Investors, stock exchanges and financial regulatory institutions can be used as strong levers for making firms accountable for achieving sustainable operational performance and not just maximizing profits. The objective of this research study is to enhance the quantitative tools available to stakeholders for evaluating relative operational performance of firms, thereby encouraging the financial investors to base their portfolio investment decisions on the basis of sustainable operational performance of firms. The study reviews the existing literature on evaluating relative operational performance of firms on sustainability metrics and proposes multi-level multi criteria decision making (MCDM) quantitative methods for measuring the same. The research work demonstrates the research framework proposed in the study by evaluating the 2014 Sustainable Operational Performance of firms in the oil & gas sector. The reason for choosing the oil & gas sector for this case study is in view of the relative large ecological and social impact which this industry has on different stakeholders. Due to the same reasons, the oil & gas sector is a bit more advanced in terms of its sustainability performance reporting standards. The review of past literature and the sustainability reports of firms for the year 2014 is initially used to develop the construct for measuring the firm operational performance on three pillars of TBL i.e. for the ecological, social and economic dimensions. / February 2017

Offshore oil and gas exploitation is principally conducted using dry or wet tree systems, otherwise called the subsea Xmas tree system. Due to the shift to deeper waters, subsea production system (SPS) has come to be a preferred technology with attendant economic benefits. At the centre of the SPS is the subsea control module (SCM), responsible for the proper functioning and monitoring of the entire system. With increasing search for hydrocarbons in deep and ultra-deepwaters, the SCM system faces important environmental, safety and reliability challenges and little research has been done in this area. Analysis of the SCM reliability then becomes very fundamental due to the huge cost associated with failure. Several tools are available for this analysis, but the FMECA stands out due to its ability to not only provide failure data, but also showcase the system’s failure modes and mechanisms associated with the subsystems and components being evaluated. However, the technique has been heavily challenged in various literatures for several reasons. To close this gap, a novel multi-criteria approach is developed for the analysis and ranking of the SCM failures modes. This research specifically focusses on subsea tree-mounted electro-hydraulic (E-H) SCM responsible for the underwater control of oil and gas production. A risk identification of the subsea control module is conducted using industry experts. This is followed by a comprehensive component based FMECA analysis of the SCM conducted with the conventional RPN technique, which reveals the most critical failure modes for the SCM. A novel framework is developed using multi-criteria fuzzy TOPSIS methodology and applied to the most critical failure modes obtained from the FMECA evaluation using unconventional parameters. Finally, a validation of these results is performed using a stochastic input evaluation and SCM failure data obtained from the offshore industry standard reliability database, OREDA.

This diploma thesis deals with description of methods and original on-line application for solving multicriteria evaluation of alternatives problems. Methods based on maximisation of utility value (WSA), minimisation of distance from ideal alternative (TOPSIS), evaluation of preference relations (ELECTRE) and evaluation along preference flows (PROMETHEE) are described and implemented in the application. The thesis introduces an original web application written in PHP language which is developed for solving multicriteria evaluation of alternatives problems in internet environment. The application running on web-server allows solving multicriteria evaluation of alternatives problems by four above mentioned methods. The application is controlled by any web browser. A run-time complexity of used algorithms is measured and discussed.

Cílem diplomové práce je aplikace modelů vícekriteriálního rozhodování na reálný rozhodovací problém ve firmě INVEST TEL AUTO s.r.o. V praktické části je pomocí několika metod vícekriteriálního hodnocení variant nejprve vybrána nejvhodnější automobilová značka, poté je pomocí metod spojitého vícekriteriálního rozhodování navržena skladba první objednávky vozů vybrané automobilové značky.

Demand responsive transport services are nowadays an established and recognized way to provide better social inclusion to non-urban, low population density areas. The concept has its origins in the 70´s in the USA, but just recently the advances in technology made this type of service more economically attractive. Therefore is of no surprise that this kind of transportation is starting to be a serious option in several regions across Europe. The European Commission has been promoting projects to study and implement DRT services. One of these projects, MASCARA (deMand responsive trAnsport service for increasing Social Cohesion in urbAn/Rural Areas), involved a team from the Engineering School of the University of Porto, with the participation of the author. The MASCARA project was designed to promote the cooperation between several regions in Europe to share knowledge about DRT services, evaluating DRT pilots and DRT feasibility studies. This dissertation focus on the design of a framework to help this evaluation. The work resulted in combining two known multi-criteria methodologies, namely AHP and TOPSIS. Albeit these methods were designed to help choosing (ranking) between two or more possible scenarios, the proposed framework is able to evaluate and score one scenario situations. This work can be viewed as having two parts: the first one (from chapter 1 to chapter 4) deals with the design of the framework and methodology. From chapter 5 onwards the practical application is adressed. The author work was focused on the design and software implementation of the evaluation framework.

