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Books > Business & Economics > Business & management > Management & management techniques > Operational research
Hardbound. Defined and illustrated in this book is the measurement of productivity and the sources and effects of technological change for industries and enterprises. A general framework for analysis unites general assumptions about market structure and producer motivation with new econometric methods to quantify, e.g. economics of scale and scope, learning effects and sources of biased technological change. Adaptation of accounting data to appropriate financial and economic concepts is stressed for both econometric and non-econometric measurement methods. High technology industries such as computers, semiconductors and telecommunications equipment are studied as well as regulated service enterprises. Computation and estimation routines for the SORITEC econometrics software are available on diskette from the authors.
Standards have become widespread regulatory tools that are set to promote global trade, innovation, efficiency, and quality. They contribute significantly to the creation of safe, reliable, and high quality services and technologies to ensure human health, environmental protection, or information security. Yet intentional deviations from standards by organizations are often reported in many sectors, which can either contribute to or challenge the measures of safety and quality they are designed to safeguard. Why then, despite all potential consequences, do organizations choose to deviate from standards in one way or another? This book uses structuration theory - covering aspects of both structure and agency - to explore the organizational conditions and contradictions under which different types of deviance occur. It provides empirical explanations for deviance in organizations that go beyond an understanding of individual misbehaviour where mainly a single person is held responsible. Case studies of software-developing organizations illustrate insightful generalizations on standards as a mechanism of sensemaking, resource allocation, and sanctioning, and provide ground to re-think corporate responsibility when deviating from standards in the 'audit society'.
Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence, primarily derived from a variety of data available to organizations, can be used to improve the quality of business decision-making, by helping decision makers circumvent the various cognitive biases that adversely impact how we all think. The book is built on the following premise: During the past decade, the new 'data world' emerged, in which the rush to develop competencies around business analytics and data science can be characterized as nothing less than the new commercial arms race. The ever-expanding volume and variety of data are well known, as are the great advances in data processing/analytics, data visualization, and related information production-focused capabilities. Yet, comparatively little effort has been devoted to how the informational products of business analytics and data science are 'consumed' or used in the organizational decision-making processes, as the available evidence shows that only some of that information is used to drive some business decisions some of the time. Evidence-Based Decision-Making details an explicit process describing how the universe of available and applicable evidence, which includes organizational and other data, industry benchmarks, scientific studies, and professional experience, can be assessed, amalgamated, and funneled into an objective driver of key business decisions. Introducing key concepts in relation to data and evidence, and the history of evidence-based management, this new and extremely topical book will be essential reading for researchers and students of data analytics as well as those working in the private and public sectors, and in the voluntary sector.
Like norms, translation invariant functions are a natural and powerful tool for the separation of sets and scalarization. This book provides an extensive foundation for their application. It presents in a unified way new results as well as results which are scattered throughout the literature. The functions are defined on linear spaces and can be applied to nonconvex problems. Fundamental theorems for the function class are proved, with implications for arbitrary extended real-valued functions. The scope of applications is illustrated by chapters related to vector optimization, set-valued optimization, and optimization under uncertainty, by fundamental statements in nonlinear functional analysis and by examples from mathematical finance as well as from consumer and production theory. The book is written for students and researchers in mathematics and mathematical economics. Engineers and researchers from other disciplines can benefit from the applications, for example from scalarization methods for multiobjective optimization and optimal control problems.
This book presents recent work that analyzes general issues of green logistics and smart cities. The contributed chapters consider operating models with important ecological, economic, and social objectives. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today's state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
This book focuses on the latest advances in nonlinear dynamic modeling in economics and finance, mainly-but not solely-based on the description of strategic interaction by using concepts and methods from dynamic and evolutionary game theory. The respective chapters cover a range of theoretical issues and examples concerning how the qualitative theory of dynamical systems is used to analyze the local and global bifurcations that characterize complex behaviors observed in social systems where heterogeneous and boundedly rational economic agents interact. Nonlinear dynamical systems, represented by difference and differential and functional equations, are extensively used to simulate the behavior of time-evolving economic systems, also in the presence of time lags, discontinuities, and hysteresis phenomena. In addition, some theoretical issues and particular applications are discussed, as well. The contributions gathered here offer an up-to-date review of the latest research in this rapidly developing research area.
