This book provides a detailed introduction to the theoretical and methodological foundations of production efficiency analysis using benchmarking. Two of the more popular methods of efficiency evaluation are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), both of which are based on the concept of a production possibility set and its frontier. Depending on the assumed objectives of the decision-making unit, a Production, Cost, or Profit Frontier is constructed from observed data on input and output quantities and prices. While SFA uses different maximum likelihood estimation techniques to estimate a parametric frontier, DEA relies on mathematical programming to create a nonparametric frontier. Yet another alternative is the Convex Nonparametric Frontier, which is based on the assumed convexity of the production possibility set and creates a piecewise linear frontier consisting of a number of tangent hyper planes. Three of the papers in this volume provide a detailed and relatively easy to follow exposition of the underlying theory from neoclassical production economics and offer step-by-step instructions on the appropriate model to apply in different contexts and how to implement them. Of particular appeal are the instructions on (i) how to write the codes for different SFA models on STATA, (ii) how to write a VBA Macro for repetitive solution of the DEA problem for each production unit on Excel Solver, and (iii) how to write the codes for the Nonparametric Convex Frontier estimation. The three other papers in the volume are primarily theoretical and will be of interest to PhD students and researchers hoping to make methodological and conceptual contributions to the field of nonparametric efficiency analysis.

This book is a reaction to the reductionist and exploitative ideas dominating the mainstream contemporary management discourse and practice, and an attempt to broaden the horizons of possibility for both managers and organization scholars. It brings together the scholarly fields of humanistic management and organizational aesthetics, where the former brings in the unshakeable focus on the human condition and concern for dignity, emancipation, and the common good, while the latter promotes reflection, openness, and appreciation for irreducible complexity of existence. It is a journey towards wholeness undertaken by a collective of management and organization theorists, philosophers, artists, and art curators. Reading this book's contributions can help both academics and practitioners work towards building organizational practices aimed at (re)acquiring wholeness by developing aesthetic awareness allowing for more profound understandings of performativity, insights into the dynamics of power, appreciation of ambiguity and ambivalence, and a much needed grasp of complexity. The varied ways of engaging with art explored by the authors promote imaginative insights into and reflection on the beauty and vicissitudes of organizing, of management knowledge and collective expression. It will be of interest to researchers, academics, practitioners, and students in the fields of organizational theory and practice, business and management history, human resource management, and culture management.

This book begins by introducing the topic of knowledge in literature, including its scientific foundations. Due to the ever-increasing number of scientific publications, literature reviews are becoming more and more essential to stay updated. Literature Reviews describes an innovative system for creating systematic literature reviews, through reviewing, analyzing, and synthesizing scientific and technological literature. It then discusses systematic literature reviews, content analysis, and literature synthesis separately, before presenting the methodology to combine them in one process. It showcases computational tools to aid in this technique and offers examples of the method in action. Finally, the book takes a new of future developments in the subject. This book is of interest to graduate students, as well as researchers and academics, helping them to deepen insights and improve skills needed to conduct thorough literature reviews.

This book presents some twenty case studies, showing how companies in different industry sectors and of different sizes make advances in Product Lifecycle Management (PLM). Like the author's previous volumes, this book provides a valuable resource for those wishing to learn about PLM and how to implement and apply it in their companies. Helping readers to * learn about implementing and benefiting from PLM; * learn about good PLM solutions and best practice; * improve their planning and decision-making abilities; * benefit from the lessons learned by the companies featured in the case studies; * proceed faster and further with PLM the book presents effective PLM solutions and best practices. At the same time, the case studies included demonstrate how different companies implement and benefit from PLM. Each case study is addressed in a separate chapter and details a different situation, enabling readers to put themselves in the situation and think through different actions and decisions. A valuable resource for PLM team managers and employees in engineering and manufacturing companies, the book is also of interest to researchers and students in industrial engineering fields.

