogeneity2.2.1.TheHeterogeneityoftheDegreeofEnterpriseDigitalTransformationWhenthedigitaltransformationofenterprisesreachesacertainlevel,DTCBcanplayaroleinreducinginformationasymmetry.Digitaltechnologyempowerscommercialbankstoimprovetheirabilitytoﬁndinformation,butthisisbasedontheaccumulationofreliabledata.Whenanenterpriseaccumulatesreliabledata,DTCBcanplayaroleinreducinginformationasymmetry.Ifanenterprisecompletesthedigitaltransformation,itsinformationrelatedtotechnologicalinnovation,productionandoperation,internalcontrol,andproductsalescanbemadeavailable.Thisinformationisopen,transparent,shared,andveriﬁable[43],reﬂectingtheenterprise’stechnologicalinnovation,production,andsales.Commercialbankscanaccessthedatamentionedabovetothecredittrackingsystemthroughdigitaltechnology,whichcanbetterutilizeDTCBinreducinginformationasymmetry.SinceinformationasymmetryisanimportantmechanismbywhichDTCBaffectsgreeninnovation,DTCBcanonlypromotegreeninnovationinenterpriseswithahighdegreeofdigitaltransformation.Therefore,thefollowingpropositionisproposed.Hypothesis4:DTCBcanonlypromotegreeninnovationinenterpriseswithahighdegreeofdigitaltransformation,whileitcannotpromotegreeninnovationinenterpriseswithalowdegreeofdigitaltransformation.2.2.2.TheHeterogeneityofEnterpriseOwnershipInthecaseof“ownershipdiscrimination”inthecreditmarket,state-ownedenter-priseshaveinvisiblegovernmentguaranteesanddonotfacecreditrationing.Incontrast,privateenterprisesfacecreditrationingandhavedifﬁcultyobtainingloansfrombanks.Thisisbecausetheyaresubjectto“ownershipdiscrimination”inthetraditionalﬁnancialmarket[44].AsDTCBpromotesgreeninnovationthroughincreasedﬁnancing.DTCBcanonlypromotegreeninnovationinprivateenterprises.Thus,thefollowingpropositionisproposed.Hypothesis5:DTCBcanonlypromotegreeninnovationinprivateenterprises,whileitcannotpromotegreeninnovationinstate-ownedenterprises.Sustainability2023,15,62586of153.DataandEmpiricalDesign3.1.DataThispaperselectsthedataoflistedcompaniesfrom2010to2019fortheempiricaltest.Thedeepintegrationofﬁnanceandtechnologyoriginatedin2010[14],sothispaperchooses2010asthestartingpoint.TheoutbreakofCOVID-19in2020hashadagreatimpactontheoperationandinvestmentactivitiesofprivateenterprises.InordertoeliminatetheinterferenceoftheimpactofCOVID-19ontheresearchresults,thispaperselects2019astheendpoint.ThedatacomefromtheCSMAR(ChinaStockMarketandAccountingResearchDatabase).Samplesfromtheﬁnancialsectorareremoved.Allcontinuousvariablesweretailedby1%beforeandaftertoremoveoutliersofcontinuousvariables.Atotalof7505year-companyobservationswereobtained.Thevariablesaredescribedasfollows.3.1.1.TheExplainedVariableGreeninnovation(GI).Greeninnovationdescribestechnologicalinnovationthatcon-tributestoimprovingenvironmentalquality.Referringtotheresearchofref.