Does Artificial Intelligence (AI) enhance green economy efficiency? The role of green finance, trade openness, and R&D investment

Does Artificial Intelligence (AI) enhance green economy efficiency? The role of green finance, trade openness, and R&D investment


  • Abangan AS, Kopp D, Faillettaz R (2023) Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity. Front Mar Sci 10. https://doi.org/10.3389/fmars.2023.1010761

  • Aghion P, Howitt P, Brant-Collett M et al. (1998) Endogenous growth theory. MIT Press, Cambridge, MA

    MATH 

    Google Scholar
     

  • Ahmed D, Hua HX, Bhutta US (2024) Innovation through Green Finance: a thematic review. Curr Opin Environ Sustain 66:101402. https://doi.org/10.1016/j.cosust.2023.101402

    Article 

    Google Scholar
     

  • Ahmed Z, Le HP (2021) Linking Information Communication Technology, trade globalization index, and CO2 emissions: evidence from advanced panel techniques. Environ Sci Pollut Res 28(7):8770–8781. https://doi.org/10.1007/s11356-020-11205-0

    Article 
    MATH 

    Google Scholar
     

  • Aldieri L, Makkonen T, Vinci CP (2022) Do research and development and environmental knowledge spillovers facilitate meeting sustainable development goals for resource efficiency? Resour Policy 76:102603. https://doi.org/10.1016/j.resourpol.2022.102603

    Article 

    Google Scholar
     

  • Alsaleh M, Yang Z (2023) The evolution of information and communications technology in the fishery industry: the pathway for marine sustainability. Mar Pollut Bull 193:115231. https://doi.org/10.1016/j.marpolbul.2023.115231

    Article 
    CAS 
    PubMed 
    MATH 

    Google Scholar
     

  • Arif Khan M, Qin X, Jebran K et al. (2020) Uncertainty and R&D investment: does product market competition matter? Res Int Bus Financ 52:101167. https://doi.org/10.1016/j.ribaf.2019.101167

    Article 
    MATH 

    Google Scholar
     

  • Aura CM, Nyamweya CS, Njiru JM et al. (2019) Using fish landing sites and markets information towards quantification of the blue economy to enhance fisheries management. Fish Manag Ecol 26(2):141–152. https://doi.org/10.1111/fme.12334

    Article 

    Google Scholar
     

  • Babina T, Fedyk A, He A et al. (2024) Artificial intelligence, firm growth, and product innovation. J Financ Econ 151:103745. https://doi.org/10.1016/j.jfineco.2023.103745

    Article 
    MATH 

    Google Scholar
     

  • Bakker K, Ritts M (2018) Smart Earth: a meta-review and implications for environmental governance. Global Environ Chang 52:201–211. https://doi.org/10.1016/j.gloenvcha.2018.07.011

    Article 
    ADS 
    MATH 

    Google Scholar
     

  • Bastardie F, Hornborg S, Ziegler F et al. (2022) Reducing the fuel use intensity of fisheries: through efficient fishing techniques and recovered fish stocks. Front Mar Sci 9. https://doi.org/10.3389/fmars.2022.817335

  • Bhattacharya P, Dash AK (2021) Determinants of blue economy in Asia-Pacific island countries: a study of tourism and fisheries sectors. Ocean Coast Manage 211:105774. https://doi.org/10.1016/j.ocecoaman.2021.105774

    Article 

    Google Scholar
     

  • Boeing P, Eberle J, Howell A (2022) The impact of China’s R&D subsidies on R&D investment, technological upgrading and economic growth. Technol Forecast Soc 174:121212. https://doi.org/10.1016/j.techfore.2021.121212

    Article 
    MATH 

    Google Scholar
     

  • Can M, Ahmed Z, Mercan M et al. (2021) The role of trading environment-friendly goods in environmental sustainability: does green openness matter for OECD countries? J Environ Manage 295:113038. https://doi.org/10.1016/j.jenvman.2021.113038

    Article 
    PubMed 

    Google Scholar
     

  • Cao S, Nie L, Sun H et al. (2021) Digital finance, green technological innovation and energy-environmental performance: evidence from China’s regional economies. J Clean Prod 327:129458. https://doi.org/10.1016/j.jclepro.2021.129458

    Article 
    MATH 

    Google Scholar
     

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444. https://doi.org/10.1016/0377-2217(78)90138-8

    Article 
    MathSciNet 
    MATH 

    Google Scholar
     

  • Chen C, Frey CB, Presidente G (2022a) Automation or globalization? The impacts of robots and Chinese imports on jobs in the United Kingdom. J Econ Behav Organ 204:528–542. https://doi.org/10.1016/j.jebo.2022.10.027

    Article 

    Google Scholar
     

  • Chen G, Huang B, Yang J et al. (2023a) Deep blue artificial intelligence for knowledge discovery of the intermediate ocean. Front Mar Sci 9. https://doi.org/10.3389/fmars.2022.1034188

