Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach

As significant strategic players in China's economy, high-tech industries need to evaluate and analyze the technological innovation activities from a system point of view to understand and improve their technological innovation efficiency and, thereby, promote their development. Different high-tech industries have different characteristics and thus benefit from different industrial development policies. However, few studies to date have discussed this issue from a systematic perspective. In this study, technological innovation activities are divided into a research and development (R&D) stage and a commercialization stage. A high-tech industrial evaluation framework of technological innovation efficiency based on two-stage network data envelopment analysis (DEA) is constructed with shared inputs, additional intermediate inputs, and free intermediate outputs. Our empirical results indicate that the overall efficiency of most industries is relatively low and the differences between the five high-tech industries (i.e., sub-sectors) we examined are large. The Spearman correlation shows that overall efficiency and R&D efficiency are more correlated than overall efficiency and commercialization efficiency. Additionally, R&D has better average efficiency. The sub-sector with the highest average efficiency is computers and office equipment, and the one with the lowest average efficiency is medicines. These findings indicate the inadequacy but potential for breakthroughs in the evolution of high-tech industries in China. The analysis proves that it is necessary to create different industrial policies to encourage effective progress in certain high-tech industries, and some guidelines for doing so are provided.     

技术创新项目风险分析与综合评价

文章分析了企业技术创新项目的风险因素,在此基础上设置了风险评价指标体系,建立了模糊评判模型,对企业技术创新风险进行了科学评价,并能定量地衡量企业关于某个项目的技术创新风险大小,为企业技术创新决策和采取风险控制措施提供了依据。     

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.     

企业技术创新风险与防范

技术创新是企业实现科技进步、增强核心竞争力的根本源泉,是企业生存与发展的重要基础。但是,技术创新与风险共存,创新风险已成为阻碍企业技术创新的重要因素之一。文章通过对技术创新风险的类型和成因进行分析与探讨,提出了企业防范技术创新风险的应对措施。     

基于GDP水平的区域技术创新效率测度

区域技术创新效率是区域发展的动力,是衡量区域技术创新运营机制有效程度的重要标准,反应一个地区的研发水平和投入资源的利用率。通过建立区域技术创新效率指标体系,根据2009年我国30个省、市、自治区人均GDP构造系数矩阵,确定区域间的竞合关系;应用带有系数矩阵的交叉效率模型对2009年我国30个省、市、自治区的技术创新效率进行测度得出交叉效率矩阵,最后应用熵值法确定权重并得出最终效率。实证结果表明全部30个地区的技术创新效率均具有提升空间,该方法可以对所有区域进行充分排序且与传统仁慈型和进取型交叉效率方法相比更符合实际情况。     

基于DEA模型的企业员工绩效考评研究

利用数据包络分析(DEA)方法对企业员工进行绩效考评,目的是真实、客观地反映员工的工作表现。本文提出运用只有输出(输入)和二次相对有效性的DEA模型对企业员工进行静态与动态的绩效考评,并结合实例进行实证研究,为人力资源管理提供了有价值的方法。     

湖南省中小企业技术创新模式选择

文章从分析湖南省中小企业技术创新的问题和有利因素出发,探讨了中小企业技术创新模式选择。     

Are all Scales Optimal in DEA? Theory and Empirical Evidence

Policy recommendations concerning optimal scale of production units may have serious implications for the restructuring of a sector. The piecewise linear frontier production function framework (DEA) is becoming the most popular one for assessing not only technical efficiency of operations, but also for scale efficiency and calculation of optimal scale sizes. The main purpose of the present study is to investigate if neoclassical production theory gives any guidance as to the nature of scale properties in the DEA model, and empirically explore such properties. Theoretical results indicate that the DEA model may have more irregular properties than usually assumed in neoclassical production theory, concerning shape of optimal scale curves and the M-locus. The empirical results indicate that optimal scale may be found over almost the entire size variations in outputs and inputs, thus making policy recommendations about efficient scale difficult. It seems necessary to establish the nature of optimal scale before any practical conclusions can be drawn. Proposals for indexes characterizing the nature of optimal scale are provided.     

论科技信息机构在中小企业技术创新中的作用

文章简要分析了阻碍我国中小企业技术创新的因素,列举了科技信息机构为中小企业提供技术创新服务所具有的优势,并详细阐述了科技信息机构在促进中小企业技术创新中的支撑与引领作用。     

A combination of QFD and imprecise DEA with enhanced Russell graph measure: A case study in healthcare

Quality function deployment (QFD) is a proven tool for process and product development, which translates the voice of customer (VoC) into engineering characteristics (EC), and prioritizes the ECs, in terms of customer's requirements. Traditionally, QFD rates the design requirements (DRs) with respect to customer needs, and aggregates the ratings to get relative importance scores of DRs. An increasing number of studies stress on the need to incorporate additional factors, such as cost and environmental impact, while calculating the relative importance of DRs. However, there is a paucity of methodologies for deriving the relative importance of DRs when several additional factors are considered. Ramanathan and Yunfeng [43] proved that the relative importance values computed by data envelopment analysis (DEA) coincide with traditional QFD calculations when only the ratings of DRs with respect to customer needs are considered, and only one additional factor, namely cost, is considered. Also, Kamvysi et al. [27] discussed the combination of QFD with analytic hierarchy process–analytic network process (AHP–ANP) and DEAHP–DEANP methodologies to prioritize selection criteria in a service context. The objective of this paper is to propose a QFD–imprecise enhanced Russell graph measure (QFD–IERGM) for incorporating the criteria such as cost of services and implementation easiness in QFD. Proposed model is applied in an Iranian hospital.     

The impact of oil prices and the financial market on cost efficiency in the insurance and Takaful sectors: Evidence from a stochastic frontier analysis

The Gulf Cooperation Council’s (GCC) insurance industry, including conventional insurance and Takaful, has witnessed remarkable growth during the last decade. However, the economies of this region rely on oil as the primary stream of revenue and lack development in financial markets. This could affect the insurance industry. For this reason, this paper examines the impact of oil prices and the financial market on the cost efficiency of the insurance and Takaful sectors in GCC countries using a stochastic frontier cost function with data from 2009–2016. The results show that the relationship between oil prices and efficiency changes from positive to negative when the prices increase, whereas the relationship between the financial market and efficiency is negative. No clear evidence of the impact of oil prices on efficiency arises from the differences between conventional insurance and Takaful. However, there are differences regarding the financial market, with a negative impact on conventional insurance and a positive one on the Takaful business. The results of this study have implications for regulators and management. The Takaful industry is rapidly growing compared to conventional insurance in the GCC and, therefore, the financial market may have added benefits for the GCC region. However, caution is required in relation to the impact of the financial market on conventional insurance. Furthermore, management may require the development of strategies to deal with the nature of GCC economies to avoid shocks to oil prices.     

Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification

Since the 1990s, the Akaike Information Criterion (AIC) and its various modifications/extensions, including BIC, have found wide applicability in econometrics as objective procedures that can be used to select parsimonious statistical models. The aim of this paper is to argue that these model selection procedures invariably give rise to unreliable inferences, primarily because their choice within a prespecified family of models (a) assumes away the problem of model validation, and (b) ignores the relevant error probabilities. This paper argues for a return to the original statistical model specification problem, as envisaged by Fisher (1922), where the task is understood as one of selecting a statistical model in such a way as to render the particular data a truly typical realization of the stochastic process specified by the model in question. The key to addressing this problem is to replace trading goodness-of-fit against parsimony with statistical adequacy as the sole criterion for when a fitted model accounts for the regularities in the data.