Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work,the Slacks-Based Measure(SBM)model within Data Envelopment Analysis was employed to establish a set of indicators for evaluating the energy efficiency of manufacturing workshops.The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed.The findings indicated that aside from a few workshops operating at the production frontier,the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency.Subsequently,a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops.Regression analysis revealed that technological investments,employee quality,workshop production scale,investment in clean energy,and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops.By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors,this research aids company managers in understanding the energy efficiency of the manufacturing process.It optimizes the combination of various production elements,thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops,which can contribute to enhancing the corporation’s overall energy efficiency.

Prediction Model of Data Envelopment Analysis with Undesirable Outputs

Data envelopment analysis (DEA) has become a standard non parametric approach to productivity analysis, especially to relative efficiency analysis of decision making units (DMUs). Extended to the prediction field, it can solve the prediction problem with multiple inputs and outputs which can not be solved easily by the regression analysis method.But the traditional DEA models can not solve the problem with undesirable outputs,so in this paper the inherent relationship between goal programming and the DEA method based on the relationship between multiple goal programming and goal programming is explored,and a mixed DEA model which can make all factors of inputs and undesirable outputs decrease in different proportions is built.And at the same time,all the factors of desirable outputs increase in different proportions.

Assessment of Dry Port Efficiency in Africa Using Data Envelopment Analysis

This work involves the evaluation of dry port competitiveness through analysis of efficiencies for selected dry ports in Africa. Five dry ports were selected and analysis carried out over a period of four years. The dry ports considered were Mojo and Kality in Ethiopia, Mombasa in Kenya, Isaka in Tanzania and Casablanca in Casablanca, Morocco. Data Envelopment Analysis (DEA) was applied for this work. Container throughputs for the various ports under consideration were used as the output variable for the data analysis model, while the number of reach stackers, the number of tractors, the number of forklifts and the size of the dry port were used as the input variables. From the results, the Mombasa dry port was found to be the most efficient with an average score of approximately 1 over the period under consideration. Casablanca was the second efficient dry port with an average score of 0.762, while Isaka was the least efficient with an average score of 0.142. This research is significant since the African countries have embraced the dry port concept, as witnessed in the huge investments in this sector, and would serve to highlight areas that need improvement for the few existing dry port facilities, most of which are undergoing expansion as well as modernization.

PERFORMANCE EVALUATION METHOD FOR BUSINESS PROCESS OF MACHINERY MANUFACTURER BASED ON DEA/AHP HYBRID MODEL

A set of indices for performance evaluation for business processes with multiple inputs and multiple outputs is proposed, which are found in machinery manufacturers. Based on the traditional methods of data envelopment analysis （DEA） and analytical hierarchical process （AHP）, a hybrid model called DEA/AHP model is proposed to deal with the evaluation of business process performance. With the proposed method, the DEA is firstly used to develop a pairwise comparison matrix, and then the AHP is applied to evaluate the performance of business process using the pairwise comparison matrix. The significant advantage of this hybrid model is the use of objective data instead of subjective human judgment for performance evaluation. In the case study, a project of business process reengineering （BPR） with a hydraulic machinery manufacturer is used to demonstrate the effectiveness of the DEA/AHP model.

Relative Performance Evaluation of Competing Crude Oil Prices’ Volatility Forecasting Models: A Slacks-Based Super-Efficiency DEA Model

With the increasing number of quantitative models available to forecast the volatility of crude oil prices, the assessment of the relative performance of competing models becomes a critical task. Our survey of the literature revealed that most studies tend to use several performance criteria to evaluate the performance of competing forecasting models;however, models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria—A situation where one cannot make an informed decision as to which model performs best when taking all criteria into account. In order to overcome this methodological problem, Xu and Ouenniche [1] proposed a multidimensional framework based on an input-oriented radial super-efficiency Data Envelopment Analysis (DEA) model to rank order competing forecasting models of crude oil prices’ volatility. However, their approach suffers from a number of issues. In this paper, we overcome such issues by proposing an alternative framework.

