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This paper proposes a lexicographic decomposition strategy for the two-stage network DEA model. Instead of assigning a priority over the two component stages, our proposed approach employs a lexicographic algorithm in such a way that the system efficiencies of the DMUs are lexicographically computed for each of their possible sequences while maintaining the efficiencies of those units already investigated unchanged. In particular, the system efficiency and the two component efficiencies can be uniquely determined under our proposed decomposition approach. Besides, prior to implement the proposed lexicographic evaluation procedure, we also highlight a potential infeasibility problem arising from the normalization constraint, and develop a modified iterative approach that facilitates us to guarantee a feasible search procedure. Finally, we use a numerical example to illustrate the effectiveness of the proposed approach, and conduct an empirical study to analyze China's regional high-tech innovation systems for the period of 12th Five-Year Plan (2011–2015). [ABSTRACT FROM AUTHOR]

China’s electric utility industry is among the country’s main polluters. Increasing the efficiency of China’s power supply chain is therefore essential to promote more environmentally sustainable power generation. This paper assesses the performance of China’s regional power supply chains that include electric utilities and power grid companies. We rely on the notion of sustainable supply chains to propose a multi-stage model that accounts for negative externalities such as harmful emissions, power transmission line loss, and increased mortality caused by pollution. Different from the existing studies of power supply chains, our approach is based on the exponential directional distance function defined with respect to a multiplicative production technology that can help mitigate the impact of data outliers. We use a panel of 30 Chinese provinces covering the period 2008–2018 to measure the efficiency improvement potential within regional supply chains and assess the efficiency-enhancing role of digital innovation. Our results provide evidence of considerable regional disparities and suggest that China’s eastern provinces outperform other regions due to the relatively advanced state of their technology. Furthermore, we demonstrate that the efficiency improvement potential from better management or technological innovation remains significant across the majority of provinces. Finally, our results provide evidence of a significant role of digitalization in promoting the efficiency of power supply chains. Our findings offer important perspectives on the strategies policymakers can use to promote sustainable performance of electric utilities and power grid companies. [ABSTRACT FROM AUTHOR]

The environmental issue has attracted ever-increasing attention from governments and academics in recent years. Environmental performance analysis is widely considered a crucial and useful tool for effectively protecting the environment and developing a sustainable society. Many analytical techniques have been used to assess carbon emission performance, among which data envelopment analysis (DEA) is prominent. However, few previous DEA-related carbon emission performance studies recognize that the total amount of carbon dioxide emissions is limited to a specific level by authorities; ignoring this fixed-sum requirement may lead to distortions and deviations in empirical results. This paper proposes an alternative Malmquist DEA approach for evaluating the carbon emission performance while considering fixed-sum undesirable outputs. For this purpose, we develop a generalized equilibrium efficient frontier DEA model with fixed-sum undesirable outputs and combine the model with the Malmquist productivity index (MPI). The proposed approach is applied to assess the carbon emission performance of 30 provincial regions in China from 2009 to 2015. Then we provide analytical results and policy suggestions regarding the provincial carbon emission performance in China. [ABSTRACT FROM AUTHOR]

This study constructs an index of humanitarian labor efficiency to measure labor utilization based on a factor-specific data envelopment analysis model. Compared with the traditional labor productivity index, humanitarian labor efficiency is a more reliable and comprehensive measure; it not only excludes the contribution of non-labor input but also considers the undesirable output, such as accidental deaths. The results show that China's humanitarian labor efficiency is low, ranging from 0.3 to 0.7, and it should be improved further. Unlike labor productivity, humanitarian labor efficiency did not increase markedly between 2007 and 2017. Further analysis revealed that pure labor efficiency declined while pure humanitarian efficiency increased for this period, which offset each other. Tobit regression shows that industrial structure has a significant influence on humanitarian labor efficiency. Baumol's disease, caused by the growing tertiary industry, may result in the decline of labor utilization efficiency in China. This study presents suggestions on how to deal with Baumol's disease. [ABSTRACT FROM AUTHOR]

While humanitarian efforts are critical for assisting those affected by natural disasters, it is also essential for those affected by poverty, such as China's rural poor. In this regard, China introduced the rural minimum living security system to provide humanitarian relief to its rural poor. The aim of this study is to explore the influencing factors and efficiency of humanitarian supply chains funds using rural minimum living security funds (RMLSF) as an example. Based on data from 31 provinces (autonomous regions and municipalities) in China from 2007 to 2016, this study employs the logarithmic mean Divisia index approach to decompose the RMLSF and investigates the contributions of seven factors on the change therein. This study also uses the three-stage data envelopment analysis method to assess the poverty reduction efficiency of RMLSF. The results show that the economic development level, the extent to which minimum living security funds are tilted toward rural areas, and the fiscal expenditure scale are the three main factors for the increase in RMLSF. Moreover, the technical efficiency in most provinces and the average technical efficiency in the eastern and central regions are underestimated due to external ambient factors, whereas the average technical efficiency in the western region is overestimated. These results provide a basis for increasing the scale and efficiency of RMLSF. [ABSTRACT FROM AUTHOR]

The purpose of this contribution is to compute the popular Malmquist productivity index while adding a component representing plant capacity utilisation. In particular, this is—to the best of our knowledge—the first empirical application estimating both input- and output-oriented Malmquist productivity indices in conjunction with the corresponding input- and output-oriented plant capacity utilisation measures. Our empirical application focuses on a provincial data set of tourism activities in China over the period 2008–2016. The results contain the output- and input-oriented Malmquist productivity indices, some Spearman rank correlations between both, a t-test whether these indices differ from unity, and some bootstrapping analysis. [ABSTRACT FROM AUTHOR]