This book discusses the main techniques and newest trends to manage and optimize the production and service systems. The book begins by examining the three main levels of decision systems in production: the long term (strategic), the middle term (tactical) and short term (operational). It also considers online management as a new level (a sub level of the short term). As each level encounters specific problems, appropriate approaches to deal with these are introduced and explained. These problems include the line design, the line balancing optimization, the physical layout of the production or service system, the forecasting optimization, the inventory management, the scheduling etc. Metaheuristics for Production Systems then explores logistic optimization from two different perspectives: internal (production management), addressing issues of scheduling, layout and line designs, and external (supply chain management) focusing on transportation optimization, supply chain evaluation, and location of production. The book also looks at NP-hard problems that are common in production management. These complex configurations may mean that optimal solutions may not be reached due to variables, but the authors help provide a good solution for such problems. The effective new results and solutions offered in this book should appeal to researchers, managers, and engineers in the production and service industries.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises' productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

This book presents a collection of essays written by leading researchers to honor Roman Slowinski's major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding. The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.

With the constant evolution of change in healthcare from both a technology and governmental perspective, it is imperative to take a step back and view the big picture. Relying on hunches or beliefs is no longer sustainable, so avoid jumping to conclusions and making decisions without thoroughly understanding the statistics being analyzed. The triple aim of statistics is a conceptual model laying the foundation for improving healthcare outcomes through statistics. This foundation is: know your numbers; develop behavioral interventions; and set goals to drive change. With the availability of electronic data sources, the quantity and quality of data have grown exponentially to the point of information overload. Translating all this data into words that tell a meaningful story is overwhelming. This book takes the reader on a journey that navigates through this data to tell a story that everyone can understand and use to drive improvement. Readers will learn to tell a narrative story based on data, to develop creative, innovative and effective solutions to improve processes and outcomes utilizing the authors' tools. Topics include mortality and readmission, patient experience, patient safety survey, governmental initiatives, CMS Star Rating and Hospital Compare. Storytelling with Data in Healthcare combines methodology and statistics in the same course material, making it coherent and easier to put into practice. It uses storytelling as a tool for knowledge acquisition and retention and will be valuable for courses in nursing schools, medical schools, pharmacy schools or any healthcare profession that has a research design or statistics course offered to students. The book will be of interest to researchers, academics, healthcare professionals, and students in the fields of healthcare management and operations as well as statistics and data visualization.

This book combines two distinctive topics: data science/image analysis and materials science. The purpose of this book is to show what type of nano material problems can be better solved by which set of data science methods. The majority of material science research is thus far carried out by domain-specific experts in material engineering, chemistry/chemical engineering, and mechanical & aerospace engineering. The book could benefit materials scientists and manufacturing engineers who were not exposed to systematic data science training while in schools, or data scientists in computer science or statistics disciplines who want to work on material image problems or contribute to materials discovery and optimization. This book provides in-depth discussions of how data science and operations research methods can help and improve nano image analysis, automating the otherwise manual and time-consuming operations for material engineering and enhancing decision making for nano material exploration. A broad set of data science methods are covered, including the representations of images, shape analysis, image pattern analysis, and analysis of streaming images, change points detection, graphical methods, and real-time dynamic modeling and object tracking. The data science methods are described in the context of nano image applications, with specific material science case studies.

This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material); and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems and prepares the reader to use simulation in research as well as practice.

The book is a rigorous, but concise treatment, emphasizing lasting principles but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this. An online solutions manual for end of chapter exercises is also be provided. "

Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. It covers the theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates applications through the analysis of numerous practical examples. The author draws on his 50 years of experience in the field to give your students a better understanding of probability theory and stochastic processes and enable them to use stochastic modeling in their work. New to the Second Edition Completely rewritten part on probability theory-now more than double in size New sections on time series analysis, random walks, branching processes, and spectral analysis of stationary stochastic processes Comprehensive numerical discussions of examples, which replace the more theoretically challenging sections Additional examples, exercises, and figures Presenting the material in a student-friendly, application-oriented manner, this non-measure theoretic text only assumes a mathematical maturity that applied science students acquire during their undergraduate studies in mathematics. Many exercises allow students to assess their understanding of the topics. In addition, the book occasionally describes connections between probabilistic concepts and corresponding statistical approaches to facilitate comprehension. Some important proofs and challenging examples and exercises are also included for more theoretically interested readers.

This book contains twelve selected papers presented at the International Workshop on Traffic Data Collection and its Standardization held on September 8-9th 2008 in Barcelona. Organized and chaired by Barcelo and Kuwahara, the workshop was intended to examine the purposes and quality of data and how it is collected and used in traffic analysis, with the overall intent of improving and standardizing the practice.

