1 Nabil R. Adam and Ali Dogramaci Measuring, analyzing, and improving productivity in a given organization is a complex process that involves the contributions of economists, industrial engineers, operations researchers, management scientists, and lawyers. The objective of this book is to provide the reader with a sample of original papers that relate to these productivity topics at the organizational level. In the book, the word organization refers to business firms and municipal organizations. The hook is divided into three parts: perspectives on productivity mea surement, a range of studies at the micro level, and some productivity issues in public organizations. Part I, which consists of three chapters, deals with productivity measurement. The first two chapters of this part cover a broad framework of measurement concepts and techniques; the last chapter, on the other hand, provides the reader with an example of productivity measurement for a specific industry (in this case, food retail ing). Thus, a spectrum of productivity measurement issues is covered in this part of the book."

The past decade has shown an increasing level of interest, research and application of quantitative models and computer based tools in the process industry. These models and tools constitute the basis of so-called Advanced Planning Systems which have gained considerable attention in practice. In particular, OR methodology has been applied to analyze and support the design of supply networks, the planning and scheduling of operations, and control issues arising in the production of food and beverages, chemicals, pharmaceutical, for instance. This book provides both new insights and successful solutions to problems of production planning and scheduling, logistics and supply chain management. It comprises reports on the state of the art, applications of quantitative methods, as well as case studies and success stories from industry. Its contributions are written by leading experts from academia and business. The book addresses practitioners working in industry as well as academic researchers in production, logistics, and supply chain management.   

This book introduces readers to a new approach to identifying stock market bubbles by using the illiquidity premium, a parameter derived by employing conic finance theory. Further, it shows how to develop the closed form formulas of the bid and ask prices of European options by using Black-Scholes and Kou models. By using the derived formulas and sliding windows technique, the book explains how to numerically calculate illiquidity premiums. The methods introduced here will enable readers interested in risk management, portfolio optimization and hedging in real-time to identify when asset prices are in a bubble state and when that bubble bursts. Moreover, the techniques discussed will allow them to accurately recognize periods of exuberance and panic, and to measure how different strategies work during these phases with respect to calmer periods of market behavior. A brief history of financial bubbles and an outlook on future developments serve to round out the coverage.

1 Ali Dogramaci and Nabil R. Adam 1.1. OVERVIEW With the decline of U.S. productivity growth, interest has surged to under stand the behavior of productivity measures through time, the conceptual foundations of productivity analysis, and the linkage between productivity performance and other major forces in the economy. The purpose of this volume is to present a brief overview of some of the concepts used in aggre gate and industry-level productivity analyses and the results of some of the recent research in this field. The book is divided into three parts. Part I covers some of the methodo logical approaches used in aggregate and industry-level productivity studies. Part II deals with the movement of labor productivity measures through time. The papers in this part of the book study productivity changes as uni variate time series and analyze some of the characteristics of the patterns displayed. The papers in Part III address the issues of measurement of capi tal, the relation of capital formation to productivity growth, and the rela tion of imported intermediate inputs to U.S. productivity performance."

This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.

In a world with highly competitive markets and economic instability due to capitalization, industrial competition has increasingly intensified. In order for many industries to survive and succeed, they need to develop highly effective coordination between supply chain partners, dynamic collaborative and strategic alliance relationships, and efficient logistics and supply chain network designs. Consequently, in the past decade, there has been an explosion of interest among academic researchers and industrial practitioners in innovative supply chain and logistics models, algorithms, and coordination policies. Mathematically distinct from classical supply chain management, this emerging research area has been proven to be useful and applicable to a wide variety of industries. This book brings together recent advances in supply chain and logistics research and computational optimization that apply to a collaborative environment in the enterprise.

This book provides a comprehensive overview of recent developments in network dynamics and control with applications to supply chains, manufacturing and logistics systems. It systemizes these developments in the form of new taxonomies and methodological principles to shape the research domain of supply network dynamics control. Uniquely, the book links the fundamentals of control and system theories and artificial intelligence with supply chain and operations management. It addresses the needs of researchers and practitioners alike, revealing the challenges and opportunities of supply chain and operations management by means of dynamic system analysis.