[45],thenumberofgreeninventionpatentsgrantedisadoptedtomeasurethelevelofgreeninno-vationoftheenterprises.TheWorldIntellectualPropertyOrganization(WIPO)launchedtheGreenListofInternationalPatentClassiﬁcationsin2010.Thislistisusedtodeterminewhethereachofthecompany’spatentsisagreenpatent.3.1.2.TheCoreExplanatoryVariableDTCBattheenterpriselevel(DTCBE).DTCBEismeasuredbythelevelofdigitaltransformationofcommercialbanksthatlendtocompanies.Thispaperreferstothemethodofref.[46]toconstructDTCBE,includingthefollowingfoursteps.(1)Theﬁvemostwidelyuseddigitaltechnologiesincommercialbanksareselectedaskeywords,i.e.,bigdata,artiﬁcialintelligence,cloudcomputing,blockchaintechnology,andtheInternetofthings.(2)Web-crawledtechnologyisusedtoobtainnewssearchresultsforthecombinationofcommercialbanknamesandkeywords(suchas“Chinabank”+“bigdata”)eachyearandtothencalculatethetotalnumberofnewssearchresultsforthecombinationineachyearfrom2010to2019.(3)Thelogarithmofthetotalnumberofnewssearchresultsisusedasthelevelofdigitaltransformationofthecommercialbank.(4)Theweightedaveragelevelofdigitaltransformationofacommercialbank’slendingtoanenterprise,DTCBE,iscalculated.Theweightusedistheproportionofloansobtainedbytheenterpriseineachcommercialbankinthecurrentyear.3.1.3.TheMechanismVariables(1)R&Dexpenditure(RD).R&DexpenditureismeasuredbytheR&Dexpenditureoftheenterpriseinthecurrentyear.(2)Agencycost(AC).Agencycostismeasuredbytheratiooftheadministrativeexpensestotheoperatingrevenue.3.1.4.TheControlVariablesReferringto[47]and[48],aseriesofvariablesdescribingtheimportantcharacteristicsofenterprisesoraffectingenterprisegreeninnovationaresetascontrolvariables.ThecontrolvariablesandtheirspeciﬁcdeﬁnitionsareshowninTable1.TheresultsofthedescriptivestatisticsforthemainvariablesareshowninTable2.Wecanseethatthestandarddeviationsofgreeninnovation,DTCBE,R&Dexpenditure,andagencycostare0.377,4.284,1.402,and0.083,respectively.ThedatashowthatthestandarddeviationofDTCBEisthehighest,reﬂectingthelargedifferenceinthedigitaltransfor-mationofcommercialbankslendingtoenterprises.TofurtherreﬂectthedistributionofDTCBEindifferentyears,thenucleardensitymapofDTCBEovertimeisshowninFig-ure2.TheestimatedpeaknucleardensityofDTCBEisincreasingyearbyyear,indicatinganupwardtrendofDTCBE.TheupwardshiftofthenucleardensitycurveindicatesanSustainability2023,15,62587of15increaseintheconcentrationoftheBTCBEdistribution.TheaccurateimpactofDTCBongreeninnovationwillbefurtherstudiedusingthesubsequenteconometricmodel.−−−−−GIit=C+α1DTCBEit+α2∑control_mmit+μi+ut+εitRDit=C+α3DTCBEit+α4∑control_mitm+μi+ut+εitACit=C+α5DTCBEit+α6∑control_mitm+μi+ut+εitGIitDTCBEit∑control_mitm––αμiutεitRDitACitFigure2.ThenucleardensitymapofDTCBE.Table1.Variabledescriptions.VariablesIndexDeﬁnitionExplainedvariableGIGreeninnovationLogarithmofthenumberofgreenpatents.ExplanatoryvariableDTCBEDTCBattheenterpriselevelThedigitaltransformationlevelofcommercialbanksthatlendtocompanies.MechanismvariableRDR&DexpenditureLogarithmofR&Dexpenditure.ACAgencycostTheratioofadministrativeexpensestooperatingrevenue.ControlvariableCSCompanysizeThelogarithmofthenumberofemployeesinthecompany.SOEState-ownedenterpriseSetat1ifitisastate-ownedenterprise,0otherwise.ALRAsset–liabilityratioTotalliabilitiesdividedbytotalassets.IRBRIncreasingrateofbusinessrevenueGrowthrateofcurrent-periodoperatingrevenuerelativetoprevious-periodoperatingrevenue.CLRCapital–laborratioNetﬁxedassetsdividedbythenumberofemployees,andfollowedbytheapplicationofthelogarithm.DLDualleadershipSetat1iftheCEOisalsotheboardchairman.BSBoardSizeThelogarithmofthenumberofboardmembers.PIDProportionofindependentdirectorsTheratioofindependentdirectorstoalldirectors.GSCGovernmentsubsidieschangesThechangerateofgovernmentsubsidies.ATBCActualtaxburdenchangesThechangerateoftheactualtaxburden.Sustainability2023,15,62588of15Table2.Descriptivestatisticsofvariables.VariableObs.MeanStd.Dev.Min.Max.GI75110.1070.37702.890DTCBE751111.244.2840.22316.21RD751117.751.40211.7822.09AC75110.1070.08250.006440.772CS75117.6791.1123.82911.29SOE75110.3050.46101ALR75110.4580.2000.04000.993IRBR75110.2200.593−0.6748.507CLR751112.501.1058.69416.41DL75110.2920.45501BS75112.1210.2001.6092.708PID75110.3770.05640.2730.667GSC7511−0.00050.0197−0.2060.243ATBC7511−0.00060.00695−0.04500.04993.2.EmpiricalDesignThispaperusesaﬁxed-effectsmodeltotesttheimpactofDTCBongreeninnovation.Themodelissetupasfollows.GIit=C+α1DTCBEit+α2∑mcontrol_mit+µi+ut+εit(1)RDit=C+α3DTCBEit+α4∑mcontrol_mit+µi+ut+εit(2)ACit=C+α5DTCBEit+α6∑mcontrol_mit+µi+ut+εit(3)InEquation(1),GIitisgreeninnovation.DTCBEitisthelevelofdigitaltransformationofcommercialbanksattheenterpriselevel.∑mcontrol_mitreferstoasetofcontrolvariablesincludingcompanysize(CS),state-ownedenterprise(SOE),asset–liabilityratio(ALR),increaserateofbusinessrevenue(IRBR),capital–laborratio(CLR),dualleadership(DL),boardsize(BS),proportionofindependentdirectors(PID),governmentsubsidieschanges(GSC),andactualtaxburdenchanges(ATBC).αistheparametertobeestimated,µiandutreﬂectsthetimeﬁxedeffects,andεitistheresidualterm.Additionally,duetothelargedifferencesingreeninnovationamongindustries,theﬁxedeffectsoftheindustryarecontrolledinModel(1).InbothEquations(2)and(3),RDitandACitrepresentR&Dexpenditureandagencycosts,respectively.ThesettingsofothervariablesandparametersareconsistentwithEquation(1).4.EmpiricalResultsandDiscussion4.1.BaselineResultsTable3reportstheregressionresults.Model(1)onlycontrolstheﬁxedeffectsintimeandindividual,andModel(2)addscontrolvariablesthataffectgreeninnovation.Models(3)and(4)reporttheregressionresults,withoutcontrollingindividualﬁxedeffectsforcomparison.ThecoefﬁcientofDTCBEissigniﬁcantlypositiveinbothModels(1)–(4),indicatingthatDTCBsigniﬁcantlypromotescorporategreeninnovation,whichsupportsHypothesis1.Thisisduetothefollowingreasons.First,commercialbanksincreaseloanstocompaniesthroughdigitaltransformation,allowingcompaniestoinvestingreeninnovationactivities.Second,theuseofdigitaltechnologybycommercialbankscanimprovetheirabilitytosuperviseenterprises.Understrongerexternalsupervision,managersreduceself-interestedbehaviors,suchason-the-jobconsumption,andattachmoreimportancetogreeninnovationactivities.Inaddition,theobtainedloansignalsoperateingoodcondition,helpingenterprisestoobtainﬁnancingfromotherchannels,thuspromotinggreeninnovation.Sustainability2023,15,62589of15Table3.Baselineregressionresults.FEREVariablesModel(1)Model(2)Model(3)Model(4)GIGIGIGICoefﬁcientStd.ErrCoefﬁcientStd.ErrDTCBE0.004(3.59)0.003(2.59)0.004(4.12)0.004(3.51)CS0.031(3.06)0.029(5.13)SOE−0.014(−0.40)0.012(0.80)ALR0.069(1.84)0.086(3.11)IRBR−0.011(−1.89)−0.014(−2.58)CLR0.020(2.65)0.011(1.99)DL−0.032(−2.51)−0.016(−1.59)BS−0.060(−1.41)0.018(0.59)PID−0.033(−0.27)0.050(0.52)GSC−0.201(−1.21)−0.262(−1.65)ATBC0.479(0.98)0.316(0.67)Constant0.027(0.16)−0.314(−1.24)−0.023(−0.29)−0.470(−3.28)YearFEYESYESYESYESEnterpriseFEYESYESNoNoIndustryFEYESYESYESYESN7511751175117511Adj.R-sq0.02440.02980.01540.0189Thevaluesinparenthesesaret-statistics.p<0.1,p<0.05,p<0.01.4.2.TheRobustnessTest4.2.1.ReplaceCoreExplanatoryVariables(1)ReplacethewayDTCBEisconstructed.ThispaperusesthismethodtoreplacethewayDTCBEisconstructedfortherobustnesstest.Referringto[46],thenewssearchresultsforthevariouskeywordsregardingcommercialbanksfrom2010to2019areobtainedbasedonWebcrawlertechnology.First,thelog-valueofthekeywordnewssearchresultsiscalculated.Second,basedonthenewssearchresultsforeachkeywordeachyear,thefactoranalysismethodisusedtocalculatethelevelofdigitaltransformationofcommercialbanks.Finally,etheweightedaveragedigitaltransformationlevelofcommercialbanklendingtoanenterprise,DTCBE,iscalculated.(2)Usethedigitalizationofregionalcommercialbanksasaproxyvariable.Thispa-perusesthedigitalizationofregionalcommercialbanksasaproxyvariablefortherobustnesstest.Thisstudyfollowsthemethodsofstudiesinref.[49]tomeasurethedigitalizationofregionalcommercialbanks.ThedegreeofthedigitalizationofregionalcommercialbanksisconstructedbasedonthedegreeofDTCBatthecommer-cialbanklevelandthegeographicdistributiondataofthecommercialbankbranches.Table4reportstheregressionresults,andtheDTCBEcoefﬁcientinModels(1)and(2)issigniﬁcantlypositive,indicatingthattheconclusionthatDTCBsigniﬁcantlypromotesgreeninnovationisrobust.Sustainability2023,15,625810of15Table4.Robusttestwiththealternativecoreexplanatoryvariablesandthealternativesample.VariablesModel(1)Model(2)Model(3)GI(ReplacetheWayDTCBEIsConstructed)GI(UsetheDigitalizationofRegionalCommercialBanks)GI(DeletetheSampleofMDUCG)CoefﬁcientStd.ErrCoefﬁcientStd.ErrCoefﬁcientStd.ErrDTCBE0.022(3.23)0.035(1.85)0.004(2.74)Constant−0.285(−1.12)−0.321(−0.66)−0.357(−1.07)ControlledvariableYESYESYESEnterpriseFEYESYESYESYearFEYESYESYESIndustryFEYESYESYESN751175116232Adj.R-sq0.03040.03860.0345Thevaluesinparenthesesaret-statistics.p<0.1andp<0.01.4.2.2.ExcludeMunicipalitiesDirectlyundertheCentralGovernmentReferringto[50],themunicipalitiesdirectlyunderthecentralgovernment(MDUCG)wereremovedtocarryouttherobustnesstest.ThisisduetothehighdegreeofDTCBinMDUCG,whichmayleadtothemoresigniﬁcantimpactofDTCBongreeninnovationinMDUCG.TheregressionresultsareshowninModel(3)inTable4.ItcanbeseenthatthecoefﬁcientofDTCBEisstillsigniﬁcantlypositiveafterexcludingthesamplesofMDUCG.Thisindicatesthatthecoreconclusionsofthispaperarerobust.4.2.3.TreatmentofEndogeneityTheaboveregressionresultsshowthatDTCBcanpromotegreeninnovation.However,theaboveregressionresultsmaybechallengedbyendogeneityproblems.Consideringthatenterprises’greeninnovationinthecurrentperiodisoftenaffectedbythegreeninnovationinthelagperiod,theremaybeaserialcorrelationinthetimedimension.Therefore,thispaperintroducestheﬁrst-orderlaggedvalueofgreeninnovationinthebenchmarkregres-sionmodeltomitigateendogeneityproblems,andtheresultsareshownincolumn(1)inTable5.Thecoefﬁcientoftheﬁrst-orderlaggedvalueofgreeninnovationissigniﬁcantlypositive,indicatingthatthegreeninnovationofenterprisesinthecurrentperiodissigniﬁ-cantlyaffectedbythegreeninnovationinthepreviousperiod.ThecoefﬁcientofDTCBEissigniﬁcantlypositive,indicatingthatDTCBstillsigniﬁcantlypromotesgreeninnovationafterconsideringtheserialcorrelationinthetimedimensionofgreeninnovation.Table5.TreatmentofendogeneitywiththeﬁrstorderlaggedvalueofDTCBEandGI.VariablesModel(1)Model(2)GI(UsetheFirstOrderLaggedValueofGI)GI(UsetheFirstOrderLaggedValueofDTCBE)CoefﬁcientStd.ErrCoefﬁcientStd.ErrL.GI0.050(3.57)L.DTCBE0.002(1.92)DTCBE0.002(1.99)Constant−0.146(−0.46)−0.317(−1.24)ControlledvariableYESYESEnterpriseFEYESYESYearFEYESYESIndustryFEYESYESN64986498Adj.R-sq0.02780.0265Thevaluesinparenthesesaret-statistics.p<0.1,p<0.05,p<0.01.Sustainability2023,15,625811of15TheimpactofDTCBongreeninnovationisusuallyalong-termcumulativeprocess,whichmayhaveacertainlag.Therefore,referringtothemethodof[51],weuseaﬁrst-orderlaggedvalueofDTCBEasaproxyforDTCBEtomitigatetheunderlyingestimationerror.Theestimationresultsaredisplayedincolumn(2)inTable5.Theresultsindicatethatthecoefﬁcientoftheﬁrst-orderlaggedvalueofDTCBEissigniﬁcantlypositive,whichonceagainconﬁrmsourconclusions.4.3.MechanismAnalysisTheoreticalanalysisshowsthatDTCBcanpromotegreeninnovationbyincreasingtheexpendituresofenterprisesonR&Dandstrengtheningthegovernanceofdebtsforenterprises.Therefore,thispapernextexaminestheimpactofDTCBonR&Dexpendituresandagencycosts,andtheregressionresultsareshowninTable6.ThecoefﬁcientofDTCBEissigniﬁcantlypositiveinModel(1),indicatingthatDTCBcansigniﬁcantlyincreasetheR&Dexpenditure.ThecoefﬁcientofDTCBEissigniﬁcantlynegativeinModel(2),indicatingthatDTCBcanstrengthenthegovernanceofdebtoftheenterprises,thusreducingagencycosts.Therefore,Hypothesis2andHypothesis3aresupported.Table6.Mechanismtestresults.VariablesModel(1)Model(2)RDACCoefﬁcientStd.ErrCoefﬁcientStd.ErrDTCBE0.018(5.81)−0.001(−2.33)CS0.681(29.78)−0.003(−2.04)SOE−0.063(−0.93)0.003(0.65)ALR−0.178(−2.28)0.020(3.48)IRBR0.042(2.83)−0.016(−16.76)CLR0.197(11.63)0.003(2.74)DL0.028(1.04)−0.002(−1.01)BS0.219(2.46)−0.011(−1.64)PID0.224(0.86)−0.009(−0.50)GSC0.399(1.15)0.124(4.75)ATBC0.045(0.04)−0.408(−5.47)Constant9.982(15.76)0.027(0.68)EnterpriseFEYESYESYearFEYESYESIndustryFEYESYESN75117511Adj.R-sq0.43170.1212Thevaluesinparenthesesaret-statistics.p<0.05andp<0.01.4.4.HeterogeneityAnalysis4.4.1.HeterogeneityofOwnershipThetheoreticalanalysisshowsthattheinﬂuenceofDTCBoncorporategreeninno-vationisonlysigniﬁcantinprivateenterprises.Therefore,thispaperexploreswhetherthereisownershipheterogeneityintheimpactofDTCBongreeninnovation.Enterprisesaredividedintostate-ownedandprivateenterprises,andtheregressionisconductedbygroup.TheregressionresultsarereportedinTable7.TheresultsshowthatDTCBcansigniﬁcantlypromotegreeninnovationinprivateenterprises,butitisunabletopromotegreeninnovationinstate-ownedenterprises.ThisveriﬁesHypothesis4.Sustainability2023,15,625812of15Table7.Resultsbasedontheheterogeneityofthedegreeofenterprisedigitaltransformation.VariablesModel(1)Model(2)GI(EnterpriseswithaLowDegreeofDigitalTransformation)GI(EnterpriseswithaHighDegreeofDigitalTransformation)CoefﬁcientStd.ErrCoefﬁcientStd.ErrDTCBE0.003(1.61)0.005(2.04)Constant−0.204(−0.63)−0.103(−0.29)ControlledvariableYESYESEnterpriseFEYESYESYearFEYESYESIndustryFEYESYESN38943617Adj.R-sq0.03650.0376Thevaluesinparenthesesaret-statistics.p<0.05.4.4.2.HeterogeneityoftheDegreeofDigitalTransformationofEnterprisesTheoreticalanalysisshowsthatonlywhenenterpriseshaverealizedacertaindegreeofdigitaltransformationcanDTCBpromotegreeninnovation.Therefore,thispaperexamineswhethertheeffectofDTCBongreeninnovationisheterogeneousbetweenenterpriseswithdifferentdegreesofdigitaltransformation.Thispaperusesthemethodof[52–55]tocon-structtheindicatorsreﬂectingthedegreeofenterprisedigitaltransformation.Thespeciﬁcstepsareasfollows.Firstly,withthehelpofthesemanticexpressionofnationalpoliciesrelatedtothedigitaleconomy,197wordsrelatedtoenterprisedigitaltransformation,withafrequencyofmorethanorequalto5times,areselectedtoformadigitaldictionary.Then,themachinelearning-basedtextanalysismethodisusedtoanalyzethetextofthe‘managementdiscussionandanalysis’partoftheannualreportoflistedcompanies,andthefrequencyof197wordsrelatedtothedigitaltransformationoftheenterpriseisobtainedfromtheannualreport.Finally,acomprehensiveindicatorisconstructedreﬂectingthedegreeofenterprisedigitaltransformationbasedontheabovefrequencydata.Accordingtothemedianofthedegreeofenterprisedigitaltransformation,wedividethesamplesintothegroupwithahighdigitaltransformationdegreeandthegroupwithalowdigitaltransformationdegree.Thentheregressionisconductedbygroups.TheregressionresultsareshowninTable8.TheresultsshowthatDTCBcanonlypromotegreeninnovationinenterpriseswithahighdegreeofdigitaltransformation,butitisunabletopromotegreeninnovationinenterpriseswithalowdegreeofdigitaltransformation.ThisveriﬁesHypothesis5.Table8.Resultsbasedontheheterogeneityofﬁrmownership.VariablesModel(1)Model(2)GI(State-OwnedEnterprise)GI(PrivateEnterprise)CoefﬁcientStd.ErrCoefﬁcientStd.ErrDTCBE0.001(0.10)0.005(3.06)Constant−0.363(−0.88)−0.405(−1.61)ControlledvariableYESYESEnterpriseFEYESYESYearFEYESYESIndustryFEYESYESN23305181Adj.R-sq0.03440.0345Thevaluesinparenthesesaret-statistics.p<0.01.5.ConclusionsThedevelopmentofdigitalﬁnancehaschangedthewayﬁnancialservicesareprovidedandimprovedtheabilityoftheﬁnancialsystemtoservetherealeconomy.ManyscholarsSustainability2023,15,625813of15havefocusedontheimpactofdigitalﬁnanceongreeninnovationandhavedrawnsomeusefulconclusions.However,existingstudiesonlydiscusstheimpactofthedevelopmentofﬁntechcompaniesongreeninnovation,ignoringtheimpactofthedigitaltransformationofcommercialbanks(DTCB)ongreeninnovation.Therefore,thispaperﬁllsthisgapandexplorestheimpactofDTCBoncorporategreeninnovation.Basedonthedataoflistedcompaniesfrom2010to2019,thisstudyexplorestheimpactofDTCBonenterprisegreeninnovation.WeﬁndthatDTCBhassigniﬁcantlypromotedenterprisegreeninnovation.MechanismanalysisshowsthatDTCBcanpromotegreeninnovationbyincreasingR&Dexpendituresandreducingagencycosts.TheheterogeneityanalysisindicatesthatDTCBcanonlypromotegreeninnovationinprivateenterprisesandenterpriseswithahighdegreeofdigitaltransformation,butitcannotpromotegreeninnovationinstate-ownedenterprisesandenterpriseswithalowdegreeofdigitaltransformation.Thefollowingrecommendationscanbederivedfromourstudy,basedontheaboveconclusions.First,thegovernmentshouldfocusonsolvingtheproblemoftheinadequatesharingofenterprise-relatedinformation.ThemechanismanalysisshowsthattheDTCBincreasesloanstoenterprisesbyreducinginformationasymmetry,thuspromotinggreeninnovation.Atpresent,enterprise-relatedinformationisscattered,sothegovernmentshouldbroadentheinformationsourcesofcommercialbanksbybuildingenterprise-relatedinformationsharingplatformsandallowingDTCBtoplayafullroleinpromotinggreeninnovation.Theinformationsharingplatformcancollectandsharetheinformationwithinthepurviewoflocalgovernments,suchasenterprisetaxpaymentinformation,realestateinformation,compulsoryadministrativeinformation,andwaterandelectricfeepaymentinformation.Second,thegovernmentshouldguideandsupportthedigitaltransformationofenterprises.TheheterogeneityanalysisshowsthatonlywhenthedigitaltransformationofenterprisesreachesacertainlevelcanDTCBsigniﬁcantlypromotegreeninnovation.Therefore,thegovernmentshouldguideandsupportenterprisestoimplementdigitaltransformation.Thegovernmentcangivefullplaytotheguidingroleofcentralﬁnancialfundsandencouragelocalgovernmentstoprovidepreferentialsupporttothedigitaltransformationoftheseenterprises.Inaddition,thegovernmentcanbuildsomeplatformstoprovideenterpriseswithdigitalservices,suchastransformationconsultingandsoftwareapplications.ThispaperclariﬁestheimpactofDTCBonenvironmentalgreeninnovation.However,duetothedifﬁcultyinobtainingthedigitaltransformationlevelofcommercialbanksthatprovideloanstounlistedcompanies,thispaperdoesnotexploretheimpactofDTCBonunlistedcompanies.Inthefuture,ifweobtainthedigitaltransformationindexofcommer-cialbanksthatprovideloanstounlistedcompanies,wewillfurthertesttodeterminetheimpactofDTCBongreenenvironmentalinnovationinunlistedcompaniestodeepenandexpandourﬁndings.AuthorContributions:Conceptualization,F.M.andS.F.;methodology,F.M.;software,F.M.;validation,F.M.andS.F.;formalanalysis,S.F.;investigation,S.F.;resources,S.Y.;datacuration,S.F.;writing—originaldraftpreparation