Figure - available from: Energy Efficiency
This content is subject to copyright. Terms and conditions apply.
Source publication
Energy efficiency (EE) is an important strategy for China to save energy and reduce energy-related emissions. With significant regional diversities in China, it is important to conduct the EE assessment at the regional level. Usually, the regional EE assessment is applied to 30 regions in Mainland China using the data envelopment analysis (DEA) tec...
Citations
... Zhang and Chen (2022) applied the SBM-DEA model to evaluate the energy efficiency in 13 RCEP countries and found that the energy efficiency of developed countries is higher than that of developing countries. Both Meng et al. (2019) and Qu et al. (2022) analyzed the heterogeneity of energy efficiency in different regions of China. Meng showed that the 30 provinces in China have the least rank reversal when SBM-DEA is adopted. ...
... That is the goal of this research: to find (Meng et al. 2019) out how the GCF can collect and distribute money so that worldwide climate management and the GCF's fiscal equilibrium can be met. ...
Since there is little progress being made in multinational climate discussions, climate finance is at a crossroads as lenders must come up with new plans for the “Future of Environment Funds.” The mission of effectively and efficiently distributing money to support the shift to low-carbon, climate-resilient economies has been given to climate finance organizations. Due to its purpose to contribute to a paradigm shift, the Green Climate Fund (GCF) is anticipated to help the most vulnerable populations adapt to and mitigate climate change. This research alters the premise of the Baumol and Oates public externality model to make it more appropriate for global climate governance analysis. This research then deduces the special pricing conditions to persuade the market to comply with Pareto optimality criteria by contrasting the Pareto optimality model of global climate governance and the market equilibrium model. The rules and potential approaches that must be followed for raising capital and allocating GCFs are then determined by taking into account global Pareto optimality and fiscal balance. The study finds that when each country assumes that the GCF aims to achieve Pareto optimality in climate governance globally and its own fiscal balance, the equilibrium results of the international climate game will not achieve both the financial balance of the GCF and global Pareto optimality simultaneously. The GCF may successfully finance non-bankable components of bigger “almost bankable projects,” according to our empirical analysis of the GCF portfolio structure and strategy in this research. This lends credence to an alternative interpretation of the GCF.
... After a novel approach was developed based on the adapted model, product changes were made in response to consumer preferences (Meng et al., 2019). This economic path leads to further consolidation of the new value offer and the emergence of additional clients in the new business beyond the core customers, who first recommended different apps. ...
This study explores the relationship between the business environment, economic growth, and funding sources of Chinese small- and medium-sized enterprises (SMEs) to determine the relevance of the business environment for technological SMEs. The agency theory was used as a theoretical framework to describe how asymmetric information among SMEs and borrowers affects SMEs’ financial decisions as well as China’s investment climate and GDP growth. A binary logistic test was used to assess the financing of SMEs and business development for economic recovery after the pandemic in China. Data from the World Economic Forum and Development Bank were examined. According to the results, funding (e.g., formal and informal) under the banking structure and tax regulation may potentially boost standard credit choices and lower casual credit choices. Consequently, it has demonstrated a considerable impact on GDP growth for technologically small and medium-sized enterprises. This study is the first to examine the asymmetric information and institutional theory regarding funding a café. These findings are essential for business leaders and policymakers concerned with the financial health of small and medium-sized enterprises. Policy implications for important stakeholders are also included in this study.
... 4 Assuming energy the only input for the GDP, sing-factor indictor such as energy intensity (energy input per unit output) omit other essential inputs, such as capital, labor, and their substitution (Hu and Wang, 2006;Chen et al., 2021). While a multiple-factor indicator, i.e., TFEE is more beneficial than the partial indicators (Meng et al., 2018). ...
A R T I C L E I N F O Keywords: Energy efficiency Club convergence Belt and road initiative Outward foreign direct investment A B S T R A C T Countries along with the Belt and Road Initiative (BRI) differ in geographical location, technological levels, and resource endowment. It is worth paying attention to the evolution of the gap in energy efficiency of BRI countries. Therefore, this study investigated club convergence in total-factor energy efficiency (TFEE) of BRI countries, and the role of China's outward foreign direct investment (OFDI) in TFEE convergence, by adopting panel data over 1996-2019. Results indicate that the TFEE of the BRI countries showed a trend of divergence as a whole, but converged to three convergence clubs with different characteristics of 1) high TFEE and convergence rates (20 countries); 2) middle TFEE and convergence rates (13 countries), 3) low TFEE and convergence rates (27 countries). We also found that China's OFDI in low-carbon industries in BRI countries contributed to the convergence of clubs with high energy efficiency and convergence rates. Moreover, China's OFDI in high-carbon industries showed a pollution halo effect, causing lower energy efficiency countries to converge to the high energy efficiency and convergence rate club.
