Evaluation efficiency of large-scale data set with negative data:an artificial neural network approach

Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and productivity of decision-making units (DMUs). The need for huge computer resources in terms of memory and CPU time in DEA is inevitable for a large-scale data set, especially with negative measures. In recent years, wide ranges of studies have been conducted in the area of artificial neural network and DEA combined methods. In this study, a supervised feed-forward neural network is proposed to evaluate the efficiency and productivity of large-scale data sets with negative values in contrast to the corresponding DEA method. Results indicate that the proposed network has some computational advantages over the corresponding DEA models; therefore, it can be considered as a useful tool for measuring the efficiency of DMUs with (large-scale) negative data.

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

Performance analysis of brazilian public and philanthropic hospitals

This paper presents the results of a research that aimed at identifying optimal performance standards of Brazilian public and philanthropic hospitals. In order to carry out the analysis, a model based on Data Envelopment Analysis (DEA) was developed. We collected financial data from hospitals’ financial statements available on the internet, as well as operational data from the Information Technology Department of the Brazilian Public Health Care System – SUS (DATASUS). Data from 18 hospitals from 2007 to 2011 were analyzed. Our DEA model used both operational and financial indicators (variables). In order to develop this model, two indicators were considered inputs: Values (in Brazilian Reais) of Fixed Assets and Planned Capacity. On the other hand, the following indicators were considered outputs: Net Margin, Return on Assets and Institutional Mortality Rate. As regards the proposed model, there were five hospitals with optimal performance and four hospitals were considered inefficient, upon the analysis of the variables, considering the analyzed period. Analysis of the weights indicated the most relevant variables for determining efficiency and scale variable values, which is an important tool to aid the decision-making by hospital managers. Finally, the scale variables determined the returns on production, indicating that 14 hospitals work with scale diseconomies. This may indicate inefficiency in the resource management of the Brazilian public health-care system, by analyzing this set of proposed variables.

A comparative benchmarking analysis of main Iberian container terminals: a DEA approach

Benchmarking is an important tool to organisations to improve their productivity, product quality, process efficiency or services. From Benchmarking the organisations could compare their performance with competitors and identify their strengths and weaknesses. This study intends to do a benchmarking analysis on the main Iberian Sea ports with a special focus on their container terminals efficiency. To attain this, the DEA (data envelopment analysis) is used since it is considered by several researchers as the most effective method to quantify a set of key performance indicators. In order to reach a more reliable diagnosis tool the DEA is used together with the data mining in comparing the sea ports operational data of container terminals during 2007.Taking into account that sea ports are global logistics networks the performance evaluation is essential to an effective decision making in order to improve their efficiency and, therefore, their competitiveness.

Azorean Agriculture Efficiency by PAR

Copyright © 2013 Springer Netherlands.

Sustainable Tourism and Agriculture Multifunctionality by PAR: A Variable Selection Approach

Copyright © 2013 Springer Netherlands.

Efficiency Measures in the Agricultural Sector: With Applications

Copyright 2013 Springer Netherlands.

Shiva's dance: Crisis, local institutions and private firms

The uneven spatial distribution of start-ups and their respective survival may reflect comparative advantages resulting from the local institutional background. For the first time, we explore this idea using Data Envelopment Analysis (DEA) to assess the relative efficiency of Portuguese municipalities in this specific context. We depart from the related literature where expenditure is perceived as a desirable input by choosing a measure of fiscal responsibility and infrastructural variables in the first stage. Comparing results for 2006 and 2010, we find that mean performance decreased substantially 1) with the effects of the Global Financial Crisis, 2) as municipal population increases and 3) as financial independence decreases. A second stage is then performed employing a double-bootstrap procedure to evaluate how the regional context outside the control of local authorities (e.g. demographic characteristics and political preferences) impacts on efficiency.

Determinants of school efficiency : The case of primary schools in the State of Geneva, Switzerland

