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学者姓名：李双杰
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Abstract ：
This paper introduces an improved slack-based game cross-efficiency measurement model that enhances the existing cross-efficiency framework and integrates it with the Data Envelopment Analysis (DEA) game cross-efficiency. The model ensures the fairness of its results through the implementation of a more stringent selection of frontier face weights. It accounts for the competitive relationships among Decision Making Units (DMUs), achieving a Nash equilibrium solution through continuous iterations. Furthermore, the model accounts for undesirable outputs and various strategic orientations, enhancing its applicability. The model's effectiveness is validated through comparative analyses of diverse case studies. Additionally, the model's practical utility is demonstrated through the analysis of industrial data from various Chinese provinces between 2010 and 2019. Analysis results show that the proposed model measures production efficiency with greater precision and comparability than alternative models.
Keyword ：
energy efficiency energy efficiency slacks-based measure slacks-based measure game cross-efficiency game cross-efficiency data envelopment analysis data envelopment analysis
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| GB/T 7714 | Huang, Tingyang , Li, Shuangjie , Liu, Fang et al. A Slacks-Based Measure Model for Computing Game Cross-Efficiency [J]. | SYSTEMS , 2024 , 12 (3) . |
| MLA | Huang, Tingyang et al. "A Slacks-Based Measure Model for Computing Game Cross-Efficiency" . | SYSTEMS 12 . 3 (2024) . |
| APA | Huang, Tingyang , Li, Shuangjie , Liu, Fang , Diao, Hongyu . A Slacks-Based Measure Model for Computing Game Cross-Efficiency . | SYSTEMS , 2024 , 12 (3) . |
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Abstract ：
The traditional economic development mode can no longer meet the increasingly stringent demands for innovation and environmental sustainability. Consequently, green innovation has emerged as a pivotal development trend. Accurate measurement of green innovation efficiency is crucial in this context. This study employs the SBM-DDF-GML model to evaluate the green innovation efficiency of 30 Chinese provinces from 2000 to 2020, incorporating enhanced indicators for both expected and unexpected outputs. Additionally, the K-means algorithm, a machine learning technique, was utilized to cluster the comprehensive development factors of these provinces, enabling an analysis of their spatiotemporal heterogeneity. The findings indicate that the improved model enhances the precision of regional green innovation efficiency rankings, providing a more accurate reflection of actual regional changes. Furthermore, compared to traditional regional classification methods, the K-means clustering based on comprehensive regional development factors exhibited greater inter-group differences, aligning more closely with the heterogeneity analysis of regional green innovation efficiency. The spatiotemporal heterogeneity analysis of the new groupings revealed that the evolution of green innovation efficiency is predominantly influenced by advancements in green innovation technology.
Keyword ：
SBM-DDF-GML model SBM-DDF-GML model K Means K Means Spatio-Temporal heterogeneity Spatio-Temporal heterogeneity Green innovation efficiency Green innovation efficiency Vertical-and-Horizontal scatter degree method Vertical-and-Horizontal scatter degree method
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| GB/T 7714 | Zhao, Xiongfei , Li, Shuangjie , Huang, Tingyang . New measurement and spatio-temporal heterogeneity of regional green innovation efficiency in China [J]. | ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY , 2024 . |
| MLA | Zhao, Xiongfei et al. "New measurement and spatio-temporal heterogeneity of regional green innovation efficiency in China" . | ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY (2024) . |
| APA | Zhao, Xiongfei , Li, Shuangjie , Huang, Tingyang . New measurement and spatio-temporal heterogeneity of regional green innovation efficiency in China . | ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY , 2024 . |
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Abstract ：
This paper introduces a novel decomposition method for analyzing production efficiency based on the Data Envelopment Analysis framework, addressing the limitations of traditional approaches that often fail to isolate the contributions of individual factors. The proposed method disaggregates production efficiency into capacity utilization, labor utilization efficiency, energy utilization efficiency, and technological change, providing a more granular view of how different factors contribute to overall efficiency. By incorporating both contemporaneous and intertemporal perspectives, this approach enables a comprehensive understanding of efficiency dynamics and factor interactions over time. To demonstrate the feasibility and robustness of the proposed method, we apply it to the thermal power industry using data from 30 Chinese provinces covering the period from 2011 to 2021. The empirical results validate the effectiveness of the decomposition framework, revealing distinct regional disparities in efficiency and providing insights for targeted resource optimization strategies. Based on these findings, we offer recommendations to enhance capacity utilization, improve energy efficiency, and support sustainable development within the thermal power sector. This research contributes a powerful analytical tool for disaggregating production efficiency and offers a theoretical foundation for future studies seeking to understand the nuanced relationships between comprehensive production efficiency and single-factor efficiencies, thereby supporting better policy and management decisions in complex production systems.
