This research explores the feasibility of providing innovative and effective solutions for traffic congestion. The design of reservation systems is being considered as an alternative and/or complementary travel demand management (TDM) strategy. A reservation indicates that a user will follow a booking procedure defined by the reservation system before traveling so as to obtain the right to access a facility or resource. In this research, the reservation system is introduced for a cordon-based downtown road network, hereafter called the Downtown Space Reservation System (DSRS). The research is executed in three steps. In the first step, the DSRS is developed using classic optimization techniques in conjunction with an artificial intelligence technology. The development of this system is the foundation of the entire research, and the second and third steps build upon it. In the second step, traffic simulation models are executed so as to assess the impact of the DSRS on a hypothetical transportation road network. A simulation model provides various transportation measures and helps the decision maker analyze the system from a transportation perspective. In this step, multiple simulation runs (demand scenarios) are conducted and performance insights are generated. However, additional performance measurement and system design issues need to be addressed beyond the simulation paradigm. First, it is not the absolute representation of performance that matters, but the concept of relative performance that is important. Moreover, a simulation does not directly demonstrate how key performance measures interact with each other, which is critical when trying to understand a system structure. To address these issues, in the third step, a comprehensive performance measurement framework has been applied. An analytical technique for measuring the relative efficiency of organizational units, or in this case, demand scenarios called network Data Envelopment Analysis (DEA), is used. The network model combines the perspectives of the transportation service provider, the user and the community, who are the major stakeholders in the transportation system. This framework enables the decision maker to gain an in-depth appreciation of the system design and performance measurement issues. / Ph. D.

This dissertation brings together the areas of safety science and operations management through a mixed-methods approach to investigate the complex relationships between two, often conflicting, organizational goals - efficiency and safety, in sociotechnical systems (STSs). This research mainly focuses on production pressure (PrP) which is considered as one of the main negative outcomes of overprioritizing the efficiency aspect of STSs. This work seeks to introduce novel methodologies for assessing PrP in real time for the purpose of mitigating its risks and unwanted consequences, particularly in safety critical environments such as traffic control centers (TCCs). Essay 1 concentrates on the theoretical underpinnings of PrP by systematically reviewing the existing literature to clarify and unify the concept under the context of safety science. It identifies key factors contributing to PrP, its negative effects on safety performance in various industries, and potential mitigation strategies. By doing so, this essay contributes to the field through laying the groundwork for more effective management strategies to improve workplace safety. Essay 2 addresses a significant gap identified in Essay 1 by developing a methodology based on Data Envelopment Analysis (DEA) for the ongoing measurement and monitoring of PrP. This innovative approach introduces a quantitative mechanism that juxtaposes efficiency and safety related outcomes of hourly performance in safety critical environments. This proposed method allows for a detailed analysis of performance dynamics within STSs. The practical application of this model is demonstrated through its implementation in the infrastructure management system of INFRABEL, the Belgian National Railroad Company. Essay 3 advances the conversation by tackling the predictive limitations of the DEA model established in Essay 2. It integrates Machine Learning (ML) techniques with DEA to develop an innovative method for forecasting near-future PrP levels for proactive management of safety risks. The major contribution of Essay 3 is the novel interface between ML and DEA that can improve decision-making capabilities of managers in safety-critical STSs through real-time monitoring and predictive analytics. Together, these studies contribute to the theoretical discussions around PrP and present practical solutions to longstanding challenges in safety science and operational management. / Doctor of Philosophy / In today's increasingly complex world, the systems that run our industries, from traffic control to healthcare, face a dilemmatic balance between pushing for higher productivity and ensuring safety. This dissertation explores the trade-offs between efficiency and safety which has become more pronounced with the advancement of technology. Traditional safety approaches which used to be effective in simpler systems, struggle in modern STSs where causes and effects are not linear but tangled in a web of unpredictable interactions. Production pressure (PrP), at the core of the mentioned balance, is the drive to maximize output and efficiency, often at the expense of safety. This pressure can lead to unintended and sometimes catastrophic outcomes in the long term, especially in environments where safety is critical, such as rail traffic control centers. Despite its vital impact, there has been a noticeable gap in understanding and managing PrP. In fact, existing safety frameworks are struggling to capture the dynamic nature of PrP, consequently, its real-time measurement and control remain difficult to achieve. This work, therefore, tries to broaden our understanding of PrP and to develop methods to monitor, measure, and predict it, to equip managers and policymakers with the tools to navigate the efficiency-safety dichotomy more effectively. Through a series of essays, this dissertation reviews the current state of knowledge on PrP to identify its sources and impacts and also innovates a novel approach to quantify PrP in real-time and predict its future trends.