The public primary school system in the State of Geneva, Switzerland, is characterized by centrally evaluated pupil performance measured with the use of standardized tests. As a result, consistent data are collected among the system. The 2010-2011 dataset is used to develop a two-stage data envelopment analysis (DEA) of school efficiency. In the first stage, DEA is employed to calculate an individual efficiency score for each school. It shows that, on average, each school could reduce its inputs by 7% whilst maintaining the same quality of pupil performance. The cause of inefficiency lies in perfectible management. In the second stage, efficiency is regressed on school characteristics and environmental variables;external factors outside of the control of headteachers. The model is tested for multicollinearity, heteroskedasticity and endogeneity. Four variables are identified as statistically significant. School efficiency is negatively influenced by (1) the provision of special education, (2) the proportion of disadvantaged pupils enrolled at the school and (3) operations being held on multiple sites, but positively influenced by school size (captured by the number of pupils). The proportion of allophone pupils; schools located in urban areas and the provision of reception classes for immigrant pupils are not significant. Although the significant variables influencing school efficiency are outside of the control of headteachers, it is still possible to either boost the positive impact or curb the negative impact. Dans le canton de Genève (Suisse), les écoles publiques primaires sont caractérisées par un financement assuré par les collectivités publiques (canton et communes) et par une évaluation des élèves à l'aide d'épreuves standardisées à trois moments distincts de leur scolarité. Cela permet de réunir des informations statistiques consistantes. La base de données de l'année 2010-2011 est utilisée dans une analyse en deux étapes de l'efficience des écoles. Dans une première étape, la méthode d'analyse des données par enveloppement (DEA) est utilisée pour calculer un score d'efficience pour chaque école. Cette analyse démontre que l'efficience moyenne des écoles s'élève à 93%. Chaque école pourrait, en moyenne, réduire ses ressources de 7% tout en conservant constants les résultats des élèves aux épreuves standardisées. La source de l'inefficience réside dans un management des écoles perfectible. Dans une seconde étape, les scores d'efficience sont régressés sur les caractéristiques des écoles et sur des variables environnementales. Ces variables ne sont pas sous le contrôle (ou l'influence) des directeurs d'école. Le modèle est testé pour la multicolinéartié, l'hétéroscédasticité et l'endogénéité. Quatre variables sont statistiquement significatives. L'efficience des écoles est influencée négativement par (1) le fait d'offrir un enseignement spécialisé en classe séparée, (2) la proporition d'élèves défavorisés et (3) le fait d'opérer sur plusieurs sites différents. L'efficience des écoles est influencée positivement par la taille de l'école, mesurée par le nombre d'élèves. La proporition d'élèves allophones, le fait d'être situé dans une zone urbaine et d'offrir des classes d'accueil pour les élèves immigrants constituent autant de variables non significatives. Le fait que les variables qui influencent l'efficience des écoles ne soient pas sous le contrôle des directeurs ne signifie pas qu'il faille céder au fatalisme. Différentes pistes sont proposées pour permettre soit de réduire l'impact négatif soit de tirer parti de l'impact positif des variables significatives.

Essays on the measurement of school efficiency

Measuring school efficiency is a challenging task. First, a performance measurement technique has to be selected. Within Data Envelopment Analysis (DEA), one such technique, alternative models have been developed in order to deal with environmental variables. The majority of these models lead to diverging results. Second, the choice of input and output variables to be included in the efficiency analysis is often dictated by data availability. The choice of the variables remains an issue even when data is available. As a result, the choice of technique, model and variables is probably, and ultimately, a political judgement. Multi-criteria decision analysis methods can help the decision makers to select the most suitable model. The number of selection criteria should remain parsimonious and not be oriented towards the results of the models in order to avoid opportunistic behaviour. The selection criteria should also be backed by the literature or by an expert group. Once the most suitable model is identified, the principle of permanence of methods should be applied in order to avoid a change of practices over time. Within DEA, the two-stage model developed by Ray (1991) is the most convincing model which allows for an environmental adjustment. In this model, an efficiency analysis is conducted with DEA followed by an econometric analysis to explain the efficiency scores. An environmental variable of particular interest, tested in this thesis, consists of the fact that operations are held, for certain schools, on multiple sites. Results show that the fact of being located on more than one site has a negative influence on efficiency. A likely way to solve this negative influence would consist of improving the use of ICT in school management and teaching. Planning new schools should also consider the advantages of being located on a unique site, which allows reaching a critical size in terms of pupils and teachers. The fact that underprivileged pupils perform worse than privileged pupils has been public knowledge since Coleman et al. (1966). As a result, underprivileged pupils have a negative influence on school efficiency. This is confirmed by this thesis for the first time in Switzerland. Several countries have developed priority education policies in order to compensate for the negative impact of disadvantaged socioeconomic status on school performance. These policies have failed. As a result, other actions need to be taken. In order to define these actions, one has to identify the social-class differences which explain why disadvantaged children underperform. Childrearing and literary practices, health characteristics, housing stability and economic security influence pupil achievement. Rather than allocating more resources to schools, policymakers should therefore focus on related social policies. For instance, they could define pre-school, family, health, housing and benefits policies in order to improve the conditions for disadvantaged children.