Traffic data is the cornerstone to everything from the most classical traffic control analysis to the most advanced real-time control and management implementing modern Intelligent Transportation Systems (ITS) applications. These applications are primarily based on the availability of traffic data supplied by a Data Collection System which, equipped with more or less sophisticated technologies, provides measurements on the fundamental traffic variables, ideally with the required level of temporal aggregation, and perhaps, when the technology allows it, additional measurements on other variables of interest, depending on the type of application in which they will be used. The applications are in turn supported by models, and in fact the primary use of the data is to provide the input to traffic models whose quality depends on the quality, consistency, robustness, completion and other characteristics of the data.

The main papers presented at the workshop dealt with

• which kind of data are available and under what conditions,

• what kind of data are needed for
• • online applications
  • model calibration/validation
  • safety analysis
• data source reliability
• how standardization can accelerate developments in the field, and how traffic data can be accessed more easily

The papers presented, from which the final twelve were chosen:

1. Calibrating the Fundamental Diagram in Congestion: Methods Based on Observations at Consecutive Loop-Detectors

2. Nicolas Chiabaut, Ludovic Leclercq, Tiphaine Bretin, Christine Buisson

   Universite de Lyon, INRETS / ENTPE, LICIT,

3. A cost-effective Method for the Detection of Queue Lengths at Traffic Lights

Thorsten Neumann

German Aerospace Center, Institute of Transportation Systems

3. Fusing Road Travel Time Data

F. Soriguera CENIT Center for Innovation in Transport, Technical

University of Catalonia (UPC)

D. Abeijon, CENIT Center for Innovation in Transport, Technical University of Catalonia (UPC),

F. Robuste, School of Civil Engineering, Technical University of Catalonia

1. Floating Car Data Based Analysis of Urban Travel Times for the Provision of Traffic Quality

2. Jan Fabian Ehmke, Stephan Meisel, Dirk Christian Mattfeld, Universitat Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group

3. Extended Floating Car Data in cooperative traffic management

4. Thomas Scheider, Martin Bohm, AustriaTech,

5. Long-term Investigations of Quality and Reliability of the Video Image Detection System m3

6. Ralf Reulke, Beate Meffert, Bjorn Piltz

   Humboldt-Universitat zu Berlin,

   Sascha Bauer, Daniel Hein, Marc Hohloch, Karsten Kozempel

   German Aerospace Center, Institute for Transportation Systems,

7. Data Mining For Traffic Flow Analysis: Visualization Approach

8. Takahiko KUSAKABE, Takamasa IRYO, Yasuo ASAKURA

   Graduate School of Engineering, Kobe University

9. Microscopic data collection method for analyzing driving behavior at traffic signals

10. Francesco Viti, Serge P. Hoogendoorn, Henk J. van Zuylen

    Delft University of Technology

    Isabel R. Wilmink, Bart van Arem

    TNO, business unit Mobility & Logistics,

11. Data Collection for Measuring Performance of an Integrated Transportation System

12. Wei-Bin Zhang, Alex Skabardonis, Meng Li, Jingquan Li, Kun Zhou, Liping Zhang

    California PATH Program, University of California at Berkeley,

13. Data Requirements for Experimental and Operational Validations of Real-time Traffic Simulation Tools

14. Christine BUISSON, Aurelien DURET

    Universite de Lyon, ENTPE-INRETS, Laboratoire d Ingenierie Circulation Transports LICIT.

15. Parameterization of distribution using survey data: The influence of spatial factors on commuting trips in The Netherlands

16. Tom Thomas, Bas Tutert

    University of Twente, The Netherlands

17. Using floating car data for traffic state estimation in signalized urban networks

18. Henk van Zuylen, Yusen Chen, Fangfang Zheng

    Delft University of Technology

19. Exploring floating car data as a-priori information to dynamic origin destination matrix estimation

20. Yusen Chen, Henk van Zuylen, Runa Asmundsdottir

    Delft University of Technology

21. Data Collection, Use and Provision at the Transport Data Centre, New South Wales, Australia

22. Peter Hidas

    Manager, Transport Model Application Transport Data Centre, NSW Ministry of Transport

23. Hysteresis in the fundamental diagram: impact of measurement methods

24. Jorge A. Laval

    School of Civil and Environmental Engineering, Georgia Institute 4 of Technology

25. Notes on traffic data, traffic applications and traffic models

26. Jaume Barcelo, Dept. of Statistics and Operations Research,

    Technical University of Catalonia

27. Standardising Traffic Data Managed by a Road Authority

28. Stuart Ballingall, Manager Road Information Services, VicRoads

29. International Traffic Data Base

Mark Miska, Masao Kuwahara, University of Tokyo"

