Achievement and benchmarking of countries at the Summer Olympics using cross efficiency evaluation method

In this paper, an extension tool of data envelopment analysis (DEA), namely cross efficiency evaluation method, is used to measure the performance of the nations participating in the last six Summer Olympic Games. The model in the paper considers two inputs (GDP per capita and population) and three outputs (number of gold, silver and bronze medals won), and the weight restrictions are included to guarantee that a unit of silver medal corresponds to a higher valuation than a unit of bronze medal, and the highest for gold medal. The results for the last six Summer Olympic Games are analyzed, and a unique ordering of the participants based on average cross efficiency is provided, also cluster analysis technique is used to select the more appropriate targets for poorly performing countries to use as benchmarks.     

Measuring the performance of nations at the Summer Olympics using data envelopment analysis

In this paper a well known tool for relative efficiency assessment, namely Data Envelopment Analysis (DEA), is used to measure the performance of the nations participating at the last five Summer Olympic games. The proposed approach considers two inputs (GNP and population) and three outputs (number of gold, silver and bronze medals won). To increase the consistency of the results, weight restrictions are included, guaranteeing a higher valuation for gold medals than for silver medals and higher for the latter than for bronze medals. Variable returns to scale are assumed. The results for the last five Summer Olympics are analysed. For each of them, a performance index as well as benchmarks are computed for each country. In addition, plotting the performance of a specific country for the different games can help identify trends as well as objective successes and disappointments.     

The medal points’ incenter for rankings in sport

This work addresses the issue of finding a system of points for medals in Olympic ranking and scoring systems in sport. The incenter of a convex cone is used to obtain this system. The work deals also with the scoring systems. In applications, we present a ranking of countries in the 2010 Olympic Games and a ranking of drivers in the 2011 Formula One World Championship.     

Partially ordered sets and stratification

We employ partially ordered sets to describe the stratification of a social system, using rank to define the strata. We present a simple method of computing the matrix corresponding to the Hasse diagram and prove its correctness. This methodology is applied to analyze the hierarchy of countries that have won at least one Olympic medal. Four different definitions of dominance are given, leading to four different hierarchies and Hasse diagrams. We also prove that any of these definitions preserve any ordering based on giving different weights to gold, silver, and bronze medals. We study dominance between adjacent strata and note how the system changes with time. We present a case analysis for Poland as an illustration of the set of data that can be computed for any country.     

Measuring the performance of nations at the Olympic Games using DEA models with different preferences

It is well known that Olympic Games often use Lexicographic preference to rank the nations that won the medals. However, Lexicographic preference is not the underlying preference that is used in the standard DEA models. Hence, we discuss the issue of the underlying preferences in DEA models for measuring the performance of nations at the Olympic Games, and then propose new DEA models with Lexicographic preference to measure the performance of the nations.     

加权欧氏距离及其应用

本文定义了加权欧氏距离并讨论了它的性质 ,然后应用加权欧氏距离对 2 0 0 0年奥运金牌榜国家前 10名进行了聚类分析。     

The linear formulation of the ZSG-DEA models with different production technologies

The zero sum gains data envelopment analysis models (ZSG-DEA models) are non-linear. In this paper, we first show that the ZSG-DEA models can be transformed to linear or parametric linear models and discuss the feasible domains of the parameters. Second, we show that the linear formulations of ZSG-DEA models under the equal output reduction strategy and the proportional output reduction strategy in a single output case are equivalent to the output-oriented super-efficiency model under variable returns-to-scale (VRS) assumption. As a matter of course, the models may encounter infeasibility. Third, we propose the linear transformations of ZSG-DEA models under constant returns-to-scale (CRS) assumption and compare them with the VRS models. In the end, we evaluate the participant countries at the Olympic Games by the linear equivalent models with multiple outputs under different weight restrictions. Our results are compared with the efficiencies obtained from the original ZSG-DEA model with an aggregated output under both CRS and VRS assumptions. It is found that the original method with aggregated output tends to underestimate the efficiencies of DMUs.     

