This book pulls together many perspectives on the theory, methods and practice of drawing judgments from panels of experts in assessing risks and making decisions in complex circumstances. The book is divided into four parts: Structured Expert Judgment (SEJ) current research fronts; the contributions of Roger Cooke and the Classical Model he developed; process, procedures and education; and applications. After an Introduction by the Editors, the first part presents chapters on expert elicitation of parameters of multinomial models; the advantages of using performance weighting by advancing the "random expert" hypothesis; expert elicitation for specific graphical models; modelling dependencies between experts' assessments within a Bayesian framework; preventive maintenance optimization in a Bayesian framework; eliciting life time distributions to parametrize a Dirichlet process; and on an adversarial risk analysis approach for structured expert judgment studies. The second part includes Roger Cooke's oration from 1995 on taking up his chair at Delft University of Technology; one of the editors reflections on the early decade of the Classical Model development and use; a current overview of the theory of the Classical Model, providing a deep and comprehensive perspective on its foundations and its application; and an interview with Roger Cooke. The third part starts with an interview with Professor Dame Anne Glover, who served as the Chief Scientific Advisor to the President of the European Commission. It then presents chapters on the characteristics of good elicitations by reviewing those advocated and applied; the design and development of a training course for SEJ; and on specific experiences with SEJ protocols with the intention of presenting the challenges and insights collected during these journeys. Finally, the fourth (and largest) part begins with some reflections from Willy Aspinall on his many experiences in applying the Classical Model in several application domains; it continues with related reflections on imperfect elicitations; and then it presents chapters with applications on medicines policy and management, supply chain cyber risk management, geo-political risks, terrorism and the risks facing businesses looking to internationalise.

This book examines inventory and production strategies that can reduce unexpected breakdown costs. It highlights different EPQ models to deal with such problems, providing optimal value derivations for decision variables. It provides proofs for concavity or convexity of objective functions. The chapters also include numerical examples for all the developed mathematical models. Imperfect Inventory Systems: Inventory and Production Management and Breakdown should be useful for professionals working on supply chains, but also researchers in operations research and inventory management.

This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of 'productivity analysis/data envelopment analysis' and 'data science/big data'. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others. Examples of data science techniques include linear and logistic regressions, decision trees, Naive Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubt that nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data. Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.

The well-ordered, fully aligned view of organization and management practice, with its unfailingly positive results, bears little relationship to the world that managers and others experience every day. This straight-line, 'do this and you'll get that' idealization is far removed from the wiggly reality. Despite this, the former continues to dominate the ways in which management is spoken about and judged in formal organizational arenas and wider society. This creates unrealistic expectations of what managers (from CEO to the front line) can sensibly achieve independently of the actions of others. Crucially, too, it distorts the ways in which they and others account formally for their actions. And so, the fantasy continues. Against this background, the book offers a radically different way of thinking about, and engaging with, the irreducible complexity of organization and management practice. Using straightforward language throughout, it sets out to help managers and others to become consciously aware of what they already know deep down about how organization works and what they - and everyone else - are actually doing in practice. It then offers a practical approach to everyday practice that takes complexity seriously. Armed with these new insights, readers will be better placed to apply their innate understanding and practical judgement to the demands that they and others face day to day. Whether these arise from their roles as managers, other practitioners, policy makers, regulatory authorities, or participants more generally.

This book contains international perspectives that unifies the themes of strategic management, decision theory, and data science. It contains thought-provoking presentations of case studies backed by adequate analysis adding significance to the discussions. Most of the decision-making models in use do take due advantage of collection and processing of relevant data using appropriate analytics oriented to provide inputs into effective decision-making. The book showcases applications in diverse fields including banking and insurance, portfolio management, inventory analysis, performance assessment of comparable economic agents, managing utilities in a health-care facility, reducing traffic snarls on highways, monitoring achievement of some of the sustainable development goals in a country or state, and similar other areas that showcase policy implications. It holds immense value for researchers as well as professionals responsible for organizational decisions.