Keyword ：
production efficiency production efficiency decomposition method decomposition method distance function distance function data envelopment analysis data envelopment analysis efficiency of factor allocation efficiency of factor allocation
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| GB/T 7714 | Huang, Tingyang , Zhao, Xiongfei , Li, Shuangjie et al. The Relationship Between Production Efficiency and Factor Allocation Efficiency: A Case Study Based on Thermal Power in China [J]. | SYSTEMS , 2024 , 12 (11) . |
| MLA | Huang, Tingyang et al. "The Relationship Between Production Efficiency and Factor Allocation Efficiency: A Case Study Based on Thermal Power in China" . | SYSTEMS 12 . 11 (2024) . |
| APA | Huang, Tingyang , Zhao, Xiongfei , Li, Shuangjie , Liu, Fang . The Relationship Between Production Efficiency and Factor Allocation Efficiency: A Case Study Based on Thermal Power in China . | SYSTEMS , 2024 , 12 (11) . |
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Abstract ：
This paper conducted an in-depth study to elucidate the impact of corporate intelligence transformation and regional financial technology on green economic growth, particularly the role of credit resource allocation. We developed a multi-sector general equilibrium model, integrating the heterogeneity of intelligent transformation in production sectors and accounting for the influence of Fintech on financial institutions. Within this model framework, panel data from 2011 to 2021 at the provincial, municipal, and micro-enterprise levels in China were used to validate the theoretical model through a mixed regression approach. The findings indicate that as intelligent transformation firms receive more credit resources, their potential for green economic growth increases, contributing to reduced regional carbon emissions. Additionally, the excess productivity of intelligent transformation firms has a significant positive impact on regional carbon reduction efforts. Moreover, the advancement of Fintech reduces financial institutional costs, further optimizing credit allocation and lowering overall market interest rates, thereby promoting green development within the region. However, advancements in Fintech may also redirect more credit resources toward low-risk general enterprises, resulting in a credit crowding-out effect for intelligent transformation firms. These findings indicate that, while promoting intelligent transformation, policy measures should also balance the resource allocation effects of Fintech across different types of enterprises.
Keyword ：
Crowding-out effect Crowding-out effect Credit resources Credit resources Financial institutions Financial institutions Carbon emissions Carbon emissions Heterogeneous sectors Heterogeneous sectors
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| GB/T 7714 | Zhao, Xiongfei , Li, Shuangjie , Lu, Kaili et al. Intelligent transformation, fintech, and green Growth:A general equilibrium analysis based on credit allocation perspective [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 371 . |
| MLA | Zhao, Xiongfei et al. "Intelligent transformation, fintech, and green Growth:A general equilibrium analysis based on credit allocation perspective" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 371 (2024) . |
| APA | Zhao, Xiongfei , Li, Shuangjie , Lu, Kaili , Zhong, Yifan . Intelligent transformation, fintech, and green Growth:A general equilibrium analysis based on credit allocation perspective . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 371 . |
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Abstract ：
本发明提供了一种技术效率及全要素能源效率的测度方法及系统，属于生产资源配置测度领域，方法包括：获取目标导向、各决策单元的投入指标及产出指标；基于目标导向，采用带有非期望产出的基于松弛值测算的模型，根据各决策单元的投入指标及各决策单元的产出指标，确定各决策单元的初步技术效率值、各决策单元的松弛向量、各决策单元的目标决策单元及各决策单元的权重向量；采用基于松弛值测算的博弈交叉效率模型，对各决策单元的技术效率进行迭代计算，以得到各决策单元的最终技术效率值；根据决策单元的投入指标及各决策单元的松弛向量，确定决策单元的全要素能源效率。本发明提高了技术效率及全要素能源效率测算的科学性和精度。
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| GB/T 7714 | 李双杰 , 黄庭阳 . 一种技术效率及全要素能源效率的测度方法及系统 : CN202310973182.X[P]. | 2023-08-04 . |
| MLA | 李双杰 et al. "一种技术效率及全要素能源效率的测度方法及系统" : CN202310973182.X. | 2023-08-04 . |
| APA | 李双杰 , 黄庭阳 . 一种技术效率及全要素能源效率的测度方法及系统 : CN202310973182.X. | 2023-08-04 . |
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Abstract ：
This study aims to investigate the impact of ICT capital services on economic growth and energy efficiency in China at both national and industrial levels during the period 2000-2020. To achieve this aim, this study introduces a measurement method for capital services, explores ICT's contributions to economic growth, and analyzes the impact of ICT on energy efficiency. The empirical results of this study indicate that although the ICT capital services scale is relatively small, accounting for only 8.87% of the total in 2020, its growth rate is faster than that of non-ICT capital services, and the distribution of ICT capital services varies widely among different industries. Additionally, based on the economic growth decomposition framework, this study finds that the contribution of ICT capital services to economic growth is 6.95% on average. It is significantly higher in certain industries, such as Financial industry; Information transmission, software and information technology services; Construction; and Manufacturing compared to others. The total factor energy efficiency (TFEE) reveals that industries with higher energy consumption have lower energy efficiency, while the panel regression model illustrates that the development of ICT has a positive impact on improving energy efficiency, with variability across industries. Overall, the findings of this study provide crucial scientific evidence and policy implications for promoting the development of ICT and integrating it with various industries, which can significantly contribute to boosting economic growth and energy efficiency.
