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Books > Business & Economics > Business & management > Management & management techniques > Operational research
Globalization has made both operations and supply chains more complex than ever before. Inputs are sourced from many locations all over the world to serve different needs and market segments throughout the planet, making it a global challenge that necessitates a global strategic response. Managing Operations Throughout Global Supply Chains is a crucial academic resource that discusses concepts, methodologies, and applications of emerging techniques for operations and supply chain management processes that promote cost efficiency. While highlighting topics such as global operations, resource planning, and business forecasting, this publication explores how organizations manage the procurement of all necessary resources at every stage of the production cycle from the original source to the final consumers. This book is ideally designed for researchers, academicians, practitioners, professional organizations, policymakers, and government officials.
Evaluating the role of logistics and supply chain management skills or applications is necessary for the success of any organization or business. As market competition becomes more aggressive, it is crucial to evaluate ways in which a business can maintain a strategic edge over competitors. The Handbook of Research on Information Management for Effective Logistics and Supply Chains highlights strategies, tools, and skills necessary for supply management within organizations and companies. Featuring best practices and empirical research within the field, this handbook is a critical reference source for scholars, practitioners, researchers, information systems and telecommunication specialists, and managers.
This book on Applied Operations Research and Financial Modelling in Energy (AORFME) presents several applications of operations research (OR) and financial modelling. The contributions by a group of OR and Finance researchers focus on a variety of energy decisions, presenting a quantitative perspective, and providing policy implications of the proposed or applied methodologies. The content is divided into three main parts: Applied OR I: Optimization Approaches, Applied OR II: Forecasting Approaches and Financial Modelling: Impacts of Energy Policies and Developments in Energy Markets. The book appeals to scholars in economics, finance and operations research, and to practitioners working in the energy sector. This is the eighth volume in a series of books on energy organized by the Centre for Energy and Value Issues (CEVI). For this volume, CEVI collaborated with Hacettepe University's Energy Markets Research and Application Center. The previous volumes in the series are: Financial Aspects in Energy (2011), Energy Economics and Financial Markets (2012), Perspectives on Energy Risk (2014), Energy Technology and Valuation Issues (2015), Energy and Finance (2016), Energy Economy, Finance and Geostrategy (2018), and Financial Implications of Regulations in the Energy Industry (2020).
This book presents a rich collection of studies on the analysis of sustainable development from a multiple criteria decision-making (MCDM) perspective, written by some of the most prominent authors in the field of MCDM/A. The book constitutes a unique international reference guide to the analysis, measurement, and management of sustainability in a multidimensional decision analysis context. Chiefly intended for academics and policymakers, it reflects some of the latest methodological advances in decision-making, which are illustrated in real-life applications to sustainability-related topics in both the private and public sector.
This book focuses on selected aspects of the current and upcoming trends in transportation, logistics and decision making. In detail the included transportation management, optimization and management of logistics system, big data technology and method, financial engineering and risk management, investment decision and risk management, data-driven process management decision, scheduling optimization and combination decision, theory and method of forecasting and decision making, data mining and knowledge management, operation and green supply chain management, industrial engineering and operation management, information system and business intelligence, Internet + green manufacturing, strategic emerging industries and Industrial finance, big data and smart city. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of International Conference on Intelligent Transportation and Logistics with Big Data & International Forum on Decision Sciences, which took place in Harbin, Heilongjiang province, China, in 2022.
This innovative Handbook draws together and reflects on the specific methodological challenges that an international business scholar is likely to face when undertaking a qualitative research project. With a practical, hands-on approach to methodological debates, the Handbook raises concerns specific to international business scholars. Covering the entire life cycle of a research project from its philosophical underpinnings to publication hurdles, the book explores existing practices and gives voice to multiple, even contrasting perspectives. This invaluable source of experiential knowledge, as well as conceptual understanding, has been achieved by a truly international authorship. Including fascinating vignettes written by senior academics, the result is a guide that will be indispensable. Capturing the experiences and practices of qualitative researchers, the Handbook of Qualitative Research Methods for International Business should be on the bookshelves of students and scholars of IB, researchers in international management and marketing, and teachers of cross-cultural and IB research methods.
This book presents a structured approach to develop mathematical optimization formulations for several variants of facility layout. The range of layout problems covered includes row layouts, floor layouts, multi-floor layouts, and dynamic layouts. The optimization techniques used to formulate the problems are primarily mixed-integer linear programming, second-order conic programming, and semidefinite programming. The book also covers important practical considerations for solving the formulations. The breadth of approaches presented help the reader to learn how to formulate a variety of problems using mathematical optimization techniques. The book also illustrates the use of layout formulations in selected engineering applications, including manufacturing, building design, automotive, and hospital layout.
