Analysis on pure e-commerce congestion effect,productivity effect and profitability in China

This paper examines the relationship of e-commerce congestion effect, productivity effect and profit generation in China. The technique of Data Envelopment Analysis (DEA) is used to measure returns to scale and total factor productivity in e-commerce. The results show that e-commerce firms achieve productivity growth but suffer from input congestion. Congestion weakens profitability and leads to negative returns of inputs to outputs. This finding offers a new insight to explain the determinants of profit change. This research enriches production theory of internet companies, and helps managers strengthen their profitability by measuring the existence of congestion and eliminating input congestion resources.     

基于DEA方法集的物流企业生产效率分析——以沪深股市上市公司为例

根据物流企业的职工人数、固定资产等经济数据,能够构建反映其生产效率的指标体系,然后运用集成数据包络分析进行效率分析,可以算出物流企业生产效率指标及其规模收益等状况。通过实证分析认为,中国物流企业的生产效率总体尚可,但个体差异较大;由于产出不足,造成许多企业规模收益递减;细化深化专业分工和改造现有业务流程,仍然是多数物流企业当前的紧迫任务。     

Evaluating Productivity Growth Measures in the EU

In this paper we evaluate the productivity growth of the member countries in the European Union (EU) before and after the enforcement of the Maastricht convergence criteria in 1992. Total factor productivity was measured by employing the growth-accounting approach and Tornqvist indices. The evaluation of productivity growth was performed by employing the non-parametric method of Data Envelopment Analysis (DEA) in particular years and within three time periods. DEA was also used to evaluate the relative efficiency of EU members with respect to the convergence criteria with important implications for their economic integration. TFP growth was found to have contributed the most in the EU, while its share in the latest recessions was the smallest as compared to labor and capital share.     

Measuring and Evaluating Efficiency of Hospitals Through Total Quality Management

ABSTRACT

The purpose of this study is to measure and evaluate the efficiency of 12 hospitals in Turkey using a multi-criteria Data Envelopment Analysis (DEA) methodology. Number of beds, number of physicians and the critical factors of total quality management in the health care sector were used as inputs of the model. The outputs used in this analysis incorporated financial and non-financial performance of hospitals, number of outpatients and number of patient days. Performance of the hospitals was measured using subjective measures based on executive's perception of how their organization performed relative to the competition. Results provide management with information regarding the relatively best practice hospitals in the observation sets and locate the relatively inefficient hospitals by comparison with the best practice ones. At last some suggestions are made for the least efficient hospital.     

Productivity effects on Mexican manufacturing employment

We examine the effects of labor productivity and total factor productivity (TFP) on employment across 25 Mexican manufacturing industries from 1984 to 2000. Employing panel data methods, several interesting findings emerge. First, we observe a strong and positive impact of NAFTA on employment. Second, productivity exerts a procyclical, positive effect on employment but this effect becomes smaller after NAFTA. Third, partitions of our sample according to capital-labor intensity suggest that industries which are less capital-intensive were affected negatively on impact by NAFTA but that productivity impacted employment positively after NAFTA. In contrast, more capital-intensive industries display these results in reverse.     

Neoclassical Growth Accounting and Frontier Analysis: A Synthesis

The standard measure of productivity growth is the Solow residual. Its evaluation requires data on factor input shares or prices. Since these prices are presumed to match factor productivities, the standard procedure amounts to accepting at face value what is supposed to be measured. In this paper we estimate total factor productivity growth without recourse to data on factor input prices. Factor productivities are defined as Lagrange multipliers to the program that maximizes the level of domestic final demand. The consequent measure of total factor productivity is shown to encompass not only the Solow residual, but also the efficiency change of frontier analysis and the hitherto slippery terms-of-trade effect. Using input-output tables from 1962 to 1991 we show that the source of Canadian productivity growth has shifted from technical change to terms-of-trade effects.     

