Six SCI or SSCI-indexed papers have been published by the research team headed by Professor Aijun Li at The Center for Economic Research, Shandong University in 2022. The detail about publications are as follows.
（1）Measuring efficiency and technology inequality of China's electricity generation and transmission system: A new approach of network Data Envelopment Analysis prospect cross-efficiency models. Energy. 2022, 246, 123274. (SCI，IF：7.147，Top journal)
Abstract：In the power sector, electricity transmission is highly linked with electricity generation. However, quite limited number of studies have considered the combined performance of electricity generation and transmission system. To do so, this study adopts network DEA models. To the best of our knowledge, the existing network DEA cross-efficiency models may suffer from one important drawback, since these models generally assume that DMUs are completely rational and neglect the potential effects of DMUs' risk attitudes that may play an important role in the evaluation process. To relax this assumption, this study proposes a new type of network DEA prospect cross-efficiency models. To our knowledge, such work cannot be found in the existing studies. Empirically, this study focuses on the case of China's electricity generation-transmission system from 2010 to 2019. The main conclusions are summarized as follows. First, China succeeded in achieving an overall improvement with an annual growth rate of 2.84% during the analysis period. Second, within-group 2 was the most important driving factor affecting technology diffusion, accounting for 63.32% of the overall Gini coefficient. Finally, significant method heterogeneity has been confirmed among alternative DEA models, implying that method selection is important for modelers to perform empirical analysis.
（2）A new intermediate network data envelopment analysis model for evaluating China's sustainability. Journal of Cleaner Production. 2022, 356, 131845. (SCI，IF：9.297，Top journal)
Abstract：The existing studies on network data envelopment analysis (DEA) generally adopt radial or non-radial approaches to capture internal structures of production systems. To our knowledge, however, no study has utilized the intermediate approach to construct network DEA models. To fill the research gap, this study proposes a new intermediate network DEA model, by combining the intermediate approach with network DEA. Our new model has several methodological advantages. In addition, sustainability involves a three-stage system (i.e., economic growth, environmental protection and health promotion). Towards the holistic system, quite limited studies have evaluated the performance. Following this research line, our study proposes a new methodological framework consisting of intermediate network DEA, rank sum test, Gini coefficient and decomposition analysis. By adopting this framework, this study examines multi-dimensional efficiency measures, evaluates technology inequality measures and identifies technology diffusion barriers. Empirically, the current study considers the sustainability system of Chinese provinces from 2009 to 2017. The main findings are as follows. First, China has succeeded in realizing a general improvement in overall efficiency scores. Second, significant differences have been statistically confirmed among three stages. Third, convergent trends have been confirmed across stage efficiency measures. Finally, cross-group Gini coefficient accounts for the largest part in explaining technology inequality, where the stage of environmental protection plays an important role.
（3）Technology Inequality, Marginal Rate of Transformation and Rate of Substitution measurement by DEA: The Sustainability Improvement of Passenger Cars. Journal of Cleaner Production. In press. (SCI，IF：9.297，Top journal)
Abstract：To the best of our knowledge, the previous Data Envelopment Analysis studies on passenger-car sustainability have neglected to measure technology-based measures, technology inequality, and technology diffusion barriers. To fill this research gap, this study proposes a new framework consisting of Data Envelopment Analysis, K-means clustering method, Gini coefficient, and the group-based decomposition method. Adopting these methods, this study examines the Marginal Rate of Transformation and the Rate of Substitution, identifies both desirable congestion (or eco-innovation) and undesirable congestion, evaluates technology inequality, and explores the main barriers to technology diffusion. Empirically, we assess new passenger cars released in the United States in 2020. The main conclusions are summarized as follows: First, under managerial disposability, the generally negative Marginal Rate of Transformation and Rate of Substitution across passenger cars suggests that the majority of car manufacturers are environmentally conscious. This outcome is partly the result of the minimum environmental standards set for car manufacturers. Second, the majority of passenger cars displayed the possibility of strong desirable congestion (clean-technology innovation) and no undesirable congestion simultaneously. The majority of passenger cars need to decrease carbon dioxide emissions along with an increase in fuel consumption efficiency (miles per gallon). This finding indicates that regulatory strategies have been mostly effective at directing eco-technological innovation toward mitigating a significant source of climate change. Finally, technology inequality was driven by both cross-group and within-group inequalities. Moreover, considerable heterogeneity existed in the within-group decomposition of the overall efficiency Gini coefficient result.