This book showcases state-of-the-art advances in service science and related fields of research, education, and practice. It presents emerging technologies and applications in contexts ranging from healthcare, energy, finance, and information technology to transportation, sports, logistics, and public services. Regardless of its size and service, every service organization is a service system. Due to the socio-technical nature of service systems, a systems approach must be adopted in order to design, develop and deliver services aimed at meeting end users' utilitarian and socio-psychological needs alike. Understanding services and service systems often requires combining multiple methods to consider how interactions between people, technologies, organizations and information create value under various conditions. The papers in this volume highlight a host of ways to approach these challenges in service science and are based on submissions to the 2021 INFORMS Conference on Service Science.
This book examines the Analytical Hierarchy Process (AHP) method, its varied uses, as well as its limitations for solving real-world scenarios. While the simplicity of the method compels users to find shortcuts to a real-world problem, it also leads to obtaining wrong results that do not represent reality. By alerting practitioners about the core necessities of a new scenario, this book helps solve this problem, as well as contribute to the field of Multicriteria Decision Making Method (MDCM). The authors use a demonstrative, rather than a theoretical approach, and examine 30 subjects that displays the shortcomings and drawbacks of the AHP. Each one is examined in-depth, discussed, debated and reasoned, using examples, some of them numeric. The book highlights the rationality and common sense of the subjects, and in most cases, validates the criticism by showing through numerical examples, the impossibility of the AHP method to address, let alone solve real-world projects. At the conclusion of each subject, a table is built comparing the similarities and differences between the opinions of the authors and other experts, along with the respective pros and cons.
This book is focused on quality management, and four different lenses which can be used to explore the phenomenon. It introduces emergence as a paradigm in thinking about quality, and explores conditions which are beneficial to radical innovation. The Emergence Paradigm in Quality Management provides an overview of the existing movements in thinking about quality, and discusses why these movements in fact represent paradigms. Three paradigms, the Empirical Paradigm, the Reference Paradigm and the Reflective Paradigm, are explained followed by a search for the Fourth Paradigm, the so-called Emergence Paradigm, which presents a route to radical innovation in organizations when plans, strategies and models fail. It presents the debates around the paradigms, and explores which is the best approach. This professional text will be ideal for strategy and policy makers wanting to establish a link between their conceived plans and the attention for quality, while finding ways to facilitate innovation. Professionals in a range of for-profit and non-profit organizations, including healthcare, will be able to expand their knowledge on quality management, operations management, and organizational studies.
As businesses undergo digital transformation, technologies will lead to greater efficiencies and change how we interact in traditional relationships among suppliers, producers, and customers, as well as between human and machine. One such technology is the introduction of management information systems (MIS) that provide a company with the coordination, control, analysis, and visualization of information by collecting from various digital environments. In today's digital age, information needs to be managed, and MIS have the ability to transfer the information obtained by computer systems to the business operations within the business models, business processes, and management functions. Advanced MIS and Digital Transformation for Increased Creativity and Innovation in Business is an essential reference source that discusses the impact of digital technologies in enterprises and their competitive environment on management information systems and examines the application of new technologies to support strategic decisions and realize exciting visions. Featuring research on topics such as machine learning, resource planning, and e-commerce, this book is ideally designed for managers, executives, IT specialists, analysts, business professionals, training officers, software engineers, business administrators, scholars, researchers, and practitioners seeking coverage on future trends, issues, and challenges in relation to management information systems.
This first book on Maritime Informatics describes the potential for Maritime Informatics to enhance the shipping industry. It examines how decision making in the industry can be improved by digital technology, and introduces the technology required to make Maritime Informatics a distinct and valuable discipline. Based on participating in EU funded research over the last six years to improve the shipping industry, the editors stipulate that there is a need for the new discipline of Maritime Informatics, which studies the application of information systems to increasing the efficiency, safety, and ecological sustainability of the world's shipping industry. This book examines competition and collaboration between shipping companies, and also companies who serve shipping needs, such as ports and terminals. Practical examples from leading experts give the reader real world examples for better understanding.
This book provides relevant theoretical frameworks and the latest empirical research findings of Operations Research/Management Science applied to Internet of Things. This book identifies and describes ways in which OR and MS have been applied and influenced the development of IoT. Examples are from smart industry; city; transportation; home and smart devices. It discusses future applications, trends, and potential benefits of this new discipline. It is written for professionals who want to improve their understanding of the strategic role of IoT at various levels of the organization, that is, IoT at the global economy level, at networks and organizations level, at teams and work groups, at information systems and, finally, IoT at the level of individuals, as players in the networked environments.