  • Chen S, Yang Q (2024) Renewable energy technology innovation and urban green economy efficiency. J Environ Manag 353:120130. https://doi.org/10.1016/j.jenvman.2024.120130

    Article 
    CAS 

    Google Scholar
     

  • Chen S, Zhang H, Wang S (2022b) Trade openness, economic growth, and energy intensity in China. Technol Forecast Soc 179:121608. https://doi.org/10.1016/j.techfore.2022.121608

    Article 
    MATH 

    Google Scholar
     

  • Chen X, Yu Z, Di Q et al. (2023b) Assessing the marine ecological welfare performance of coastal regions in China and analysing its determining factors. Ecol Indic 147:109942. https://doi.org/10.1016/j.ecolind.2023.109942

    Article 

    Google Scholar
     

  • Cochrane KL (2021) Reconciling sustainability, economic efficiency and equity in marine fisheries: has there been progress in the last 20 years? Fish Fish 22(2):298–323. https://doi.org/10.1111/faf.12521

    Article 
    MATH 

    Google Scholar
     

  • Danish, Khan S, Haneklaus N (2023) Sustainable economic development across globe: the dynamics between technology, digital trade and economic performance. Technol Soc 72:102207. https://doi.org/10.1016/j.techsoc.2023.102207

    Article 
    MATH 

    Google Scholar
     

  • Dash MK, Singh C, Panda G et al. (2023) ICT for sustainability and socio-economic development in fishery: a bibliometric analysis and future research agenda. Environ Dev Sustain 25(3):2201–2233. https://doi.org/10.1007/s10668-022-02131-x

    Article 
    MATH 

    Google Scholar
     

  • Debrah C, Chan APC, Darko A (2022) Green finance gap in green buildings: a scoping review and future research needs. Build Environ 207:108443. https://doi.org/10.1016/j.buildenv.2021.108443

    Article 

    Google Scholar
     

  • Ding H, Liu C (2024) Carbon emission efficiency of China’s logistics industry: measurement, evolution mechanism, and promotion countermeasures. Energy Econ 129:107221. https://doi.org/10.1016/j.eneco.2023.107221

    Article 
    MATH 

    Google Scholar
     

  • Ding L, Yang Y, Wang L et al. (2020) Cross efficiency assessment of China’s marine economy under environmental governance. Ocean Coast Manag 193:105245. https://doi.org/10.1016/j.ocecoaman.2020.105245

    Article 
    MATH 

    Google Scholar
     

  • Dou Y, Zhao J, Malik MN et al. (2021) Assessing the impact of trade openness on CO2 emissions: evidence from China–Japan–ROK FTA countries. J Environ Manag 296:113241. https://doi.org/10.1016/j.jenvman.2021.113241

    Article 

    Google Scholar
     

  • Evans O, Mesagan EP (2022) ICT-trade and pollution in Africa: do governance and regulation matter? J Policy Model 44(3):511–531. https://doi.org/10.1016/j.jpolmod.2022.06.003

    Article 
    MATH 

    Google Scholar
     

  • Feijóo C, Kwon Y, Bauer JM et al. (2020) Harnessing artificial intelligence (AI) to increase wellbeing for all: the case for a new technology diplomacy. Telecommun Policy 44(6):101988. https://doi.org/10.1016/j.telpol.2020.101988

    Article 

    Google Scholar
     

  • Füller J, Hutter K, Wahl J et al. (2022) How AI revolutionizes innovation management—perceptions and implementation preferences of AI-based innovators. Technol Forecast Soc 178:121598. https://doi.org/10.1016/j.techfore.2022.121598

    Article 

    Google Scholar
     

  • Gao Y, Fu Z, Yang J et al. (2022) Spatial–temporal differentiation and influencing factors of marine fishery carbon emission efficiency in China. Environ Dev Sustain. https://doi.org/10.1007/s10668-022-02716-6

  • Gao Z, Zhao Y, Li L et al. (2024) Economic effects of sustainable energy technology progress under carbon reduction targets: an analysis based on a dynamic multi-regional CGE model. Appl Energy 363:123071. https://doi.org/10.1016/j.apenergy.2024.123071

    Article 

    Google Scholar
     

  • Ge L, Zhao H, Yang J et al. (2022) Green finance, technological progress, and ecological performance—evidence from 30 Provinces in China. Environ Sci Pollut Res 29(44):66295–66314. https://doi.org/10.1007/s11356-022-20501-w

    Article 

    Google Scholar
     

  • Goodell JW, Kumar S, Lim WM et al. (2021) Artificial intelligence and machine learning in finance: identifying foundations, themes, and research clusters from bibliometric analysis. J Behav Exp Financ 32:100577. https://doi.org/10.1016/j.jbef.2021.100577