Understand the Strategic Behavior in Queueing Systems Rational Queueing provides one of the first unified accounts of the dynamic aspects involved in the strategic behavior in queues. It explores the performance of queueing systems where multiple agents, such as customers, servers, and central managers, all act but often in a noncooperative manner. The book first addresses observable queues and models that assume state-dependent behavior. It then discusses other types of information in queueing systems and compares observable and unobservable variations and incentives for information disclosure. The next several chapters present relevant models for the maximization of individual utilities, social welfare, and profits. After covering queueing networks, from simple parallel servers to general network structures, the author describes models for planned vacations and forced vacations (such as breakdowns). Focusing on supply chain models, he then shows how agents of these models may have different goals yet they all profit when the system operates efficiently. The final chapter allows bounded rationality by lowering the assumption of fully rational agents.

The second edition of Leadership offers a unique, highly-applied academic treatise on leadership, uniquely blending a chronological analysis of the last 100 years of leadership theory with exclusive CEO interviews. The case studies, expert insights and other teaching aids are timely and hard hitting, making this textbook relevant, insightful and informative, while a research chapter empowers the reader to competently question the leaders that shape our world. The world has turned on its political and corporate axis since the first edition of Leadership was published, and it became necessary to produce a second edition that fully encapsulated, respected and observed these changes. Numerous new case studies, discussion starters and examples subsequently reflect today's volatile technological, political, financial and social shifts, while exclusive interviews with successful CEOs powerfully blend theory with practice. Readers will learn the importance of navigating leadership in the most testing of times. A new chapter, 'Researching leadership', offers the reader the opportunity to develop significantly as a leadership researcher and to ably question reality in a post-truth world. A self-leadership chapter equips the reader to develop their own leadership capabilities, while retaining the ability to avoid destructive leadership. Ultimately, readers will become empowered to appreciate the complex, intersectional nature of leadership and to learn what it takes to lead in today's politically, technologically and socially tumultuous world. This book will be particularly engaging for students and educators at secondary school, college, undergraduate and postgraduate level, and for leadership/management consultants. While the book's primary role remains as a core text for leadership, management and business modules, it will also be of interest to students on many other courses (e.g. psychology, politics, sociology). Packed with teaching resources which educators will find particularly useful, Leadership is the only textbook of its kind to offer such an applied view of this subject via the inclusion of 12 (mostly CEO) expert insights. The first edition was an "Amazon Hot New Release", so this second edition might also hold interest for a general readership.

Over the last three decades the world economy has grown strongly on the back of 'globalization' supported by the policies of free-trade, open markets and privatisation. Support has also grown for the concept of 'sustainability', meeting the needs of the present without compromising the ability of future generations to meet their own needs. But as the Earth's systems come under increasing strain, the inherent conflict between sustainability and globalization has been exposed. Green Outcomes in a Real World examines the shift in thinking required to reconcile these two important areas of policy. In this ground breaking book, Peter McManners has coined the term 'Proximization' to define a new policy framework. The principles of Proximization are: 'sustainability', 'subsidiarity', 'primacy of the state' and 'market economics' and the application of these familiar concepts towards a sustainable globalised world is novel and different. The author argues that adherence to the principles of proximization will return world society to a stable natural order, and will mean changes. Global commodity flows will reduce and barriers to migration will increase. National governments will demand more control over their finances leading to restrictions on capital flows. Indeed, Peter believes that an element of 'selfish determination' is needed. The new world order will be sustainable by design. Global organisations such as the UN, national governments and global corporations will have to understand and apply a different paradigm. The arguments in this book do not reflect the idealism or even naivety of some of the green movement. This book is about hard-edged reality presented by an author with huge experience and a deep understanding of the business perspective. It will appeal to a wide range of professionals involved in setting policy and future direction for businesses, governments, and non-governmental bodies, as well as to those with an academic interest in business, economics, social and environmental issues, and public policy.

