Yes / This article examines the potential benefits of solving a stochastic DEA model over solving a deterministic DEA model. It demonstrates that wrong decisions could be made whenever a possible stochastic DEA problem is solved when the stochastic information is either unobserved or limited to a measure of central tendency. We propose two linear models: a semi-stochastic model where the inputs of the DMU of interest are treated as random while the inputs of the other DMUs are frozen at their expected values, and a stochastic model where the inputs of all of the DMUs are treated as random. These two models can be used with any empirical distribution in a Monte Carlo sampling approach. We also define the value of the stochastic efficiency (or semi-stochastic efficiency) and the expected value of the efficiency.

Yes / Data envelopment analysis (DEA) is a technique for identifying the best practices of a given set of decision-making units (DMUs) whose performance is categorized by multiple performance metrics that are classified as inputs and outputs. Although DEA is regarded as non-parametric, the sample size can be an issue of great importance in determining the efficiency scores for the evaluated units, empirically, when the use of too many inputs and outputs may result in a significant number of DMUs being rated as efficient. In the DEA literature, empirical rules have been established to avoid too many DMUs being rated as efficient. These empirical thresholds relate the number of variables with the number of observations. When the number of DMUs is below the empirical threshold levels, the discriminatory power among the DMUs may weaken, which leads to the data set not being suitable to apply traditional DEA models. In the literature, the lack of discrimination is often referred to as the “curse of dimensionality”. To overcome this drawback, we provide a simple approach to increase the discriminatory power between efficient and inefficient DMUs using the well-known pure DEA model, which considers either inputs only or outputs only. Three real cases, namely printed circuit boards, Greek banks, and quality of life in Fortune’s best cities, have been discussed to illustrate the proposed approach. / panish Ministry of Economy, Industry and Competitiveness (Ministerio de Economía, Industria y Competitividad), the State Research Agency (Agencia Estatal de Investigación) and the European Regional Development Fund (Fondo Europeo de Desarrollo Regional) under grant MTM2016-79765-P (AEI/FEDER, UE).

Yes / The traditional Lerner index is limited in its capacity to estimate the level of competition in the economic sector from the perspective that it mainly focuses on the overall level of market power for each individual decision-making unit. Recently, Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) estimated the Lerner index by applying the nonparametric data envelopment analysis (DEA) to calculate the marginal cost, which is an important component in the estimation of the Lerner index. Our study further extends the study of Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) by estimating the marginal cost under the DEA in a multi-product setting. Our proposed methodology benefits from the ability to find positive marginal costs for all the products and specifies all decision-making units are profit maximizers. In order to achieve this, the marginal cost is estimated by referring to the nearest point on the best practice cost-efficient frontier for the profit-maximizing firms. We then apply our innovative method to the Chinese real estate industry. The result shows that the Chinese real estate industry has higher market power in the residential commodity housing market than that in the commodity housing market. This is also the case for different geographical areas in China. Overall, for both of these two different markets, the level of market power experiences a level of volatility.

Univ., Diss.--Münster, 2003.

