基于超效率DEA和Tobit模型的中国上市煤炭企业经营效率现状分析

本文运用数据包络分析（DEA）方法和Tobit回归模型,首先选取2011年沪深两市具有代表性的18家煤炭上市公司为研究对象,以货币资金、流动资产合计、长期股权投资、固定资产和非流动资产合计为投入变量,主营业务收入、主营业务利润、利润总额为产出变量,运用CCR模型从技术效率、纯技术效率和规模效率等方面对其经营效率进行评价和分析;其次运用超效率DEA模型对CCR模型下DEA有效的决策单元计算其超效率值,从而为所有决策单元提供完整的效率值排序;最后,本文运用Tobit模型,分析影响中国上市煤炭企业经营效率的重要因素,为决策者提供提高企业经营效率的方向和政策。     

不良贷款约束下我国商业银行效率的测评——基于两阶段DEA模型的分析

在两阶段DEA模型的基础上引入不良贷款作为非期望产出,改进传统两阶段DEA模型,分别用新模型与原模型测算16家上市商业银行的效率,对总效率和子阶段效率分别进行分析,并比较存款获取阶段与利润获取阶段的效率,结果显示：不良贷款对银行效率有显著影响;“四大行”的效率高于股份制商业银行;2008年以前我国银行业主要依赖存款获取阶段来提升效率,在2008年以后主要依赖利润获取阶段来提升效率。     

Online banking performance evaluation using data envelopment analysis and axiomatic fuzzy set clustering

This paper presents a hybrid model to conducting performance measurements for Internet banking by using data envelopment analysis (DEA) and axiomatic fuzzy set (AFS) clustering. For each bank, DEA is applied to select a best combination by computing an aggregated efficiency score based on outputs, such as web metrics and revenue; and inputs, such as equipment, operation cost and employees. Then AFS clustering method is used to classify the best combination into different groups and provide the definitely semantic interpretations for the evaluation results. Identification of operational fitness and business orientation of each firm, in this way, will yield insights into understanding the weaknesses and strengths of banks, which are considering moving into Internet banking.     

A combined machine learning algorithms and DEA method for measuring and predicting the efficiency of Chinese manufacturing listed companies

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in the private and public sectors. However, if a new DMU needs to be known its efficiency score, the DEA analysis would have to be re-conducted, especially nowadays, datasets from many fields have been growing rapidly in the real world, which will need a huge amount of computation. Following the previous studies, this paper aims to establish a linkage between the DEA method and machine learning (ML) algorithms, and proposes an alternative way that combines DEA with ML (ML-DEA) algorithms to measure and predict the DEA efficiency of DMUs. Four ML-DEA algorithms are discussed, namely DEA-CCR model combined with back-propagation neural network (BPNN-DEA), with genetic algorithm (GA) integrated with back-propagation neural network (GANN-DEA), with support vector machines (SVM-DEA), and with improved support vector machines (ISVM-DEA), respectively. To illustrate the applicability of above models, the performance of Chinese manufacturing listed companies in 2016 is measured, predicted and compared with the DEA efficiency scores obtained by the DEA-CCR model. The empirical results show that the average accuracy of the predicted efficiency of DMUs is about 94%, and the comprehensive performance order of four ML-DEA algorithms ranked from good to poor is GANN-DEA, BPNN-DEA, ISVM-DEA, and SVM-DEA.     

股改背景下上市公司并购的绩效分析

十几年来我国上市公司并购发展迅速,对国民经济生活影响越来越大。中国市场如此多的并购案例,究竟能否增强企业的绩效,能否改善企业的状况,股权分置改革又能为并购绩效影响带来什么样的变化,这是非常需要值得研究的问题。文章以股权分置改革为背景,选取了2005年发生并购的229家上市公司作为样本,结合股改前后并购特征对收购方财务数据进行了研究。通过DEA模型分析并购对公司绩效的影响。     

中国省际高技术产业效率测度与分解——基于共享投入关联DEA模型

本文基于高技术产业科技成果产出和科技成果转化为生产力两阶段视角,考虑"中间产品产出再投入"和"初始投入在两个子系统间的分配结构",构建共享投入关联DEA模型,利用1999～2010年我国29个省份的面板数据,测算高技术产业系统效率和子系统的纯技术效率,并与关联DEA模型、BCC模型的结果进行比较。结果表明,共享投入关联DEA模型在计算效率水平的同时,还可得到中间产品的转化信息和初始投入的配置信息。     