    Article 

    Google Scholar
     

  • Guo J, Yuan X, Song W (2022) Driving forces on the development of China’s marine economy: efficiency and spatial perspective. Ocean Coast Manag 224:106192. https://doi.org/10.1016/j.ocecoaman.2022.106192

    Article 
    MATH 

    Google Scholar
     

  • Güven İ, Şimşir F (2020) Demand forecasting with color parameter in retail apparel industry using artificial neural networks (ANN) and support vector machines (SVM) methods. Comput Ind Eng 147:106678. https://doi.org/10.1016/j.cie.2020.106678

    Article 

    Google Scholar
     

  • Hafner S, Jones A, Anger-Kraavi A et al. (2020) Closing the green finance gap—a systems perspective. Environ Innov Soc Transit 34:26–60. https://doi.org/10.1016/j.eist.2019.11.007

    Article 
    MATH 

    Google Scholar
     

  • Hansen MT (1999) The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits. Admin Sci Q 44(1):82–111. https://doi.org/10.2307/2667032

    Article 
    MATH 

    Google Scholar
     

  • Hdom HAD, Fuinhas JA (2020) Energy production and trade openness: assessing economic growth, CO2 emissions and the applicability of the cointegration analysis. Energy Strategy Rev 30:100488. https://doi.org/10.1016/j.esr.2020.100488

    Article 

    Google Scholar
     

  • Horowitz MC, Allen GC, Saravalle E et al. (2022) Artificial intelligence and international security. Center for a New American Security

  • Hua M, Li Z, Zhang Y et al. (2024) Does green finance promote green transformation of the real economy? Res Int Bus Financ 67:102090. https://doi.org/10.1016/j.ribaf.2023.102090

    Article 
    MATH 

    Google Scholar
     

  • Huh J-H (2017) PLC-based design of monitoring system for ICT-integrated vertical fish farm. Hum-Centric Comput Inf Sci 7(1):20. https://doi.org/10.1186/s13673-017-0101-x

    Article 
    MathSciNet 
    MATH 

    Google Scholar
     

  • Hülsmann M, Grapp J, Li Y (2008) Strategic adaptivity in global supply chains—competitive advantage by autonomous cooperation. Int J Prod Econ 114(1):14–26. https://doi.org/10.1016/j.ijpe.2007.09.009

    Article 

    Google Scholar
     

  • Hussain S, Gul R, Ullah S (2023) Role of financial inclusion and ICT for sustainable economic development in developing countries. Technol Forecast Soc 194:122725. https://doi.org/10.1016/j.techfore.2023.122725

    Article 
    MATH 

    Google Scholar
     

  • Ji J, Li Y (2021) The development of China’s fishery informatization and its impact on fishery economic efficiency. Mar Policy 133:104711. https://doi.org/10.1016/j.marpol.2021.104711

    Article 
    MATH 

    Google Scholar
     

  • Jia J, He X, Zhu T et al. (2023) Does green finance reform promote corporate green innovation? Evidence from China. Pac-Basin Finance J 82:102165. https://doi.org/10.1016/j.pacfin.2023.102165

    Article 

    Google Scholar
     

  • Johnson PC, Laurell C, Ots M et al. (2022) Digital innovation and the effects of artificial intelligence on firms’ research and development—automation or augmentation, exploration or exploitation? Technol Forecast Soc 179:121636. https://doi.org/10.1016/j.techfore.2022.121636

    Article 

    Google Scholar
     

  • Kantorowicz J, Collewet M, DiGiuseppe M et al. (2024) How to finance green investments? The role of public debt. Energy Policy 184:113899. https://doi.org/10.1016/j.enpol.2023.113899

    Article 

    Google Scholar
     

  • Keding C, Meissner P (2021) Managerial overreliance on AI-augmented decision-making processes: how the use of AI-based advisory systems shapes choice behavior in R&D investment decisions. Technol Forecast Soc 171:120970. https://doi.org/10.1016/j.techfore.2021.120970

    Article 

    Google Scholar
     

  • Kolluri S, Lin J, Liu R et al. (2022) Machine learning and artificial intelligence in pharmaceutical research and development: a review. AAPS J 24(1):19. https://doi.org/10.1208/s12248-021-00644-3

    Article 
    PubMed 
    MATH 

    Google Scholar
     

  • Kwan CH (2020) The China–US Trade War: deep-rooted causes, shifting focus and uncertain prospects. Asian Econ Policy R 15(1):55–72. https://doi.org/10.1111/aepr.12284

    Article 
    MATH 

    Google Scholar
     

  • Laddha Y, Tiwari A, Kasperowicz R et al. (2022) Impact of Information Communication Technology on labor productivity: a panel and cross-sectional analysis. Technol Soc 68:101878. https://doi.org/10.1016/j.techsoc.2022.101878

    Article 
    MATH 

    Google Scholar
     

  • Lee C-C, Wang C-s, He Z et al. (2023) How does green finance affect energy efficiency? The role of green technology innovation and energy structure. Renew Energ 219:119417. https://doi.org/10.1016/j.renene.2023.119417