Le tourisme a été généralement défini comme le voyage d'une personne à une destination pour y faire une escale avant de revenir à son milieu d'origine. La perception d'une destination est donc au centre de l’étude lors de l'examen de laproposition du tourisme expliqué dans le cadre de cette thèse. Mais la perception de la destination a aussi des caractéristiques très difficiles. Afin de vérifier cela, nous devons considérer ce que le marketing des professionnels et des chercheurs ont apporté. Metelka (1990, p.46) et Vukonic (1997) ont défini une destination comme “un lieu géographique où les gens peuvent séjourner », tandis que Gunn (1994) explique une destination comme une zone géographique "suffisamment développé pour répondre aux objectifs de voyageurs" (Gunn, 1994, p.27). De ce point de vue, les destinations touristiques peuvent être associées soit à un pays ou soit à un (ou plusieurs) région, une ville ou des sites touristiques ; la destination est une notion géographique ou spatiale qui est d'abord définie par ses propres visiteurs. Dans la condition où le lieu n’est pas familier au touriste, l'endroit ne peut pas être considéré comme destination. Cependant, de nombreuses questions sont abordées dans la présente thèse pour comprendre comment une place peut devenir ensuite une destination, ainsi que les implications de cette transformation. / Firstly, tourism has been defined as a journey of an individual to a destination for a stopover, then return to his/her origin environment. The perception of a destination is therefore at a centre, considering the tourism proposition explained here. Above and beyond this, the perception of a destination also has significantly difficult characteristics. To verify this, we have to consider what marketing professionals and researchers bring to it. Metelka (1990, p.46) describes a destination as "the geographic location to which someone travels." Vukonic (1997) also relates the term to that factor whereas Gunn (1994) explains a destination is recognised by the travel market as a geographical area "sufficiently developed to meet the objectives of travellers" (Gunn, 1994, p.27). From this standpoint, tourist destinations may have the scope of being a country or (one or more) region, city or an exact site. The destination is a geographical or spatial notion that is first definedby its visitors. In the condition that no stranger visits a place, that place cannot be deliberated as a destination. This image gives the impression of asserting the obvious. However, many issues are discussed in this paper for a place tosubsequently become a destination, as well as the implications of this transformation.

Made available in DSpace on 2016-04-15T00:31:11Z (GMT). No. of bitstreams: 2 Necesio Jose Faria Tavares1.pdf: 2033252 bytes, checksum: 8b63c2b863899e404c67387e2131f57d (MD5) Necesio Jose Faria Tavares2.pdf: 2811029 bytes, checksum: d3712cd52d1b9c01aec2a33386aaf793 (MD5) Previous issue date: 2008-10-20 / DEA, Data Envelopment Analysis, is a non parametric modeling technique which came about in 1976 when three prominent researchers, Charnes, Cooper and Rhodes were in search of a procedure to evaluate productivity/efficiency without recourse to price information. Soon after, new and more complex models were developed with wide acceptance among researchers mainly in the Management Sciences field. Nowadays, DEA finds its use in areas like hospitals, banks, industries, universities and capital markets. This research aims at using DEA as a tool to evaluate the top Brazilian companies listed in the local stock exchange based in a model which simultaneously combine several inputs to generate income and net profits. A second step evaluates how shareholders value the income and profit generated by the firms. A third step evaluates how efficiently each firm succeeds in directly transforming its endowments in shareholder´s value. The proposed model goes further in that it uses outputs produced by a first stage evaluation, like income and net profit, as inputs to the second phase evaluation. Furthermore, this research combines DEA with the Malmquist Productivity Index providing information on how the largest companies went along in between 2001-2006, as far as productivity and efficiency is concerned. / DEA, Data Envelopment Analysis, é uma técnica não paramétrica que surgiu em 1976 quando os pesquisadores Charnes, Cooper e Rhodes procuravam uma metodologia para calcular eficiência e produtividade em situações onde as informações sobre preços de insumos e de produtos não eram disponíveis. Ao longo dos anos seus métodos se sofisticaram, passando de um simples modelo que exigia a restrição de que todas as empresas operavam em uma situação de retornos constantes de escala a modelos mais complexos que levantaram tal restrição. Atualmente, DEA é utilizada em áreas tão diversas como finanças empresariais, mercado de capitais, avaliação de universidades, bases aéreas, bibliotecas, etc. O modelo utilizado nesta tese para avaliação de desempenho empresarial se baseia na modelagem matemática de DEA que permite a utilização de vários inputs e outputs simultaneamente para a determinação da eficiência/produtividade de cada firma. A avaliação de desempenho das empresas é realizada sob 3 óticas distintas: (i) avalia a eficiência da empresa em gerar receita e lucro, (ii) avalia como o mercado valoriza a receita e o lucro produzidos pela empresa, e (iii) analisa também como a empresa consegue transformar seus fatores de produção diretamente em valor ao acionista. DEA permite distinguir os conceitos de eficiência e produtividade, fornecendo relevantes informações para tomada de decisões estratégicas. Como parte do processo de análise, obtém-se uma fronteira das melhores práticas entre as empresas analisadas permitindo a identificação da situação de retornos de escala de cada uma das empresas estudadas. Ademais, torna possível a associação com os conceitos do Índice de Malmquist, possibilitando uma avaliação da trajetória de cada empresa ao longo de um período estudado e identificando como ela evoluiu em termos de eficiência e/ou produtividade e se ela conseguiu acompanhar as inovações tecnológicas de seu grupo.

