基于DEA模型的区域创新系统效率评价研究

文章构建了区域创新系统效率的评价指标体系,并引入数据包络分析方法,并将其作为评价区域创新系统效率的定量评价方法。根据构建的指标体系与C2R模型,可以对区域创新系统的效率进行评价。     

基于DEA模型的区域物流效率评价实证分析

基于“十一五”期间全国31个省、自治区、直辖市的物流经济发展相关数据,构建CCR、BCC、SE数据包络分析模型进行物流综合效率、技术效率和规模效率分析,通过多次效率评价构建区域经济物流效率有效性的雁行形态图,对相对有效DMU,采用超效率DEA模型进行效率全排序,对无效DMU,分析其投入要素冗余和调整量。     

基于DEA的区域高等院校协作效率评价

本文应用DEA方法从定量的角度研究通过区域内和区域之间的合作带来的益处。通过构建评价高等院校协作效率的DEA模型,对某地14所院校的区域内和区域间的高等院校协作效率进行评价。计算结果表明,通过区域内合作,每一个区域内都有部分院校的效率有较大的提高,最高的超过30％。     

山西省能源产业的金融支持效率研究——基于DEA模型

能源产业的优化发展离不开金融支持。山西作为能源大省,能源产业在其经济中占有举足轻重的地位,而金融支持是否有效,直接影响着能源产业持续健康发展。文章通过数据包络分析法,对山西省十家上市能源企业进行金融支持效率的实证分析,根据实证结果分析能源产业金融支持有效性,从而得出推进资本市场发展,完善商业银行金融服务体系,以及能源企业加大产品创新,提高自身综合竞争力的金融支持策略选择。     

基于效率视角的金融生态研究综述

金融生态是具有中国特色的概念。学界对金融生态的研究,对提高我国金融业效率具有重要意义。本文基于效率视角从理论和实证两方面对金融生态理论研究进行了梳理,重点梳理并评析金融生态的内涵、假设前提、金融生态和金融效率的关系三个方面,并对金融生态的进一步研究作出展望。     

基于金融效率的我国金融结构分析

本文通过对金融结构和金融效率的相关概念理论进行回顾,根据我国金融效率的缺失特征来推断金融结构存在的问题,并提出我国金融结构优化的建议。通过分析,发现我国现行金融体系存在的结构问题有:银行国有产权、融资结构不合理以及区域金融结构不协调的问题,因此本文认为我国应当大力发展非国有金融机构及非国有商业银行、加强金融产业结构化进程,并发展区域性证券交易市场,实现地区间金融协调发展。     

基于DEA模型的区域技术效率评价与实证研究

1、引言 河北省地处中国东部沿海,环绕北京、天津,区位优势独特,自然风光秀美,是全国唯一兼有海滨、平原、湖泊、丘陵、山地、高原的省份.     

基于DEA的供应链效率评价研究

为有效提高供应链效率,运用数据包络分析(Data Envelopment Analysis,DEA)方法,构建供应链系统数据包络(Data Envelopment Analysis-Supply Chain All,DEA-SCA)评价模型;使用DEAP2.1仿真软件平台对卷烟14条供应链系统进行数据计算仿真,量化供应链系统整体效率。仿真结果表明:较传统的DEA-CCR效率分析,DEA-SCA效率评价模型能够有效甄别供应链上下游组织中存在的问题;提高供应链系统的整体效率。     

基于DEA模型的科技金融结合效率研究——以四川省为例

科技与金融的有效结合是实现创新驱动发展,提升区域综合竞争力的重要引擎。在建立科技金融效率评价指标体系的基础上,运用DEA模型对2016年30个省(自治区、直辖市)及2002—2016年四川省金融投入与科技产出进行横向和纵向分析(1),横向对比显示四川省2016年科技金融综合效率、纯技术效率及规模效率均处于相对有效状态,需进行一定程度的调整和改进才能达到有效状态;由纵向分析可知在2002—2016年这15年间,四川省科技金融总体效率有13年未达到有效状态,其中7年存在投入冗余和产出不足问题。基于实证分析结果,提出了促进四川省科技金融发展的政策性建议。     

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。     

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.     

基于DEA的废旧家电回收模式评价研究

在大量电子废弃物成为焦点的今天,家电企业要在既定的环境下选择一种最有效的家电回收模式,将产生的废弃物资回收,重新加以利用,已成为迫在眉睫的问题。针对废旧家电回收问题,介绍了四种废旧家电的回收模式,建立了一套评价指标体系,提出了采用数据包络分析方法对四种回收模式进行选择,且最后给出了一个算例,证明了该方法的可行性和有效性。     

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.     

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.     

DEA of financial statements data: The U.S. computer industry

DEA (data envelopment analysis) is a technique for determining the efficiencyfrontier (the envelope) to the inputs and outputs of a collection of individual corporations or other productive units. DEA is here employed to estimate the intertemporal productive efficiency of U.S. computer manufactures, using financial data brought from earnings statements and balance sheets. The results indicate that a few corporations, including Apple Computer Inc., Compaq Computer Corp., and Seagate Technology were able to stay at the productivity efficiency frontier throughout the time period investigated. But not all successful corporations did; sometimes subefficiency (=disequilibrium) actually goes together with very rapid growth. A new Malmquist type productivity index is calculated for each corporation, measuring shifts of the estimated intertemporal efficiency frontier.     

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).     

基于DEA的全国31个省市财政科技支出效率测评

财政科技支出效率建立了一个科学且切实可行的评价体系,利用DEA模型,结合2006年全国31个省市财政科技支出的实例,对财政科支出效率进行分析。     

基于DEA方法的零售企业经营效率的分析

目前,我国零售业正处于一场深刻变革之中,我国零售企业面临着严峻的竞争。本文选取了在国内外上市的十二家零售企业,应用DEA(Data Envelopment Analysis,数据包络分析)方法,对各企业的经营效率进行分析,并根据分析结果提出针对性的改进措施。     

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.