基于DEA-SBM/Malmquist的广东省创新型产业集群的创新效率研究

分析了创新型产业集群的特征,指出创新型产业集群中丰富的协同创新活动是促进企业创新绩效的有效方法,并提出创新平台是协同创新的优良载体,建设创新平台能有效促进企业创新。在实证分析中利用DEA SBM超效率模型和Malmquist指数,将创新平台加入到创新效率测度的投入变量中,以专利申请数为产出变量,对广东省不同地区的创新型产业集群的创新效率进行了测度。研究结果表明：广东省不同地区创新型产业集群之间的创新效率整体较高但是存在一定差异;创新平台作为创新投入变量是一个能深刻影响测量结果的因素;集群之间的创新平台建设差异较大,一些地区创新平台建设滞后。基于此提出5点政策建议。     

基于DEA视窗分析的渤海湾地区港口内部运营效率

既往对港口效率的研究大多仅考虑空间维度,忽略时间的作用。为了弥补这一不足,运用DEA视窗分析模型,从空间和时间两个维度出发,利用面板数据,对渤海湾地区三大主要港口的内部运营效率进行研究,并利用在DEA相对有效面上的投影分析,明确港口偏离有效的原因。此外,运用灰色关联模型对影响港口效率的因素进行了测算。研究发现,青岛港内部运营效率较高,其次为天津港,而大连港则一直处于非DEA有效状态;投入拥挤、产出不足以及资源配置不合理是造成非DEA有效的主要成因;各投入要素对三大港口内部运营效率的影响程度存在较大差异。     

基于DEA模型的广东省级工程中心技术效率研究

以广东21个城市为决策单元,选用数据包络分析（DEA）中的C2R和BC2模型,评价分析2008年广东省级工程中心技术效率情况。研究表明：全省省级工程中心技术效率总体水平偏低,但珠三角地区相对比较高;纯技术非有效问题比较严重,规模非有效问题非常突出;纯技术效率对技术效率有显著影响;16个无效城市的省级工程中心资源投入冗余比较大,产出不足问题比较突出,尤其是专利授权数。提出了制定省级工程中心发展规划、转变研发重点、实施标杆管理等提升省级工程中心技术效率的政策建议。     

基于DEA的中国包装行业资源配置效率研究

针对中国包装行业的资源配置效率,运用数据包络分析（DEA）方法构建评价模型,并以2005—2016年包装行业的投入产出数据为依据,通过DEAP软件进行评价分析。研究结果表明：技术是造成包装行业资源配置无效的主要原因;产出要素中的专利授权数出现产出不足现象,投入各要素出现了不同程度的冗余。针对研究结果,提出了一些相应的改进建议。     

上市公司冷链业务经营效率研究 ——基于16家上市公司的DEA模型分析

基于16家以冷链物流相关业务为主的上市公司2016—2019年间的企业经营数据,选取主营业务成本、研发投入、研发人员占比、固定资产投入为投入指标,主营业务收入、净利润为产出指标,从综合效率、纯技术效率、规模效率与投入产出情况4个角度,对样本企业的实际经营状况进行DEA模型分析。研究结果表明：技术水平是影响企业经营效率的...     

模糊权重约束的DEA模型及其应用

基于Zadeh模糊优越集定义,应用模糊权重约束DEA模型对医院服务效率进行评价.通过最大化模糊隶属函数来确定投入与产出权重的上限和下限,以避免传统DEA模型中权重为0的缺陷.实例选取期末实有床位数和医护人员数为两个投入变量,总诊疗人次和总出院人次为两个产出变量,评价广州市15所医院的相对服务效率.评价结果对医院管理决策更具客观性和实用性.     

基于超效率DEA方法的全要素能源效率分析

运用在C2R模型基础上建立起来的超效率DEA模型,以能源消费量、劳动力、资本存量作为输入指标,以GDP产出作为输出指标,分析了1998~2008年河北省全要素能源效率问题。在实证分析的基础上,提出相关建议,以有效提升河北省的能效水平。     

湖北省科技发展战略的DEA分析

运用DEA模型，以科技活动的有效性分析为基础，对湖北省已实施的科技发展战略的成效进行了评价。一方面，通过对湖北省1995-2000年科技投入产出的DEA分析，得出了湖北的科技活动在大多数年份里相对有效，但规模收益不变、甚至递减的结论；另一方面，对湖北省“十五”科技攻关重大项目有效性进行了分析，揭示出不同项目的DEA特征。最后为湖北省科技发展战略的调整与优化提出了建议。     