上市企业效率评估：聚焦水运业

水运是我国融入经济全球化的战略通道。在当前的国际金融危机之下,我国的水上运输和港口企业已受到较为严重的影响,文章利用数据包络分析、因子分析等研究方法．借助在沪、深两市上市的水运业21家公司2007年度数据,算得各企业的总体技术效率、纯技术效率、规模效率和规模收益状态,从而评价其经营的相对效率,给出对应的管理建议,以期为这些水上运输业企业提供有益参考,     

中国高技术产业的全要素生产率及产业比较

基于2001～2007年中国5个高技术产业的细分行业的面板数据,运用Malmquist指数构建一个三投入三产出的模型,分别测算了高技术产业及其细分行业的全要素生产率。结果显示,5个细分行业全要素生产率的增长率差异较大,而且整个高技术产业的全要素生产率的增长率不稳定,主要原因是技术进步因素发生波动。     

Localized Innovation and Productivity Growth in Asia: An Intertemporal DEA Approach

Recent contributions to growth theory stress the importance of localized innovation for the performance of more backward countries. In earlier papers, analyses by means of DEA techniques confirmed this intuition. In this paper, we extend this type of analysis by relaxing the macroeconomic viewpoint adopted until now. New databases on output, labor and capital input in the agricultural and manufacturing sectors are developed for 40 countries. Using intertemporal DEA, it is found that changes in the global production frontier are localized at high levels of capital intensity. This result is stronger in agriculture than in manufacturing. Further, a decomposition of labor productivity growth in eight Asian countries for the period 1975–1992 into the effects of capital intensification, learning and innovation is made. The results suggest that there is a particular development path in which increases in capital intensity appear to be a prerequisite to benefit from international technology spillovers.JEL Classification: O14, O30, O40, O47     

基于MEA和Luenberger生产率指数的中国商业银行效率及生产率模式评估

引入多方向效率分析模型(MEA)模型对我国16家上市商业银行2011—2018年各指标的效率进行了评估,结果显示国有银行效率低下的主要原因是净利息利润、存款和劳动力的效率较低。为进一步研究中国商业银行生产率的构成情况,引入基于方向性距离函数的Luenberger生产率指数及其分解结果,来评价中国商业银行各指标的生产率,得到中国商业银行生产率的变化主要归功于净利息利润和净非利息利润生产率的变化。     

A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016

In recent years there has been an exponential growth in the number of publications related to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and Rhodes (1978) introduced DEA as a tool for measuring efficiency and productivity of decision making units. DEA has immediately been recognized as a modern tool for performance measurement. Since then, a large and considerable amount of articles has been appeared, including significant breakthroughs in theory and a great portion of works on DEA applications, both public and private sectors, to assess the efficiency and productivity of their activities. Although there have been several bibliographic collections reported, a comprehensive analysis and listing of DEA-related articles covering its first four decades of history is still missing. This paper, thus, aims to report an extensive listing of DEA-related articles including theory and methodology developments and \"real\" applications in diversified scenarios from 1978 to end of 2016. Some summary statistics of the publications' growth, the most utilized academic journals, authorship analysis, as well as keywords analysis are also provided.     

Applying efficiency measurement techniques to the measurement of productivity change

Deterministic frontier analysis (DFA), stochastic frontier analysis (SFA), and data envelopment analysis (DEA) are alternative analytical techniques designed to measure the efficiency of producers. All three techniques were originally developed within a cross-sectional context, in which the objective is to compare the efficiencies of producers. More recently all three techniques have been extended for use in a panel data context. In the latter context it is possible to measure productivity change, and to decompose measured productivity change into its sources, one of which is efficiency change. However when efficiency measurement techniques, particularly SFA, have been applied to panel data, it has infrequently been made clear what the objective of the analysis is: the measurement of efficiency, which may vary through time as well as across producers, or the measurement and decomposition of productivity change. In this paper I explore the use of each technique in a panel data context. I find DFA and DEA to have achieved a more satisfactory reorientation toward productivity measurement than SFA has.     

