基于DEA模型的河南省物流产业效率评价

以物流业投资的固定资产、物流业从业人数作为投入指标,以物流业的增加值、货物周转量作为产出指标,构建了河南省物流产业效率评价指标体系,运用DEA效率评价模型对河南2004-2012年物流系统的相对有效性、技术有效性、规模效益有效性和超效率进行分析,结果显示,河南物流投入、产出总体有效性为44%,在此结果基础上分析了物流产业效率制约因素,并提出了物流产业效率提升要点及提升策略。     

Identifying “best” applicants in recruiting using data envelopment analysis

Selecting the most promising candidates to fill an open position can be a difficult task when there are many applicants. Each applicant achieves certain performance levels in various categories and the resulting information can be overwhelming. We demonstrate how data envelopment analysis (DEA) can be used as a fair screening and sorting tool to support the candidate selection and decision-making process. Each applicant is viewed as an entity with multiple achievements. Without any a priori preference or information on the multiple achievements, DEA identifies the non-dominated solutions, which, in our case, represent the “best” candidates. A DEA-aided recruiting process was developed that (1) determines the performance levels of the “best” candidates relative to other applicants; (2) evaluates the degree of excellence of “best” candidates’ performance; (3) forms consistent tradeoff information on multiple recruiting criteria among search committee members, and, then, (4) clusters the applicants.     

中国主要工业省区能源效率分析：1990～2006年

本文基于DEA方法,计算了中国13个主要工业省区1990～2006年的能源效率。结果显示,13个省区的能源效率差异较大。比较几个模型,我们发现能源的相对定价并没有为节约能源提供合适的激励。两阶段估计结果表明,技术进步和工业内部结构是影响能源效率的重要因素。此结论的政策含义是,为了节能减排,这些工业省区需要:(1)吸引外资和技术,推进自主创新,加快技术进步;(2)改变重型化的工业结构,促使工业结构优化升级;(3)适当提高能源的使用成本。     

Sequential Malmquist Indices of Productivity Growth: An Application to OECD Industrial Activities

The paper applies both the standard DEA methodology with contemporaneous frontiers and DEA with sequential frontiers to study changes in productivity and efficiency in manufacturing for a sample of eleven OECD countries over a twenty-year period. It uses a decomposition of the industrial Malmquist productivity indices to locate the sources of productivity growth: 'technical progress' and 'catching up.' The alternative indices are interrelated in a unifying framework that provides an interpretation to their difference. We argue that for manufacturing industries, in which technological regress is unlikely to occur, DEA with sequential frontiers provides a more adequate measure for the contribution of technical changes than standard DEA.     

Stochastic leader–follower DEA models for two-stage systems

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). In recent years, it has been widely used to evaluate two-stage systems under different organization mechanisms. This study modifies the conventional leader–follower DEA models for two-stage systems by considering the uncertainty of data. The dual deterministic linear models are first constructed from the stochastic CCR models under the assumption that all components of inputs, outputs, and intermediate products are related only with some basic stochastic factors, which follow continuous and symmetric distributions with nonnegative compact supports. The stochastic leader–follower DEA models are then developed for measuring the efficiencies of the two stages. The stochastic efficiency of the whole system can be uniquely decomposed into the product of the efficiencies of the two stages. Relationships between stochastic efficiencies from stochastic CCR and stochastic leader–follower DEA models are also discussed. An example of the commercial banks in China is considered using the proposed models under different risk levels.     

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.     

方法、数据与全要素生产率测算差异

研究目标：检验不同方法之间TFP测算结果的“一致性”和“稳健性”,探讨测算方法和数据选取问题。研究方法：以中国2004~2012年总量分行业面板数据为例,从多个角度比较TFP测算结果,以及通过统计检验选取适用测算方法。研究发现：第一,研究的问题不同,测算方法之间“一致性”的检验结论不同;第二,在选择测算方法时,进行相关统计量检验是必要的,这有助于鉴别模型设定是否合理,缩小可选模型范围;第三,测算方法的选择,要符合数据本身的特征,基于宏观分行业面板数据,DEA是更为适用的TFP测算方法,而劳动力投入应选取全社会从业人员指标。研究创新：多种测算方法和统计检验的应用。研究价值：本文尝试构建如何选择TFP测算方法的一般框架。     

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.     

The Measurement of Consumption Efficiency Considering the Discrete Choice of Consumers

In this study we propose a mathematical definition of the consumption efficiency of multi-attribute products in the price–quality space. A new model, the discrete Range Adjusted Measure (RAM) model, is suggested as an empirical tool to measure the level of consumption efficiency. We further discuss the effect of consumption efficiency on the innovation incentive. Empirical work is made for the mobile phone market. We expect that the consumption efficiency concept will contribute to the extension of the traditional framework of production efficiency analysis on the one hand and to the understanding of the nature of innovation in a technology-intensive market on the other hand.JEL Classification: C67, D11, D12, D21     

The Application of Mathematical Programming Approaches to Estimating Container Port Production Efficiency

Container terminal production is both an important and complicated element in the contemporary global economy. This paper aims to evaluate the efficiency of the world’s most important container ports and terminals using the two alternative techniques of Data Envelopment Analysis (DEA) and the Free Disposal Hull (FDH) model. The results give an insight into the current efficiency ranking of the world’s major container ports and terminals. They also confirm expectations that the available mathematical programming methodologies lead to different results and that appropriate variable definition of input and output factors is a crucial element in meaningful applications of DEA and FDH. It is also concluded that the availability of panel data, rather than cross-sectional data would greatly improve the validity of the efficiency estimates derived from all the mathematical programming techniques applied.JEL Classification:C61, D24, E23, L23, L25, L92