    Article 

    Google Scholar
     

  • Lee H-S (2022) Integrating SBM model and Super-SBM model: a one-model approach. Omega 113:102693. https://doi.org/10.1016/j.omega.2022.102693

    Article 

    Google Scholar
     

  • Lei X, Chen X, Zhang B (2024) Unleashing the spillover potential: exploring the role of technology-seeking investment in driving green innovation of host countries. Technol Forecast Soc 200:123200. https://doi.org/10.1016/j.techfore.2023.123200

    Article 

    Google Scholar
     

  • Li G, Zhou Y, Liu F et al. (2021a) Regional difference and convergence analysis of marine science and technology innovation efficiency in China. Ocean Coast Manage 205:105581. https://doi.org/10.1016/j.ocecoaman.2021.105581

    Article 
    MATH 

    Google Scholar
     

  • Li M, Ahmad M, Fareed Z et al. (2021b) Role of trade openness, export diversification, and renewable electricity output in realizing carbon neutrality dream of China. J Environ Manage 297:113419. https://doi.org/10.1016/j.jenvman.2021.113419

    Article 
    CAS 
    PubMed 
    MATH 

    Google Scholar
     

  • Li R, Li L, Wang Q (2022) The impact of energy efficiency on carbon emissions: evidence from the transportation sector in Chinese 30 provinces. Sustain Cities Soc 82:103880. https://doi.org/10.1016/j.scs.2022.103880

    Article 

    Google Scholar
     

  • Li R, Wang Q, Guo J (2024) Revisiting the Environmental Kuznets Curve (EKC) hypothesis of carbon emissions: exploring the impact of geopolitical risks, natural resource rents, corrupt governance, and energy intensity. J Environ Manage 351:119663. https://doi.org/10.1016/j.jenvman.2023.119663

    Article 
    PubMed 

    Google Scholar
     

  • Li R, Wang Q, Liu Y et al. (2021c) Per-capita carbon emissions in 147 countries: the effect of economic, energy, social, and trade structural changes. Sustain Prod Consum 27:1149–1164. https://doi.org/10.1016/j.spc.2021.02.031

    Article 
    MATH 

    Google Scholar
     

  • Li Z, Wang J (2022) The dynamic impact of digital economy on carbon emission reduction: evidence city-level empirical data in China. J Clean Prod 351:131570. https://doi.org/10.1016/j.jclepro.2022.131570

    Article 
    CAS 

    Google Scholar
     

  • Liu J, Chang H, Forrest JY-L et al. (2020) Influence of artificial intelligence on technological innovation: evidence from the panel data of China’s manufacturing sectors. Technol Forecast Soc 158:120142. https://doi.org/10.1016/j.techfore.2020.120142

    Article 

    Google Scholar
     

  • Liu P, Zhu B, Yang M (2021a) Has marine technology innovation promoted the high-quality development of the marine economy?—Evidence from coastal regions in China. Ocean Coast Manag 209:105695. https://doi.org/10.1016/j.ocecoaman.2021.105695

    Article 
    MATH 

    Google Scholar
     

  • Liu Y, Dong F (2021) How technological innovation impacts urban green economy efficiency in emerging economies: a case study of 278 Chinese cities. Resour Conserv Recycl 169:105534. https://doi.org/10.1016/j.resconrec.2021.105534

    Article 

    Google Scholar
     

  • Liu Y, Sadiq F, Ali W et al. (2022) Does tourism development, energy consumption, trade openness and economic growth matters for ecological footprint: testing the environmental Kuznets Curve and pollution haven hypothesis for Pakistan. Energy 245:123208. https://doi.org/10.1016/j.energy.2022.123208

    Article 

    Google Scholar
     

  • Liu Y, Zhao C, Dong K et al. (2023) How does green finance achieve urban carbon unlocking? Evidence from China. Urban Clim 52:101742. https://doi.org/10.1016/j.uclim.2023.101742

    Article 

    Google Scholar
     

  • Liu Z, Chen S, Tang T et al. (2024) How public education investment and advanced human capital structure affect regional innovation: a spatial econometric analysis from the perspective of innovation value chain. Socio-Econ Plan Sci 91:101800. https://doi.org/10.1016/j.seps.2023.101800

    Article 

    Google Scholar
     

  • Liu Z, Song J, Wu H et al. (2021b) Impact of financial technology on regional green finance. Comput Syst Sci Eng 39(3)

  • Lou R, Lv Z, Dang S et al. (2023) Application of machine learning in ocean data. Multimed Syst 29(3):1815–1824. https://doi.org/10.1007/s00530-020-00733-x

    Article 
    MATH 

    Google Scholar
     

  • Lovell CK (1996) Applying efficiency measurement techniques to the measurement of productivity change. J Prod Anal 7(2):329–340. https://doi.org/10.1007/BF00157047