AHP model for competitiveness analysis of selected countries

Competitiveness analysis of countries and regions stands in the foreground in recent years. Different methods as well as indicators are used to assess competitiveness, but no single procedure is considered to be the main one and it can hardly be stated, which of the measurement approaches is the most proper. The IMD World Competitiveness Online database represents one of such tools, containing the Overall Competitiveness ranking that evaluates 59 world countries by more than 300 individual indicators in 2012. The paper proposes an original Analytic Hierarchy Process (AHP) model for competitiveness ranking of selected countries. The model is based, due to the high number of indicators and countries, on absolute measurement and expert evaluation. The results given by the AHP model are compared to IMD competitiveness ranking. Differences of both results are analysed and discussed.     

基于APC和GPS数据的青奥会期间南京公共交通的调度与优化

为了得到青奥会期间南京市合理有效的公交调度方案,本文针对青奥会场馆、运动员村、旅游点等附近的南京公共交通线路,建立模型与算法.首先,通过APC数据与GPS数据的匹配,对客流数据进行站点匹配预处理,根据已有客流量数据,训练小波神经网络,从而对客流分布情况进行预测,然后基于客流预测结果,采用有序聚类法,实现客流高低峰时段的合理划分.其次,详细分析调度问题的关键所在,以时段总发车次数和乘客等待时间两个因素作为目标函数,将时段最大、最小发车间隔和满载率等作为约束条件,提出基于APC和GPS的公交车辆辅助调度模型,通过遗传算法对模型进行求解,得出不同时段的发车间隔和配车次数,并对模型的性能进行评估.以南京市D7路公交运营线路的实际客流数据为例,采用MATLAB软件进行仿真实验,得出优化结果.结果表明所建模型是合理的,从而为调度时刻表的生成提供了科学的依据.     

奥运会男子现代五项前三名成绩的灰色预测模型的研究

研究了奥运会男子现代五项前三名成绩的灰色预测模型.将奥运会第16届至第29届男子现代五项前三名成绩数据进行分析处理,采用包络线法和新陈代谢法建立GM(1,1)灰色预测模型,预测了第30届男子现代五项前置名成绩.并对预测结果进行了分析.结果表明:该模型精度较高、预测误差小,预测结果可为我国体育决策部门、教练和运动员提供参...     

奥运会男子十项全能前三名成绩的灰色预测模型的研究

研究了奥运会男子十项全能前三名成绩的灰色预测模型.将奥运会第20届至第28届男子十项全能前三名成绩数据进行分析处理,采用包络线法和新陈代谢法建立GM(1,1)灰色预测模型,该模型不仅贴近实际,还可以对第29届男子十项全能前三名成绩进行预测.     

初始因子在奥运会径赛数据分析中的应用——兼与Johnson R A和Wichern D W教授、王学民同志商榷

这里将初始因子的一些应用观点和结论列出,并通过奥运会男子径赛数据,指出初始因子应用中存在的问题,应用因子分析模型L及其精确解,初始因子解决问题的步骤,解决了奥运会男子径赛数据分析中存在的一些问题.     

Factors affecting primary health care centers’ economic and production efficiency

Little is known about the efficiency of health centers, despite their central role in primary health care strategy for several countries. This study evaluates the health centers in Greece, and identifies factors impeding the achievement of efficiency, with the aim of determining how their efficiency could be improved. Two alternative conceptual models are used to ensure the consistency of the efficiency results: one model is focusing on production efficiency and the other on economic efficiency. Subsequently a second stage analysis is performed to account for the impact of explanatory variables on efficiency. The use of DEA models alongside with bootstrap techniques allows calculating more accurately the efficiency scores that can reflect the performance of health centers more properly. The main drivers of health centers’ technical efficiency for both conceptual models were the location characteristics, the population growth, the mortality rate and the competition. The scale efficiency of health centers in production model is reflected by the size of their respective covered populations, the location characteristics and the mortality rate while the economic model is affected by their size, the location characteristics and the percentage of population working in agriculture. Determining how these variables influence on efficiency is essential for determining performance improvement strategies.     

Mean value and volume-based sensitivity analysis for Olympic rankings

This article describes two methods of creating Olympic rankings based on number of medals won. One method is based on the weighted mean value, which we will show is equivalent to the compromise programming known in Multi-Criteria Decision Analysis (MCDM). The other method uses volume-based sensitivity analysis. Both methods presented in this paper can also be used to construct rankings that include more than just the three top positions.     

