港口绿色评价指标体系

在引入绿色理念的基础上,定量分析港口对经济贡献的同时加入对资源消耗的占用和对环境的影响,形成新的投入产出港口评价体系,对港口发展做出多维评价,并在评价的基础上提出了港口的经济效益与环境影响协调分析,为港口的可持续发展提供有力数据支持。     

港口物流综合能力评价体系构建研究

港口物流综合能力评价能够系统地分析港口物流系统的综合运行状况,是港口物流系统规划建设的重要依据。文中从港口物流的概念和作用入手,提出了港口物流综合能力的概念,把港口物流综合能力分为五大类,建立了较全面的港口物流综合能力评价指标体系,并运用层次分析法构建了港口物流综合能力评价模型。通过层次分析法对港口物流综合能力进行定量分析,给出了各指标的权重,为港口有效提高物流综合服务水平提供了参考依据,以期有效地支持港口物流系统的建设和发展。     

基于熵权-TOPSIS法的港口集疏运能力评价

集疏运能力建设对于提高港口运营效率和综合竞争力具有重要意义。基于熵权-TOPSIS法建立了港口集疏运能力综合评价模型，并进行了案例分析。运用熵权法确定评价指标权重，用TOPSIS法对各港口的贴近度进行计算，通过实证可得到港口集疏运能力相对客观的评价结果，能够为港口企业经营决策提供参考。     

辽宁省港口集疏运体系评价研究

文章通过对辽宁省港口现状、港口分布、地理位置、腹地经济、集疏运方式等指标的调研分析,运用专家调查法和层次分析法对主要港口进行评价,为辽宁省主要港口的提升提供技术支持。     

DHGF模型在港口装卸作业安全管理评价中的应用

文中以DHGF模型为基础，以某港口P为案例，建立港口装卸作业安全管理评价模型，并求出评价结果，即港口P装卸作业安全管理等级，并对评价结果进行分析。     

基于模糊物元模型的港口节能减排水平评价

对我国沿海主要港口节能减排水平进行客观分析与评价是实现港口节能减排的必经之路,针对港口节能减排水平评价指标存在的模糊性,以及各个指标之间的不相容性等特点,建立了复合模糊物元评价模型,采用熵值法计算各指标权重系数,并对选定的5个港口节能减排水平进行了实证评价,评价结果与我国港口现阶段节能减排水平情况一致,此模型具有实用性。     

论生态型港口评价体系的建立

港口作为大型物资流转地,无论对其所在的港城还是对整个国家而言,都意义非凡。同样的,生态型港口的建设也是既符合国情又顺应时代要求的举措。文章通过对国内外研究现状的分析,提出了通过DPSRC模型来建立生态型港口评价体系,并对具体的指标内容进行了列举说明,希望能够为我国生态港口的评价体系的发展做一些贡献。     

论生态型港口评价体系的建立

港口作为大型物资流转地,无论对其所在的港城还是对整个国家而言,都意义非凡。同样的,生态型港口的建设也是既符合国情又顺应时代要求的举措。文章通过对国内外研究现状的分析,提出了通过DPSRC模型来建立生态型港口评价体系,并对具体的指标内容进行了列举说明,希望能够为我国生态港口的评价体系的发展做一些贡献。     

基于DEA的港口物流产业集群创新能力评价-以宁波为例

通过对港口物流产业集群创新能力作用机理的分析,得出创新资源的投入以主体要素和服务支持要素为基础,并形成有效的创新资源产出,作用于港口物流产业集群的发展。其次,运用DEA评价模型,以宁波港口物流产业集群为典型案例代表,对其进行了创新能力投入产出效率评价测定,并根据DEA效率与规模计算输出结果,提出宁波提升港口物流产业集群创新能力的对策措施。     

基于DEA的港口物流产业集群创新能力评价——以宁波为例

通过对港口物流产业集群创新能力作用机理的分析,得出创新资源的投入以主体要素和服务支持要素为基础,并形成有效的创新资源产出,作用于港口物流产业集群的发展。其次,运用DEA评价模型,以宁波港口物流产业集群为典型案例代表,对其进行了创新能力投入产出效率评价测定,并根据DEA效率与规模计算输出结果,提出宁波提升港口物流产业集群创新能力的对策措施。     

基于超效率DEA模型的辽宁省集装箱港口生产效率评价

对超效率DEA模型进行了介绍,并采用超效率DEA模型对辽宁省集装箱港口的生产效率进行了评价.评价结果表明辽宁省的大部分集装箱码头处于规模收益递增或规模收益不变的状态;同建港时间最长、规模最大、吞吐量最高的大连港相比,一些新兴的集装箱码头的生产效率更高.     