    Article 
    MATH 

    Google Scholar
     

  • Mealy P, Teytelboym A (2022) Economic complexity and the green economy. Res Policy 51(8):103948. https://doi.org/10.1016/j.respol.2020.103948

    Article 
    MATH 

    Google Scholar
     

  • Muganyi T, Yan L, Sun H-P (2021) Green finance, fintech and environmental protection: evidence from China. Environ Sci Ecotechnol 7:100107. https://doi.org/10.1016/j.ese.2021.100107

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Murshed M (2020) An empirical analysis of the non-linear impacts of ICT-trade openness on renewable energy transition, energy efficiency, clean cooking fuel access and environmental sustainability in South Asia. Environ Sci Pollut Res 27(29):36254–36281. https://doi.org/10.1007/s11356-020-09497-3

    Article 
    CAS 
    MATH 

    Google Scholar
     

  • Mushtaq R, Bruneau C (2019) Microfinance, financial inclusion and ICT: implications for poverty and inequality. Technol Soc 59:101154. https://doi.org/10.1016/j.techsoc.2019.101154

    Article 
    MATH 

    Google Scholar
     

  • Nchofoung TN, Asongu SA (2022) ICT for sustainable development: global comparative evidence of globalisation thresholds. Telecommun Policy 46(5):102296. https://doi.org/10.1016/j.telpol.2021.102296

    Article 

    Google Scholar
     

  • Nejati M, Taleghani F (2022) Pollution halo or pollution haven? A CGE appraisal for Iran. J Clean Prod 344:131092. https://doi.org/10.1016/j.jclepro.2022.131092

    Article 
    CAS 

    Google Scholar
     

  • Nthane TT, Saunders F, Gallardo Fernández GL et al. (2020) Toward sustainability of South African small-scale fisheries leveraging ICT transformation pathways. Sustainability 12(2):743

    Article 

    Google Scholar
     

  • Ntiri P, Ragasa C, Anang SA et al. (2022) Does ICT-based aquaculture extension contribute to greater adoption of good management practices and improved incomes? Evidence from Ghana. Aquaculture 557:738350. https://doi.org/10.1016/j.aquaculture.2022.738350

    Article 

    Google Scholar
     

  • Nunn N, Qian N (2014) US food aid and civil conflict. Am Econ Rev 104(6):1630–1666. https://doi.org/10.1257/aer.104.6.1630

    Article 
    MATH 

    Google Scholar
     

  • Probst WN (2019) How emerging data technologies can increase trust and transparency in fisheries. ICES J Mar Sci 77(4):1286–1294. https://doi.org/10.1093/icesjms/fsz036

    Article 
    MATH 

    Google Scholar
     

  • Puszkarski J, Śniadach O (2022) Instruments to implement sustainable aquaculture in the European Union. Mar Policy 144:105215. https://doi.org/10.1016/j.marpol.2022.105215

    Article 
    MATH 

    Google Scholar
     

  • Qamri GM, Sheng B, Adeel-Farooq RM et al. (2022) The criticality of FDI in environmental degradation through financial development and economic growth: implications for promoting the green sector. Resour Policy 78:102765. https://doi.org/10.1016/j.resourpol.2022.102765

    Article 
    MATH 

    Google Scholar
     

  • Qin L, Aziz G, Hussan MW et al. (2024) Empirical evidence of fintech and green environment: using the green finance as a mediating variable. Int Rev Econ Financ 89:33–49. https://doi.org/10.1016/j.iref.2023.07.056

    Article 

    Google Scholar
     

  • Razzaq A, Yang X (2023) Digital finance and green growth in China: appraising inclusive digital finance using web crawler technology and big data. Technol Forecast Soc 188:122262. https://doi.org/10.1016/j.techfore.2022.122262

    Article 

    Google Scholar
     

  • Ren W, Ji J, Chen L et al. (2018) Evaluation of China’s marine economic efficiency under environmental constraints—an empirical analysis of China’s eleven coastal regions. J Clean Prod 184:806–814. https://doi.org/10.1016/j.jclepro.2018.02.300

    Article 
    MATH 

    Google Scholar
     

  • Romer PM (1990) Endogenous technological change. J Polit Econ 98(5, Part 2):S71–S102

    Article 
    MATH 

    Google Scholar
     

  • Rosenthal SS, Strange WC (2020) How close is close? The spatial reach of agglomeration economies. J Econ Perspect 34(3):27–49. https://doi.org/10.1257/jep.34.3.27

    Article 
    MATH 

    Google Scholar
     

  • Saeed Meo M, Karim MZA (2022) The role of green finance in reducing CO2 emissions: an empirical analysis. Borsa Istanb Rev 22(1):169–178. https://doi.org/10.1016/j.bir.2021.03.002