基于超效率DEA模型的陆军部队指挥所指挥效率评价

指挥所指挥效率评估是复杂的系统性问题,对提高部队指挥、作战、保障能力具有重要意义。主要运用数据包络的方法,不探讨指挥所的内部结构问题,通过对陆军典型部队指挥所输入输出数据进行分析,运用CCR-DEA和超效率DEA模型,对指挥效率问题进行研究排序,并针对输入数据提出改进建议,评估方法简单、可操作性强,对于陆军部队指挥所构建和指挥能力提升具有重要意义。

基于CH-DEA模型的中国制造业产业安全研究

2020年初,新冠疫情在世界范围内全面暴发,中国制造业受冲击显著,影响了中国整体经济健康稳定的发展。因此,分析中国制造业产业安全态势以应对制造业安全风险势在必行。创新地提出CH-DEA方法,并基于产业安全理论建立了制造业安全评价指标体系,从而科学合理地认识中国制造业产业安全现状。结果显示,2005~2020年期间中国制造业产业安全度总体呈现上升趋势,即制造业应对风险等突发事件能力及独立发展能力不断提高。微观障碍因素分析发现,现阶段中国制造业所面临的主要障碍是规模缩减,应利用科研创新能力提升制造业增加值。宏观环境影响因素分析显示,制造业产业安全与GDP、产品市场显著正相关。产品市场的良性竞争可以促使制造企业投入更多的资金采取规模化生产并更新设备,从而提升行业竞争力。

Application of a mixed DEA model to evaluate relative efficiency validity

Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.

基于DEA模型部分传统工业城市转型效率评价研究

在建国初期,国家在部分城市建立了重要的能源战略安全基地,有力保障了新中国工业经济实现大跨越大发展。但随着我国经济发展方式逐渐向高效集约的转变,这些工业型城市也面临着可采能源逐渐枯竭、转型发展迫在眉睫的情况。现从国家分三批确定的69个典型资源枯竭型城市选取8个样本,运用相关性分析法和数据包络分析法(DEA)[1],从技术效益、规模效益、产出不足率等方面对2022年部分工业城市转型效率进行研究,根据模型运算结果剖析各城市投入产出情况,并以数据和现实需求有针对性地给出建议。

基于AHP-DEA法的浙江省科技金融绩效评价及对策研究

科技与金融的有效结合可以有力促进科技创新发展。运用AHP-DEA(层次分析法-数据包络分析法)对2007—2021年浙江省科技金融绩效进行分析。结果表明:浙江省科技金融结合效率呈W形,2013—2019年总体效率较低;科技金融绩效逐年稳步上升,2012—2013年出现停滞,主要因为科技金融投入与产出多个要素下降或增长放缓,且科技金融结合效率较低。浙江省需进一步加大科技金融投入,优化投入结构,更合理、高效配置科技金融资源,以提升科技金融绩效。

Prediction of efficient outputs based on GM(1,N) model and weak DEA efficiency

This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.

基于熵权约束锥DEA的废水输运管材比选研究

废水在输运过程中极易引起集输管道腐蚀和结垢。为减缓因管道腐蚀和结垢引起的堵塞风险,建立以试验数据驱动的熵权约束锥数据包络分析(Data Envelopment Analysis,DEA)管材比选方法。以聚氯乙烯(Polyvinyl Chloride,PVC)、无规共聚聚丙烯(Polypropylene Random,PPR)、丙烯腈丁二烯苯乙烯(Acrylonitrile Butadiene Styrene,ABS)3种常见高分子塑料管材为对象进行研究。基于渗滤液静态浸置管材样片的试验案例,分析3种管材的功能属性。研究结果显示,试验周期内ABS管材的耐腐蚀和抗结垢能力最优,其表面无明显变化,平均结垢量仅为0.448 mg/cm^(2);PPR管材次之,平均结垢量为0.617 mg/cm^(2);PVC管材的腐蚀结垢最为严重,平均结垢量为0.743 mg/cm^(2)。3种管材均对渗滤液中的钙离子和无机碳影响较大,2者在试验周期内质量浓度变化率均超过50%。在此基础上,结合材料的经济性与环境属性评价,发现ABS管材的综合性能最佳,其次为PPR管材和PVC管材。此外,通过将选材结果与其他常见的多准则决策方法评价进行比较,结果显示本文研究方法具有适应性和有效性,可为管材的设计与制造提供参考。

