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."

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.

This book applies Multicriteria Decision Making (MCDM) tools and techniques to problems in location analysis. It begins with a generic model for MCDM and subsequently develops specific versions of the technique for particular location problems. Throughout the book, MCDM is understood to encompass all tools and techniques that choose or rank existing or feasible solutions, including discrete multi-attribute decision making (MADM) problems, which typically include an attribute table that specifies the consequences of each decision with regard to the given criteria, as well as multi-objective linear problems (MOLPs), which incorporate all objectives in a single optimization problem.  The book is organized as follows: the first four chapters introduce readers to the basic tools and techniques used in single-objective optimization, multicriteria decision making, location analysis, and other tools, such as statistical regression and geographical information systems. This is followed by ten chapters on model applications, each of which introduces readers to a specific location problem and applies one technique to solve it. The book is then wrapped up in a closing chapter that looks at the location process from a practitioner’s point of view.  This book is intended as a textbook for upper-undergraduate and master-level courses on location analysis. It will also benefit decision-makers who actually need to locate facilities. 

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.   

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."

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.

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.

Because it deals with sustainably supplying cities and reducing congestion and pollution related to goods transport in urban areas, city logistics is an important field in transportation sciences. These logistics systems need to be sustainable and reliable to ensure the continued flow of goods. Logistics and Transport Modeling in Urban Goods Movement is a pivotal reference source that provides vital research on the main approaches and techniques used in urban goods transport modelling while addressing planning and management issues. Highlighting topics such as urban logistics, vehicle routing, and greenhouse emissions, this book is ideally designed for civil/transport engineers, planners, transport economists, geographers, computer scientists, practitioners, professionals, researchers, and students seeking current research on urban goods modelling.

This book covers central issues in mitigating supply chain risks from various perspectives. Today's supply chains are vulnerable to disruptions that can have a significant impact on firms, business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions. In this regard, the book presents a wealth of methods, strategies and analyses that are essential for mitigating supply chain risks. As a comprehensive collection of the latest research and cutting-edge developments in supply chain risk and its mitigation, the book is structured into four main parts, addressing supply chain risk strategies and developments; supply chain risk management review; supply chain sustainability and resilience; and supply chain analysis and risk management applications. The contributing authors are leading academic researchers and practitioners, who combine findings and research results with a practical and contemporary view on how companies can best manage supply chain risks and disruptions, as well as how to create resilient and sustainable supply chains. This book can be used as an essential resource for students and scholars who are interested in pursuing research or teaching courses on the rapidly growing field of supply chain management. It also offers an interesting and informative read for managers and practitioners who need to deepen their understanding of effective supply chain risk management.

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 book presents a selection of current research results in the field of intelligent systems and draws attention to their practical applications and issues connected with the areas of decision-making, economics, business and finance. The nature of the contributions is interdisciplinary - combining psychological and behavioural aspects with the theory and practice of decision-support, design of intelligent systems and development of machine learning tools. The authors, among other topics, discuss the multi-expert evaluation with intangible criteria, suggest a redefinition of the standard multiple-criteria decision-making framework, propose novel methods for causal map analysis and new feature selection methods. The topics are selected to stress the potential of the up-to-date intelligent methods to deal with practical problems relevant in these areas and to provide inspiration for advanced students, researchers and practitioners in the respective fields.

This book covers sustainable development in smart society's 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.

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 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 gathers selected peer-reviewed papers from the 15th World Congress on Engineering Asset Management (WCEAM), which was hosted by The Federal University of Mato Grosso do Sul Campo Grande, Brazil, from 15--18 August 2021 This book covers a wide range of topics in engineering asset management, including: strategy and standards; sustainability and resiliency; servitisation and Industry 4.0 business models; asset information systems; and asset management decision-making. The breadth and depth of these state-of-the-art, comprehensive proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students.

