This Palgrave Pivot presents tournament design mainly within the axioms of incentive compatibility and fairness. It illustrates the advantages of an axiomatic approach through various examples, including several FIFA and UEFA tournaments, and uses theoretical tools and simulation methodology in its analysis. Chapter 1 discusses scoring systems of championships with multiple competitions, ranking in Swiss-system tournaments, and tie-breaking rules in round-robin leagues. It is followed by a thorough critical analysis of the current and previous FIFA World Rankings. The broad focus is substantially narrowed in Chapter 2, which turns to the topic of incentive (in)compatibility in multiple qualifiers. It is revealed that UEFA has faced at least three times recently this problem in the qualification to the UEFA Europa League, qualification to the UEFA Champions League, and the draw of the UEFA Champions League groups. Analogously, Chapter 3 discusses incentive (in)compatibility when there is only one group-based tournament but the complex progression rules to the subsequent stage can be designed poorly. Our examples include the qualifying tournaments of recent FIFA World Cups and UEFA European Championships. Chapter 4 moves to the problem of penalty shootout rules in soccer, where the fairness and complexity of some alternative mechanisms from the literature are evaluated. Fairness remains the central issue in Chapter 5, which presents the challenges of designing a tournament with 24 teams if the number of teams per group cannot exceed four. As expected, there is no perfect solution, and both FIFA and UEFA have introduced a reform in this format recently. Chapter 6 deals with the qualification for the 2020 UEFA European Football Championship. Its tournament design is perhaps the most complicated one that has ever been implemented in the real-world and suffers from serious shortcomings.

< p=""> The book covers the domain of multi-criteria decision making, a topic which has gained significant attention of researchers and practitioners spanning a variety of disciplines for enhancing their decision making in real life situation. The topics in this volume help readers understand the techniques in the model building and analysis stage. The chapters cover a variety of techniques and their applications for interesting problems. This book will be of interest to readers in diverse disciplines such as engineering, business, management, humanities, psychology and law. ^

Michael Porter is recognized as one of the top authorities on corporate strategy and business competition. The historical review of strategic management clearly shows that Porter's research has bridged up two general paradigms (before and after the 1980s) thus helping both researchers and practitioners to better understand unanticipated global changes. His two generic strategies: costs and diversification, the two interdependent strategic options, are key in the context of the competitiveness of orthodox microeconomic theory. This is where Porter went further, constructing a popular value chain concept that provides the ability to disaggregate the key activities of business process in creating products and services in terms of cost analysis and value creation. This book is a collection of seven interconnected chapters that provides a coherent understanding of Michael Porter's contribution to the field of strategic management. It addresses key changes and challenges in the global business environment. The value chain concept has become highly applicable in both theory and practice. In the book, the authors offer an original interpretation of the Porters' research on strategic management in order to unravel or simplify his key theoretical concepts. It will be of interest to researchers, academics, practitioners, and students in the fields of strategic management and international business.

The papers presented in this open access book address diverse challenges in decarbonizing energy systems, ranging from operational to investment planning problems, from market economics to technical and environmental considerations, from distribution grids to transmission grids, and from theoretical considerations to data provision concerns and applied case studies. While most papers have a clear methodological focus, they address policy-relevant questions at the same time. The target audience therefore includes academics and experts in industry as well as policy makers, who are interested in state-of-the-art quantitative modelling of policy relevant problems in energy systems. The 2nd International Symposium on Energy System Optimization (ISESO 2018) was held at the Karlsruhe Institute of Technology (KIT) under the symposium theme "Bridging the Gap Between Mathematical Modelling and Policy Support" on October 10th and 11th 2018. ISESO 2018 was organized by the KIT, the Heidelberg Institute for Theoretical Studies (HITS), the Heidelberg University, the German Aerospace Center and the University of Stuttgart.