Offshore oil and gas exploitation is principally conducted using dry or wet tree systems, otherwise called the subsea Xmas tree system. Due to the shift to deeper waters, subsea production system (SPS) has come to be a preferred technology with attendant economic benefits. At the centre of the SPS is the subsea control module (SCM), responsible for the proper functioning and monitoring of the entire system. With increasing search for hydrocarbons in deep and ultra-deepwaters, the SCM system faces important environmental, safety and reliability challenges and little research has been done in this area. Analysis of the SCM reliability then becomes very fundamental due to the huge cost associated with failure. Several tools are available for this analysis, but the FMECA stands out due to its ability to not only provide failure data, but also showcase the system’s failure modes and mechanisms associated with the subsystems and components being evaluated. However, the technique has been heavily challenged in various literatures for several reasons. To close this gap, a novel multi-criteria approach is developed for the analysis and ranking of the SCM failures modes. This research specifically focusses on subsea tree-mounted electro-hydraulic (E-H) SCM responsible for the underwater control of oil and gas production. A risk identification of the subsea control module is conducted using industry experts. This is followed by a comprehensive component based FMECA analysis of the SCM conducted with the conventional RPN technique, which reveals the most critical failure modes for the SCM. A novel framework is developed using multi-criteria fuzzy TOPSIS methodology and applied to the most critical failure modes obtained from the FMECA evaluation using unconventional parameters. Finally, a validation of these results is performed using a stochastic input evaluation and SCM failure data obtained from the offshore industry standard reliability database, OREDA.

For any given reason, every year many countries spend a lot of money purchasing at least one weapon. Due to the secret character of the military, the decision process for specific weapon procurement is shrouded. Moreover, there are several funds loss cases due to mistakes in weapon contractions. Weapon procurement requires very large amounts of money which comes from tax payers. Therefore, an effort to reduce a possible monetary loss is needed. A decision process based on an analytic model can present a better chance to decision makers for better weapon decisions. In general, weapon procurement decision is a multi criteria environment. Decision making in such environments is defined as Multi-Criteria Decision Making (MCDM). MCDM is broadly classified into two areas: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM). MADM methods are used for selecting an alternative from a small explicit list of alternatives. MODM methods are used for designing problems involving an infinite number of alternatives implicitly defined by mathematical constraints. This research is intended to be used by the South Korean Navy when there is a need to select one weapon type among several candidate types. Therefore, MADM methods are used in this research.Many researches for developing an analytical model for better decision-making have been done. However, there is no research for a generalized weapon procurement decision model that is easy to implement. For this reason, whenever there is a need for weapon procurement decision, the Navy has to spend a lot of effort in determining the best weapon. These efforts can be reduced with a generalized model that is proposed in this research for naval weapon procurement. MADM methods determine alternatives ranking orders and the highest ranked alternative is the best one. Various MADM methods are used in computing the alternatives ranking scores.

Οι επιχειρήσεις λειτουργούν και αναπτύσσονται σε ένα περιβάλλον που συνεχώς εξελίσσεται και αλλάζει και όπως είναι φυσικό οφείλουν να προσαρμόζονται στα νέα δεδομένα. Το προσωπικό των επιχειρήσεων αποτελεί ένα σημαντικό παράγοντα για την επιβίωση, την εξέλιξη και γενικά την καλή λειτουργία των επιχειρήσεων. Η παρούσα διπλωματική εργασία πραγματεύεται το πρόβλημα της επιλογής και αξιολόγησης του προσωπικού μιας επιχείρησης. Πρέπει να αναφέρουμε ότι είναι δύο ξεχωριστά προβλήματα που έχουμε να αντιμετωπίσουμε, η επιλογή και η αξιολόγηση, χωρίς αυτό να σημαίνει ότι δεν συνδέονται ή ότι δεν μπορούν να χρησιμοποιηθούν παρόμοια εργαλεία επίλυσης. Έχουν προταθεί αρκετά μαθηματικά υποδείγματα για την επίλυση αυτού του προβλήματος. Τα μαθηματικά υποδείγματα που χρησιμοποιούνται για την επίλυση αυτών των προβλημάτων σκοπό έχουν να βοηθήσουν τους αποφασίζοντες να πάρουν ορθότερες αποφάσεις. Με τη χρήση μαθηματικών μεθοδολογιών για την επιλογή και αξιολόγηση του προσωπικού, επιτυγχάνεται μεγαλύτερη αντικειμενικότητα καθώς και η τυποποίηση της διαδικασίας. Μία τέτοια μεθοδολογία είναι και η TOPSIS, μια από τις πρώτες που παρουσιάστηκε στη βιβλιογραφία. Είναι μια εύκολα εφαρμόσιμη μέθοδος και με αξιόπιστα αποτελέσματα. / Organizations function and grow in an environment that is constantly developing and changing, so they have to adjust with the new data. The personnel has a crucial role for the survival, the evolution and generally the good function of every organization. This dissertation is about the problem of selection and evaluation an organization's personnel. Many mathematical patterns have been proposed for the solution of this problem. We will discuss some of them with details in this dissertation. At this point, we must mention that selection and evaluation process are two different problems that we have to face. This does not mean that they do not connect or that we can not solve both with the same tools. Certainly, the first step is the choice of an employee and the second is the evaluation. Choosing the right employee for the right job is a very difficult problem and that because is hard to judge objectively the candidates΄ personalities. Also, it is difficult to decide about the criteria, based on which the choice will be maid. For example, the experience or the knowledge is more important for a certain job, and how that’s can be represent with numbers or functions at a mathematical pattern. Organizations have to ensure that they made the right choice of a new employee and afterwards they have to measure the efficiency of the other employees. In the first step, we try to predict the future working behavior of a new employee, as well as in the second to describe the working behavior of the employees that already working in an organization.