从北京奥运会看概率在体育中的体现和应用

概率论是从数量上研究随机现象统计规律性的一门数学学科,在科技、管理、经济等领域具有着重要作用.同样,在充满变数的奥运会里面,也有着广泛的应用和体现.从北京奥运会里面的一些问题加以总结,以扩大对于概率论在体育中应用的了解,增加学习概率论的兴趣.     

A new method for ranking non-extreme efficient units in data envelopment analysis

Data envelopment analysis (DEA) evaluates the performance of decision making units (DMUs). When DEA models are used to calculate efficiency of DMUs, a number of them may have the equal efficiency 1. In order to choose a winner among DEA efficient candidates, some methods have been proposed. But most of these methods are not able to rank non-extreme efficient DMUs. Since, the researches performed about ranking of non-extreme efficient units are very limited, incomplete and with some difficulties, we are going to develop a new method to rank these DMUs in this paper. Therefore, we suppose that DMU _o is a non-extreme efficient under evaluating DMU. In continue, by using “Representation Theorem”, DMU _o can be represented as a convex combination of extreme efficient DMUs. So, we expect the performance of DMU _o be similar to the performance of convex combination of these extreme efficient DMUs. Consequently, the ranking score of DMU _o is calculated as a convex combination of ranking scores of these extreme efficient DMUs. So, the rank of this unit will be determined.     

Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management

The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.     

Applicability and effectiveness of classifications models for achieving the twin objectives of growth and outreach of microfinance institutions

Measuring performance of microfinance institutions (MFIs) is challenging as MFIs must achieve the twin objectives of outreach and sustainability. We propose a new measure to capture the performance of MFIs by placing their twin achievements in a 2 × 2 grid of a classification matrix. To make a dichotomous classification, MFIs that meet both their twin objectives are classified as ‘1’ and MFIs who could not meet their dual objectives simultaneously are designated as ‘0’. Six classifiers are applied to analyze the operating and financial characteristics of MFIs that can offer a predictive modeling solution in achieving their objectives and the results of the classifiers are comprehended using technique for order preference by similarity to ideal solution to identify an appropriate classifier based on ranking of measures of performance. Out of six classifiers applied in the study, kernel lab-support vector machines achieved highest accuracy and lowest classification error rate that discriminates the best achievement of the MFIs’ twin objective. MFIs can use both these steps to identify whether they are on the right path to attaining their multiple objectives from their operating characteristics.     

Supply chain performance evaluation using fuzzy network data envelopment analysis: a case study in automotive industry

Supply chain performance evaluation problems are evaluated using data envelopment analysis. This paper proposes a fuzzy network epsilon-based data envelopment analysis for supply chain performance evaluation. In the common data envelopment analysis models which are used for evaluation of decision-maker units efficiency, there are several inputs and outputs. One of the bugs of such models is that the intermediate products and linking activities are overlooked. Considering these intermediate activities and products, the current study evaluates the performance of decision-maker units in an automotive supply chain. There are ten decision-maker units in the supply chain in which there are three suppliers, two manufacturers, two distributors, and four customers. Moreover, the overall efficiency of input-oriented (input-based) model and input-oriented divisional efficiency are calculated. In order to improve the efficiencies, the projections onto the frontiers are obtained by using the outputs of the solved model and Lingo software. In order to show the applicability of the proposed model, it is applied on automotive industry, as a case study, to evaluate supply chain performance. Then, the overall efficiencies of DMUs and each sections (divisions) of DMUs were calculated separately. Therefore, every organization can apply this evaluation method for improving the performance of alternative factors.

     

奥运会男子现代五项前三名成绩的灰色马尔可夫链预测模型的研究

研究了奥运会男子现代五项前三名成绩的预测模型.将灰色GM(1,1)模型和马尔可夫模型结合,构建了灰色马尔可夫预测模型.对奥运会男子现代五项前三名成绩趋势进行了预测,给出了第30届奥运会男子现代五项前三名成绩的预测结果,并大大提高了预测精度.