    Article 
    MATH 

    Google Scholar
     

  • Saqib N, Abbas S, Ozturk I et al. (2024) Leveraging environmental ICT for carbon neutrality: Analyzing the impact of financial development, renewable energy and human capital in top polluting economies. Gondwana Res 126:305–320. https://doi.org/10.1016/j.gr.2023.09.014

    Article 
    ADS 

    Google Scholar
     

  • Sarkar S, Paramanik AR, Mahanty B (2024) A Z-number slacks-based measure DEA model-based framework for sustainable supplier selection with imprecise information. J Clean Prod 436:140563. https://doi.org/10.1016/j.jclepro.2024.140563

    Article 
    MATH 

    Google Scholar
     

  • Saville R, Hatanaka K, Sano M et al. (2015) Application of information and communication technology and data sharing management scheme for the coastal fishery using real-time fishery information. Ocean Coast Manag 106:77–86. https://doi.org/10.1016/j.ocecoaman.2015.01.019

    Article 
    MATH 

    Google Scholar
     

  • Shao Y, Chen Z (2022) Can government subsidies promote the green technology innovation transformation? Evidence from Chinese listed companies. Econ Anal Policy 74:716–727. https://doi.org/10.1016/j.eap.2022.03.020

    Article 
    MATH 

    Google Scholar
     

  • Shreesha S, Pai MMM, Pai RM et al. (2023) Pattern detection and prediction using deep learning for intelligent decision support to identify fish behaviour in aquaculture. Ecol Inform 78:102287. https://doi.org/10.1016/j.ecoinf.2023.102287

    Article 
    MATH 

    Google Scholar
     

  • Song X, Zhou Y, Jia W (2019) How do economic openness and R&D investment affect green economic growth?—Evidence from China. Resour Conserv Recycl 146:405–415. https://doi.org/10.1016/j.resconrec.2019.03.050

    Article 
    MATH 

    Google Scholar
     

  • Song Y, Gong Y, Song Y (2024) The impact of digital financial development on the green economy: an analysis based on a volatility perspective. J Clean Prod 434:140051. https://doi.org/10.1016/j.jclepro.2023.140051

    Article 
    MATH 

    Google Scholar
     

  • Sonnewald M, Lguensat R, Jones DC et al. (2021) Bridging observations, theory and numerical simulation of the ocean using machine learning. Environ Res Lett 16(7):073008. https://doi.org/10.1088/1748-9326/ac0eb0

    Article 
    ADS 

    Google Scholar
     

  • Sun J, Zhai N, Miao J et al. (2023) How do heterogeneous environmental regulations affect the sustainable development of marine green economy? Empirical evidence from China’s coastal areas. Ocean Coast Manag 232:106448. https://doi.org/10.1016/j.ocecoaman.2022.106448

    Article 

    Google Scholar
     

  • Suresh A (2023) Contextualising credit transactions in artisanal marine fishing: insights from Kerala, India. Rev Fish Biol Fisher 33(3):699–715. https://doi.org/10.1007/s11160-023-09782-7

    Article 

    Google Scholar
     

  • Teniwut WA, Hasyim CL, Pentury F (2022) Towards smart government for sustainable fisheries and marine development: an intelligent web-based support system approach in small islands. Mar Policy 143:105158. https://doi.org/10.1016/j.marpol.2022.105158

    Article 

    Google Scholar
     

  • Terhaar J, Goris N, Müller JD et al. (2024) Assessment of global ocean biogeochemistry models for ocean carbon sink estimates in RECCAP2 and recommendations for future studies. J Adv Model Earth Syst 16(3). https://doi.org/10.1029/2023MS003840

  • Thompson BS (2022) Blue bonds for marine conservation and a sustainable ocean economy: status, trends, and insights from green bonds. Mar Policy 144:105219. https://doi.org/10.1016/j.marpol.2022.105219

    Article 
    MATH 

    Google Scholar
     

  • Tone K (2001) A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res 130(3):498–509. https://doi.org/10.1016/S0377-2217(99)00407-5

    Article 
    MathSciNet 
    MATH 

    Google Scholar
     

  • Tone K, Tsutsui M (2010) An epsilon-based measure of efficiency in DEA—a third pole of technical efficiency. Eur J Oper Res 207(3):1554–1563. https://doi.org/10.1016/j.ejor.2010.07.014

    Article 
    MathSciNet 
    MATH 

    Google Scholar
     

  • Vanderklift MA, Marcos-Martinez R, Butler JRA et al. (2019) Constraints and opportunities for market-based finance for the restoration and protection of blue carbon ecosystems. Mar Policy 107:103429. https://doi.org/10.1016/j.marpol.2019.02.001

    Article 

    Google Scholar
     

  • Wang C, Li Z, Wang T et al. (2021) Intelligent fish farm—the future of aquaculture. Aquacult Int 29(6):2681–2711. https://doi.org/10.1007/s10499-021-00773-8