Historicamente, o papel do Estado está sempre se alterando, contudo ele é sempre essencial. As mudanças necessárias recentes no papel do Estado relacionam-se a um conjunto de transformações do final do século XX, tanto no cenário político quanto econômico. A primeira questão que surge no debate sobre a revisão do papel do Estado é o tamanho de suas necessidades de financiamento para promover a estabilidade, o crescimento e o bem-estar. A arrecadação tributária constitui a principal fonte de recursos utilizados no financiamento de programas governamentais e, por meio delas, o governo custeia suas despesas, suas necessidades de investimento e implanta políticas públicas. No Brasil, a reforma do Estado de 1995 buscou criar novas instituições legais e organizacionais que visavam sua modernização e aumento de eficiência. Neste sentido, a Receita Federal do Brasil, instituição que tem como objetivo arrecadação fiscal, vem aumentado sua receita tributária para que o governo estruture e implemente políticas públicas e sociais. Assim, este trabalho busca verificar a eficiência na arrecadação dos recursos pelo governo federal como forma de promover o desenvolvimento e, conseqüente, bem-estar. Para avaliar a eficiência foi aplicada a técnica de Análise Envoltória de Dados. Os resultados indicam que apenas uma das dez regiões fiscais apresentou eficiência em todos os períodos, e outras duas apresentaram eficiência em pelo menos um período. Com relação à eficiência, o estudo revelou a formação de quatro clusters, em que são agrupadas as regiões fiscais. Os resultados sugerem a utilização da região fiscal eficiente como benchmark. / Historically, the role of the State is always changing, however it is always essential. The necessary changes in the recent role of the State are related to a number of changes to the end of the twentieth century, both the political scene as economic. The first question that arises in debate on the review of the role of the State is the size of your funding needs to promote stability, growth and welfare. The incoming tax is the main source of resources used in the financing of government programs and, through them, the government funds their expenses, their for investment and deploy public policies. In Brazil, the reform of the State in 1995 sought to create new organizational and legal institutions that aimed at its modernization and increased efficiency. In this way, the Federal Incoming Office of Brazil, an institution that aims to tax collection, has increased its incoming tax to the government structure and implement social and public policies. Therefore, this paper checks the efficiency in collection of resources by the federal government as a way of promoting development and, consequently, welfare. To assess the efficiency it was applied the Data Envelopment Analysis technique. The results indicate that only one of ten regions tax presented efficiency at all times, and two others had efficiency by at least one period. With respect to efficiency, the study revealed the formation of four clusters, which are grouped in the regions tax. The results suggest the use the efficient region tax as a benchmark.