This book gathers selected papers presented at the International Conference on Advances in Applied Probability and Stochastic Processes, held at CMS College, Kerala, India, on 7-10 January 2019. It showcases high-quality research conducted in the field of applied probability and stochastic processes by focusing on techniques for the modelling and analysis of systems evolving with time. Further, it discusses the applications of stochastic modelling in queuing theory, reliability, inventory, financial mathematics, operations research, and more. This book is intended for a broad audience, ranging from researchers interested in applied probability, stochastic modelling with reference to queuing theory, inventory, and reliability, to those working in industries such as communication and computer networks, distributed information systems, next-generation communication systems, intelligent transportation networks, and financial markets.

Exploring the three levels of project management, this edited collection analyses the practice of problem structuring approaches (PSAs) with an aim to improve organisational adaptability and value creation. By studying these approaches, the authors present techniques for enhancing project management knowledge, informing decision-making and guiding management actions. This book is an insightful and timely read, as it addresses the need for organisations to adapt in order to tackle new challenges within today's changing business landscape. Undoubtedly useful to those studying project management and operational research, this book is also an important read for managers and decision-makers within organisations as it identifies and examines the effective outcomes of PSAs.

This fifth edition of "Product Lifecycle Management" updates and adds to the successful fourth edition, the most frequently cited PLM publication. It gives the reader a thorough explanation of Product Lifecycle Management (PLM) and provides them with a full understanding and the skills to implement PLM within their own business environment. This new and expanded edition is fully updated to reflect the many technological and management advances made in PLM since the release of the fourth edition. "Product Lifecycle Management" will broaden the reader's understanding of PLM, nurturing the skills needed to implement PLM successfully and to achieve world-class product performance across the lifecycle. Among the components of PLM described are product-related business processes, product data, product data management (PDM) systems, other PLM applications, best practices, company objectives and organisation. This book also describes the relationships of PLM with the Internet of Things, Industry 4.0, Digital Twins and Digital Threads. "Product Lifecycle Management" (5th edition) explains what PLM is, and why it is needed. It describes the environment in which products are ideated, developed, manufactured, supported and retired, before addressing the main components of PLM and PLM Initiatives. Key activities in PLM Initiatives described include organisational change management (OCM) and project management. The final part of the book addresses the PLM Initiative, showing the typical steps and activities of a PLM project or initiative.

Assembly Line Planning and Control describes the basic fundamentals of assembly lines for single model lines, mixed model make-to-stock lines, mixed model make-to-order lines and for one-station assembly. The book shows how to select the quantity of units to schedule for a shift duration, compute the number of operators needed on a line, set the conveyor speed, coordinate the main line with sub-assembly lines, assign the work elements to the operators on the line, sequence the models down the line, sequence the jobs down the line, calculate the part and component requirements for a line and for each station, determine the replenish needs of the parts and components from the suppliers, compute the similarity between the models being produced and show applications, use learning curves to estimate time and costs of assembly, and measure the efficiency of the line. The material is timeless and the book will never become obsolete. The author presents solutions with easy-to-understand numerical examples that can be applied to real-life applications. "

The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets. The different chapters, written by active researchers in their respective areas, are structured to provide a coherent picture of this interdisciplinary yet still evolving field of science. They describe key tools and give practical insights into and research perspectives on the use of Atanassov's intuitionistic fuzzy sets and logic, and generalized nets for describing and dealing with uncertainty in different areas of science, technology and business, in a single, to date unique book. Here, readers find theoretical chapters, dealing with intuitionistic fuzzy operators, membership functions and algorithms, among other topics, as well as application-oriented chapters, reporting on the implementation of methods and relevant case studies in management science, the IT industry, medicine and/or education. With this book, the editors wish to pay homage to Professor Krassimir Todorov Atanassov for his pioneering work on both generalized nets and intuitionistic fuzzy set.