Evaluating the operational performance of knowledge-based industries: the perspective of intellectual capital

Performance evaluation is more than a quantitative concept but should also take industrial characteristics into account in order to form an accurate evaluation. In the past, evaluations of the operational performance of knowledge-based industries have missed out a significant factor, which is intellectual capital (IC). By adopting data envelopment analysis (DEA), a multiple-objective decision making method, this study aims to construct an efficiency evaluation model for the Taiwanese digital content industry based on the perspective of IC. The empirical results suggest that the scale of the digital content companies does play an important role in influencing the operating efficiency. The firms have a small amount of capital can still attain optimal efficiency, from the perspective of IC. In addition, human resource capital and customer capital are the most significant influential factors that deserve digital content firms’ attention. It is suggested that enterprises in the digital content industries should focus more on managing their IC. DEA can provide the semiconductor firms’ operations with insights into resource allocation and competitive advantage as well as help with strategic decision-making.     

基于我国民用客机机上网络主要盈利模式的探讨

随着我国经济高速发展,越来越多的人首选民用航空客机作为出行交通工具。仅2013年上半年,全行业完成旅客运输量1.7亿人次,同比增长11%。随着旅客数量的骤增和信息网络的高速发展,高空使用互联网已经成为越来越多旅客的普遍需要。我国民用客机机上网络近两年才开始探索,与国外有较大差距,因此,对于国内航空公司而言,如何提供便捷、高效的机上无线网络服务已刻不容缓;同时作为一项新的航空服务,如何开发利用好其巨大的市场和盈利空间亦是各航空公司迫切需要解决的。     

Does intellectual capital matter? Assessing the profitability and marketability of IC design companies

Under a highly competitive market and a dynamic industrial environment, how to evaluate and enhance an integrated circuit (IC) design company??s good performance is important. This paper develops a two-stage data envelopment analysis (DEA) combined intellectual capital theory through financial and non-financial data to evaluate a performance process on the IC design company. It adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. This paper further uses the Simar and Wilson procedure with a truncated regression to explore the impact of intellectual capital variables on performance and competitive advantage. From the study we suggest to the company in how to enhance precisely its performance to create company value and success.     

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.     

基于DEA模型的旅游上市公司成本控制效率评价研究

成本控制是保证成本管理目标实现的管理行为之一,目的是实现企业利益最大化。在资金流动率较大的旅游上市公司中,由于受到旅游业发展不成熟等因素的限制,其对成本控制效率的考核较为疏忽。然而,成本控制效率的准确评估可以促进相应策略的有效实施,改善企业经营管理,转变经营机制,全面提高企业素质,使企业在市场竞争的环境下生存、发展和壮大。因此,本文在创新应用DEA模型的同时,进行了实证分析,以说明考核成本控制效率的意义和重要性。     

Efficiency in fundraising and distributions to cause-related social profit enterprises

Managerial efficiency is as important in social profit enterprises (SPEs) as it is for more traditional financial-profit organizations. In this regard, both donors and SPE executives use efficiency information in making decisions. Here, we suggest a linked, two-stage Data Envelopment Analysis (DEA) methodology for assessing efficiency in both charitable fundraising and cause delivery, while empirically investigating results for international aid organizations. The model allows efficiency assessment for both the fundraising and utilization of generated funds when directed for cause-related purposes. This, in particular, allows for measurement of the organization’s managerial efficiency relative to both multiple phased goals and peer organizations. Additionally, the approach provides benchmarks for identifying sources of improved performance in fundraising and program/cause service delivery. It can also project the results of changes in inputs on the amount of resources available for the charitable organization’s cause.The proposed model(s) allow the examiner to assess performance while, at the same time, identifying those instances wherein the simple ratio measures commonly used in non-profit assessment are (1) deficient, and/or (2) misleading because of the use of ‘incorrect’ variables, or the ‘hiding’ of inefficiency if/when tax form categories are filed by an SPE. Importantly, the suggested two-stage DEA methodology can be useful for any organization with multiple-linked goals.     