Effeciency Changes at Major Container Ports in Japan: A Window Application of Data Envelopment Analysis

Container ports in Japan are not experiencing rapid cargo handling growth. Recently, however, a reorganization of port use is taking place due to a variety of factors like growing container ship size, diversified Asian shipping routes, increasing import cargo and the Great Hanshin earthquake in Kobe in 1995. This paper analyzes the operational efficiency of eight major international container ports using a "window" application of data envelopment analysis for the period between 1990 and 1999. The paper shows a distinction between ports with timely development and sound demand growth and those with deferred re–planning and slow demand recovery. The Port of Tokyo has successfully redeveloped to receive large–sized container vessels and is observing increased and well–balanced incoming and outgoing traffic, and hence remains DEA efficient in our analysis. The Port of Kobe still needs to implement further measures to attract new users and previous users due to the Great Hanshin earthquake. The BCC model of the DEA takes into account small–scale operations of Yokkaichi and Shimizu Ports, and appraises their recent increasing demand for Asian routes. The appropriate design of window length is also proposed in the study.     

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     

Measuring efficiency under fixed proportion technologies

Data Envelopment Analysis (DEA) applications frequently involve nonsubstitutable inputs and nonsubstitutable outputs (that is, fixed proportion technologies). However, DEA theory requires substitutability. In this paper, we illustrate the consequences of nonsubstitutability on DEA efficiency estimates, and we develop new efficiency indicators that are similar to those of conventional DEA models except that they require nonsubstitutability. Then, using simulated and real-world datasets that encompass fixed proportion technologies, we compare DEA efficiency estimates with those of the new indicators. The examples demonstrate that DEA efficiency estimates are biased when inputs and outputs are nonsubstitutable. The degree of bias varies considerably among Decision Making Units, resulting in substantial differences in efficiency rankings between DEA and the new measures. And, over 90% of the units that DEA identifies as efficient are, in truth, not efficient. We conclude that when inputs and outputs are not substituted for either technological or other reasons, conventional DEA models should be replaced with models that account for nonsubstitutability.     

Using DEA to evaluate the state of society as measured by multiple social indicators

This paper presents an approach for discussing the state of society, which is measured by multiple social indicators, using data envelopment analysis (DEA). Replacing inputs and outputs in DEA with negative and positive social indicators respectively, we analyze the desirability of living in the 47 prefectures of Japan. This is also a proposal for the potential use of DEA in multi-dimensional evaluation analysis other than the standard DEA efficiency analysis. The results using eight social indicators identify 26 DEA desirable prefectures out of the 47 and present other useful knowledge and information. It is concluded that DEA, which can avoid uniform evaluation by an a priori weighting system, provides availability as a comprehensive evaluation tool different from traditional ones.     

A PCA–DEA approach to measure the quality of life in Estonian counties

This paper investigates the application of a PCA–DEA model to assess the quality of life (QOL) scores in Estonian counties and analyses the model's results. The dataset is a balanced panel of 15 Estonian counties covering the period from 2000 to 2011. We consider a PCA–DEA model as an alternative method to estimate and predict QOL scores and rankings of Estonian counties. The method consists of a two-stage analysis that begins with a principal component analysis. In the second stage, the standard DEA is used. The results from the conventional DEA model and the PCA–DEA model are compared and discussed. A comparison of the methodologies demonstrates that a PCA–DEA model provides a powerful tool for performance ranking. The rankings of Estonian counties using QOL scores for different model specifications are presented. Finally, the QOL ranking of Estonian counties is revised using PCA–DEA.     

银行效率DEA分析的可信度检验

近年来涌现出大量基于DEA方法的银行效率这一热点问题的研究成果,但是由于DEA方法自身的局限性,诸如对效率值的估计偏低且离散程度较大,以及不能方便地检验结果的显著性等等问题,使其研究的结果受到影响;而Bootstrap技术是基于对经验数据及其相关估计的重复抽样来提高估计置信区间和临界值精度的统计技术,可有效地克服DEA方法结果可信度的这种内在依赖性。本文给出了基于Boot-strap技术的DEA方法来计量银行效率的手段,提高了效率分析结果的可信度,并对我国四大国有商业银行的效率进行了对比性实证分析。     

基于改进的DEA/AHP模型的人工成本投入产出效率评价

通过采用0.1-0.9标度这种更为简便实用的判断尺度,建立了具有完全一致性的互补判断矩阵,妥善解决了AHP判断矩阵的一致性问题,改进了DEA/AHP模型。并基于DEA模型和改进的DEAHP模型分别对盐城市22个行业2009年的人工成本投入产出进行效率评价分析。研究结果显示,基于改进的DEA/AHP模型的评价结果更加具有可区分性,具有更高的解析能力。     

Incorporating quality into the measurement of hospital efficiency: a double DEA approach

This paper uses “double DEA” to assess how accounting for quality influences DEA technical efficiency scores of a sample of 1,074 US hospitals. In the first use of DEA, quality indices are estimated using a variety of process and outcome measures of quality. In the second use of DEA, technical efficiency is assessed while controlling for quality. A variety of DEA quality indices and a DEA variety of efficiency models are compared to determine how the treatment of quality influences findings regarding technical efficiency. Controlling for efficiency does matter, with outcome measures having an apparently greater impact than process measures. Given the call for improved quality and better cost containment, controlling for quality is an important contribution to efficiency analysis.