Multiple Criteria Decision Making (MCDM) is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management planning process. A key area of research in OR/MS, MCDM is now being applied in many new areas, including GIS systems, AI, and group decision making. Additionally, there has been very rapid growth in recent years in evolutionary Multiobjective optimization, stochastic analysis, robustness, and regression-based methods, and thus, the need for a look at the newest trends in the field.

This volume is in effect the third book in the Springer ISOR series by these editors, bringing the latest developments in MCDM into focus. It presents research from leaders in the field on such topics as Problem Structuring Methodologies; Measurement Theory and MCDA; Recent Developments in Evolutionary Multiobjective Optimization; Habitual Domains and Dynamic MCDM in Changeable Spaces; Stochastic Multicriteria Acceptability Analysis; and more.

This book presents a panorama about the recent progress of industrial mathematics from the point of view of both industrials and researchers. The chapters correspond to a selection of the contributions presented in the "Industry Day" and in the Minisymposium "EU - MATHS - IN: Success Stories of Applications of Mathematics to Industry" organized in the framework of the International Conference ICIAM 2019 held in Valencia (Spain) on July 15-19, 2019. In the Industry Day, included for the first time in this series of Conferences, representatives of companies from different countries and several sectors presented their view about the benefits regarding the usage of mathematical tools and/or collaboration with mathematicians. The contributions of this special session were addressed to industry people. Minisymposium contributions detailed some collaborations between mathematicians and industrials that led to real benefits in several European companies. All the speakers were affiliated in some of the European National Networks that constitute the European Service Network of Mathematics for Industry and Innovation (EU-MATHS-IN).

This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models. It is intended as a follow-on and companion to Modeling Markets (2015), in which the authors presented the basics of modeling markets along the classical steps of the model building process: specification, data collection, estimation, validation and implementation. This volume builds on the concepts presented in Modeling Markets with an emphasis on advanced methods that are used to specify, estimate and validate marketing models, including structural equation models, partial least squares, mixture models, and hidden Markov models, as well as generalized methods of moments, Bayesian analysis, non/semi-parametric estimation and endogeneity issues. Specific attention is given to big data. The market environment is changing rapidly and constantly. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today's environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. This volume provides an authoritative and comprehensive review, with each chapter including: * an introduction to the method/methodology * a numerical example/application in marketing * references to other marketing applications * suggestions about software. Featuring contributions from top authors in the field, this volume will explore current and future aspects of modeling markets, providing relevant and timely research and techniques to scientists, researchers, students, academics and practitioners in marketing, management and economics.

This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards. In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.

This book offers the first introduction to the concepts, theories, and applications of pricing and revenue optimization. From the initial success of "yield management" in the commercial airline industry down to more recent successes of markdown management and dynamic pricing, the application of mathematical analysis to optimize pricing has become increasingly important across many different industries. But, since pricing and revenue optimization has involved the use of sophisticated mathematical techniques, the topic has remained largely inaccessible to students and the typical manager. With methods proven in the MBA courses taught by the author at Columbia and Stanford Business Schools, this book presents the basic concepts of pricing and revenue optimization in a form accessible to MBA students, MS students, and advanced undergraduates. In addition, managers will find the practical approach to the issue of pricing and revenue optimization invaluable. With updates to every chapter, this second edition covers topics such as estimation of price-response functions and machine-learning-based price optimization. New discussions of applications of dynamic pricing and revenue management by companies such as Amazon, Uber, and Disney, and in industries such as sports, theater, and electric power, are also included. In addition, the book provides current coverage of important applications such as revenue management, markdown management, customized pricing, and the behavioral economics of pricing.