Este estudo tem por objetivo analisar o impacto das variáveis tamanho e localização na eficiência operacional de usinas de cana-de-açúcar no Brasil. Para isso, foram utilizados os dados referentes à moagem e produção de açúcar e de etanol das usinas brasileiras listadas no anuário da cana-de-açúcar na safra 2008/2009. Desta forma, realizou-se um estudo de eficiência operacional, por meio da aplicação da Análise Envoltória de Dados (DEA), na qual foi possível identificar as usinas mais eficientes dentre um universo de 355 usinas e classifica-las por tamanho, localização e eficiência operacional. A análise quantitativa sugere que existe uma maior concentração de usinas classificadas como eficientes e de tamanho grande, localizadas no estado de São Paulo. Objetivando uma análise em profundidade foi realizado um estudo de múltiplos casos em um grupo de usinas. Ademais, foi feita uma entrevista com especialistas do setor sucroalcooleiro. Dessa forma, conclui-se que a eficiência operacional de usinas de cana-de-açúcar depende da variável tamanho, na medida em que as usinas de maior porte tendem a investir mais em tecnologias que proporcionam um maior ganho de eficiência operacional. A eficiência também depende da variável localização, na medida em que o estado de São Paulo apresenta condições edafoclimáticas mais favoráveis à extração de uma cana-de-açúcar com maior teor de sacarose, que, consequentemente, pode influenciar na eficiência operacional de usinas de cana-de-açúcar. O presente estudo, portanto, fornece subsídios para que gestores destas empresas possam alcançar maior eficiência operacional, bem como fornecer suporte a decisões de investimento nesse setor, uma vez que a escolha da localização e da tecnologia pode influenciar na eficiência. / This research aims to analyze the impact of the variables size and location over the operational efficiency of sugarcane mills producing sugar and ethanol in Brazil. Thus, data concerning total milling and total production of sugar and ethanol plants, was collected regarding Brazilian sugarcane mills listed in the 2008/2009 sugarcane yearbook. A ranking of operational efficiency was developed, applying Data Envelopment Analysis (DEA) technique, through which was possible to verify which were the most efficient among 355 sugarcane mills and, therefore, compare the variables size, location and operational efficiency among the Brazilian mills. The quantitative analysis suggests that among the efficient groups, there is a major concentration of larger mills, located in the state of São Paulo. Aiming an in-depth analysis, a multiple-case study was conducted in a group of sugarcane mills, and interviews with experts in the sugarcane industry were developed. Therefore, the conclusion is that operational efficiency of sugarcane mills depends on the variable location, as larger mills tend to invest more in technologies that provide major gain in operational efficiency. The operational efficiency depends also on the location of the sugarcane mill, as the state of São Paulo provides favorable edaphoclimatic conditions for the juice extraction of sugarcane with a higher level of sucrose content, hence possibly having influence over the operational efficiency. This study, therefore, provides subsidies so that managers may obtain higher levels of operational efficiency, as well as support decisions of investments in the sugarcane industry, as the decisions concerning location and size may influence the sugarcane mill efficiency.

Tese de Doutoramento. Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 2012

Η παρούσα διπλωματική εργασία εκπονήθηκε στα πλαίσια του μεταπτυχιακού προγράμματος MBA «Νέες αρχές Διοίκησης Επιχειρήσεων» του τμήματος Διοίκησης Επιχειρήσεων του Πανεπιστημίου Πατρών, κατά το έτος 2013. Αντικείμενο της εργασίας είναι η παρουσίαση μιας μεθοδολογίας που μπορεί να αξιοποιηθεί για τον σχεδιασμό καλύτερων υπηρεσιών. Η εφαρμογή πραγματοποιείται για την διερεύνηση της αποδοτικότητας των υπηρεσιών μιας τράπεζας. Για τον σκοπό αυτό χρησιμοποιήθηκαν προκαθορισμένα κριτήρια (πρόταση από φίλο, φήμη, έξοδα λογαριασμών, τοποθεσία, επιτόκια δανείων, πάρκινγκ, πιστωτική πολιτική) τα οποία διαδραματίζουν σημαντικό ρόλο στην απόφαση των πελατών για την τράπεζα που θα επιλέξουν. Τα κριτήρια αυτά εξετάζονται ξεχωριστά για κάθε τμήμα της τραπεζικής