La question centrale que cherche à aborder cette thèse tourne autour d’une proposition de délimitation du concept de la gouvernance dans les organisations non gouvernementales. La question de la gouvernance a été largement étudiée par les économistes du « public choice » sans pour autant proposer une application aux ONG, chose qui devient nécessaire vu le développement sociétal quantitatif et qualitatif de ces organisations et leurs impacts croissants sur la société. Face aux défaillances des Etats, et aux besoins d’interventions spécifiques dans quelques domaines, des actions collectives organisées ont émergé et se sont développées. L’approche adoptée cherche à présenter en premier lieu l’émergence des normes de coopération et d’entraide pour ensuite définir les structures de propriétés et de prise de décisions au sein des ONG. Cette étude présente ensuite les caractéristiques des différentes composantes du cadre opérationnel des interventions des ONG : relations avec les donateurs, transparence de l’information, structures de coûts… Le choix du Liban émane du caractère unique d’un petit pays qui a connu une prolifération large d’ONG depuis plus qu’une cinquantaine d’années. Après avoir présenté les résultats de l’enquête menée auprès d’un échantillon représentatif des organisations au Liban, on propose un modèle d’évaluation de l’efficacité de l’action de ces organisations basé sur les travaux de Cooper, Charnes et Rhodes sur le modèle de Data Envelopment Analysis DEA. / The central question that this thesis seeks to address revolves around a proposal for delimitation of the concept of governance in non-governmental organizations. The issue of governance has been widely studied by economists of the public choice without nonetheless proposing an application to NGOs, something that has become necessary due to the quantitative and qualitative development of these organizations and their growing impact on society. Given the shortcomings of States, and specific needs that have begun to arise requiring interventions in some areas in societies, organized collective action emerged and developed. The approach used in this proposal seeks to present first the emergence of norms of cooperation and mutual assistance, and then define the properties and structures of decision-making processes within NGOs. This study then presents the characteristics of the different components of the operational framework of NGO interventions: donor relations, information and transparency, cost structures ... The choice of Lebanon comes from the uniqueness of a small country that has seen a large proliferation of NGOs from more than fifty years. presented the results of the survey of 90 organizations in Lebanon, an evaluation of the effectiveness of the action of the organization is presented based on the work of Cooper, Charnes and Rhodes on the model of Data envelopment analysis DEA.

A set of technical issues are addressed related to benchmarking best practice behavior in warehouses. In order to identify best practice, first performance needs to be measured. There are a variety of tools available to measure productivity and efficiency. One of the most common tools is data envelopment analysis (DEA). Given a system that consumes inputs to generate outputs, previous work has shown production theory can be used to develop basic postulates about the production possibility space and to construct an efficient frontier which is used to quantify efficiency. Beyond inputs and outputs warehouses typically have practices (techniques used in the warehouse) or attributes (characteristics of the environment of the warehouse including demand characteristics) which also influence efficiency. Previously in the literature, a two-stage method has been developed to investigate the impact of practices and attributes on efficiency. When applying this method, two issues arose: how to measure efficiency in small samples and how to identify outliers. The small sample efficiency measurement method developed in this thesis is called multi-input / multi-output quantile based approach (MQBA) and uses deleted residuals to estimate efficiency. The outlier detection method introduces the inefficient frontier. Both overly efficient and overly inefficient outliers can be identified by constructing an efficient and an inefficient frontier. The outlier detection method incorporates an iterative procedure previously described, but has not been implemented in the literature. Further, this thesis also discusses issues related to selecting an orientation in super efficiency models. Super efficiency models are used in outlier detection, but are also commonly used in measuring technical progress via the Malmquist index. These issues are addressed using two data sets recently collected in the warehousing industry. The first data set consists of 390 observations of various types of warehouses. The other data set has 25 observations from a specific industry. For both data sets, it is shown that significantly different results are realized if the methods suggested in this document are adopted.

