Dynamically evaluating the comprehensive efficiency of technological innovation and low-carbon economy in China's industrial sectors

Technological innovation and low-carbon economy are significant for the high-quality development of China's industrial sectors. However, few scholars combine the two stages closely and discuss their coordinated development. This paper establishes an evaluation index system of technological innovation and low-carbon economy in China's industrial sectors. The technological innovation efficiency, low-carbon economy efficiency, and comprehensive efficiency of technological innovation and low-carbon economy are dynamically investigated by the two-stage data envelopment analysis (DEA) model and the DEA window analysis with 35 subsectors panel data during 1996–2018. The inter-industrial differences in the technological innovation efficiency and low-carbon economy efficiency are considered, and the influencing factors of the comprehensive efficiency of technological innovation and low-carbon economy are studied by the bootstrap truncation regression. The results show that: (1) The development of the technological innovation and low-carbon economy is uncoordinated, and the low-carbon economy efficiency needs improvement; (2) There is heterogeneous of the technological innovation efficiency and low-carbon economy efficiency in the 35 subsectors; (3) The density of science and technology institutions, and the average enterprises scale are positive to the comprehensive efficiency of technological innovation and low-carbon economy, while excessive reliance on technology introduction has a negative impaction. The corresponding suggestions are provided for promoting technological innovation efficiency and low-carbon economy efficiency of industrial sectors.     

Operating efficiency in Chinese universities: An extended two-stage network DEA approach

The result shows that it accepts the null hypothesis. Namely, there is no significant difference in the operating efficiency of universities in different regions. That is to say, although the efficiency of the central and western universities is slightly better than that of the eastern universities in terms of the average efficiency, there is no significant efficiency difference among the eastern, central, and western regions statistically. Therefore, it shows a balanced development trend for the efficiency of universities in different regions.     

Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis

Considering the interrelationships between periods and the influences of non-operational factors, a new framework based generalized three-stage DEA model, grey relational analysis theory and disparity disassembly model is proposed in this paper. Then, we measure the technical efficiency, scale efficiency, and pure technical efficiency of innovation in China's semiconductor industry between 2009 and 2014. In addition, we conducted projection analysis of the inputs to innovation and the disparities analysis in innovation efficiency across the industrial chain and within each segment. The results of our analyses reveal four key findings. The overall innovation efficiency of China's semiconductor industry is increasing; however, each segment of the industrial chain had different trends and different levels of innovation efficiency. All segments show a consistently upward trend except for package testing, which dipped in 2012 due to the time lag between the inputs and outputs associated with major technological advancements. The most efficient innovation is occurring in design and package testing, followed by manufacturing, materials, and equipment, in that order. Low levels of innovation efficiency were found to be the most significant factor restricting further improvement in the design, manufacturing, and equipment segments of the industrial chain. But the opposite is true for the package testing segment, where pure technical efficiency is the main factor. A range of redundancies in input were found across the industrial chain, mostly in manufacturing and equipment. These two segments are capital-intensive and characterized by a high level of technical complexity coupled with a long research cycle. The disparities in innovation efficiency in and between the segments decreased over the period. However, interestingly, the main disparities were found among the enterprises within each segment, which we attribute to the Chinese government's concerted efforts to support particular companies. Package testing and manufacturing had the highest levels of disparity due to relatively high agglomeration of these two segments. The materials segment had the lowest disparity, with equipment and design falling somewhere in-between.     

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

Research performance evaluation of Chinese university: A non-homogeneous network DEA approach

Performance evaluation for universities or research institutions has become a hot topic in recent years. However, the previous works rarely investigate the multiple departments’ performance of a university, and especially, none of them consider the non-homogeneity among the universities’ departments. In this paper, we develop data envelopment analysis (DEA) models to evaluate the performance of general non-homogeneous decision making units (DMUs) with two-stage network structures and then apply them to a university in China. Specifically, the first stage is faculty research process, and the second stage is student research process. We first spit each DMU (i.e. department) into a combination of several mutually exclusive maximal input subgroups and output subgroups in terms of their homogeneity in both stages. Then an additive DEA model is proposed to evaluate the performance of the overall efficiency of the non-homogeneous DMUs with two-stage network structure. By analyzing the empirical results, some implications are provided to support the university to promote the research performance of each department as well as the whole university.     

Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain"

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

基于DEA模型的我国商业银行效率的实证研究

以我国9家已上市的股份制商业银行为研究对象,基于各银行2006年的统计数据,运用数据包络分析方法,研究他们的投入产出效率值。并用该模型的测算结果与已有文献中2002年的银行效率排名作对比。经研究表明,股份制商业银行的效率已经有了很大改观,股份制改革对国有商业银行经营效率有一定的推动作用;政府也利用内部调整以及放松管制等手段,给予国有商业银行很大帮助。本研究的重要意义在于,为迅速有效得提高我国商业银行的经营效率,达到国际一流的银行业水平提供借鉴和参考。     

Efficiency evaluation of China's high-tech industry with a multi-activity network data envelopment analysis approach

This paper employs a Russell multi-activity network DEA model and divides the overall innovation process into the upstream Research and Development (R&D) process and the downstream commercialization process to appraise the innovation performance of China's high-tech industries from 2009 to 2013. This model can deal with the problems of intermediates, shared inputs and slack-based measure in a unified framework, and the result can provide policy makers with process-specific information on how to improve the innovation performance of China's high-tech industries. The main findings are presented as follows. First, the overall efficiency of China's high-tech industries still remains at a low level, which has its roots mainly in commercialization inefficiencies other than R&D inefficiencies. Second, for most provinces, their R&D efficiencies do not match up with their commercialization efficiencies. Finally, the innovative activities of China's high-tech industries should be driven by the market demand -oriented for the improvement of innovation efficiency.     

基于三阶段DEA模型的中国出版印刷业效率评价北大核心

采用省域面板数据,运用三阶段DEA模型对中国31个省市区(港澳台除外)出版印刷业的投入产出效率进行评价。研究发现:文化产业的发展能够提高出版印刷业的资产利用效率,降低资本投入冗余;中国出版印刷业的综合技术效率值不高,但呈现逐年增长的趋势,同时存在着明显的省际差异,西部地区与中东部地区的差异巨大,主要表现为规模效率的差异;出版印刷业的纯技术效率较高、规模效率偏低,企业规模弱小与行业规模不足成为制约出版印刷业投入产出效率的主要因素。为实现中国出版印刷业的高质量发展,应充分利用有利的外部因素,挖掘效率潜力;扩大印刷出版企业规模,提升行业规模效益;考虑效率区域差异,采取有针对性的策略。     

基于DEA的北京市高技术产业R＆D效率比较分析

本文运用DEA模型全面测算了北京市高技术产业1996—2010年间R＆D的生产前沿面效率、综合技术效率、纯技术效率以及规模效率,对规模收益变化和投入产出的冗余与不足进行了具体分析,并针对北京市政府如何提高高技术产业的R＆D效率提出了建议。     

Research efficiency analysis of China's university faculty members: A modified meta-frontier DEA approach

Traditionally, data envelopment analysis (DEA) requires all decision-making units (DMUs) to have similar characteristics and experiences within the same external conditions. In many cases, this assumption fails to hold, and thus, difficulties will be encountered to some extent when measuring efficiency with a standard DEA model. Ideally, the performance of DMUs with different characteristics could be examined using the DEA meta-frontier framework. However, some of these DMUs are mixed-type DMUs that may affiliate with more than one group. Furthermore, the total number of observations of these mixed-type DMUs is limited. This is one of the common problems when studies focus on faculty research performance in higher education institutions. In general, a faculty member is affiliated with a certain department, and if the departmental assessment policy is not suitable for faculty members who are involved in interdisciplinary research, their performance could be underestimated. Therefore, the proposed model is an extension of the DEA meta-frontier framework that can assess the performance of mixed-type DMUs by constructing the reference set without the same type of DMUs. In this paper, the scientific research efficiency of faculty members at the Inner Mongolia University is used as an example to provide a better understanding of the proposed model. The proposed model is intended to provide a fair and balanced performance assessment method that reflects actual performance, especially for mixed-type DMUs.     

Estimating the multi-period efficiency of high-tech research institutes of the Chinese Academy of Sciences: A dynamic slacks-based measure

Although a large amount of past research has studied the measurement of institutional research and development (R&D) efficiency, there has been limited dynamic empirical investigation of this topic. This study differs from previous studies in its consideration of R&D capital stock, which is defined as a carry-over activity between two consecutive periods. To further test high-tech institutes’ R&D performance in the pre-reform and post-reform periods, we evaluate a panel of 29 high-tech institutes of the Chinese Academy of Sciences (CAS) for 2011–2017 with a dynamic slacks-based measure. (a) The empirical value of the average overall efficiency is 0.5559, and the clustering analysis shows that institutes operating above the average overall efficiency level follow an increasing and then decreasing trend, while those operating below the average overall efficiency level follow a decreasing and then increasing trend. (b) The efficiency of low-performing institutes has increased from 0.2259 in the pre-reform period to 0.2727 in the post-reform period, which does not reflect the efficiency improvements of high-performing institutes. (c) High-tech institutes selected as pilot institutes have an average efficiency level of 0.6524, which is higher than that of non-pilot institutes (0.4765), indicating the benchmarking effect of pilots. (d) The types of pilot institutes can be ordered as follows: feature institutes > centres of excellence > innovative academies. (e) The total-factor input efficiency level has decreased in the post-reform period. Only the total-factor efficiency of high-quality papers has increased in the post-reform period (by 0.0094).     

Unveiling the endogeneity between social-welfare and labor efficiency: Two-stage NDEA neural network approach

This paper estimates intersectoral labor efficiencies and its covariances in Brazil from 2003 to 2016 using a two-stage neural network model. It investigates whether there is a positive relationship between education and productivity. At the first stage, a static Markov chain regression provides labor quantitative efficiency (volume) and labor value efficiency (value added). The second stage runs a dynamic regression model between each estimated efficiency and the social contextual variables to unveil endogeneities from covariances among the variables set. Strong covariances are found between the efficiencies and fertility rate, suggesting that there is a relevant gap between the productive sector and worker qualification, leading to lower levels of efficiency in Brazil, as shown in the theoretical model. The economy is unable to allocate efficiently the stock of qualified workers.     

Assessing efficiency and innovation in the 3PL industry: an empirical analysis

ABSTRACT

The Third-party Logistics (3PL) industry is facing both important growth rates and increasing competitive pressure. 3PL providers are required to continuously sustain a more and more competitive cost structure (i.e. efficiency) and develop capabilities to improve their services (i.e. innovation); hence, the evaluation of these key success factors is considered a key issue. This paper develops a quantitative analysis of 71 Italian 3PL providers by using Data Envelopment Analysis to jointly assess efficiency and innovation. Furthermore, through a case study research, it corroborates the quantitative results by investigating the strategies of best-in-class companies. Results allowed identifying 13 3PL providers as efficiency leaders and 6 as leaders from both the efficiency and the innovation side. Their input composition indicates a diversification of the business models. A breakdown of the analysis by size and industry focus, along with empirical evidence on the strategies enhancing efficiency and innovation, is also provided.     

New evidence on the efficiency of Italian airports: A bootstrapped DEA analysis

A bootstrapped DEA procedure is used to estimate technical efficiency of 18 Italian airports during the period 2000-2004. Departing from previous studies, we separate the efficiency related to ability to manage airside activities (operational) from that related to the management of all business activities (financial). In general, Italian airports operate at poor levels of efficiency, with slightly better performance in terms of their financial activities. In the current study, selected intrinsic and environmental characteristics are considered as possible drivers of Italian airport performance. In particular, we found that: (i) the airport dimension does not allows for operational efficiency advantages, (ii) on the other hand, the airport dimension allows for financial efficiency advantages for the case of hubs and disadvantages for the case of the smallest airports (iii) the type(s) of concession agreement(s) might be considered as important source of technical efficiency differentials for those airports running marginal commercial activities; (iv) the introduction of a dual-till price cap regulation might create incentives which lead to the increase of financial efficiency at the detriment of the operational performance. Lastly, the development of a second hub (Milano Malpensa), has negatively affected the performance of the country’s national hub (Roma Fiumicino).     

Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis

This paper proposes a new framework based on the combination of the dynamic DEA, meta-frontier analysis theory, and truncated regression model, and then focuses on the efficiency evaluation of regional high-tech industries in China. For all of the overall technical efficiency, technical efficiency, and scale efficiency scores, the east area is always in the lead, with the central and west areas obviously lagging behind. The eastern area has the highest technology level, whereas the west and central areas fall behind in turn. However, the meta-technology ratio of the west area has rapidly increased and presents a trend of catching up with the east. The variables of GRP per capital, total exports and imports, highway mileage per capita, and ratio of tertiary industry to GRP have positive relationships with technical efficiency, and the time trend exhibits a negative coefficient.     

Measuring the impact of restructuring and country-specific factors on the efficiency of post-crisis East Asian banking systems: Integrating DEA with SFA

This paper investigates the relationship between post-crisis bank restructuring, country-specific conditions and bank efficiency in Asian countries from 1997 to 2001 using an approach that integrates data envelopment analysis and stochastic frontier analysis. We focus on restructuring measures related to bank ownership. The results indicate that although domestic mergers produce more efficient banks, overall, restructuring does not lead to more efficient banking systems. Banking system inefficiencies are mostly attributed to country-specific conditions, particularly, high interest rates, concentrated markets and economic development.     

基于DEA模型的房地产上市企业经营效率研究

本文选取了在沪深两市的A股上市的14家房地产企业2016-2020年的年报数据,运用DEA方法研究了房地产企业的经营效率。本文通过分析发现:房地产经营效率整体水平一般,无论是整体经营水平、技术管理水平,还是规模大小的适宜程度都存在一定的提升空间。     

京津冀区域创新网络建设的理论基础与现状分析

随着京津冀一体化上升为重大国家战略,京津冀三地协同发展的步伐不断加快。实践表明京津冀一体化发展的根本出路在于三地协同创新,共同建设完善的跨区域创新网络。本文旨在构建跨区域创新网络的理论体系,并以此体系来分析京津冀区域创新网络的建设现状与制约因素。