Submitted by Eduardo Silbert (eduardosilbert@outlook.com) on 2017-07-11T16:11:16Z No. of bitstreams: 1 Dissertação_Eduardo_Silbert.pdf: 2002407 bytes, checksum: f44ff42733828e5dbf20ee290d0903c1 (MD5) / Approved for entry into archive by Maria Almeida (maria.socorro@fgv.br) on 2017-07-20T19:04:11Z (GMT) No. of bitstreams: 1 Dissertação_Eduardo_Silbert.pdf: 2002407 bytes, checksum: f44ff42733828e5dbf20ee290d0903c1 (MD5) / Made available in DSpace on 2017-07-20T19:05:06Z (GMT). No. of bitstreams: 1 Dissertação_Eduardo_Silbert.pdf: 2002407 bytes, checksum: f44ff42733828e5dbf20ee290d0903c1 (MD5) Previous issue date: 2017-05-31 / Episódios como a intervenção da ANEEL no grupo Rede Energia em 2012 despertam discussões acerca do papel do regulador e de que forma situações como essa poderiam ser evitadas por meio do uso e aplicação de instrumentos e mecanismos de monitoramento das empresas concessionárias. Neste contexto, ferramentas capazes de proporcionar precisão na tomada de decisão e uma análise profunda dos indicadores dessas empresas podem ser muito úteis. Assim, o presente trabalho sugere a aplicação de uma metodologia para desenvolvimento de um ranking de distribuidoras do setor elétrico brasileiro com o objetivo de classificar as empresas de forma a tornar mais precisa, transparente e eficaz a ação do regulador, sendo capaz assim de prevenir casos como o do Rede. A pesquisa é fundada no uso de índices/critérios quantitativos e qualitativos e no método de análise multicritério TOPSIS, responsável por hierarquizar as distribuidoras. Para ilustrar a metodologia, serão apresentados exemplos numéricos com base em indicadores financeiros, operacionais e de governança corporativa de uma amostra de distribuidoras.

Este trabalho apresenta o processo de seleção de estratégia de reconversão industrial de uma pequena refinaria de petróleo no Sul do Brasil através da aplicação de uma modelagem integrada, utilizando um método multicriterial e programação matemática. Neste estudo foram identificadas linhas de negócio potencialmente aplicáveis à realidade da companhia e definido um conjunto de critérios de análise abrangendo as três dimensões da sustentabilidade empresarial: econômica, social e ambiental. Com base na avaliação da importância relativa de cada critério, atribuída por um grupo de decisores, e no desempenho das linhas de negócio em cada um dos critérios, foi aplicado método fuzzy TOPSIS para análise e ordenação das linhas de negócio. As informações resultantes desta análise, juntamente com dados econômicos objetivos, foram utilizadas em um modelo de programação linear inteira para avaliar portfólios viáveis de linhas de negócio, identificando estratégias candidatas à implementação na refinaria. O desempenho global de cada estratégia candidata, obtido mediante agregação dos desempenhos individuais das linhas de negócio e calculado conforme método fuzzy TOPSIS, foi analisado através de ferramentas gráficas, de modo a gerar elementos para subsidiar a seleção da melhor estratégia de reconversão. Os resultados obtidos demonstraram a eficiência da abordagem proposta, no sentido de facilitar o entendimento e a exploração da situação problema e, assim, oferecer um adequado suporte à tomada de decisão. / This dissertation presents a selection process of industrial reconversion strategy in a small oil refinery in southern Brazil by applying an integrated modeling approach, using a multicriteria and a mathematical programming method. Potentially performing business lines were identified, as well a set of criteria covering the three dimensions of corporate sustainability: economic, social and environmental. Based on the relative importance evaluation of each criteria given by a group of decision-makers, and on performance of the business lines in each of the criteria, fuzzy TOPSIS method was applied for analysis and sorting of business lines. The information resulting from this analysis, along with objective economic data, were used in integer linear programming model to evaluate effective portfolios of business lines, identifying candidate strategies to implement in the refinery. Fuzzy TOPSIS is used to generate overall performance scores of each candidate strategy, aggregating the individual performance of the business lines. The sustainability assessment was analyzed through graphical tools in order to generate information to support the selection of the best strategy for the industrial reconversion. The results demonstrated the efficiency of the proposed approach to facilitate the understanding and exploitation of the problem situation and thus offer adequate support to decision making.