    Article 
    CAS 
    MATH 

    Google Scholar
     

  • Wang J, Dong X, Dong K (2022a) How does ICT agglomeration affect carbon emissions? The case of Yangtze River Delta urban agglomeration in China. Energy Econ 111:106107. https://doi.org/10.1016/j.eneco.2022.106107

    Article 
    MATH 

    Google Scholar
     

  • Wang J, Yang J, Yang L (2023a) Do natural resources play a role in economic development? Role of institutional quality, trade openness, and FDI. Resour Policy 81:103294. https://doi.org/10.1016/j.resourpol.2023.103294

    Article 
    MATH 

    Google Scholar
     

  • Wang K-L, Sun T-T, Xu R-Y et al. (2022b) How does internet development promote urban green innovation efficiency? Evidence from China. Technol Forecast Soc 184:122017. https://doi.org/10.1016/j.techfore.2022.122017

    Article 

    Google Scholar
     

  • Wang L, Zhou Z, Yang Y et al. (2020) Green efficiency evaluation and improvement of Chinese ports: a cross-efficiency model. Transp Res Part D 88:102590. https://doi.org/10.1016/j.trd.2020.102590

    Article 
    MATH 

    Google Scholar
     

  • Wang M, Zhu C, Wang X et al. (2023b) Effect of information and communication technology and electricity consumption on green total factor productivity. Appl Energy 347:121366. https://doi.org/10.1016/j.apenergy.2023.121366

    Article 
    MATH 

    Google Scholar
     

  • Wang Q, Li Y, Li R (2024a) Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI). Hum Soc Sci Commun 11(1). https://doi.org/10.1057/s41599-024-03520-5

  • Wang Q, Sun T, Li R (2023c) Does artificial intelligence promote green innovation? An assessment based on direct, indirect, spillover, and heterogeneity effects. Energy Environ-Uk. https://doi.org/10.1177/0958305X231220520

  • Wang Q, Zhang F, Li R (2024b) Artificial intelligence and sustainable development during urbanization: perspectives on AI R&D innovation, AI infrastructure, and AI market advantage. Sustain Dev. https://doi.org/10.1002/sd.3150

  • Wang Q, Zhang F, Li R et al. (2024c) Does artificial intelligence promote energy transition and curb carbon emissions? The role of trade openness. J Clean Prod 447:141298. https://doi.org/10.1016/j.jclepro.2024.141298

    Article 
    CAS 

    Google Scholar
     

  • Wang W, Rehman MA, Fahad S (2022c) The dynamic influence of renewable energy, trade openness, and industrialization on the sustainable environment in G-7 economies. Renew Energy 198:484–491. https://doi.org/10.1016/j.renene.2022.08.067

    Article 
    MATH 

    Google Scholar
     

  • Wang X, Lu Y, Chen C et al. (2024d) Total-factor energy efficiency of ten major global energy-consuming countries. J Environ Sci-China 137:41–52. https://doi.org/10.1016/j.jes.2023.02.031

    Article 
    MATH 

    Google Scholar
     

  • Wang X, Zhang T, Luo S et al. (2023d) Pathways to improve energy efficiency under carbon emission constraints in iron and steel industry: using EBM, NCA and QCA approaches. J Environ Manage 348:119206. https://doi.org/10.1016/j.jenvman.2023.119206

    Article 
    PubMed 

    Google Scholar
     

  • Willis KA, Serra-Gonçalves C, Richardson K et al. (2022) Cleaner seas: reducing marine pollution. Rev Fish Biol Fisher 32(1):145–160. https://doi.org/10.1007/s11160-021-09674-8

    Article 

    Google Scholar
     

  • Winther J-G, Dai M, Rist T et al. (2020) Integrated ocean management for a sustainable ocean economy. Nat Ecol Evol 4(11):1451–1458. https://doi.org/10.1038/s41559-020-1259-6

    Article 
    PubMed 
    MATH 

    Google Scholar
     

  • WMA (2022) State of the global climate 2021. Retrieved from https://policycommons.net/artifacts/2434625/1290_statement_2021_en/3456217/. Accessed 2 Apr 2024

  • Wu H (2022) Trade openness, green finance and natural resources: a literature review. Resour Policy 78:102801. https://doi.org/10.1016/j.resourpol.2022.102801

    Article 
    ADS 

    Google Scholar
     

  • Wu H (2023) Evaluating the role of renewable energy investment resources and green finance on the economic performance: evidence from OECD economies. Resour Policy 80:103149. https://doi.org/10.1016/j.resourpol.2022.103149

    Article 

    Google Scholar
     

  • Wu P, Wang Y, Chiu Y-h et al. (2019) Production efficiency and geographical location of Chinese coal enterprises—undesirable EBM DEA. Resour Policy 64:101527. https://doi.org/10.1016/j.resourpol.2019.101527

    Article 
    MATH 

    Google Scholar
     

  • Xu J, Chen F, Zhang W et al. (2023a) Analysis of the carbon emission reduction effect of Fintech and the transmission channel of green finance. Financ Res Lett 56:104127. https://doi.org/10.1016/j.frl.2023.104127

