A decision-support framework for industrial green transformation: empirical analysis of the northeast industrial district in China
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DOI: 10.1007/s00168-024-01300-2
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- Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
- Guan, Jian Cheng & Yam, Richard C.M. & Mok, Chiu Kam & Ma, Ning, 2006. "A study of the relationship between competitiveness and technological innovation capability based on DEA models," European Journal of Operational Research, Elsevier, vol. 170(3), pages 971-986, May.
- Fan, Dongyan & Sun, Hai & Yao, Jun & Zhang, Kai & Yan, Xia & Sun, Zhixue, 2021. "Well production forecasting based on ARIMA-LSTM model considering manual operations," Energy, Elsevier, vol. 220(C).
- Zha, Donglan & Kavuri, Anil Savio & Si, Songjian, 2017. "Energy biased technology change: Focused on Chinese energy-intensive industries," Applied Energy, Elsevier, vol. 190(C), pages 1081-1089.
- Du, Kerui & Cheng, Yuanyuan & Yao, Xin, 2021. "Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities," Energy Economics, Elsevier, vol. 98(C).
- Zhu, Lin & Luo, Jian & Dong, Qingli & Zhao, Yang & Wang, Yunyue & Wang, Yong, 2021. "Green technology innovation efficiency of energy-intensive industries in China from the perspective of shared resources: Dynamic change and improvement path," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
- Wu, Lifeng & Liu, Sifeng & Fang, Zhigeng & Xu, Haiyan, 2015. "Properties of the GM(1,1) with fractional order accumulation," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 287-293.
- Zeng, Bo & Li, Chuan, 2016. "Forecasting the natural gas demand in China using a self-adapting intelligent grey model," Energy, Elsevier, vol. 112(C), pages 810-825.
- Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013.
"Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis,"
Applied Energy, Elsevier, vol. 104(C), pages 105-116.
- Ke Wang & Yi-Ming Wei & Xian Zhang, 2014. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," CEEP-BIT Working Papers 60, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
- Dilaver, Zafer & Hunt, Lester C., 2011.
"Turkish aggregate electricity demand: An outlook to 2020,"
Energy, Elsevier, vol. 36(11), pages 6686-6696.
- Zafer Dilaver & Lester C Hunt, 2011. "Turkish Aggregate Electricity Demand: An Outlook to 2020," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 132, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
- Gong, Xu & Wang, You & Lin, Boqiang, 2021. "Assessing dynamic China’s energy security: Based on functional data analysis," Energy, Elsevier, vol. 217(C).
- Goto, Mika & Otsuka, Akihiro & Sueyoshi, Toshiyuki, 2014. "DEA (Data Envelopment Analysis) assessment of operational and environmental efficiencies on Japanese regional industries," Energy, Elsevier, vol. 66(C), pages 535-549.
- Tziogkidis, Panagiotis & Philippas, Dionisis & Leontitsis, Alexandros & Sickles, Robin C., 2020. "A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1011-1024.
- Chen, Hai-Bao & Pei, Ling-Ling & Zhao, Yu-Feng, 2021. "Forecasting seasonal variations in electricity consumption and electricity usage efficiency of industrial sectors using a grey modeling approach," Energy, Elsevier, vol. 222(C).
- Zhou, Xiaoxiao & Cai, Ziming & Tan, Kim Hua & Zhang, Linling & Du, Juntao & Song, Malin, 2021. "Technological innovation and structural change for economic development in China as an emerging market," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
- Nazemi, Abdolreza & Baumann, Friedrich & Fabozzi, Frank J., 2022. "Intertemporal defaulted bond recoveries prediction via machine learning," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1162-1177.
- An, Ning & Zhao, Weigang & Wang, Jianzhou & Shang, Duo & Zhao, Erdong, 2013. "Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting," Energy, Elsevier, vol. 49(C), pages 279-288.
- Meng, Ming & Niu, Dongxiao & Shang, Wei, 2014. "A small-sample hybrid model for forecasting energy-related CO2 emissions," Energy, Elsevier, vol. 64(C), pages 673-677.
- Ghosh, Ranjan & Kathuria, Vinish, 2016. "The effect of regulatory governance on efficiency of thermal power generation in India: A stochastic frontier analysis," Energy Policy, Elsevier, vol. 89(C), pages 11-24.
- Pao, Hsiao-Tien, 2006. "Comparing linear and nonlinear forecasts for Taiwan's electricity consumption," Energy, Elsevier, vol. 31(12), pages 2129-2141.
- Zuo, Wei & Li, Jing & Zhang, Yuntian & Li, Qingqing & He, Zhu, 2020. "Effects of multi-factors on comprehensive performance of a hydrogen-fueled micro-cylindrical combustor by combining grey relational analysis and analysis of variance," Energy, Elsevier, vol. 199(C).
- Ding, Song & Zhang, Huahan, 2023. "Forecasting Chinese provincial CO2 emissions: A universal and robust new-information-based grey model," Energy Economics, Elsevier, vol. 121(C).
- Turken, Nazli & Carrillo, Janice & Verter, Vedat, 2020. "Strategic supply chain decisions under environmental regulations: When to invest in end-of-pipe and green technology," European Journal of Operational Research, Elsevier, vol. 283(2), pages 601-613.
- Saab, Samer & Badr, Elie & Nasr, George, 2001. "Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon," Energy, Elsevier, vol. 26(1), pages 1-14.
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JEL classification:
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
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