This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: * Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) * Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics * An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata * A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters - Static Simulation Optimization, Reinforcement Learning and Convergence Analysis - this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

The subject for this book is my life work on the enterprise modeling and integration by a stochastic/queuing form, and the book plan was conceived before my stay in the USA in 1996-97 as a visiting scholar. The rst title was "Stochastic Management and Design of Manufacturing Systems." The rst version was attempted in 2001; however, this version was inappropriate and was not revised till now. It is 40 years since I attempted a stochastic approach to manufacturing and management due to the limitations of statistical approaches. The century in which industrial engineering and management rose to the forefront was one in which a static/statistical approach was applied to the development of classical models and general/average theory. This book presents a stochastic management approach to the manufacturing and service enterprise with risks by a game/strategic view, and is based on many papers in production/queueing studies that have appeared in famous journals. The book's objective is to discuss and show the goals and constraints on manufacturing and service enterprises, and to provide a strategic/collaborative solution for management with risks in heterogeneity. This book mainly focuses on the three manufacturing classes: continuous, poi- wise, and exible stream types under risks. These manufacturing streams are rst studied using the respective stochastic processes, and are characterized and dev- oped as a queueing/strategic control problem of look-ahead/buffer, selection/swit- over, and arrangement/routings. Moreover, the behaviors of some design/control variables are shown and useful theories for design are established.

This book deals with the choice of methods to be applied in the decision processes within organizations. It discusses the use of voting procedures for group decision in business organizations, focusing on decision-making contexts. Within this book the reader explores the relevant part of the decision-making process consisting of choosing the voting procedures and recognizing the drawbacks of that procedure. This book includes a unique feature of providing a framework for choosing the voting procedure that is the most appropriate for a particular business decision process. The book is useful for a broad researcher audience dealing with the group decision making processes within business organizations and for practitioners and students working in the group decision and negotiation field.

This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions. Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.

Certain consultants argue leaders can quickly, easily, and considerably alter their organization cultures to improve performance. Conversely, field researchers have described situations where leaders could do little to alter the existing organization culture. Between these extreme positions, a spectrum of varying degrees of leader influence exists, and organizations fall at various places along this spectrum. This book presents five field studies dealing with team, service, and sales cultures where both expected and unexpected outcomes arose. In multiple instances, leaders hoped showing some employee appreciation would compensate for offering below market average wages. Several leadership groups were prospering based on cost cuts or increased sales. Those below often had their work intensified and they were experiencing greater stress. Eight paradoxical situations were uncovered and the interpretations of the participants were based in part on their personal work histories and the history of their current organization. In each case, evidence of employee informal organization and managerial operating cultures were documented. Analyzing Organization Cultures uses detailed case studies of five work organizations to offer a comparative approach to analyzing organizational culture. It shows the latest state of knowledge on the topic and will be of interest to researchers, academics, and students in the fields of organizational studies, management history, human resource management, and organizational theory.

With the beginning of the twentieth century, American corporations in the chemical and electrical industries began establishing industrial research laboratories. Some went on to become world-famous not only for their scientific and technological breakthroughs but also for the new union of science and industry they represented. Innovative ideas do not simply appear out of the blue and spread on their own merit. Rather, the laboratory's diffusion takes place in a cultural context that goes beyond corporate capital and technological change. Using discourse analysis as a method to comprehensively capture the organizational field of the early American R&D laboratories from 1870 to 1930, this book uncovers the collective meanings associated with the industrial laboratory. Meanings such as what and where a laboratory is supposed to be, who the scientist is, and what it means to practice science provided cultural resources that made the transfer of the laboratory from academic science into an industrial setting possible by rendering such meanings understandable and operable to big business and organizational entrepreneurs fighting for hegemony in a rapidly evolving market. It analyzes not only the corporations that established laboratories in the United States but also their contexts - economic, political, and especially scientific - showing how "the industrial laboratory" was transformed from an organizational novelty into an expected institution in less than two decades. This book will be of interest to researchers, academics, historians, and students in the fields of organizational change, discourse studies, the management of technology and innovation, as well as business and management history.