Specification of Distance Functions Using Semi- and Nonparametric Methods with an Application to the Dynamic Performance of Eastern and Western European Air Carriers

In this paper we examine the productive performance of a group of three East European carriers and compare it to thirteen of their West European competitors during the period 1977–1990. We first model the multiple output/multiple input technology with a stochastic distance frontier using recently developed semiparametric efficient methods. The endogeneity of multiple outputs is addressed in part by introducing multivariate kernel estimators for the joint distribution of the multiple outputs and potentially correlated firm random effects. We augment estimates from our semiparametric stochastic distance function with nonparametric distance function methods, using linear programming techniques, as well as with extended decomposition methods, based on the Malmquist index number. Both semi- and nonparametric methods indicate significant slack in resource utilization in the East European carriers relative to their Western counterparts, and limited convergence in efficiency or technical change between them. The implications are rather stark for the long run viability of the East European carriers in our sample.     

The Fixed Weighting Nature of A Cross-Evaluation Model

Cross-evaluation has been touted as a powerful extension of Data Envelopment Analysis that provides, not only a unique ordering among the Decision Making Units (DMUs), but also eliminates unrealistic weighting schemes without requiring the elicitation of weight restrictions from application area experts. The goal of this paper is to prove, in the single-input, multiple-output case, cross-evaluation implicitly uses a single fixed set of weights. We demonstrate how this unseen fixed set of weights may still be unrealistic.     

信息产业行业内生产率变动及影响因素的差异探究——基于中国上市公司公开数据的实证

采用数据包络分析方法中的Malmquist指数法,以我国信息技术业上市公司为主要研究对象,对我国信息技术产业及其细分行业的生产效率做出考察,并在此基础上对影响我国信息技术业及该产业中各核心子行业生产效率的主要内部影响因素进行实证分析。分析结果表明：以信息技术行业上市公司为代表对象的我国信息技术行业的全要素生产率正处于稳定上升期,但各分行业的全要素生产率由于技术进步效率的不同而存在着较大的波动,且全行业的全要素生产率进步更多地是依赖规模效率而非技术进步效率,同时,财务因素对信息制造业类企业的生产效率提高具有显著的正向影响,但对信息服务业而言,其影响并不显著。     

私募股权、公开上市和生产效率

本文以公司在资本市场上公开上市为背景,以是否具有私募股权融资背景为标准,选取了384家上市公司为研究样本,使用索洛余值法、随机前沿分析模型等方法,实证分析私募股权投资对改善企业生产效率的作用。研究结果发现,无论是否有私募股权投资,企业上市后的全要素生产率均高于上市前;有私募股权投资的企业全要素生产率在上市前要低于无私募股权投资的企业,但是上市后则超过了无私募股权投资的企业。     

Lower Bound Restrictions on Intensities in Data Envelopment Analysis

We propose an extension to the basic DEA models that guarantees that if an intensity is positive then it must be at least as large as a pre-defined lower bound. This requirement adds an integer programming constraint known within Operations Research as a Fixed-Charge (FC) type of constraint. Accordingly, we term the new model DEA_FC. The proposed model lies between the DEA models that allow units to be scaled arbitrarily low, and the Free Disposal Hull model that allows no scaling. We analyze 18 datasets from the literature to demonstrate that sufficiently low intensities—those for which the scaled Decision-Making Unit (DMU) has inputs and outputs that lie below the minimum values observed—are pervasive, and that the new model ensures fairer comparisons without sacrificing the required discriminating power. We explain why the low-intensity phenomenon exists. In sharp contrast to standard DEA models we demonstrate via examples that an inefficient DMU may play a pivotal role in determining the technology. We also propose a goal programming model that determines how deviations from the lower bounds affect efficiency, which we term the trade-off between the deviation gap and the efficiency gap.