This book presents innovative operations research applications in business, specifically industrial engineering and its sub-disciplines. It investigates new perspectives in operations research and management science with regard to research methods, the research context, and industrial engineering, offering readers a broad range of new approaches to management problems. The book features the latest work of researchers who have worked with Professor Fusun Ulengin or built upon her work in their academic careers. Written in honor of Prof. Ulengin, this book was edited by her former Ph.D. students, who are now experts in operations research, multiple criteria decision making, competitiveness, logistics, and supply chain management. Prof. Ulengin's impact in academia is visible in the range of topics and methodologies featured in this book: Location and transportation problems, competitiveness of nations, food supply chains, debt collection, mathematical modelling, multiple criteria decision making, data envelopment analysis, random forests, and Bayesian networks.

Operations research tools are ideally suited to providing solutions and insights for the many problems health policy-maker's face. Indeed, a growing body of literature on health policy analysis, based on operations research methods, has emerged to address the problems mentioned above and several others. The research in this field is often multi-disciplinary, being conducted by teams that include not only operations researchers but also clinicians, economists and policy analysts. The research is also often very applied, focusing on a specific question driven by a decision-maker and many times yielding a tool to assist in future decisions. The goal of this volume was to bring together a group of papers by leading experts that could showcase the current state of the field of operations research applied to health-care policy. There are 18 chapters that illustrate the breadth of this field. The chapters use a variety of techniques, including classical operations research tools, such as optimization, queuing theory, and discrete event simulation, as well as statistics, epidemic models and decision-analytic models. The book spans the field and includes work that ranges from highly conceptual to highly applied. An example of the former is the chapter by Kimmel and Schackman on building policy models, and an example of the latter is the chapter by Coyle and colleagues on developing a Markov model for use by an organization in Ontario that makes recommendations about the funding of new drugs. The book also includes a mix of review chapters, such as the chapter by Hutton on public health response to influenza outbreaks, and original research, such as the paper by Blake and colleagues analyzing a decision by Canadian Blood Services to consolidate services. This volume could provide an excellent introduction to the field of operations research applied to health-care policy, and it could also serve as an introduction to new areas for researchers already familiar with the topic. The book is divided into six sections. The first section contains two chapters that describe several different applications of operations research in health policy and provide an excellent overview of the field. Sections 2 to 4 present policy models in three focused areas. Section 5 contains two chapters on conceptualizing and building policy models. The book concludes in Section 6 with two chapters describing work that was done with policy-makers and presenting insights gained from working directly with policy-makers.

The authors contend that current knowledge management efforts in organizations need to be re-focused so that they can be better poised for success. Topics discussed include: missing capabilities of knowledge management, knowledge management in strategic alliances, customer knowledge management, knowledge markets, and knowledge management systems, among others. The authors take a pragmatic approach to knowledge management and present the material in a jargon free and accessible way.

The book consolidates systems thinking as a new world-hypothesis that is already suggesting itself behind the advancement of quantum mechanics and Ashby's cybernetics. In particular, it shows how Einstein's misgivings about quantum mechanics boil down to his persistence in defending the principle of contiguity at the root of the modern cosmology and, in relation to neo-cybernetics, the book rediscovers Ashby's theory of adaptive behaviour enabling a new synthesis between physiology, psychology and ethology that has implications for systems practice. Furthermore, this new "cosmology" comes with a new "anthropology" that informs utopics, the science of utopic systems, and sheds new light on the actual founding fathers of the domain of human science. In particular, the book provides an understanding of how our human world works and how it is being constituted by utopic systems that look into the future to realize something possible. Finally, it points the way to the future unification of knowledge bringing together systems philosophy and systems science given that world-hypothesis is what makes logically possible the development and consolidation of all the different domains of science.