基于DEA的供电企业安全投入产出分析

供电企业的安全投入产出是一个多投入多产出的复杂系统,有必要对安全投入产出效益进行分析以制定改进措施提高安全投资管理水平。在对供电企业安全投入与安全效益界定的基础上,选取7个输入指标及2个输出指标,建了基于DEA的供电企业安全投入产出模型,并进行了实例分析,发现部分供电企业安全投入产出效率较低,需要对现有投资进行优化。结果表明,DEA法可以对供电企业的安全投入产出效益进行有效评价,从而发现不足优化安全投入成本。     

基于技术差距的长江水系主要内河港口效率

长江水系港口效率评价对科学反映港口效率现状,实现港口有效运营,建设长江经济带具有重要意义。为了弥补现有关于港口效率研究中忽略港口之间存在技术水平异质性的不足,从技术差异影响港口效率这一视角出发,在DEA分析的基础上结合共同边界技术（Meta Frontier production function）,对长江水系主干线21家主要内河港口2010～2012年的共同效率、组群效率以及共同技术比率进行分析。结果显示,长江水系三大群组共同效率均值最大仅为027,总体上效率偏低,存在很大提升空间;群组效率均值分别为058、067和027,不同群组之间技术水平存在差异,技术水平受经济发展程度和地理位置的影响;群组三的共同技术比率为1,虽然达到了潜在最佳共同边界技术水平,但普遍存在管理组织上的无效率,群组一和群组二不论是技术水平还是管理效率都有待进一步提升;长江水系主要内河港口普遍存在严重的投入拥挤、产出不足现象。最后,就如何提升长江水系内河港口效率提出了建议。     

Effectiveness of maritime safety control in different navigation zones using a spatial sequential DEA model: Yangtze River case

This paper aims to analyze the effectiveness of maritime safety control from the perspective of safety level along the Yangtze River with special considerations for navigational environments. The influencing variables of maritime safety are reviewed, including ship condition, maritime regulatory system, human reliability and navigational environment. Because the former three variables are generally assumed to be of the same level of safety, this paper focuses on studying the impact of navigational environments on the level of safety in different waterways. An improved data envelopment analysis (DEA) model is proposed by treating the navigational environment factors as inputs and ship accident data as outputs. Moreover, because the traditional DEA model cannot provide an overall ranking of different decision making units (DMUs), the spatial sequential frontiers and grey relational analysis are incorporated into the DEA model to facilitate a refined assessment. Based on the empirical study results, the proposed model is able to solve the problem of information missing in the prior models and evaluate the level of safety with a better accuracy. The results of the proposed DEA model are further compared with an evidential reasoning (ER) method, which has been widely used for level of safety evaluations. A sensitivity analysis is also conducted to better understand the relationship between the variation of navigational environments and level of safety. The sensitivity analysis shows that the level of safety varies in terms of traffic flow. It indicates that appropriate traffic control measures should be adopted for different waterways to improve their safety. This paper presents a practical method of conducting maritime level of safety assessments under dynamic navigational environment.     

A new data envelopment analysis (DEA) model to select eco-efficient technologies in the presence of undesirable outputs

Recent global attention to the challenges of environmental protection is forcing firms and governments to evaluate, rank, and select eco-efficient technologies. Technologies may consume inputs to produce both desirable and undesirable outputs. It seems that the data envelopment analysis (DEA) is a proper method to evaluate eco-efficient technologies. There are some DEA extensions for dealing with undesirable output, and sometimes it is difficult to choose a suitable model to evaluate the technologies. The challenge becomes much more complex when the outcomes of models are not similar. In such a condition, subjective selection of alternative DEA models may lead to deviation from an optimal decision. Accordingly, the objective of this paper is to develop a combined model to include all characters of the previous DEA techniques in a flexible model to select optimum eco-efficient technology in the presence of undesirable outputs. A case study demonstrates the application of proposed procedure.     

Evaluating and selecting investments in industrial robots

This paper proposes an alternative methodology for the selection of industrial robots using data envelopment analysis (DEA). It aims at the identification, in a cost/benefit perspective, of the optimal robot, by measuring, for each robot, the relative efficiency through the resolution of linear programming problems. The methodology adopted is based on a sequential dual use of DEA with restricted weights. This approach increases the discriminatory power of standard DEA and makes it possible to achieve a better balancing of robot performances. Further benefits refer to the possibility of extending the use of this approach to various multi-attribute decision-making problems where each performance may depend on a number of factors. An empirical application of the methodology, using data from 12 robot manufacturers, confirms the applicability of revised DEA to advanced manufacturing technology selection, and reinforces its use as a tactical/operational tool in the area of production/operations. In order to evaluate the overall balancing of robot performance indicators, a sensitivity analysis (with variable weight restrictions) is also carried out. The comparison of the results with those obtained by applying cross-efficiency, another DEA-based methodology (Baker and Talluri 1997 Computers and Industrial Engineering , 32 , 101- 108), is also addressed and discussed. Finally, the dual model of DEA has helped to provide a useful economical and technological analysis of the inefficient robots.     