This book presents the potential use and implementation of intelligent techniques in decision making processes involved in organizations and companies. It provides a thorough analysis of decisions, reviewing the classical decision theory, and describing usual methods for modeling the decision process. It describes the chronological evolution of Decision Support Systems (DSS) from early Management Information Systems until the appearance of Intelligent Decision Support Systems (IDSS). It explains the most commonly used intelligent techniques, both data-driven and model-driven, and illustrates the use of knowledge models in Decision Support through case studies. The author pays special attention to the whole Data Science process, which provides intelligent data-driven models in IDSS. The book describes main uncertainty models used in Artificial Intelligence to model inexactness; covers recommender systems; and reviews available development tools for inducing data-driven models, for using model-driven methods and for aiding the development of Intelligent Decision Support Systems

Hardbound. This book is a result of recent developments in several fields. Mathematicians, statisticians, finance theorists, and economists found several interconnections in their research. The emphasis was on common methods, although the applications were also interrelated.The main topic is dynamic stochastic models, in which information arrives and decisions are made sequentially. This gives rise to what finance theorists call option value, what some economists label quasi-option value. Some papers extend the mathematical theory, some deal with new methods of economic analysis, while some present important applications, to natural resources in particular.

In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the "Advanced Analytics in Mining Engineering Book" as a practical road map and tools for unleashing the potential buried in your company's data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners - undergraduate and graduate IT and mining engineering students - with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain - in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins - in line with leading "digital" industries.

This book showcases how the latest and most advanced types of analytical modeling and empirical analysis can help to create value in the global supply chain. Focusing on practical relevance, it shares valuable management insights and addresses key issues in operations management (OM), demonstrating how past research has led to various practices and impacts, while also exploring the aspirations of the latest research. It presents current research on various topics such as global supply chain design, service supply chains, product design, responsible supply chains, performance and incentives in operations, data analytics in health services, new business models in the digital age, and new digital technology advances such as blockchain. In addition, it presents practical case studies on the aforementioned topics. Beyond the value of its contents, the book is intended as a tribute to Professor Morris Cohen, who has been a major contributor to advancing the research frontier in operations management and a driving force in shaping the field. Given its scope, the book will appeal to a wide readership, from researchers and PhD students to practitioners and consultants.

The emergence of internet technologies have provided organisations and customers with access to vast amounts of data, information, and services which have revolutionized the process of exchanging products and services online. Trends in E-Business, E-Services, and E-Commerce: Impact of Technology on Goods, Services, and Business Transactions provides insights into issues, challenges, and solutions related to the successful application and management aspects of electronic business. This book will bring together a comprehensive framework for researchers and practitioners in understanding the growing demand of e-business research.

This book identifies the responsibilities of management in the regulatory territories of the FAA (USA), the EASA (European Union) and the GCAA (UAE), identifying the daily challenges of leadership in ensuring their company is meeting the regulatory obligations of compliance, safety and security that will satisfy the regulator while also meeting the fiducial responsibilities of running an economically viable and efficient lean company that will satisfy the shareholders.

Detailing each responsibility of the Accountable Manager, the author breaks them down to understandable and achievable elements where methods, systems and techniques can be applied to ensure the role holder is knowledgeable of accountabilities and is confident that they are not only compliant with the civil aviation regulations but also running an efficient and effective operation. This includes the defining of an Accountable Manager "tool kit" as well as possible software "dashboards" that focus the Accountable Manager on the important analytics, such as the information and data available, as well as making the maximum use of their expert post holder team.

This book will be of interest to leadership of all aviation- related companies, such as airlines, charter operators, private and executive operators, flying schools, aircraft and component maintenance facilities, aircraft manufacturers, engine manufacturers, component manufacturers, regulators, legal companies, leasing companies, banks and finance houses, departments of transport, etc; any relevant organisation regulated and licensed by civil aviation authority. It can also be used by students within a wide range of aviation courses at colleges, universities and training academies.

This Festschrift honors George Samuel Fishman, one of the founders of the eld of computer simulation and a leader of the disciplines of operations research and the management sciences for the past ve decades, on the occasion of his seventieth birthday. The papers in this volume span the theory, methodology, and application of computer simulation. The lead article is appropriately titled "George Fishman's Professional Career." In this article we discuss George's contributions to operations research and the m- agement sciences, with special emphasis on his role in the advancement of the eld of simulation since the 1960s. We also include a brief personal biography together with comments by several individuals about the extraordinary effect that George has had on all his students, colleagues, and friends. Thesecondarticle, titled"AConversationwithGeorgeFishman,"isthetranscript of an extended interview with George that we conducted in October 2007. In the article titled "Computer Intensive Statistical Model Building," Russell Cheng studies resampling methods for building parsimonious multiple linear regr- sion models so as to represent accurately the behavior of the dependent variable in terms of the smallest possible subset of explanatory (independent) variables. The author shows how bootstrap resampling can be used not only for rapid identi cation of good models but also for ef cient comparison of competing models.