    Article 
    MATH 

    Google Scholar
     

  • Xu S, Liu Y (2023) Research on the impact of carbon finance on the green transformation of China’s marine industry. J Clean Prod 418:138143. https://doi.org/10.1016/j.jclepro.2023.138143

    Article 
    CAS 

    Google Scholar
     

  • Xu T, Dong J, Qiao D (2023b) China’s marine economic efficiency: a meta-analysis. Ocean Coast Manag 239:106633. https://doi.org/10.1016/j.ocecoaman.2023.106633

    Article 
    MATH 

    Google Scholar
     

  • Yu L, Zhao D, Xue Z et al. (2020) Research on the use of digital finance and the adoption of green control techniques by family farms in China. Technol Soc 62:101323. https://doi.org/10.1016/j.techsoc.2020.101323

    Article 
    MATH 

    Google Scholar
     

  • Zeng W, Li L, Huang Y (2021) Industrial collaborative agglomeration, marketization, and green innovation: evidence from China’s provincial panel data. J Clean Prod 279:123598. https://doi.org/10.1016/j.jclepro.2020.123598

    Article 

    Google Scholar
     

  • Zhang D, Mohsin M, Rasheed AK et al. (2021a) Public spending and green economic growth in BRI region: mediating role of green finance. Energy Policy 153:112256. https://doi.org/10.1016/j.enpol.2021.112256

    Article 

    Google Scholar
     

  • Zhang G, Guo B, Lin J (2023a) The impact of green finance on enterprise investment and financing. Financ Res Lett 58:104578. https://doi.org/10.1016/j.frl.2023.104578

    Article 
    MATH 

    Google Scholar
     

  • Zhang J, Chen X, Zhao X (2023b) A perspective of government investment and enterprise innovation: marketization of business environment. J Bus Res 164:113925. https://doi.org/10.1016/j.jbusres.2023.113925

    Article 
    MATH 

    Google Scholar
     

  • Zhang X, Sun D, Zhang X et al. (2021b) Regional ecological efficiency and future sustainable development of marine ranch in China: an empirical research using DEA and system dynamics. Aquaculture 534:736339. https://doi.org/10.1016/j.aquaculture.2021.736339

    Article 

    Google Scholar
     

  • Zhao P, Gao Y, Sun X (2022a) How does artificial intelligence affect green economic growth?—Evidence from China. Sci Total Environ 834:155306. https://doi.org/10.1016/j.scitotenv.2022.155306

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Zhao S, Hafeez M, Faisal CMN (2022b) Does ICT diffusion lead to energy efficiency and environmental sustainability in emerging Asian economies? Environ Sci Pollut Res 29(8):12198–12207. https://doi.org/10.1007/s11356-021-16560-0

    Article 
    MATH 

    Google Scholar
     

  • Zheng H, Wu Y, He H et al. (2024) Urbanization and urban energy eco-efficiency: a meta-frontier super EBM analysis based on 271 cities of China. Sustain Cities Soc 101:105089. https://doi.org/10.1016/j.scs.2023.105089

    Article 

    Google Scholar
     

  • Zheng H, Zhang L, Zhao X (2022) How does environmental regulation moderate the relationship between foreign direct investment and marine green economy efficiency: an empirical evidence from China’s coastal areas. Ocean Coast Manag 219:106077. https://doi.org/10.1016/j.ocecoaman.2022.106077

    Article 
    MATH 

    Google Scholar
     

  • Zhong M-R, Cao M-Y, Zou H (2022) The carbon reduction effect of ICT: a perspective of factor substitution. Technol Forecast Soc 181:121754. https://doi.org/10.1016/j.techfore.2022.121754

    Article 
    MATH 

    Google Scholar
     

  • Zhou G, Zhu J, Luo S (2022) The impact of fintech innovation on green growth in China: mediating effect of green finance. Ecol Econ 193:107308. https://doi.org/10.1016/j.ecolecon.2021.107308

    Article 

    Google Scholar
     

  • Zhou Y, Li G, Zhou S et al. (2023) Spatio-temporal differences and convergence analysis of green development efficiency of marine economy in China. Ocean Coast Manag 238:106560. https://doi.org/10.1016/j.ocecoaman.2023.106560

    Article 
    MATH 

    Google Scholar
     

  • Zhu M, Huang H, Ma W (2023) Transformation of natural resource use: moving towards sustainability through ICT-based improvements in green total factor energy efficiency. Resour Policy 80:103228. https://doi.org/10.1016/j.resourpol.2022.103228

    Article 
    MATH 

    Google Scholar
     

  • Zou W, Yang Y, Yang M et al. (2023) Analyzing efficiency measurement and influencing factors of China’s marine green economy: based on a two-stage network DEA model. Front Mar Sci 10. https://doi.org/10.3389/fmars.2023.1020373



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