αγοράς (στεγαστικά δάνεια, καταναλωτικά δάνεια, πιστωτικές κάρτες, άλλα δάνεια, λογαριασμοί ταμιευτηρίου, λογαριασμοί προθεσμιακών καταθέσεων και μερίδια αμοιβαίων κεφαλαίων) και υπολογίζονται οι συντελεστές στάθμισης που αντιστοιχούν στο καθένα. Οι συντελεστές αυτοί, έχουν ιδιαίτερη αξία για τα στελέχη της τράπεζας γιατί δείχνουν την αξία που έχει κάθε κριτήριο για τον πελάτη. Με αυτό τον τρόπο, τα στελέχη έχουν την δυνατότητα να σχεδιάσουν τις τραπεζικές υπηρεσίες δίνοντας μεγαλύτερη έμφαση στα κριτήρια με τη μεγαλύτερη βαρύτητα έτσι ώστε να επιτυγχάνεται καλύτερη ικανοποίηση των αναγκών των πελατών. Πιο συγκεκριμένα, στην παρούσα εργασία μελετάται η περίπτωση μιας ελληνικής τράπεζας, που κατέχει υψηλό μερίδιο αγοράς και για καθεμία από τις υπηρεσίες της υπολογίζονται οι συντελεστές στάθμισης. Η τράπεζα αυτή αναφέρεται ως Τράπεζα Χ στην υπόλοιπη εργασία για ευνόητους λόγους. Η επίλυση του προβλήματος πραγματοποιείται με δύο τρόπους: 1) με την χρήση της μεθοδολογίας AHP (Analytic Hierarchy Process) σε συνδυασμό με τη μέθοδο QFD (Quality Function Deployment) για την συμπλήρωση του πίνακα HOQ (House of Quality) και 2) την χρήση της μεθοδολογίας DEAHP (Data Envelopment Analytic Hierarchy Process) σε συνδυασμό με το QFD για την συμπλήρωση του HOQ. Τα αποτελέσματα της παρούσας μελέτης δείχνουν ότι και στις δύο μεθοδολογίες η κατάταξη των κριτηρίων βάσει των προτιμήσεων των πελατών είναι σχεδόν η ίδια. Συγκεκριμένα, τα δύο πρώτα κριτήρια στα οποία οι πελάτες δίνουν μεγαλύτερη βαρύτητα είναι τα έξοδα λογαριασμών και τα επιτόκια δανείων. Ακολουθούν τα κριτήρια φήμη, πρόταση από φίλο, πάρκινγκ κατά φθίνουσα σειρά κατάταξης και τελευταία είναι τα κριτήρια τοποθεσία και πιστωτική πολιτική. Ωστόσο, οι συντελεστές βαρύτητας των κριτηρίων που υπολογίστηκαν είναι διαφορετικοί στο συνδυασμό των μεθοδολογιών QFD-AHP σε σχέση με QFD-DEAHP. Αυτό συμβαίνει λόγω των διαφορετικών τρόπων επίλυσης και διαφορετικών υποθέσεων που χρησιμοποιούνται σε καθεμία μεθοδολογία. / This study was conducted at the Department of the Postgraduate program “New principles of Business Administration” in department of Business Administration of the University of Patras. The objective of this study is to present a methodology which can be used to design better services. This methodology is applied in order to investigate the efficiency of the services of a bank. For this purpose we used pre-defined criteria (recommendation by friends, reputation, expense accounts, location, interest charges on loans, parking, credit policy) which play an important role when the customers select a bank. These criteria are examined separately for each segment for the banking market (housing loans, consumer loans, credit cards, other loans, direct access deposits, time deposit accounts, matual funds shares) and we calculate the relative weight of each criterion. The relative weights above are important for the bank executives because they show the impact of each criterion in the opinion of customers. In this way, executives are able to design their banking services placing emphasis on the criteria with the highest preference in order to satisfy customer needs. Specifically, in this study we examine the case of a Greek bank with high market share and we calculate the weights for each service of the bank. This bank is called Bank X in the remaining study for obvious reasons. The problem was solved with two different ways: 1) by using the combination of AHP (Analytic Hierarchy Process) with QFD (Quality Function Deployment) methodology in order to complete the matrix of HOQ (House of Quality) and 2) by using DEAHP (Data Envelopment Analytic Hierarchy Process) methodology and QFD in order to complete the HOQ. The results of this study show that the ranking of bank selection criteria is almost the same for both methodologies. Specifically the first two criteria which customers seems to prefer are the expenses accounts and interest charges on loans. The rest of criteria are reputation, recommendation by friends, parking in descending order of priority and finally are the criteria location and credit policy. However, the weights which calculated for each criterion are different in combination of methodologies QFD-AHP compared with QFD-DEAHP. This happens because of the different ways of solving and different assumptions which are used in each methodology.