This book aims at providing cases with inspiring findings for global researchers in capacity allocation and reservation. Capacity allocation mechanisms are introduced in the book, as well as the measures to build models and the ways to achieve supply chain coordination. In addition, it illustrates the capacity reservation contract and quantity flexible contract with comparisons and some numerical studies. The book is divided into 7 chapters. Chapter 1 introduces the background and the latest development of the research. Chapter 2 introduces how to manage downstream competition through capacity allocation in symmetric market, including proportional mechanism and lexicographic mechanism. Demand competition is introduced in Chapter 3 as well as the uniform allocation mechanism and the comparisons among three different mechanisms. In Chapter 4, we give information about demand competition with fixed factor allocation, and the comparison with other allocations. Chapter 5 provides the optimal strategies under fixed allocation with multiple retailers and the impacts of fixed proportions. Chapter 6 illustrates how to achieve supply chain coordination through capacity reservation contract and its comparison with the quantity flexibility contract, and in Chapter 7 we describe outsourcing decisions and order policies in different systems with some numerical studies. We sincerely hope that this book can provide some useful suggestions and inspirations for scholars around the world who have the same interests in this field.

This is an open access book discusses readers to various methods of modeling plans and policies that address public sector issues and problems. Written for public policy and social sciences students at the upper undergraduate and graduate level, as well as public sector decision-makers, it demonstrates and compares the development and use of various deterministic and probabilistic optimization and simulation modeling methods for analyzing planning and management issues. These modeling tools offer a means of identifying and evaluating alternative plans and policies based on their physical, economic, environmental, and social impacts. Learning how to develop and use the mathematical modeling tools introduced in this book will give students useful skills when in positions of having to make informed public policy recommendations or decisions.

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 monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed size from a multivariate Gaussian random vector, so as to maximize Shannon's differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynamic programming, approximation algorithms, 0/1 optimization (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.

This book represents the compilation of several research approaches on opera tional freight carrier planning carried out at the Chair of Logistics, University of Bremen. It took nearly three years from the first ideas to the final version, now in your hands. During this time, several persons helped me all the time to keep on going and to re-start when I got stuck in a dead end or when I could not see the wood for the trees. I am deeply indebted to them for their encouragement and comments. Prof. Dr. Herbert Kopfer, holder of the Chair of Logistics, introduced me into the field of operational transport planning. He motivated and supervised me. Furthermore, he supported me constantly and allowed me to be as free as possible in my research and encouraged me to be as creative as necessary. In addition, I have to thank Prof. Dr. Hans-Dietrich Haasis, Prof. Dr. Martin G. Mohrle and Prof. Dr. Thorsten Poddig. On behalf of all my colleagues, who supported me in numerous ways, I have to say thank you to Prof. Dr. Dirk C. Mattfeld, Prof. Dr. Christian Bierwirth, Henner Gratz, Prof. Dr. Elmar Erkens, Nadja Shigo and Katrin Dorow. They all helped me even with my most obscure and dubious problems. My family supported me all the time. They always showed me their trust and encouraged me continuously. Special thanks are dedicated to my parents Monika and Heinz-Jiirgen."

Newtonian Nonlinear Dynamics for Complex Linear and Optimization Problems explores how Newton's equation for the motion of one particle in classical mechanics combined with finite difference methods allows creation of a mechanical scenario to solve basic problems in linear algebra and programming. The authors present a novel, unified numerical and mechanical approach and an important analysis method of optimization.

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

Waiting in lines is a staple of everyday human life. Without really noticing, we are doing it when we go to buy a ticket at a movie theater, stop at a bank to make an account withdrawal, or proceed to checkout a purchase from one of our favorite department stores. Oftentimes, waiting lines are due to overcrowded, overfilling, or congestion; any time there is more customer demand for a service than can be provided, a waiting line forms. Queuing systems is a term used to describe the methods and techniques most ideal for measuring the probability and statistics of a wide variety of waiting line models. This book provides an introduction to basic queuing systems, such as M/M/1 and its variants, as well as newer concepts like systems with priorities, networks of queues, and general service policies. Numerical examples are presented to guide readers into thinking about practical real-world applications, and students and researchers will be able to apply the methods learned to designing queuing systems that extend beyond the classroom. Very little has been published in the area of queuing systems, and this volume will appeal to graduate-level students, researchers, and practitioners in the areas of management science, applied mathematics, engineering, computer science, and statistics.