Determination of the efficiency of the world railway companies by method of DEA and comparison of their efficiency by Tobit analysis

This paper attempts to measure the performance of railway companies that produce passenger and freight services around the world. The data covering 10 years from 2000 to 2009 is analyzed first via the data envelopment analysis method in order to obtain technical efficiency and allocative efficiency scores of 31 railway companies for the purpose of the study. In the analysis conducted by use of the CCR model, while total 17 firms were efficient in the first year, this figure reaches to 18 companies for the last year with one more addition. While only two companies seem efficient in the first year, this figure goes down to one for the last year. With input oriented and variable return analysis conducted by use of the BCC model, the firms having technical efficiency at the beginning of the period were 20 in number. At the end of the period, the figure reaches to 24. Next, the outputs of DEA are correlated by Tobit regression and tried to determine decisiveness of the outputs on the efficiency. It has been seen that the same output composition used with Tobit analysis gives more compliant results with the allocative efficiency scores rather than with the technical efficiency scores.     

基于DEA-AHP的港口物流绩效评价研究

基于层次分析法(AHP)和数据包络分析法(DEA),构建了适合港口物流绩效评价的新型指标体系,建立了AHP和DEA相结合的两阶段评价模型。该模型首先进行定性指标的层次分析,然后将分析结果作为DEA的输入输出项,并结合其他定量指标进行DEA评价,最后结合实例验证评价方法的可行性。     

基于DEA的我国物流企业绩效评价

以2009年沪深两市24家物流上市公司为研究对象,运用数据包络分析(DEA)方法,对其经营绩效进行了评价。研究发现,我国物流上市公司总体绩效并不理想,平均绩效值只有0.819;造成绩效不高的原因主要是规模无效率。同时结合分析结果,提出了提高企业经营效率的对策。     

基于DEA方法的企业物流系统绩效评价模型探讨

本文从企业的角度出发，通过分析DEA方法的原理及其应用于企业物流系统绩效评价的可行性．提出运用DEA方法，通过构建模型，从横向和纵向两个方面评价企业物流系统的相对有效性。     

Electronic supply chain management applications by Swedish SMEs

The Internet has become an integral part of business activities of most corporations today. Electronic supply chain management (SCM) can improve the operational efficiency of the firm by streamlining processes between the company and its suppliers, business partners, and customers. This research explores the extent and the degree of Internet application in Swedish small- and medium-sized enterprises (SMEs). The analyses of the data show that the Swedish SMEs use the Internet in their supply chain activities to a large degree. The study establishes some differences between smaller and larger organizations as well as between manufacturing and service companies.     

国家审计促进公共支出效率的路径与机理——基于中国省级面板数据的实证分析

提高公共支出效率是建立现代财政制度的题中之义。围绕国家审计提高公共支出效率这一主题,构建国家审计提高公共支出效率的理论框架,并基于投入导向的超效率 DEA 模型测算2008—2013年中国各省份的公共支出效率,运用Tobit模型进行数据检验,结果显示：国家审计通过审计揭示功能、审计处理处罚功能与审计建议功能之间的协同作用对公共支出效率产生积极影响,共同提升公共支出效率。因此,国家审计机关要在揭露违法违规问题、进行处理处罚的基础上,重点挖掘体制、机制和制度层面的原因,提出高质量的审计建议并推动其实施,共同促进公共支出的效率效果。     

电子商店的营销策略

随着信息技术与网络的发展，网络正成为一个低成本，接触面广的营销渠道，这对于企业意义重大，尤其在竞争激烈的如今，所以，如何建立一个网上商店并使它醒目，吸引人是每个企业急需解决的问题，本文讨论这个问题并试图在电子商店的营销策略方面提出一些建议。     

Exploring the operating efficiency of Technology Development Programs by an intellectual capital perspective—A case study of Taiwan

Government supported technological research and development can help the private sector to compete globally. A more accurate evaluation system considering multi-factor performance is highly desired. This study offers an alternative perspective and characterization of the performance of Technology Development Programs (TDPs) via a two-stage process that emphasizes research and development (R&D) and technology diffusion. This study shall employ a sequential data envelopment analysis (DEA) with a non-parametric statistical analysis to analyze differences in intellectual capital variables among various TDPs. The results reveal that R&D performance is better than technology diffusion performance for the TDPs. In addition, the “Mechanical, Mechatronic, and Transportation field” is more efficient than the other fields in both R&D and technology diffusion performance models. The findings of this study point to the importance of intellectual capital in achieving high levels of TDP efficiency. The potential applications and strengths of DEA and intellectual capital in assessing the performance of TDP are also highlighted.