,F.M.;writing—reviewandediting,F.M.andS.F.;visual-ization,F.M.;supervision,F.M.;projectadministration,Y.Z.;fundingacquisition,F.M.andS.F.Allauthorshavereadandagreedtothepublishedversionofthemanuscript.Funding:ThisresearchwasfundedbytheShaanxiSocialScienceFederation,grantnumber2022HZ1843,andtheDepartmentofEducationofShaanxiProvince,grantnumber2022HZ1314.InstitutionalReviewBoardStatement:Notapplicable.InformedConsentStatement:Notapplicable.DataAvailabilityStatement:Notapplicable.ConﬂictsofInterest:Theauthorsdeclarenoconﬂictofinterest.Thefundershadnoroleinthedesignofthestudy;inthecollection,analyses,orinterpretationofdata;inthewritingofthemanuscript,orinthedecisiontopublishtheresults.Sustainability2023,15,625814of15References1.Ba,S.;Li,N.;Zhang,J.DigitalFinanceandCorporateGreenInnovation:ExclusionorIntegration?Res.Financ.Econ.Issues2022,57–68.2.Wang,C.H.Anenvironmentalperspectiveextendsmarketorientation:Greeninnovationsustainability.Bus.StrategyEnviron.2020,29,3123–3134.[CrossRef]3.Sahoo,S.;Kumar,A.;Upadhyay,A.Howdogreenknowledgemanagementandgreentechnologyinnovationimpactcorporateenvironmentalperformance?Understandingtheroleofgreenknowledgeacquisition.Bus.StrategyEnviron.2023,32,551–569.[CrossRef]4.Yu,C.-H.;Wu,X.;Zhang,D.;Chen,S.;Zhao,J.Demandforgreenﬁnance:ResolvingﬁnancingconstraintsongreeninnovationinChina.EnergyPolicy2021,153,112255.[CrossRef]5.Opler,T.C.;Titman,S.FinancialDistressandCorporatePerformance.J.Financ.1994,49,1015–1040.[CrossRef]6.Wang,X.Frominnovationaversiontoinnovationtolerance:Astudyofinﬂuenceofbankdebtgovernancetowardstechnologicalinnovation.Sci.Res.Manag.2015,36,184–192.7.Yu,C.;Zhang,Z.;Lin,C.;Wu,Y.J.KnowledgeCreationProcessandSustainableCompetitiveAdvantage:TheRoleofTechnologicalInnovationCapabilities.Sustainability2017,9,2280.[CrossRef]8.David,P.;O’Brien,J.P.;Yoshikawa,T.TheImplicationsofDebtHeterogeneityforR&DInvestmentandFirmPerformance.Acad.Manag.J.2008,51,165–181.9.Yu,D.;Tao,S.;Hanan,A.;Ong,T.S.;Latif,B.;Ali,M.FosteringGreenInnovationAdoptionthroughGreenDynamicCapability:TheModeratingRoleofEnvironmentalDynamismandBigDataAnalyticCapability.Int.J.Environ.Res.PublicHealth2022,19,10336.[CrossRef]10.Stiglitz,J.;Weiss,A.CreditRationinginMarketswithImperfectInformation.Am.Econ.Rev.1981,71,393–410.11.Wang,S.;Xie,X.EconomicPressureorSocialPressure:TheDevelopmentofDigitalFinanceandtheDigitalInnovationofCommercialBanks.Economist2021,1,100–108.12.Omarini,A.TheDigitalTransformationinBankingandTheRoleofFinTechsintheNewFinancialIntermediationScenario.Int.J.Financ.Econ.Trade(IJFET)2017,1,1–6.13.Wang,X.;Huang,Y.;Xun,Q.;Qiu,H.HowDigitalTechnologiesChangeFinancialInstitutions:China’sPracticeandInternationalImplications.Int.Econ.Rev.2022,70–85+6.14.Hu,B.;Ren,X.TheDevelopmentofFinTech:Characteristics,ChallengesandRegulatoryStrategies.Reform2021,82–90.15.Wang,X.;Sun,X.;Zhang,H.;Xue,C.DigitalEconomyDevelopmentandUrbanGreenInnovationCA-Pability:BasedonPanelDataof274Prefecture-Le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