The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions and assess their merits. In sum, two main methodological contributions are presented. The first contribution consists of proposing a mathematical programming based approach, commonly referred to as Data Envelopment Analysis (DEA), as a multidimensional framework for relative performance evaluation of competing forecasting models or methods. As opposed to other performance measurement and evaluation frameworks, DEA allows one to identify the weaknesses of each model, as compared to the best one(s), and suggests ways to improve their overall performance. DEA is a generic framework and as such its implementation for a specific relative performance evaluation exercise requires a number of decisions to be made such as the choice of the units to be assessed, the choice of the relevant inputs and outputs to be used, and the choice of the appropriate models. In order to present and discuss how one might adapt this framework to measure and evaluate the relative performance of competing forecasting models, we first survey and classify the literature on performance criteria and their measures – including statistical tests – commonly used in evaluating and selecting forecasting models or methods. In sum, our classification will serve as a basis for the operationalisation of DEA. Finally, we test DEA performance in evaluating and selecting models to forecast crude oil prices. The second contribution consists of proposing a Multi-Criteria Decision Analysis (MCDA) based approach as a multidimensional framework for relative performance evaluation of the competing forecasting models or methods. In order to present and discuss how one might adapt such framework, we first revisit MCDA methodology, propose a revised methodological framework that consists of a sequential decision making process with feedback adjustment mechanisms, and provide guidelines as to how to operationalise it. Finally, we adapt such a methodological framework to address the problem of performance evaluation of competing forecasting models. For illustration purposes, we have chosen the forecasting of crude oil prices as an application area.

The purpose of this study is to determine whether the Data Envelopment Analysis (DEA) can be applied to Chief Executive Officer (CEO) remuneration of companies listed on the Johannesburg Stock Exchange (JSE) by defining inputs in terms of remuneration factors and outputs in terms of business factors in order to establish a benchmark for CEO remuneration. An exploratory study is conducted, using cross-sectional data from a secondary source. The sample consists of 221 companies listed on the JSE that disclosed their financial and non-financial information during 2010. The DEA was performed to estimate the relative technical efficiency of CEOs to convert their remuneration into company performance indicators. Base Pay, Perquisites and Pension, Annual Bonus Plans and Long-term Incentives were used as the inputs to the DEA model and company performance and size, measured by Return on Equity (ROE) and Total Assets respectively, were used as the outputs to the model. The empirical results prove that the DEA can be successfully applied as a benchmarking model for CEO remuneration that incorporates multiple inputs and outputs and establishes benchmarks and potential improvements for overpaid, inefficient CEOs. The CEOs from 80 of the 221 companies included in the sample emerged as the benchmark CEOs and formed the efficiency frontier against which inefficient CEOs were compared in order to determine the potential improvements for these CEOs. From a research perspective, this study contributes to the advancement of CEO remuneration research by introducing an alternative model by which CEO remuneration can be analysed. Future studies can analyse CEO remuneration by using other variables or time series data in the DEA model or combine the DEA with other methods like the regression analysis to perform more comprehensive investigations. From a practical perspective, the DEA can be used to establish a benchmark for CEO remuneration. Remuneration committees can use the results of the DEA as a guide to determine acceptable remuneration levels and decrease the pay gap between CEOs and the average worker. The originality of this study lies in the fact that it is the first South African study that used the DEA instead of the regression analysis to analyse CEO remuneration of companies listed on the JSE. This study also disaggregated Total CEO Remuneration into Base Pay, Perquisites and Pension, Annual Bonus Plans and Long-term Incentives to provide more accurate benchmark information. In addition, this is the first study that established benchmark CEO remuneration levels and suggested improvements to the remuneration package structure of overpaid, under-performing CEOs of companies listed on the JSE. / Thesis (MCom (Management Accountancy))--North-West University, Potchefstroom Campus, 2013.