（4）Measuring environmental efficiency and technology inequality of China’s power sector: methodological comparisons among data envelopment analysis, free disposable hull, and super free disposable hull models. 2022. Environmental Science and Pollution Research. （IF：4.958）
Abstract：China’s power sector has received great research attention because of its large energy consumption and CO2 emissions. This study assesses the environmental efficiency and technology inequality of China’s power sector from 2008 to 2017. Methodologically, this study proposes a non-radial FDH (free disposable hull) model and a super non-radial FDH model. The non-radial FDH model relaxes the convex assumption and captures all inefficiencies of inputs, desirable output and undesirable output. The super non-radial model is capable of discriminating efficient power sectors and always has feasible solutions. We also compare their performance with the non-radial data envelopment analysis (DEA) model. The main conclusions are summarized as follows: First, the environmental efficiency of China’s power sector has experienced steady growth; the power sectors in the east region outperform those in other regions. Second, the proposed FDH models are more applicable and reliable than the non-radial DEA model in efficiency measurement of China’s power sector, due to the indivisibility of labor. Third, there has been growing technology inequality and the main driving factor determining technology inequality is the inter-region efficiency Gini coefficient. To improve environmental efficiency and eliminate technology inequality, the government should mainly solve the issue of excessive labor input and establish a free technology market for technology trading.
（5）Measuring technology inequality across African countries using the concept of efficiency Gini coefficient. Environment, Development and Sustainability. 2022. (SCI, IF：3.219)
Abstract：In the context of global climate change, much hope is placed in technological progress's ability to address environmental problems. However, the persistence of technology inequality across countries undermines environmental technology innovation’s contribution to environmental issues. In such a context, this paper introduces a new approach that combines Data Envelopment Analysis (DEA) with the Gini coefficient to gauge technology inequality. Additionally, decomposition analysis is adopted to identify the driving factors affecting technology diffusion. Empirically, the proposed approach is applied to 49 African countries from 2000 to 2017. The results of our study show that, although the unified efficiency of African countries improved slightly during the study period, there is still much room for improvement in terms of economic prosperity and environmental performance. Secondly, there is group heterogeneity between two groups of African countries (low-efficiency group and high-efficiency group) under both managerial and natural disposability. Thirdly, the inequality decomposition revealed that cross-group inequality is the source of group heterogeneity and the main barrier to technology diffusion, followed by within-group inequality. Finally, environmental technology progress exhibits a low contribution to enhancing sustainability in Africa due to technological inequality persistence. In future, it would be quite meaningful to perform sector-level analysis, which could provide more detailed information on sustainability.
（6）A modified super-efficiency network data envelopment analysis: Assessing regional sustainability performance in China. Socio-Economic Planning Sciences. 2022. (SSCI&SCI, IF：4.923)
Abstract：The super-efficiency technique aims to improve the discriminating power of data envelopment analysis (DEA) through re-evaluation after excluding the evaluated object from the reference set. However, the super-efficiency radial network DEA with undesirable production variables faces the infeasibility problem as the traditional DEA. To solve this issue, this paper detects one new origin of infeasibility in network DEA not existing in traditional DEA and provides the necessary and sufficient conditions of infeasibility occurrence. Then, a modified super-efficiency radial network DEA is developed without infeasibility. We apply the modified model to assess the regional sustainability performance in China from 2009 to 2017. Considering the internal connectivity and influences among the economic, environmental, and social dimensions of sustainability, we construct a three-stage network system, i.e., economic growth (EG), waste disposal (WD), and health protection (HP) subsystems. The results show that the regional sustainability performance of China was on a downward trend until 2015 but has improved significantly since then. Besides, the status quo of a regional disparity in sustainability performance is confirmed. The results suggest that the eastern region remains the leader in promoting the regional sustainability of China, the central and western regions are trying to catch up with it, and the northeast region still needs more support from the government to keep pace with the coordinated development of China.