... The J-B test contradicts the null hypothesis of normality for all variables except GDP. Therefore, it is important to use a regression test rather than just a traditional linear conduction test, which relies only on the VAR model [48]. ...
This study aims to analyze whether information and communication technology (ICT) and renewable energy (RE) can assist in enhancing environmental quality. This study employs time series data from 1990 to 2019 using econometric techniques. The results show that the use of ICTs in the US, UK, China, Russia, Canada, Australia, Sweden, Norway, Switzerland, and Italy has decreased environmental protection. The results reveal that RE use enhances the sustainability of the environment regardless of the sample size or surrogate utilized for ICT. Impulse response functions show that, on average, the influence of ICT and RE lasts between one and seven years. The error correction model segmentation study verified that ICT and RE contribute to the volatility of carbon dioxide emissions. There is strong evidence that carbon dioxide emissions, ICT, and RE use have a bidirectional causal relationship in most circumstances. Several ICTs and RE strategies have been established and explored to profit from the possible positive influence of ICT and RE usage on environmental quality.
... Meng et al. (2016) systematically reviewed the literature on regional energy and carbon emission efficiency (EE&CE) research from the aspects of application attribute, variable scheme, model aspect, and analyzed the differences in the calculation results of six different DEA models. Moreover, Meng et al. (2019) studied the ranking reversal phenomenon of China's regional energy efficiency under different DEA models (namely Radial, M-Radial, SBMT, RAM and DDF model). ...
... Thereafter proposed the classic BCC model. Radial models, such as CCR and BCC, which are widely used (Meng et al., 2019). ...
Special Issue of JMSE: New advances in DEA and its applications under big data
Guest editors: Prof. Dr. Guoliang Yang & Prof. Dr. Ali Emrouznejad
... Additionally, the factors that cause higher energy performance measures are needed for the development of the economics model. The study by Meng et al. (2019) and Piñeros (2020) focused on introducing a replacement information intromission analysis technique to supply environmental upgrading submissions, so it was absolutely founded on the investigation of energy efficiency index. Table 1 contains the list of inputs and output for energy efficiency assessment. ...
The objective of this study is to measure the energy efficiency index based on green finance data from 114 listed companies of China during 2009 to 2018 by using the slack-based data envelopment analysis (DEA) model to measure the energy efficiency and econometric estimation to measure the impact of debt and equity financing. The proposed research study purpose is to develop a comprehensive assessment financing efficiency index based on energy efficiency index. Results shows that 1% increase in equity financing increases the financing efficiency by 0.002, while bond financing is negatively associated with financing efficiency, whereas 1% rise in debt financing decreases the financing efficiency by −0.019 whereas coefficients of bank financing and market capitalization. Jilin and Shandong provinces are best-performing provinces in terms of financing efficiency, whereas the Henan and Hubei provinces are worst-performing provinces in overall sample. For every 1% increase in research and development, Jilin and Shandong reduce carbon dioxide emissions by considerable amount, respectively. The key findings indicate that banks continue to dominate the Chinese credit industry. A significance of arithmetic mean aggregation as mathematical tool and DEA to construct an eco-friendly index of Chinese have been discussed. The proposed research study highlights irregularities of data issues and to follow appropriate properties index number. The current study may fit in the broader spectrum and developing an eco-friendly index and developing the ranking index based on multiple indicators.
... Their works are centered on various time phases, provinces, areas, key-ins, and productivity items, and apply various dynamic envelope analysis equations that result in problems in drawing parallels concerning their findings. (Meng et al., 2019). ...
... Thus, there is no complete overview of the utilization of the dynamic envelope analysis equations to estimate provincial efficiency, taking into account diverse parameters. Hence, this study estimates a methodical overview of the empirical analysis done in recent times on China's provincial energy and CO2 pollution efficiency evaluation, applying the dynamic envelope analysis (Meng et al., 2019) and (Moon and Min 2020). ...