DEA does not like positive discrimination : a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of data envelopment analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run themselves their own efficiency analysis. Within DEA, several alternative models allow for an environment adjustment. Five alternative models, each of them easily accessible to and achievable by practitioners and decision makers, are performed using the empirical case of the 90 primary schools of the State of Geneva, Switzerland. As the State of Geneva practices an upstream positive discrimination policy towards schools, this empirical case is particularly appropriate for an environment adjustment. The alternative of the majority of DEA models deliver divergent results. It is a matter of concern for applied researchers and a matter of confusion for practitioners and decision makers. From a political standpoint, these diverging results could lead to potentially opposite decisions. Grâce à l'existence de logiciels en libre accès et de guides pédagogiques, la méthode data envelopment analysis (DEA) s'est démocratisée ces dernières années. Aujourd'hui, il n'est pas rare que les décideurs avec peu ou pas de connaissances en recherche opérationnelle réalisent eux-mêmes leur propre analyse d'efficience. A l'intérieur de la méthode DEA, plusieurs modèles permettent de tenir compte des conditions plus ou moins favorables de l'environnement. Cinq de ces modèles, facilement accessibles et applicables par les décideurs, sont utilisés pour mesurer l'efficience des 90 écoles primaires du canton de Genève, Suisse. Le canton de Genève pratiquant une politique de discrimination positive envers les écoles défavorisées, ce cas pratique est particulièrement adapté pour un ajustement à l'environnement. La majorité des modèles DEA génèrent des résultats divergents. Ce constat est préoccupant pour les chercheurs appliqués et perturbant pour les décideurs. D'un point de vue politique, ces résultats divergents conduisent à des prises de décision différentes selon le modèle sur lequel elles sont fondées.

Relative Technical Efficiency of European Transportation Systems

Talouden kasvaessa myös tavarankuljetusmäärät kasvavat. Kuljetusjärjestelmät ja niiden sujuva toiminta on erittäin tärkeää taloudellisen kasvun kannalta tällä hetkellä, ja se tulee olemaan yhä tärkeämpää tulevaisuudessa. Tulevaisuudessa tarvitaan kokonaisvaltainen ja selkeästi tehokkaampi kuljetusjärjestelmä, mikäli tulevaisuuden kuljetusvirrat halutaan hoitaa kestävästi. Tässä opinnäytetyössäni tutkin kolmen eurooppalaisen kuljetusjärjestelmän (rautatiet, lentoliikenne ja konttiliikenne meritse) suhteellista teknistä tehokkuutta ja menetelmänä on data envelopment analysis (DEA). Vertailtaessa kuljetusjärjestelmiä löytyi suuria eroja kuljetusmuotojen välille. lentoyhtiöt suoriutuivat huomattavan tasaisesti eli tehokkaiden ja ei-tehokkaiden toimijoiden välillä ei ollut suuria eroja. Rautatiepuolella erot venyivät huomattavan suuriksi niin eri yritysten välillä kuin jopa saman yrityksen sisällä eri vuosina. Pikaisemmassa laivayhtiöiden tarkastelussa erot niiden välillä olivat lähes yhtä pieniä kuin lentoyhtiöiden välillä. Tarkasteltaessa omistajuuden vaikutusta lentoyhtiöiden toiminnassa huomattiin, että yksityisessä omistuksessa olevat yritykset olivat huomattavasti tehokkaampia matkustajien kuljettamisessa. Rahtipuolella merkittäviä eroja ei havaittu. Merkittävät korrelaatiot eri mallien välillä antoivat joitain viitteitä myös kuljetuspoliittiseen päätöksentekoon; investoinnit matkustajienkuljetuksiin raiteilla parantaisivat koko rautatiepuolen teokkuutta, mutta myös samalla lentopuolen matkustajakuljetuksen tehokkuutta.

Determinants of school efficiency : The case of primary schools in the State of Geneva, Switzerland

Purpose The purpose of this paper is (1) to measure school technical efficiency and (2) to identify the determinants of primary school performance. Design/methodology/approach A two-stage Data Envelopment Analysis (DEA) of school efficiency is conducted. At the first stage, DEA is employed to calculate an individual efficiency score for each school. At the second stage, efficiency is regressed on school characteristics and environmental variables. Findings The mean technical efficiency of schools in the State of Geneva is equal to 93%. By improving the operation of schools, 7% (100 - 93) of inputs could be saved, representing 17'744'656.2 Swiss francs in 2010. School efficiency is negatively influenced by (1) operations being held on multiple sites, (2) the proportion of disadvantaged pupils enrolled at the school and (3) the provision of special education, but positively influenced by school size (captured by the number of pupils). Practical implications Technically, the determinants of school efficiency are outside of the control of the headteachers. However, it is still possible to either boost the positive impact or curb the negative impact. Potential actions are discussed. Originality/value Unlike most similar studies, the model in this study is tested for multicollinearity, heteroskedasticity and endogeneity. It is therefore robust. Moreover, one explanatory variable of school efficiency (operations being held on multiple sites) is a truly original variable as it has never been tested so far.