A complete guide for turning a relocation plan into a reality
The Office Relocation Sourcebook provides relocation teams, at firms of all sizes, with the background information and practical guidance they need to pull off a relocation project cost-effectively and with a minimum of disruption to the employees being moved. Written by the head of the Human Factors Group at Exxon Biomedical Sciences, Inc., this valuable resource:
* Arms you with all the forms, checklists, surveys, and summaries guaranteed to make any office relocation project as painless and cost-efficient as possible
* Guides you step by step through the entire relocation process, from the initial planning stages to post-project evaluation
* Covers both the nuts-and-bolts issues and crucial human factors side of the relocation equation
* Features a computer disk packed with valuable relocation tools, including a comprehensive relocation template

Take the sting out of your next relocation project with The Office Relocation Sourcebook.
Office relocation is one of the most challenging aspects of a facility professional's job. This challenge and the thrill of meeting it are even greater for members of the relocation team who have had little or no prior relocation experience. To begin with, there are the thousand and one logistical details that go into the designing, planning, and implementation of a relocation project. Then, there is the seemingly impossible task of keeping affected employees happy and supplied with everything they need to perform their jobs--without running into massive cost overruns.
The Office Relocation Sourcebook takes the sting out of relocation. Written by an author with twenty-five years' experience in facility management and human factors design, this valuable resource provides all the background information and practical guidance needed to pull off a cost-effective relocation project with a minimum of disruption. These methods and techniques are appropriate for firms of any size, regardless of the number of employees being relocated.
Writing in a warm, conversational style, peppered with handy checklists, summaries, and survey tools, Dennis Attwood guides you step by step through the entire relocation process, from the initial planning stages to post-project evaluation. He provides coverage of nuts-and-bolts issues through the human factors side of the relocation equation. For instance, Attwood explores workers' reasons for resisting relocation and describes innovative communication techniques that can substantially reduce employee resistance and the common adverse side effects of disrupting the workplace. In his discussion of work system planning, he compares traditional design arrangements, such as the neighborhood and team concepts, with alternative workplace strategies, including reuse of existing office space, and the office outside of the company.
The enclosed disk supplies a variety of useful tools and, in addition to the forms and checklists found in the book, arms you with a valuable relocation template.
Make your next office relocation project a success with The Office Relocation Sourcebook.

This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data. This book consists of eight chapters. Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods for solving linear systems will be introduced for finding the stationary distribution of a Markov chain. The chapter then covers the basic theories and algorithms for hidden Markov models (HMMs) and Markov decision processes (MDPs). Chapter 2 discusses the applications of continuous time Markov chains to model queueing systems and discrete time Markov chain for computing the PageRank, the ranking of websites on the Internet. Chapter 3 studies Markovian models for manufacturing and re-manufacturing systems and presents closed form solutions and fast numerical algorithms for solving the captured systems. In Chapter 4, the authors present a simple hidden Markov model (HMM) with fast numerical algorithms for estimating the model parameters. An application of the HMM for customer classification is also presented. Chapter 5 discusses Markov decision processes for customer lifetime values. Customer Lifetime Values (CLV) is an important concept and quantity in marketing management. The authors present an approach based on Markov decision processes for the calculation of CLV using real data. Chapter 6 considers higher-order Markov chain models, particularly a class of parsimonious higher-order Markov chain models. Efficient estimation methods for model parameters based on linear programming are presented. Contemporary research results on applications to demand predictions, inventory control and financial risk measurement are also presented. In Chapter 7, a class of parsimonious multivariate Markov models is introduced. Again, efficient estimation methods based on linear programming are presented. Applications to demand predictions, inventory control policy and modeling credit ratings data are discussed. Finally, Chapter 8 re-visits hidden Markov models, and the authors present a new class of hidden Markov models with efficient algorithms for estimating the model parameters. Applications to modeling interest rates, credit ratings and default data are discussed. This book is aimed at senior undergraduate students, postgraduate students, professionals, practitioners, and researchers in applied mathematics, computational science, operational research, management science and finance, who are interested in the formulation and computation of queueing networks, Markov chain models and related topics. Readers are expected to have some basic knowledge of probability theory, Markov processes and matrix theory.