The objective of this research is to estimate the energy-saving intensities of nations within the European Union, applying varied equations of the DEA analysis, such as the DEA, modified radial equation, Russel dynamic envelope analysis, and the adjusted Russel Dynamic envelope Analysis, throughout the period of 2010–2018. Unlike other studies, this analysis seeks to unravel whether European nations are effective in increasing the EE finance of their respective economies. Because the European Union not only has geographical ties between regions, it is also a collection of interests of various sovereign states, its energy exhibits efficiency changes under the relationship of competition and cooperation under that economic effect. Regarding this circumstance, different dynamic envelope evaluations were formulated. One primary finding is that nations such as Germany, Sweden, or Austria attain robust ecological safeguard performance, seem to be using less energy, and are ecologically efficient relative to other nations such as Denmark, Belgium, Spain, France, or Ireland. Furthermore, a group of Eastern EU nations attained reduced efficiency marks, which could be categorized as anticipated, as a result of reduced technological implementation within the principal manufacturing sectors. The main result of this study is that few nations are performing in terms of efficiency. Additionally, RE (Renewable Energy) power production expands as nations’ dynamic envelope analysis marks and creates inefficient governments nearer to the efficiency frontline. Inversely, the presence of peak-time power consumption reduced the dynamic envelope analysis marks and increased the distance from the Frontier of efficiency (the optimal value of efficiency).
... Based on the definition, Lin and Tan (2016) used a meta-frontier slack-based DEA model to estimate TFEE in Chinese four sectors. Meng et al. (2018) also combined SBM model to estimate energy efficiency of Chinese 30 regions. According to the definition of TFEE and the superior of SBM model mentioned above, following Hu and Wang (2006) and Lin and Tan (2016), TFEE in region n can be estimated from the following equation: ...
Conventional wisdom argues that environmental regulation can trigger both structural adjustments and enhanced innovation. We test this conjecture by using a difference-in-differences approach to analyze the impacts of China’s carbon emission trading (CET) pilot policy on energy consumption. We find that compliance with the CET regulation has triggered statistically significant adjustments in energy structure, industrial structure, and technological innovation. Adjustments in industrial structure also contribute to enhanced total factor energy efficiency, whereas increased technological innovation has mixed effects on energy efficiency. We show that in the short run, government-led innovation does not immediately contribute to improvement in energy efficiency, whereas enterprise-led innovation has a negative impact. It indicates that CET regulation can affect energy efficiency through industrial structure and technological innovation. Overall, our results provide new evidence for the strong version of the Porter hypothesis. Our results also provide strong scientific support for China’s recent transition towards market-based carbon mitigation strategies.
... Various studies in different areas have used this methodology and are continuously expanding. DEA has been applied in various areas such as energy systems (Meng et al. 2019; Jahangoshai-Rezaee 2015), regional planning (Yu 2019;González et al. 2018), manufacturing systems (Yang et al. 2018a, b;Azadeh et al. 2013), healthcare systems (Avkiran and McCrystal 2014;Karimdadi and Rezaee 2015), supplier selection (Yousefi et al. 2019), transportation systems (Rezaee et al. 2016, Rezaee andYousefi 2018), portfolio selection and analysis (Mohammadian and Rezaee 2018; , financial and banking sectors (Nourani et al. 2018;Naini et al. 2013). ...
Like other organizations, universities must evaluate their performance to identify areas for improvement. Although the different aspects of a university are considered for evaluation, the research section is deemed to be the most important and is where the necessity of the performance evaluation is most salient. In this study, the relative efficiency of the sub-units of several faculties of the university has been investigated through dynamic data envelopment analysis (DDEA) and inverse DDEA (IDDEA). The capability of traditional DEA to differentiate between efficient and non-efficient units decreases as the ratio of the number of inputs and outputs to the number of decision-making units increases. To remove this limitation by adding intermediate constraints between stages, a dynamic form of the method was applied in this research. The paper provides distinctions between the faculties as well as sensitivity analysis of the inputs/outputs of each faculty. The proposed IDDEA is implemented to scrutinize the changes in the input and output levels. The proposed approach is output-oriented to account for the homogeneity of faculties and their subordination under a specific unified management policy. A case study of Urmia University is used to demonstrate the proposed approach.