In order to experience significant improvement in business processes, successful organizations must launch, implement, and maintain effective transformation programs. Such programs enable companies to fully maximize benefits and avoid potential failures. Optimization of Supply Chain Management in Contemporary Organizations discusses best practices and methods in transformation initiatives that improve the overall functionality and success of supply chain processes. Focusing on performance measurement, change management, and strategy development, this book is an essential reference source for executives, managers, advanced-level students, and professionals working in the field of business transformations and supply chain development.
Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting; Introduces applied optimization to the hazardous waste blending problem; Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control; Includes an extensive bibliography at the end of each chapter and an index; GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8; Solutions manual available upon adoptions.
This book takes a unique approach to linear optimization by focusing on the underlying principles and business applications of a topic more often taught from a mathematical and computational perspective. By shifting the perspective away from heavy math, students learn how optimization can be used to drive decision making in real world business settings. The book does not shy away from the theory underlying linear optimization but rather focuses on ensuring students understand the logic without getting caught up in proving theorems. Plenty of examples, applications and case studies are included to help bridge the gap between the theory and the way it plays out in practice. The author has also included several Excel spreadsheets, showing worked-out models of linear optimization that have been used to drive decisions ranging from configuring a police force to purchasing crude oil and media planning. How can the routes and pricing structures of airlines be optimized? How much should be invested in the prevention and punishment of crimes? These are everyday problems that can be solved using linear optimization, and this book shows students just how to do that. It will prove a useful, math-free resource for all students of management science and operations research.
This volume explores ways in which an organization's existing competences can be enhanced as sources of competitive advantage - either enduring or intendedly transitional. Competence enhancing activities considered include political lobbying to extend the lifetime and value of a firm's competences, expanding services to enhance the value of manufacturing capabilities, initiating knowledge management projects, strategically adapting a firm's governance structures to take advantage of government policy initiatives, staging development of competences in internationalization processes, improving capabilities in managing alliances, understanding the factors conducive to entrepreneurial action-taking, and using individual competency development in self-managing processes for organizational competence building.
Recently, many books on multiobjective programming have been published. However, only a few books have been published, in which multiobjective programming under the randomness and the fuzziness are investigated. On the other hand, several books on multilevel programming have been published, in which multiple decision makers are involved in hierarchical decision situations. In this book, we introduce the latest advances in the field of multiobjective programming and multilevel programming under uncertainty. The reader can immediately use proposed methods to solve multiobjective programming and multilevel programming, which are based on linear programming or convex programming technique. Organization of each capter is summarized as follows. In Chapter 2, multiobjective programming problems with random variables are formulated, and the corresponding interactive algorithms are developed to obtain a satisfactory solution, in which the fuzziness of human's subjective judgment for permission levels are considered. In Chapter 3, multiobjective programming problems with fuzzy random variables are formulated, and the corresponding interactive algorithms are developed to obtain a satisfactory solution, in which not only the uncertainty of fuzzy random variables but also the fuzziness of human's subjective judgment for permission levels are considered. In Chapter 4, multiobjective multilevel programming is discussed, and the interactive algorithms are developed to obtain a satisfactory solution, in which the hierarchical decision structure of multiple decision makers is reflected. In Chapter 5, two kinds of farm planning problems are solved by applying the proposed method, in which cost coefficients of crops are expressed by random variables.
This book outlines the latest trends in the use of multicriteria analysis in agriculture by highlighting recent applications for modeling agricultural decision-making. It introduces specific case studies using multicriteria analysis as a method for selecting multiattribute discrete alternatives or solving multiobjective planning problems. The book is intended for a broad readership, including agricultural and environmental economists, engineers and all scientists whose work involves the management of agricultural resources and decision-making in agriculture. The methods and applications presented in this book cover decision-making processes in agricultural and environmental contexts. The methodologies described consider multiple criteria simultaneously in a wide range of complex decision-making contexts by taking into account multiple, conflicting criteria. Given the wide range of case studies covered, the book offers a comprehensive guide to decision-making in the agricultural context and beyond.