Prediction of corporate bankruptcy (or distress) is one of the major activities in auditing firms’ risks and uncertainties. The design of reliable models to predict distress is crucial for many decision-making processes. Although a variety of models have been designed to predict distress, the relative performance evaluation of competing prediction models remains an exercise that is unidimensional in nature. To be more specific, although some studies use several performance criteria and their measures to assess the relative performance of distress prediction models, the assessment exercise of competing prediction models is restricted to their ranking by a single measure of a single criterion at a time, which leads to reporting conflicting results. The first essay of this research overcomes this methodological issue by proposing an orientation-free super-efficiency Data Envelopment Analysis (DEA) model as a multi-criteria assessment framework. Furthermore, the study performs an exhaustive comparative analysis of the most popular bankruptcy modelling frameworks for UK data. Also, it addresses two important research questions; namely, do some modelling frameworks perform better than others by design? and to what extent the choice and/or the design of explanatory variables and their nature affect the performance of modelling frameworks? Further, using different static and dynamic statistical frameworks, this chapter proposes new Failure Prediction Models (FPMs). However, within a super-efficiency DEA framework, the reference benchmark changes from one prediction model evaluation to another one, which in some contexts might be viewed as “unfair” benchmarking. The second essay overcomes this issue by proposing a Slacks-Based Measure Context-Dependent DEA (SBM-CDEA) framework to evaluate the competing Distress Prediction Models (DPMs). Moreover, it performs an exhaustive comparative analysis of the most popular corporate distress prediction frameworks under both a single criterion and multiple criteria using data of UK firms listed on London Stock Exchange (LSE). Further, this chapter proposes new DPMs using different static and dynamic statistical frameworks. Another shortcoming of the existing studies on performance evaluation lies in the use of static frameworks to compare the performance of DPMs. The third essay overcomes this methodological issue by suggesting a dynamic multi-criteria performance assessment framework, namely, Malmquist SBM-DEA, which by design, can monitor the performance of competing prediction models over time. Further, this study proposes new static and dynamic distress prediction models. Also, the study addresses several research questions as follows; what is the effect of information on the performance of DPMs? How the out-of-sample performance of dynamic DPMs compares to the out-of-sample performance of static ones? What is the effect of the length of training sample on the performance of static and dynamic models? Which models perform better in forecasting distress during the years with Higher Distress Rate (HDR)? On feature selection, studies have used different types of information including accounting, market, macroeconomic variables and the management efficiency scores as predictors. The recently applied techniques to take into account the management efficiency of firms are two-stage models. The two-stage DPMs incorporate multiple inputs and outputs to estimate the efficiency measure of a corporation relative to the most efficient ones, in the first stage, and use the efficiency score as a predictor in the second stage. The survey of the literature reveals that most of the existing studies failed to have a comprehensive comparison between two-stage DPMs. Moreover, the choice of inputs and outputs for DEA models that estimate the efficiency measures of a company has been restricted to accounting variables and features of the company. The fourth essay adds to the current literature of two-stage DPMs in several respects. First, the study proposes to consider the decomposition of Slack-Based Measure (SBM) of efficiency into Pure Technical Efficiency (PTE), Scale Efficiency (SE), and Mix Efficiency (ME), to analyse how each of these measures individually contributes to developing distress prediction models. Second, in addition to the conventional approach of using accounting variables as inputs and outputs of DEA models to estimate the measure of management efficiency, this study uses market information variables to calculate the measure of the market efficiency of companies. Third, this research provides a comprehensive analysis of two-stage DPMs through applying different DEA models at the first stage – e.g., input-oriented vs. output oriented, radial vs. non-radial, static vs. dynamic, to compute the measures of management efficiency and market efficiency of companies; and also using dynamic and static classifier frameworks at the second stage to design new distress prediction models.