Railway Wagon Market Analysis and New Multi-Purpose Wagon Solution for Freight Transports - Finnish Manufacturing Perspective

Rautateillä käytettävät tavaravaunut ovat vanhenemassa hyvin nopeasti; tämä koskee niin Venäjää, Suomea, Ruotsia kuin laajemminkin Eurooppaa. Venäjällä ja Euroopassa on käytössä runsaasti vaunuja, jotka ovat jo ylittäneet niille suositeltavan käyttöiän. Silti niitä käytetään kuljetuksissa, kun näitä korvaavia uusia vaunuja ei ole tarpeeksi saatavilla. Uusimmat vaunut ovat yleensä vaunuja vuokraavien yritysten tai uusien rautatieoperaattorien hankkimia - tämä koskee erityisesti Venäjää, jossa vaunuvuokraus on noussut erittäin suosituksi vaihtoehdoksi. Ennusteissa kerrotaan vaunupulan kasvavan ainakin vuoteen 2010 saakka. Jos rautateiden suosio rahtikuljetusmuotona kasvaa, niin voimistuva vaunukysyntä jatkuu huomattavan paljon pidemmän aikaa. Euroopan ja Venäjän vaunukannan tilanne näkyy myös sitä palvelevan konepajateollisuuden ongelmina - yleisesti ottaen alan eurooppalaiset yritykset ovat heikosti kannattavia ja niiden liikevaihto ei juuri kasva, venäläiset ja ukrainalaiset yritykset ovat olleet samassa tilanteessa, joskin aivan viime vuosina tilanne on osassa kääntynyt paremmaksi. Kun näiden maanosien yritysten liikevaihtoa, voittoa ja omistaja-arvoa verrataan yhdysvaltalaisiin kilpailijoihin, huomataan että jälkimmäisten suoriutuminen on huomattavan paljon parempaa, ja näillä yrityksillä on myös kyky maksaa osinkoja omistajilleen. Tutkimuksen tarkoituksena oli kehittää uuden tyyppinen kuljetusvaunu Suomen, Venäjän sekä mahdollisesti myös Kiinan väliseen liikenteeseen. Vaunutyypin tarkoituksena olisi kyetä toimimaan monikäyttöisenä, niin raaka-aineiden kuin konttienkin kuljetuksessa, tasapainottaen kuljetusmuotojen aiheuttamaa kuljetuspaino-ongelmaa. Kehitystyön pohjana käytimme yli 1000 venäläisen vaunutyypin tietokantaa, josta valitsimme Data Envelopment Analysis -menetelmällä soveliaimmat vaunut kontinkuljetukseen (lähemmin tarkastelimme n. 40 vaunutyyppiä), jättäen mahdollisimman vähän tyhjää tilaa junaan, mutta silti kyeten kantamaan valitun konttilastin. Kun kantokykyongelmia venäläisissä vaunuissa ei useinkaan ole, on vertailu tehtävissä tavarajunan pituuden ja kokonaispainon perusteella. Simuloituamme yhdistettyihin kuljetuksiin soveliasta vaunutyyppiä käytännössä löytyvässä kuljetusverkostossa (esim. raakapuuta Suomeen tai Kiinaan ja kontteja takaisin Venäjän suuntaan), huomasimme lyhemmän vaunupituuden sisältävän kustannusetua, erityisesti raakaainekuljetuksissa, mutta myös rajanylityspaikkojen mahdollisesti vähentyessä. Lyhempi vaunutyyppi on myös joustavampi erilaisten konttipituuksien suhteen (40 jalan kontin käyttö on yleistynyt viime vuosina). Työn lopuksi ehdotamme uuden vaunutyypin tuotantotavaksi verkostomaista lähestymistapaa, jossa osa vaunusta tehtäisiin Suomessa ja osa Venäjällä ja/tai Ukrainassa. Vaunutyypin tulisi olla rekisteröity Venäjälle, sillä silloin sitä voi käyttää Suomen ja Venäjän, kuten myös soveltuvin osin Venäjän ja Kiinan välisessä liikenteessä.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.