This book describes the ontology structure, types of actors, their potential actions, and ways that actions can affect the things that are part of the conflict. An ontology of unconventional conflict supports the understanding of unconventional conflict in general. It also provides a tool for understanding and investigating a particular unconventional conflict. The ontology specifies the relations among the elements and supports creating a description of a particular situation. Unconventional conflict spans the range from natural disasters through human disagreements to irregular warfare (up to conventional war). Unconventional conflict involves damage to things and injuries to people; however, the critical factors are the actions, reactions, and opinions of people, including political, military, economic, social, infrastructure, and information components. This ontology supports and will appeal to military strategists, political scientists, economists, and politicians in understanding their planning for, and managing of these conflicts.

This volume consists of 14 contributed chapters written by leading experts, offering in-depth discussions of the mathematical modeling and algorithmic aspects for tackling a range of space engineering applications. This book will be of interest to researchers and practitioners working in the field of space engineering. Since it offers an in-depth exposition of the mathematical modelling, algorithmic and numerical solution aspects of the topics covered, the book will also be useful to aerospace engineering graduates and post-graduate students who wish to expand their knowledge by studying real-world applications and challenges that they will encounter in their profession. Readers will obtain a broad overview of some of the most challenging space engineering operational scenarios of today and tomorrow: this will be useful for managers in the aerospace field, as well as in other industrial sectors. The contributed chapters are mainly focused on space engineering practice. Researchers and practitioners in mathematical systems modelling, operations research, optimization, and optimal control will also benefit from the case studies presented in this book. The model development and optimization approaches discussed can be extended towards other application areas that are not directly related to space engineering. Therefore, the book can be a useful reference to assist in the development of new modelling and optimization applications.

This book offers a timely snapshot of research and developments in the area of air traffic engineering and management. It covers mathematical, modeling, reliability and optimization methods applied for improving different stages of flight operations, including both aerodrome and terminal airspace operations. It analyses and highlights important legal and safety aspects, and discusses timely issues such as those concerned with Brexit and the use of unmanned aerial vehicles. Gathering selected papers presented at the 6th edition of the International Scientific Conference on Air Traffic Engineering, ATE 2020, held in October 2020 in Warsaw, Poland, this book offers a timely and inspiring source of information for both researchers and professionals in the field of air traffic engineering and management.

This book serves as an introductory text in mathematical programming and optimization for students having a mathematical background that includes one semester of linear algebra and a complete calculus sequence. It includes computational examples to aid students develop computational skills.

Prevailing models of organisation divide people into owners, managers and employees, forcing especially the latter to obey, to behave, and to function well within a hierarchical and managerial pecking order. However, there is no natural law suggesting the need for such organisations, not in market economies and definitely not in modern democratic societies - and there is no justification for such types of organisation. Arguing that most current organisations are orthodox, hierarchical, anti-democratic, oppressive, unfair, and unjust, this book presents a viable alternative, a better type of organisation - the democratic organisation. Diefenbach develops and provides step by step a systematic, comprehensive, thorough, and detailed general model of the democratic organisation. He describes the democratic organisation's fundamental principles, values, governance, management, structures, and processes, and the ways it functions and operates both within the organisation and towards others and the environment. Crucially, and most importantly, the democratic organisation provides the institutions and organisational context for individuals to maintain and pursue their fundamental freedoms, inalienable rights, and dignity; to manage organisations in democratic, participative, and cooperative ways; and to conduct business in considerate, balanced, and sustainable ways. This book will be of interest to researchers, academics, practitioners, and students in the fields of management, organisation studies, strategic management, business ethics, entrepreneurship, and family business.

This handbook includes three parts, corresponding to the following three domains of OR/MS research related to sustainability: (i) Systems Design, Innovation, and Technology, (ii) Manufacturing, Logistics, and Transportation, and (iii) Sustainable Natural Resource Management. The first part of the handbook (Chapters 2-6) will focus on the creation and development of sustainable products, services, value chains, and organizations from a systems perspective. Key areas to be covered include Green Design & Innovation, Technology and Engineering Management, Sustainable Value Chain Systems, Sustainability Standards and Performance Evaluation, and Circular Economy and New Research Directions in Sustainability. The second part of the handbook (Chapters 7-11) will concentrate on the major operational and logistic issues faced by today's industries in pursuing sustainability. Key areas to be covered include Remanufacturing, Reverse Logistics, Closed-Loop Supply Chains, Sustainable Transportation, and New Research Directions in Green Supply Chain Management. The third part of the proposed handbook (Chapters 12-16) will center on major sustainability issues in managing engineering infrastructure and natural resources. Key areas to be covered include Renewable Energy, Sustainable Water Resource, Biofuel Infrastructure, Natural Gas, and New Research Direction in Sustainable Resource Management. The handbook aims to bridge the three main OR/MS research domains in sustainability: "Systems Design, Innovation, and Technology," "Manufacturing, Logistics, and Transportation," and "Sustainable Natural Resource Management." Traditionally, these domains are treated separately in the OR/MS literature. By combining the three domains, the handbook will provide a more holistic treatment of MS/OR methodologies to address critical sustainability issues faced by today's society. Unlike most existing handbooks which only focus on current OR/MS research in sustainability within a domain, this handbook will include a concluding chapter in each of the three parts to discuss and identify potential future research directions in each of the three main domains.