基于DEA与灰色关联算法的航校飞行训练效率分析

随着国内飞行训练航校的蓬勃发展,如何提高航校的飞行训练效率成为热点问题。利用某航校2017—2022年的飞行训练数据,运用数据包络分析(DEA)法对其数据进行时间序列分析,并采用灰色关联度模型对影响因素进行排序。研究结果表明,2017年、2018年、2019年、2021年、2022年DEA为有效,2020年非DEA有效。对DEA模型的结果进行分析,得出2020年各项投入和产出改进值。通过灰色关联度模型将指标对飞行训练综合效率影响程度进行排序,并对结果进行分析,提出改进建议。

DEA模型在首发专项结题评估中的应用研究

目的运用数据包络分析(DEA)模型评估首都卫生发展科研专项绩效。方法选取北京大学人民医院某一年结题的首都卫生发展科研专项项目,初步建立绩效评估指标体系,运用数据包络分析BC2和C2R输出模型。结果有5个项目的综合效率、纯技术效率和规模效率均为1,规模效益最优,被认为是理想状态。有1个项目仅技术有效,其规模效益为递增状态,提示项目承担单位可以考虑适当给该项目匹配一些经费。有3个项目既不是技术有效,也不是规模有效,同时规模效益递减,存在科研产出不足或投入冗余的问题,需根据评估结果进行合理调整。结论DEA模型可以对科研项目结题绩效进行有效评估和个体化分析,基于评估和分析结果,为项目负责人的项目实施和管理部门的策略制定提供依据。

大数据分析在中医教学评价中的应用

在大数据和数字化转型的大背景下,文章分析、阐述了目前中医教学评价的困难以及如何将大数据技术应用在中医教学评价过程中,总结了大数据在中医教学评价过程中的应用方法。首先需要更加广泛地采集数据,包括静态数据、实时数据、非结构化数据等;然后通过系统化的数据标准体系构建,利用数据处理技术,建立全面的教学评价数据仓库;最后结合教学评价业务目标,构建动态数据分析模型,持续不断地以可视化方式直观输出评价结果,真正帮助教师、学生、教学管理者提高教学评价效率,为教学改革提供支撑。

煤炭企业安全生产费用效率评价

为评估我国的煤炭企业安全生产费用效率,选用数据包络分析(DEA)方法,选取2012—2020年煤矿安全投入产出数据构建DEA模型,对煤炭企业每年的安全生产费用效率进行静态分析和评价;随后,利用Malmquist指数对煤炭企业安全生产费用效率作进一步动态分析研究。研究结果表明:从静态分析来看,纯技术效率呈负增长趋势是阻碍综合效率增长的主要原因,煤炭企业安全生产费用应占营业收入的4.23%;从动态分析来看,技术进步和技术效率的提高都会相应提高Malmquist指数,提高我国煤炭企业全要素生产率指数的关键是提高技术进步指数。研究结果可为煤炭企业规范使用安全生产费用提供参考。

一种基于DEA和多指标综合评价的大学科研绩效评价方法

针对传统科研评价方法的局限性,提出一种基于DEA方法和多指标综合评价法的科研绩效评价模型,该模型在多指标综合评价法给出的评价结果的基础上,结合DEA模型的计算结果,对传统评价结果进行合理的修正,使得修正后的结果具有考察不同投入规模单元之间产出绩效的比较分析功能。

运用DEA方法评价地区科技资源配置的相对有效性

本文针对我国东部、中部和西部地区科技资源状况的差异性,运用数据包络分析方法(DEA方法)来评价区域科技资源配置的相对有效性,指出了区域科技资源配置状况的非均衡性,并揭示了影响科技资源配置相对效率的原因。

DEA方法在公路网综合评价中的应用

利用DEA (数据包络分析 )方法建立公路网综合评价的非均一评价模型 ,并给出应用实例。评价结果表明 。

基于DEA的企业技术创新效率评价研究

首先阐述了数据包络分析(DEA)方法的基本原理;其次用SPSS软件对创新投入能力指标和创新产出能力指标进行了筛选,并将DEA方法用于技术创新效率评价的分析研究中;最后应用此方法,选取适当样本,对西安市高新技术企业技术创新进行了效率评价。结果表明该方法不仅可以科学、合理地评价企业技术创新的效率,而且为企业高层管理者采取有效的技术创新策略提供了理论依据和相应的决策支持,具有一定的实用性和可行性。