This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.
This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field and (2), where appropriate, extend the frontier of DEA research. It defines the state-of-the-art of DEA methodology and its uses. This handbook is intended to represent a milestone in the progression of DEA. Written by experts, who are generally major contributors to the topics to be covered, it includes a comprehensive review and discussion of basic DEA models, which, in the present issue extensions to the basic DEA methods, and a collection of DEA applications in the areas of banking, engineering, health care, and services. The handbook's chapters are organized into two categories: (i) basic DEA models, concepts, and their extensions, and (ii) DEA applications. First edition contributors have returned to update their work. The second edition includes updated versions of selected first edition chapters. New chapters have been added on: different approaches with no need for a priori choices of weights (called multipliers) that reflect meaningful trade-offs, construction of static and dynamic DEA technologies, slacks-based model and its extensions, DEA models for DMUs that have internal structures network DEA that can be used for measuring supply chain operations, Selection of DEA applications in the service sector with a focus on building a conceptual framework, research design and interpreting results. "
This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
Diverse kinds of knowledge are vital for each organization that would successfully compete today in an international scenario. The emergent relevance of knowledge and its management in an even more complex environment opens up the possibility to analyze, investigate and deepen our understanding on different aspects related to several functional areas in business management. Nowadays, firms that create new knowledge and apply it effectively and efficiently will be successful at creating competitive advantages. The choices of the firms in selecting and applying different knowledge process (such as knowledge sourcing, transferring and exploiting) as well as knowledge tools may be crucial. Thus, the role of knowledge as the key source of potential advantage for organizations and indeed whole economies is still a hot debate in the international landscape. This book develops insights for the management of knowledge in cross-functional business areas to originate an innovative approach to the classical Knowledge Management (KM) field. This book provides a fresh perspective on different knowledge related topics in an international landscape, highlighting the key role of knowledge and its management in business activities. Overall, the primary aim of this book is to extend our understandings on how KM can be helpful in several cross-functional management areas, such as strategic management, finance, HRM and innovation as well as in different business circumstances such as M&A, internationalization processes and risk management.
This book provides the readers with the overall latest research on think tanks, summarizing the characteristics of think tanks, revealing the general laws and internal logic of think tank research, applying systems, dialectical views and operations research, system theory, and cybernetics to the problems existing in the research work of think tanks at home and abroad. Based on problem-oriented, evidence-oriented and scientific orientation, this book systematically considers the methodology of think tank research, proposes the DIIS theoretical method system of think tank research, defines the standardization process of think tank research and the quality standard of think tank DIIS, and gives corresponding DIIS to the actual think tank research problem. The method aims to improve the scientificity, effectiveness, and reliability of the research results of think tanks, provide systematic theoretical analysis for think tank research, promote the professional development of think tanks, and better serve the modernization of national governance systems and governance capabilities. This book presents new theoretical and research method support and reference that contribute to macro decision-making departments, management departments, scientific research institutes, universities, and enterprises think tank research related departments, strategic decision makers, think tank managers, think tank researchers, and readers interested in think tanks reading and using. Finally yet importantly, this book embodies the research of think tank as the object of investigation, jumping out of specific social conditions, using systemic thoughts, thinking about the more general role and characteristics of think tanks from the theoretical level, important theoretical issues such as principles and logic systems that think tank research should follow.
Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research. The use of hidden Markov models (HMMs) has become one of the hottest areas of research for such applications to finance. This handbook offers systemic applications of different methodologies that have been used for decision making solutions to the financial problems of global markets. As the follow-up to the authors' Hidden Markov Models in Finance (2007), this offers the latest research developments and applications of HMMs to finance and other related fields. Amongst the fields of quantitative finance and actuarial science that will be covered are: interest rate theory, fixed-income instruments, currency market, annuity and insurance policies with option-embedded features, investment strategies, commodity markets, energy, high-frequency trading, credit risk, numerical algorithms, financial econometrics and operational risk. Hidden Markov Models in Finance: Further Developments and Applications, Volume II presents recent applications and case studies in finance and showcases the formulation of emerging potential applications of new research over the book's 11 chapters. This will benefit not only researchers in financial modeling, but also others in fields such as engineering, the physical sciences and social sciences. Ultimately the handbook should prove to be a valuable resource to dynamic researchers interested in taking full advantage of the power and versatility of HMMs in accurately and efficiently capturing many of the processes in the financial market.
Organizations increasingly use temporary designs. Many temporary organizations are assembled by "mixing and matching" building blocks from static, bureaucratic, parent organizations into a temporary configuration. At the same time, such "mixed and matched" temporary organizations often operate under difficult and dangerous circumstances. During operations, these temporary organizations can experience numerous internal problems: ranging from friendly fire in a military context to budget and time issues in construction projects and problematic coordination in a crisis management context. This book develops insight into the relationship between a "mixing and matching" temporary design strategy and operational problems. To so do, military and crisis management contexts are systematically studied from a sociotechnical design perspective that emphasizes self-organization to develop organizational controllability. Operating Under High-Risk Conditions in Temporary Organizations demonstrates that a "mixing and matching" design strategy can be related to system failure. Furthermore, it is shown that a process of self-design emerged in which operators attempted to create ad-hoc networks for meaningful, safe and controllable operations. The analyses result in a model that shows mechanisms between characteristics of organizational design and controllability of operations. Not only does this model have relevance to the military and crisis management contexts, relevance is also demonstrated for a broader family of temporary organizations and application of sociotechnical network design theory.
Until recently most observers were of the opinion that firms had to adopt a Japanese model of management or perish. They overlooked the fact that there are a number of efficient productive models and that there is no single 'best way'. This book shows the diversity of productive models and discusses the optimum macro and micro economic and social conditions that a firm needs to stay profitable. In conclusion the authors suggest an analytical framework of profitability conditions, easily accessible to practitioners, academics and students.
These proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics, supply chain management, and decision sciences. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Optimization, Transportation, Logistics and Intelligent Business. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium "The Seventh International Forum on Decision Sciences", which took place in Windsor, Canada.
This pioneering book on food study pursues an interdisciplinary approach to service science and the service engineering field. Further, it highlights a range of experiments conducted at actual business sites to verify the effectiveness of the proposed methodologies and theories. In modern society, food study has become more complex, as it involves multiple fields of science. For instance, a long-lived society entails a number of problems for human beings. A balanced intake of nutrients is important for a healthy life, but in many cases, healthy food is not the most enjoyable. As such, it is important for the food industry to provide foods that are both tasty and wholesome, based on the sciences of gastronomy and nutrition. Conventional food study proceeds along the lines of a specific field such as nutrition, agriculture, or gastronomy, though it should be conducted in an interdisciplinary manner. This book covers multifaceted research on food study to respond to today's societal demands, based mainly on the natural and social sciences. It addresses a wide range of topics, including: food production management using mathematical modeling, operations research, and production engineering; evaluation of food products based on big data analysis; psychological experiments and ethnography; food products based on consumer behavior; organoleptic assessment and health improvement; design of physical dining environments using virtual reality, pedestrian debt recognition (human indoor position measuring), and observation of behavior. Reporting on and assessing many studies conducted at actual business locations, the book offers a unique and highly practical resource.
Large-Scale Nonlinear Optimization reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. The chapters of the book, authored by some of the most active and well-known researchers in nonlinear optimization, give an updated overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.
Advances in Business and Management Forecasting is a blind refereed
serial publication published on an annual basis. The objective of
this research annual is to present state-of-the-art studies in the
application of forecasting methodologies to such areas as sales,
marketing, and strategic decision making. (An accurate, robust
forecast is critical to effective decision making.) It is the hope
and direction of the research annual to become an applications and
practitioner-oriented publication. |
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