Keyword ：
ICT capital services ICT capital services energy efficiency energy efficiency panel regression panel regression economic growth decomposition framework economic growth decomposition framework
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| GB/T 7714 | Huifang, E. , Li, Shuangjie , Wang, Liming et al. The Impact of ICT Capital Services on Economic Growth and Energy Efficiency in China [J]. | ENERGIES , 2023 , 16 (9) . |
| MLA | Huifang, E. et al. "The Impact of ICT Capital Services on Economic Growth and Energy Efficiency in China" . | ENERGIES 16 . 9 (2023) . |
| APA | Huifang, E. , Li, Shuangjie , Wang, Liming , Xue, Huidan . The Impact of ICT Capital Services on Economic Growth and Energy Efficiency in China . | ENERGIES , 2023 , 16 (9) . |
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Abstract ：
The importance and urgency of improving energy and carbon emissions efficiency in mitigating climate change and achieving carbon neutrality have become an increasingly relentless focus in recent years. Assessing the performance of energy saving and carbon emissions reduction is a significant necessity to achieve sustainable economic development. Therefore, from the perspective of production economics, this paper presents a review of the definition, models, and input-output variables for measuring total-factor energy efficiency and total-factor carbon emissions efficiency. Relevant literature in this field, published between 2006 and 2021, has been systematically analyzed using CiteSpace software, which includes a quantitative and visual review of a large body of published literature. This review found that the current definitions of total-factor energy efficiency and total-factor carbon emissions efficiency are confusing and misleading. Furthermore, future research on energy saving and carbon emissions reduction should incorporate subject areas such as economics, energy, and ecology.
Keyword ：
total-factor carbon emissions efficiency total-factor carbon emissions efficiency total-factor energy efficiency total-factor energy efficiency input-output variables input-output variables sustainable development sustainable development carbon neutral carbon neutral
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| GB/T 7714 | Li, Shuangjie , Wang, Wei , Diao, Hongyu et al. Measuring the Efficiency of Energy and Carbon Emissions: A Review of Definitions, Models, and Input-Output Variables [J]. | ENERGIES , 2022 , 15 (3) . |
| MLA | Li, Shuangjie et al. "Measuring the Efficiency of Energy and Carbon Emissions: A Review of Definitions, Models, and Input-Output Variables" . | ENERGIES 15 . 3 (2022) . |
| APA | Li, Shuangjie , Wang, Wei , Diao, Hongyu , Wang, Liming . Measuring the Efficiency of Energy and Carbon Emissions: A Review of Definitions, Models, and Input-Output Variables . | ENERGIES , 2022 , 15 (3) . |
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Abstract ：
This research examines the influence of intellectual capital on financial and environmental performance with a mediating role of green supply chain management and a moderating role of financial resources. Structural model estimation was conducted on the data set of 324 Pakistani manufacturing SMEs and showed that intellectual capital significantly encourages green supply chain management as well as significantly contributes to financial and environmental performance. Green supply chain management partially mediates the relationship between intellectual capital and performance both the financial and environmental. Financial resources significantly strengthen the relationship between intellectual capital and green supply chain management. In light of the results, we suggest that firms should encourage intellectuality among their managers and employees to adopt green practices that can improve their financial and environmental performance. In addition, it is also suggested for managers and CEOs to effectively manage financial resources that are necessary for green practices.