Consistent and robust ranking in imprecise data envelopment analysis under perturbations of random subsets of data

Data envelopment analysis (DEA) is a non-parametric method for measuring the relative efficiency of a set of decision making units using multiple precise inputs to produce multiple precise outputs. Several extensions to DEA have been made for the case of imprecise data, as well as to improve the robustness of the assessment for these cases. Prevailing robust DEA (RDEA) models are based on mirrored interval DEA models, including two distinct production possibility sets (PPS). However, this approach renders the distance measures incommensurate and violates the standard assumptions for the interpretation of distance measures as efficiency scores. We propose a modified RDEA (MRDEA) model with a unified PPS to overcome the present problem in RDEA. Based on a flexible formulation for the number of variables perturbed, MRDEA calculates the empirical distribution for the interval efficiency for the case of a random number of variables affected. The MRDEA approach also decreases the computational complexity of the RDEA model, as well as significantly increases the discriminatory power of the model without additional information requirements. The properties of the method are demonstrated for four different numerical instances.     

Data envelopment analysis with multiple modes of functioning. Application to reconfigurable manufacturing systems

In principle, data envelopment analysis (DEA) does not consider the possibility, which can occur in practice, of a production system being able to operate in different modes of functioning. In this paper, a new DEA modelling approach is proposed in which the different modes of functioning are taken into account and included in the analysis. The observed input consumption and output production in each mode of functioning is used to derive a mode-specific technology. The overall DEA technology aggregates these mode-specific technologies according to their respective time allocations. The proposed model computes a target operating point for each mode of functioning so that the operation of the overall system is efficient. The proposed approach is applied to assess the technical, cost and allocative efficiency of a reconfigurable manufacturing system. The inputs considered are modules/tools usage, labour and energy consumption. The outputs are the number of units produced of each part type. The production possibility set is determined by previous observations of the system functioning, from which the best practices can be identified. Technical, cost and allocative efficiency scores can be computed. The proposed approach not only generates input cost savings but also lead time reductions.     

A synergetic approach for assessing and improving equipment performance in offshore industry based on dependability

The objective of this paper is to present a framework for assessing and improving offshore equipment performance based on dependability. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the equipment performance. The validity of the model is verified and validated by data envelopment analysis (DEA). Furthermore, a non-parametric correlation method, namely, Spearman correlation experiment shows a high level of correlation between the findings of PCA and DEA. The equipment of offshore industries is considered according to OREDA classification. The approach identifies the critical equipment, which could initiate the major hazards in the system. At first PCA is used for assessing the performance of the equipment and ranking them. IA is then performed for the worst equipment which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward decreasing failure interdependency and magnitude of incidents which ultimately maximize overall operational effectiveness.     

A hierarchical model for optimal supplier selection in multiple sourcing contexts

This paper addresses a crucial objective of the strategic purchasing function in supply chains, i.e. optimal supplier selection. We present a hierarchical extension of the data envelopment analysis (DEA), the most widespread method for supplier rating in the literature, for application in a multiple sourcing strategy context. The proposed hierarchical technique is based on three levels. First, a modified DEA approach is used to evaluate the efficiency of each supplier according to some criteria proposed by the buyer. Second, the well known technique for order preference by similarities to ideal solution (TOPSIS) is applied to rank the maximally efficient suppliers given by the previous step. Third and finally, a linear programming problem is stated and solved to find the quantities to order from each maximally efficient supplier in the multiple sourcing context. The presented approach is able to straightforwardly discern between efficient and inefficient partners, avoid the confusion between efficient and effective suppliers and split the supply in a multiple sourcing context. The hierarchical model is applied to the supply of a C class component to show its robustness and effectiveness, while comparing it with the DEA and TOPSIS approaches.     

评价供应商的DEA方法

以制造业中采购管理为背景，讨论了供应商的评价准则，应用数据包络分析方法解决了供应商的评价问题，并在采购者对供应商有不同要求的情况下，为供应商选择问题提供了有效的技术经济分析方法。