The purpose of Business Process Engineering: Advancing the State of the Art is to outline the structure of Business Process Engineering (BPE), its practices, methods, and theory for implementing successful organization restructuring. BPE is the design and implementation of efficient and effective business processes, and the corresponding alignment of enabling information technologies and systems. The editors have assembled the best research on BPE and recreated a structured volume that provides academic researchers and practitioners with a theoretical and practical framework for implementing specific BPE solutions for business and government. Hence, the book covers theoretical efforts towards the creation of new methods in BPE and practical issues that relate to its actual implementation in the real world of business and government. Authors from industry, government, and academia have contributed individual chapters. The emphasis is on methodology that can be replicated. Industry and governmental contributors have provided a synthesis of BPE experiences or individual case studies. In both cases, the work is intended to lead to lessons learned that may be successfully employed by others. The academically oriented chapters relate BPE methodologies to other forms of organizational change, building on previous research in related areas. The chapters are grouped as follows: Structures for BPE, Model Development, Information Technology for BPE, Tools for BPE, and Case Studies of BPE. The goal of this volume is to present works that clarify the definition of the field and establish factors that lead to success in implementation. The editors' premise is that the objective of BPE is to bringabout organizational improvement by the application of scientific principles and the use of enabling information technologies. This new methodology, founded and nurtured in practice, will evolve into a mature academic field that will involve many diverse academic disciplines. This volume is intended to contribute to that development.

This book presents the state-of-the-art in social simulation as presented at the Social Simulation Conference 2018 in Stockholm, Sweden. It covers the developments in applications and methods of social simulation, addressing societal issues such as socio-ecological systems and policy making. Methodological issues discussed include large-scale empirical calibration, model sharing and interdisciplinary research, as well as decision making models, validation and the use of qualitative data in simulation modeling. Research areas covered include archaeology, cognitive science, economics, organization science, and social simulation education. This collection gives readers insight into the increasing use of social simulation in both its theoretical development and in practical applications such as policy making whereby modelling and the behavior of complex systems is key. The book will appeal to students, researchers and professionals in the various fields.