Fashion has been steadily moving from the brick and mortar to the digital market. As such, it is increasingly vital to research new methods that will help businesses to grow and succeed in this new sphere. Advanced Fashion Technology and Operations Management is a pivotal reference source for the latest development management strategies, fashion marketing, international business, and fashion entrepreneurship. Featuring extensive coverage across a range of relevant perspectives and topics, such as online shopping behavior, digital fashion, and e-commerce, this book is ideally designed for professionals, entrepreneurs, students, and researchers.
This book presents the human, cultural, and scientific contributions of professor Eliano Pessa, who recently passed away. His research interests and activities were varied, some of which included quantum physics, cognitive science and psychology, systems science, artificial intelligence, and alpinism. They were never disciplinary-separated issues, but rather some coherent dimensions of his interests in life. He lived and not only practiced interdisciplinarity and multiple dimensions; he considered it unacceptable to do only one thing in life. The contributors in this volume consider, discuss, interpret, and represent the multiplicity and interdisciplinarity experienced, lived and applied by Pessa. The chapters are inspired by, rebuild, and retrace such networked interests lived by him from the personal, cultural, and scientific points of view of the authors. This is true interdisciplinarity and usage of non-equivalences, honoring the richness of Pessa's contributions.
This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.
This book examines cross-chain control centers (4C), an ambitious concept in supply chain management and logistics that is intended to foster collaboration between different supply chains to increase efficiency. It provides an overview of the main results, insights, and other developments in the academic field of horizontal collaboration. Furthermore, it gives recommendations to governments, commercial companies, and academia on how to proceed with horizontal logistics collaboration in the years to come. To link research with practice, the book takes the Dutch project on cross-chain collaboration centers (4Cs) and identifies a typology of existing patterns for horizontal collaboration in supply chains. Finally, the book zooms in on the Netherlands as a case-study of intense public-private partnerships to develop 4C as a mature logistics value proposition. It provides an overview of the accomplishments in the government supported 4C projects and offers a critical reflection of why some more ambitious and structural solutions have not found solid ground yet. The book is of value to researchers and professionals in the supply chain domain.
This book recapitulates the major developments in Decision Support Systems (DSS) over the last 30 years in order to evaluate the research areas of decision making and in which direction the field should proceed. As it attempts to find a consensus about the next steps for the future of DSS research, the book also enforces the trends and new technologies currently in use. The book examines topics such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluation and analysis through social networks, and e-learning and its application to real environments. It clearly presents the evidence to support their cases and attempts to promote an extensive and objective discussion. In addition, the book also reflects on approaches to dead-end ideas and failures in DSS to better understand the lessons learned. The contributions for this book have been written by thought leaders and influential researchers from the EURO Working Group of Decision Support Systems (EWG-DSS).
The success of a business is largely determined by how adaptably it can facilitate innovative digital architectures and human-based resources. By redesigning this process, businesses have also changed their growth factors to incorporate a more service-driven ecosystem focused on a configuration of resources, talent, and technologies. Business Reinvention for Ecosystem Value, Flexibility, and Empowerment: Emerging Research and Opportunities provides a holistic view of how a business sets the proper mindset in light of a plethora of digital technologies, how to systematically choreograph the right components for the reinvention, and how to strategically undertake the change journey. The content within this publication examines human value, e-business, and self-determined behaviors. It is designed for academicians, corporate managers, executives, researchers, and students.
This book offers an introduction to various models and methods for green supplier evaluation and selection (GSES) within different information settings. As such, it provides valuable knowledge, useful GSES methods and practical examples that can be considered by manufacturers in selecting appropriate green suppliers to improve their environmental performance and customer satisfaction. This book is useful for practitioners and researchers working in the fields of supply chain management, operation management, information science, industrial engineering, and management science. It is also useful as a textbook for postgraduate and senior undergraduate students.
This book presents various multi-criteria analysis methods for sustainability-oriented analysis and decision-making for energy systems, under various different conditions and scenarios. It presents methodologies to answer the questions relating to which of the options are the most sustainable among the alternatives, and how multi-criteria decision analysis methods can be used to select the most sustainable energy systems. A systematic innovative methodological framework is presented, which enables the most appropriate energy system to be selected under different conditions including: Scientific decision support tools for sustainable energy system selection; Fuzzy, grey, and rough sets based multi-criteria decision analysis; Decision-making models under uncertainties; and The combination of life cycle thinking and multi-criteria decision analysis This book is of interest to researchers, engineers, decision makers, and postgraduate students within the field of energy systems, sustainability, and multi-criteria decision analysis.
This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches. |
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