This proceedings volume highlights the state-of-the-art knowledge related to optimization, decisions science and problem solving methods, as well as their application in industrial and territorial systems. It includes contributions tackling these themes using models and methods based on continuous and discrete optimization, network optimization, simulation and system dynamics, heuristics, metaheuristics, artificial intelligence, analytics, and also multiple-criteria decision making. The number and the increasing size of the problems arising in real life require mathematical models and solution methods adequate to their complexity. There has also been increasing research interest in Big Data and related challenges. These challenges can be recognized in many fields and systems which have a significant impact on our way of living: design, management and control of industrial production of goods and services; transportation planning and traffic management in urban and regional areas; energy production and exploitation; natural resources and environment protection; homeland security and critical infrastructure protection; development of advanced information and communication technologies. The chapters in this book examine how to deal with new and emerging practical problems arising in these different fields through the presented methodologies and their applications. The chapter topics are applicable for researchers and practitioners working in these areas, but also for the operations research community. The contributions were presented during the international conference "Optimization and Decision Science" (ODS2017), held at Hilton Sorrento Palace Conference Center, Sorrento, Italy, September 4 - 7, 2017. ODS 2017, was organized by AIRO, Italian Operations Research Society, in cooperation with DIETI (Department of Electrical Engineering and Information Technology) of University "Federico II" of Naples.

Over the last two decades, the field of public administration has witnessed theoretical and practical changes that have innovated the relationships between public administration and performance management. Dealing with the rising complexity of performance regimes in contemporary public administration requires that policy-makers and their organizations are able to face unpredictable problems impacting on a community's quality of life. Complex policy issues - such as immigration, pandemics, societal aging, crime, unemployment, and financial crises - cannot be easily solved by quick fixes that are focused only on a short-term and bounded vision of their causes. They rather require "robust" methods to support policy analysis and to affect sustainable community outcomes in cross-boundary settings. As illustrated in this book, Dynamic Performance Management provides a methodological framework enabling policy-makers to outline the causal relationships among policy outcomes, performance drivers, and related strategic resources. Such a modeling approach helps stakeholders to broaden the investigated system boundaries so to balance short- and long-term performance under different result domains. This approach blends performance management and System Dynamics modeling. Several examples and case studies are discussed to enable scholars and practitioners to appreciate the practical implications related to the use of such an approach.

Logistics and supply chain management is facing disruptive economic, technological and climate change developments that require new strategies. New technologies such as the Internet-of-Things, digital manufacturing or blockchain are emerging quickly and could provide competitive advantage to those companies that leverage the technologies smartly while managers that do not adopt and embrace change could be left behind. Last but perhaps most important for mankind, sustainability aspects such as low-carbon transportation, closed loop supply chains or socially-responsible supply chain setups will become essential to operate successfully in the future. All these aspects will affect logistics and supply chains as a whole as well as different functional areas such as air cargo, maritime logistics or sourcing/procurement. This book aims to dive into several of these functional topics to highlight the key developments in the next decade predicted by leading global experts in the field. It features contributions and key insights of globally leading scholars and senior industry experts. Their forward-looking perspectives on the anticipated trends are aimed at informing the reader about how logistics and supply chain management will evolve in the next decade and which academic qualities and skills will be required to succeed in the "new normal" environment that will be characterized by volatile and increasingly disrupted business eco-systems. Future scenarios are envisaged to provide both practitioners and students with insights that will help them to adapt and succeed in a fast changing world.

Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

This book explores clustering operations in the context of social networks and consensus-reaching paths that take into account non-cooperative behaviors. This book focuses on the two key issues in large-scale group decision-making: clustering and consensus building. Clustering aims to reduce the dimension of a large group. Consensus reaching requires that the divergent individual opinions of the decision makers converge to the group opinion. This book emphasizes the similarity of opinions and social relationships as important measurement attributes of clustering, which makes it different from traditional clustering methods with single attribute to divide the original large group without requiring a combination of the above two attributes. The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters' opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers. Graduates and researchers in the fields of management science, computer science, information management, engineering technology, etc., who are interested in large-scale group decision-making and consensus building are potential audience of this book. It helps readers to have a deeper and more comprehensive understanding of clustering analysis and consensus building in large-scale group decision-making.