Productivity growth in the construction industry is low compared to other industries, and a large unnecessary part of a construction worker’s workday is taken up by nonvalue-creating work, such as waiting, or shifting and handling of building materials. Low productivity in construction projects makes it difficult to keep to schedules and can entail costs to construction companies when delays occur. This project aims to evaluate and investigate, on behalf of Skanska Hus Ume˚a, how productivity in the construction of new apartment buildings can be improved. To carry out this assignment, a large number of qualitative and quantitative interviews have been conducted with employees at Skanska. A survey study has also been sent out to investigate how productivity in selected parts of the construction process is experienced by employees at Skanska. The interviews and the survey study have been used as a starting point for the development of mathematical models with the aim of improving the productivity at Skanska Hus in Ume˚a’s construction sites. The project has resulted in a number of proposals for improvements that can be implemented in Skanska’s current working methods to increase productivity at their construction sites. An implementation of the Data Envelopment Analysis optimization model has identified technical effective and ineffective elements in the construction process, indicating which areas Skanska Hus in Ume˚a should focus on improving. Based on these areas, concrete proposals for new working methods have been prepared and presented based on principles and tools within Lean Construction. The degree project has also resulted in a calculation program that standardizes the working method for the construction of interior walls, resulting in increased productivity as well as time and cost savings. Finally, a model for weekly production follow-up has been created to increase employee engagement, ensure high productivity throughout the construction process and create conditions for future productivity development through data collection. / Produktivitetsutvecklingen i byggbranschen är låg jämfört med andra branscher och en stor del av en yrkesarbetares arbetsdag utgörs av icke värdeadderande arbete, som till exempel väntan, förflyttning och onödig materialhantering. Låg produktivitet inom byggprojekt gör det svårt att hålla uppsatta tidplaner och innebär därmed en kostnad för både byggföretag och kunder när förseningar uppstår. På uppdrag av Skanska Hus i Umeå har detta examensarbete syftat till att utvärdera och undersöka hur produktiviteten vid nyproduktion av flerbostadshus kan förb¨attras. För att besvara problemställningarna har ett stort antal kvalitativa och kvantitativa intervjuer genomförts med anställda på Skanska. En enkätstudie har även skickats ut för att undersöka hur utvalda moment i byggprocessen upplevs av medarbetare på Skanska. Intervjuerna och enkätstudien har använts som underlag vid framtagandet av matematiska modeller med syftet att öka produktiviteten på Skanska Hus i Umeås byggarbetsplatser. Examensarbetet har resulterat i en implementering av optimeringsmodellen Data Envelopment Analysis vilken har identifierat tekniskt effektiva och ineffektiva moment i byggprocessen. Resultatet från Data Envelopment Analysis indikerar vilka områden Skanska Hus i Umeå bör fokusera på att förbättra. Utifrån dessa områden har konkreta förslag på nya arbetssätt tagits fram och presenteras utifrån principer och verktyg inom Lean Construction. Examensarbetet har även resulterat i ett beräkningsprogram som standardiserar arbetssättet vid uppbyggnad och beklädnad av innerväggar vilket ger en ökad produktivitet samt tid- och kostnadsbesparingar. Slutligen har en modell för veckovis produktionsuppföljning skapats för att öka engagemanget hos medarbetarna, säkerställa en hög produktivitet genom hela byggprocessen samt skapa förutsättningar för framtida produktivitetsutveckling genom insamling av data.