Game theory has been applied to a growing list of practical problems, from antitrust analysis to monetary policy; from the design of auction institutions to the structuring of incentives within firms; from patent races to dispute resolution. The purpose of Game Theory and Business Applications is to show how game theory can be used to model and analyze business decisions. The contents of this revised edition contain a wide variety of business functions - from accounting to operations, from marketing to strategy to organizational design. In addition, specific application areas include market competition, law and economics, bargaining and dispute resolution, and competitive bidding. All of these applications involve competitive decision settings, specifically situations where a number of economic agents in pursuit of their own self-interests and in accordance with the institutional "rules of the game" take actions that together affect all of their fortunes. As this volume demonstrates, game theory provides a compelling guide for analyzing business decisions and strategies.

The Pipeline and Hazardous Materials Safety Administration of the U.S. Department of Transportation defines hazardous materials (hazmat) as a substance or material capable of posing an unreasonable risk to health, safety, or property when transported in commerce. Hazmat accidents can result in significant impact to the population (death, injuries) and damage to the environment (destroyed or damaged buildings and infrastructure). Further, hazmat, especially explosive materials, can potentially be used by terrorists to attack civilians or to destroy critical infrastructure. This handbook provides models from Operations Research and Management Science that study various activities involving hazmat transportation: risk assessment, route planning, location decisions, evacuation planning, and emergency planning for terrorist attacks. There are two important research areas in hazmat transportation that are widely studied in the literature: risk assessment and shipment planning. In the risk assessment area, important issues include measurement of accident probabilities and consequences in hazmat transport. Example works in the risk assessment area include modeling risk probability distribution over given areas, considering hazmat types and transport modes, and environmental conditions. The first half of this handbook covers the two fields of risk assessment and shipment planning, while the second half of this handbook provides useful models and insights on other important issues including location problems for undesirable facilities, network interdiction, terrorist attack, and evacuation.

One current challenge of conducting research from the leadership-as-practice perspective is a practical one: how to capture and analyse the elusive practice of leadership within the web of mundane organising processes. Although a number of researchers have attempted to address the issue, there is not yet a definitive 'how to' guide to making sense of the empirical manifestations of leadership practices. The book responds directly to this challenge and offers a theoretical framework and practical guidance to capturing, identifying and analysing evidence of leadership practice emergence; and provides implications of this approach for leadership academics and practitioners. The developed framework enables a method for understanding these leadership instances as they are enacted by individuals within and against the evolving activities of their day-to-day work. The framework is underpinned by cultural-historical activity theory and critical realism and it conceptualises leadership practice by placing agents' actions and interactions within the context of their relationships, objectives, experiences, material and non-material artefacts and wider organising processes and organisational structures; work that has not yet been undertaken in the field. It offers a strong theoretical foundation for further development of our understanding of leadership-as-practice, providing a methodological guidance for undertaking leadership-as-practice research, and enables a discussion on the variety of underlying processes and elements as they emerge from empirical observations. It will be of value to researchers, academics, professionals, and students in the fields of business and management with a particular interest in management theory, organisational studies, and leadership research.

Sustainable Self-Governance in Businesses and Society offers a sound introduction to Stafford Beer's Viable System Model (VSM) and clarifies its relevance to support organisational sustainability and self-governance. While the VSM has been known since the early 1980s, it hasn't been always easy to understand and to apply. It explains the self-transformation methodology to analyse the way organisations manage (or not) their complexity and govern themselves. The work is supported by multiple examples of application in organisations of all scales - from small to multi-national corporations and from organised social networks to communities and national organisations. It clarifies the relevance of Beer's theory to support systemic learning and change in organisations, and to coach them to self-organise and self-govern. Readers interested in further understanding insights from complex systems and cybernetics theories for designing and transforming organisations will benefit from this book, as it works to offer very detailed insights on how to put the VSM theory into practice. It clarifies how it improves adaptive capabilities, agile and self-regulated structures, more capable of fully implementing corporate sustainability strategies and self-governing themselves. The chapters provide key reading for managers, consultants, practitioners, and post-graduate students working in organisational transformation, governance, and sustainability.