This proceedings volume convenes peer-reviewed, selected papers presented at the XXVIII International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM) that was held in Mexico City, Mexico, July 17-20, 2022, with a special focus on applications of industrial engineering and operations management for research and practice. Fields covered include operations, manufacturing, industrial and production engineering and management, emphasizing optimization models and data science applications to real-world problems. In this book, the reader will find works on topics as optimization models; stochastic optimization; digital transformation in the supply chain; data science applications in operations management; Industry 4.0: manufacturing planning & control; blockchain; intelligent transportation systems; sustainable and reverse logistics; big data and demand planning; predictive and prescriptive analytics; last-mile delivery optimization; stochastic inventory models; new trends in information technology for operation management; stochastic optimization; optimization models for omnichannel; safety in operation management; and more. This volume includes relevant information for academics, since most of the chapters focus on real-world case studies and systematic reviews, but also for professionals in the industrial sector as it presents solutions to complex industrial challenges. Previous 2018, 2019, 2020, and 2021 IJCIEOM proceedings can also be found in Springer's catalog.

As the field of Supply Chain Management has matured, maintaining the precise flow of goods to maintain schedules (hence, minimizing inventories) on a just-in-time basis still remains as a major challenge. This problem or challenge has resulted in a fair amount of quantitative research in the area, producing an array of models and algorithms to help ensure the precise flow of components and final products into inventories to meet just-in-time requirements.

Just-in-Time Scheduling: Models and Algorithms for Real Time Operating Systems is the first expository treatment surveying the theoretical work on computer systems models and algorithms utilized in just-in-time scheduling. With the impact of globalization and supply chains on manufacturing, there are immense amounts of material flowing through supply chains at any given time worldwide. Therefore the scheduling of all the stages of material arriving at different geographical points at precise times is a highly significant problem. Moreover, the theoretical work in this area has larger ramifications for operational scheduling in many application areas. The scheduling models and algorithms presented and illustrated in the book will be done so in the context of extensive use of computer systems in a "real time context." The "just-in-time" and "real-time" theoretical work in the book will be of value and interest to many Engineers, Computer Scientists and Operations Research/Management Science researchers, students and practitioners. The book will survey and synthesize all the research in this topical area.

The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank reversal. The maximum eigenvalue threshold method is proposed as the new consistency index for the AHP/ANP. An induced bias matrix model (IBMM) is proposed to identify and adjust the inconsistent data, and estimate the missing or uncertain data. Two applications of IBMM including risk assessment and decision analysis, task scheduling and resource allocation in cloud computing environment, are introduced to illustrate the proposed IBMM.

This book provides students and researchers with a resource that includes the current application of the multi-criteria decision theory in a variety of fields, including the environment, health care, engineering, and architecture. There are many critical parameters (criteria) that can directly or indirectly affect the consequences of various decisions. The application of the multi-criteria decision theory focusses mainly on the use of computational methods which include multiple criteria and orders of preference for the evaluation and the selection of the best option among many alternatives based on the desired outcome. The theory of multi-criteria decision making (MCDM) is an approach that can be extremely useful for students, managers, engineers of manufacturing companies, etc.

This edited collection addresses the question of which capabilities and competencies enable Behavioral Operational Research to provide sustained improvement to decision processes. The aim is to show how a focus on capability and competency will not only meet short-term requirements for problem solving and decision support, but also build a solid foundation for the future. The contributors present recent advances in Behavioral OR, with a focus on the ways in which users of models deal with incomplete and imprecise information, subjective boundaries and uncertainty. These chapters are structured around three key dimensions of BOR: capabilities, cognition and aspects of practice.

In the 21st century, advancements in the digital world are bringing about rapid waves of change in organizational management. As such, it is increasingly imperative to discover ways for businesses to adapt to changes in the markets and seize various digital marketing opportunities. Improving Business Performance Through Innovation in the Digital Economy is an essential reference source for the latest research on the impact of digital computing. It investigates new economic and entrepreneurial approaches to enhancing community development. Featuring research on topics such as business ethics, mobile technology, and cyber security, this book is ideally designed for knowledge workers, business managers, executives, entrepreneurs, small and medium enterprise managers, academicians, researchers, students, and global leaders seeking coverage on the management of sustainable enterprises.