This textbook teaches the basic concepts and methods of project management but also explains how to convert them to useful results in practice. Project management offers a promising working area for theoretical and practical applications, and developing software and decision support systems (DSS). This book specifically focuses on project planning and control, with an emphasis on mathematical modeling. Models and algorithms establish a good starting point for students to study the relevant literature and support pursuing academic work in related fields. The book provides an introduction to theoretical concepts, and it also provides detailed explanations, application examples, and case studies that deal with real-life problems. The chapter topics include questions that underlie critical thinking, interpretation, analytics, and making comparisons. Learning outcomes are defined and the content of the book is structured following these goals. Chapter 1 begins by introducing the basic concepts, methods, and processes of project management. This Chapter constitutes the base for defining and modeling project management problems. Chapter 2 explores the fundamentals of organizing and managing projects from an organization's perspective. Issues related to project team formation, the role of project managers, and organization types are discussed. Chapter 3 is devoted to project planning and network modeling of projects, covering fundamental concepts such as project scope, Work Breakdown Structure (WBS), Organizational Breakdown Structure (OBS), Cost Breakdown Structure (CBS), project network modeling, activity duration, and cost estimating, activity-based costing (ABC), data and knowledge management. Chapter 4 introduces deterministic scheduling models, which can be used in constructing the time schedules. Models employing time-based and finance-based objectives are introduced. The CPM is covered. The unconstrained version of maximizing Net Present Value (NPV) is also treated here together with the case of time-dependent cash flows. Chapter 5 focuses on the time/cost trade-off problem, explaining how to reduce the duration of some of the activities and therefore reduce the project duration at the expense of additional costs. This topic is addressed for both continuous and discrete cases. Chapter 6 discusses models and methods of scheduling under uncertain activity durations. PERT is introduced for minimizing the expected project duration and extended to the PERT-Costing method for minimizing the expected project cost. Simulation is presented as another approach for dealing with the uncertainty in activity durations and costs. To demonstrate the use of the PERT, a case study on constructing an earthquake-resistant residential house is presented. Classifications of resource and schedule types are given in Chapter 7, and exact and heuristic solution procedures for the single- and multi-mode resource constrained project scheduling problem (RCPSP) are presented. The objective of maximizing NPV under resource constraints is addressed, and the capital-constrained project scheduling model is introduced. In Chapter 8, resource leveling, and further resource management problems are introduced. Total adjustment cost and resource availability cost problems are introduced. Various exact models are investigated. A heuristic solution procedure for the resource leveling problem is presented in detail. Also, resource portfolio management policies and the resource portfolio management problem are discussed. A case study on resource leveling dealing with the annual audit project of a major corporation is presented. Project contract types and payment schedules constitute the topics of Chapter 9. Contracts are legal documents reflecting the results of some form of client-contractor negotiations and sometimes of a bidding process, which deserve closer attention. Identification and allocation of risk in contracts, project control issues, disputes, and resolution management are further topics covered in this Chapter. A bidding model is presented to investigate client-contractor negotiations and the bidding process from different aspects. Chapter 10 focuses on processes and methods for project monitoring and control. Earned Value Management is studied to measure the project performance throughout the life of a project and to estimate the expected project time and cost based on the current status of the project. How to incorporate inflation into the analysis is presented. In Chapter 11, qualitative and quantitative techniques including decision trees, simulation, and software applications are introduced. Risk phases are defined and building a risk register is addressed. An example risk breakdown structure is presented. The design of risk management processes is introduced, and risk response planning strategies are discussed. At the end of the Chapter, the quantitative risk analysis is demonstrated at the hand of a team discussion case study. Chapter 12 covers several models and approaches dealing with various stochastic aspects of the decision environment. Stochastic models, generation of robust schedules, use of reactive and fuzzy approaches are presented. Sensitivity and scenario analysis are introduced. Also, simulation analysis, which is widely used to analyze the impacts of uncertainty on project goals, is presented. Chapter 13 addresses repetitive projects that involve the production or construction of similar units in batches such as railway cars or residential houses. Particularly in the construction industry repetitive projects represent a large portion of the work accomplished in this sector of the economy. A case study on the 50 km section of a motorway project is used for demonstrating the handling of repetitive project management. How best to select one or more of a set of candidate projects to maintain a project portfolio is an important problem for project-based organizations with limited resources. The project selection problem is inherently a multi-objective problem and is treated as such in Chapter 14. Several models and solution techniques are introduced. A multi-objective, multi-period project selection and scheduling model is presented. A case study that addresses a project portfolio selection and scheduling problem for the construction of a set of dams in a region is presented. Finally, Chapter 15 discusses three promising research areas in project management in detail: (i) Sustainability and Project Management, (ii) Project Management in the Era of Big Data, and (iii) the Fourth Industrial Revolution and the New Age Project Management. We elaborate on the importance of sustainability in project management practices, discuss how developments in data analytics might impact project life cycle management, and speculate how the infinite possibilities of the Fourth Industrial Revolution and the new technologies will transform project management practices.

Making important business decisions is usually a difficult and complicated task. In the modern economy where businesses have to solve increasingly complex decision-making problems, it is important to learn and use methods and techniques including the analysis of behavioral data to support decision-making in practice. This book presents various methods and solutions to problems in modern data acquisition techniques and practical aspects of decision making. In particular, it addresses such important issues as: business decision making, multi-criteria decision analysis (MCDA), multidimensional comparative analysis (MCA), decision games and data acquisition techniques for decision making (declarative techniques and cognitive neuroscience techniques). Important topics such as consumers' rational behavior, environmental management accounting, operational research methods, neuroscience including epigenetics, DEA analysis etc., as well as case studies related to decision making in management are also included.