Keyword ：
SMEs SMEs Intellectual capital Intellectual capital Financial resources Financial resources Financial performance Financial performance Environmental performance Environmental performance Green supply chain management Green supply chain management
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| GB/T 7714 | Khan Najib Ullah , Anwar Muhammad , Li Shuangjie et al. Intellectual capital, financial resources, and green supply chain management as predictors of financial and environmental performance. [J]. | Environmental science and pollution research international , 2021 , 28 (16) : 19755-19767 . |
| MLA | Khan Najib Ullah et al. "Intellectual capital, financial resources, and green supply chain management as predictors of financial and environmental performance." . | Environmental science and pollution research international 28 . 16 (2021) : 19755-19767 . |
| APA | Khan Najib Ullah , Anwar Muhammad , Li Shuangjie , Khattak Muhammad Sualeh . Intellectual capital, financial resources, and green supply chain management as predictors of financial and environmental performance. . | Environmental science and pollution research international , 2021 , 28 (16) , 19755-19767 . |
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Abstract ：
Improving energy efficiency is an effective way to address the issues of economic development, energy saving and emissions reduction. For any important industries it is therefore necessary to measure energy efficiency and set a practical target for it. In this paper, we use CCR, SBM and energy intensity to measure the energy efficiency of the paper industries of 22 EU countries. Results indicate that the SBM and CCR efficiency value is more meaningful for policy makers than that of energy intensity, as measurement results of energy intensity deviate from reality and economic efficiency. The CCR and SBM have roughly the same fluctuation trends and the average SBM energy efficiency value is 0.71, always 10 percent lower than CCR model, as it takes simultaneous account of both the optimal input-output and has more discriminatory power in efficiency measurement. Furthermore, EU policy makers could improve energy efficiency by raising energy prices. As for the 2030 EU target of energy saving and emission reduction, the EU should pay more attention to five major paper producers: Finland, Sweden, Germany, the United Kingdom and Italy.
Keyword ：
2030 target 2030 target SBM SBM EU paper industry EU paper industry TFEE TFEE energy saving energy saving emission reduction emission reduction
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| GB/T 7714 | Li, Shuangjie , Li, Li , Wang, Liming . 2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry [J]. | ENERGIES , 2021 , 14 (1) . |
| MLA | Li, Shuangjie et al. "2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry" . | ENERGIES 14 . 1 (2021) . |
| APA | Li, Shuangjie , Li, Li , Wang, Liming . 2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry . | ENERGIES , 2021 , 14 (1) . |
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Abstract ：
Energy efficiency is crucial to the 2030 UN Sustainable Development Goals (SDGs), but its widely measured indicator, energy intensity, is still insufficient. For this reason, in 2006, total factor energy efficiency (TFEE) was proposed with capital, labor, and energy as inputs and GDP as the desirable output. The later TFEE approach further incorporated pollution as the undesirable output. However, it is problematic to regard GDP (the total value of final products) as the desirable output, because GDP does not include the intermediate consumption, which accounts for a large part of the production activities and may even be larger than the value of GDP. GDP is more suitable for measuring distribution, while VO (value of output) is more appropriate for sustainable production analysis. Therefore, we propose a VO TFEE approach that takes VO as the desirable output instead and correspondingly incorporates the other intermediate materials and services except energy into inputs. Finally, the empirical analysis of the textile industry of EU member states during 2011-2017 indicates that the VO TFEE approach is more stable and convergent in measuring energy efficiency, and is more suitable for helping policymakers achieve the SDGs of energy saving, emissions reduction, and sustainable economic development.
Keyword ：
Sustainable Development Goals Sustainable Development Goals System of National Accounts System of National Accounts undesirable output undesirable output VO TFEE model VO TFEE model value of output value of output
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| GB/T 7714 | Li, Shuangjie , Diao, Hongyu , Wang, Liming et al. Energy Efficiency Measurement: A VO TFEE Approach and Its Application [J]. | SUSTAINABILITY , 2021 , 13 (4) . |
| MLA | Li, Shuangjie et al. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application" . | SUSTAINABILITY 13 . 4 (2021) . |
| APA | Li, Shuangjie , Diao, Hongyu , Wang, Liming , Li, Chunqi . Energy Efficiency Measurement: A VO TFEE Approach and Its Application . | SUSTAINABILITY , 2021 , 13 (4) . |
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