The purpose of this study is to determine whether the Data Envelopment Analysis (DEA) can be applied to Chief Executive Officer (CEO) remuneration of companies listed on the Johannesburg Stock Exchange (JSE) by defining inputs in terms of remuneration factors and outputs in terms of business factors in order to establish a benchmark for CEO remuneration. An exploratory study is conducted, using cross-sectional data from a secondary source. The sample consists of 221 companies listed on the JSE that disclosed their financial and non-financial information during 2010. The DEA was performed to estimate the relative technical efficiency of CEOs to convert their remuneration into company performance indicators. Base Pay, Perquisites and Pension, Annual Bonus Plans and Long-term Incentives were used as the inputs to the DEA model and company performance and size, measured by Return on Equity (ROE) and Total Assets respectively, were used as the outputs to the model. The empirical results prove that the DEA can be successfully applied as a benchmarking model for CEO remuneration that incorporates multiple inputs and outputs and establishes benchmarks and potential improvements for overpaid, inefficient CEOs. The CEOs from 80 of the 221 companies included in the sample emerged as the benchmark CEOs and formed the efficiency frontier against which inefficient CEOs were compared in order to determine the potential improvements for these CEOs. From a research perspective, this study contributes to the advancement of CEO remuneration research by introducing an alternative model by which CEO remuneration can be analysed. Future studies can analyse CEO remuneration by using other variables or time series data in the DEA model or combine the DEA with other methods like the regression analysis to perform more comprehensive investigations. From a practical perspective, the DEA can be used to establish a benchmark for CEO remuneration. Remuneration committees can use the results of the DEA as a guide to determine acceptable remuneration levels and decrease the pay gap between CEOs and the average worker. The originality of this study lies in the fact that it is the first South African study that used the DEA instead of the regression analysis to analyse CEO remuneration of companies listed on the JSE. This study also disaggregated Total CEO Remuneration into Base Pay, Perquisites and Pension, Annual Bonus Plans and Long-term Incentives to provide more accurate benchmark information. In addition, this is the first study that established benchmark CEO remuneration levels and suggested improvements to the remuneration package structure of overpaid, under-performing CEOs of companies listed on the JSE. / Thesis (MCom (Management Accountancy))--North-West University, Potchefstroom Campus, 2013.

Η παρούσα διπλωματική εργασία μελετά την επίδραση του κόστους περιστολής της ρύπανσης σε συγκεκριμένους κλάδους της ελληνικής βιομηχανίας, την χρονική περίοδο 1993-2006, στην παραγωγικότητά τους. Από θεωρητικής πλευράς εστιάζει στις αντικρουόμενες προσεγγίσεις της win-win υπόθεσης του Porter (1990,1991) και των Porter and Van der Linde (1995) με την νεοκλασική θεωρία, που είχε ως κύριους εκφραστές τους Jaffe και Palmer (1995,1997). Η μεθοδολογική προσέγγιση που ακολουθείται στηρίζεται στην μη παραμετρική μέθοδο της DEA με στόχο την εκτίμηση δεικτών παραγωγικότητας Malmquist (Malmquist Total Factor Productivity Index). Για την μελέτη της επίδρασης του κόστους περιστολής της ρύπανσης σε κλάδους της Ελληνικής βιομηχανίας ακολουθήθηκε η μεθοδολογία που αναπτύχθηκε απο τους Aiken et al., (2009) για τον διαχωρισμό και υπολογισμό μεταξύ regulated-unregulated συναρτήσεων ορίων παραγωγής. Στην εμπειρική εφαρμογή της μελέτης χρησιμοποιήθηκαν δεδομένα απο την ετήσια έρευνα βιομηχανίας της Ελληνικής Στατιστικής Υπηρεσίας σε 23 βιομηχανικούς κλάδους, σύμφωνα με την κωδικοποίηση ΣΤΑΚΟΔ 2003, και παρατηρείται συνολικά επουσιώδης αρνητική επίδραση τους κόστους περιστολής των ρύπων στην παραγωγικότητα. Πιο συγκεκριμένα, κλάδοι με υψηλή ενεργειακή ένταση φαίνεται να εμφανίζουν μηδενική επίδραση των περιβαλλοντικών δαπανών στην παραγωγικότητά τους με μοναδική εξαίρεση του κλάδου των ορυκτών-μετάλλων. / The passage of environmental regulation has been associated with a potential negative or positive effect on firm’s productivity. The present study studies the effect of pollution abatement activities on the productive efficiency of polluting industries in Greece over the period 1993-2006. A methodological approach based on Aiken et al., (2009) study have been developed in order to specify regulated and unregulated production frontiers and to determine the possible link between pollution abatement activities and sector’s productivity growth. Data derived form the Hellenic Statistical Authority has been used in order to estimate the possible association. Our results indicate, for the majority of the manufacturing industries, that increased rates of productivity growth have been simultaneously experienced with decreased rates of pollution abatement.