This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions-that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs. It focuses on how best to frame non-profit performance and productivity, and provides a suite of tools for measurement and benchmarking. It further challenges the reader to consider alternative and appropriate uses of quantitative measures, which are fit-for-purpose in individual contexts. It is true that the risk of misusing quantitative measures is ever-present. But does that risk outweigh the benefits of forming a more precise and shared understanding of what could generate better outcomes? There will always be concerns about policy and performance management. Goodheart's Law states that once a measure becomes a target, it is no longer a good measure. This book helps to strike a meaningful balance between what can be measured, what cannot, and how best to use quantitative information in sectors that are often averse to being held up to the light and put on a scale by outsiders.

Balk argues that most professionals in government agencies are underutilized. He proposes an operational approach, called public agency democracy, that should help reduce costly and disconcerting errors. The book will interest those who wish to better understand the frustrations of public service and how to turn these to motivate change.

Well over two million very qualified individuals mediate between high-level managers and other members of public agencies. These grossly underutilized intermediary professionals must become more empowered to reduce waste, malfeasance and other costly errors. Balk proposes an applied theory of public agency democracy designed to liberate the potential of its highly trained experts.

The book begins by discussing professionals as power intermediaries and their necessary tensions with authority around matters of reform. Recognized dilemmas in the field of public administration are reviewed to demonstrate the need to resolve issues concerning public agency democracy. A model is then developed to incorporate democratic action with responses ranging from routine to whistle-blowing activities. The second part of the book shows why existing management orientations are not receptive to the need for agency democracy. Conventional orientations reject the paradoxical realities of government environments; therefore, ingrained beliefs about effectiveness and management authority are at times inappropriate. Management approaches to public service motivation lack sophistication. Four final chapters are devoted to techniques and approaches on the part of professionals to initiate change. These involve techniques to assess organizational predicaments, design resolutions and become constructively involved in processes of agency reform. Ways are proposed for professionals and others to institutionalize public agency democracy in government environments.

The book offers a comprehensive survey of interval-valued intuitionistic fuzzy sets. It reports on cutting-edge research carried out by the founder of the intuitionistic fuzzy sets, Prof. Krassimir Atanassov, giving a special emphasis to the practical applications of this extension. A few interesting case studies, such as in the area of data mining, decision making and pattern recognition, among others, are discussed in detail. The book offers the first comprehensive guide on interval-valued intuitionistic fuzzy sets. By providing the readers with a thorough survey and important practical details, it is expected to support them in carrying out applied research and to encourage them to test the theory behind the sets for new advanced applications. The book is a valuable reference resource for graduate students and researchers alike.

This book aims to provide new research methods, theories and applications from various areas of management and engineering. In detail, the included scientific papers analyze and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of the papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations. To meet the needs of consumers and to promote core competences, many institutions and firms have been developing new types of services. This proceeding focus on "AI and data driven technical and management innovation in logistics, informatics and services." In detail, the included scientific papers analyze the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. This book is the documentation of the conference "11th International Conference on Logistics, Informatics and Service Sciences," which took place at the Shandong University. Due to the impact of COVID-19, LISS 2021 took place online as a virtual conference.

The book offers a comprehensive, practice-oriented introduction to the field of fuzzy mathematical programming (FMP) as key topic of modern analytics. FMP plays a fundamental role in dealing with a varied range of problems, such as those concerning smart cities, sustainability, and renewable energies. This book includes an introduction to the basic concepts, together with extensive information on the computational-intelligence-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for analytics.

Management of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization. In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making the book a valuable reference for researchers, technical professionals, and students.

This book offers a concise introduction to the field of financial economics and presents, for the first time, recent behavioral finance research findings that help us to understand many puzzles in traditional finance. Tailor-made for master's and PhD students, it includes tests and exercises that enable students to keep track of their progress. Parts of the book can also be used at the bachelor level.

This proceedings volume gathers together selected peer-reviewed papers presented at the second edition of the XXVI International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM), which was virtually held on February 22-24, 2021 with the main organization based at the Pontifical Catholic University of Rio de Janeiro, Brazil. Works cover a range of topics in industrial engineering, including operations and process management, global operations, managerial economics, data science and stochastic optimization, logistics and supply chain management, quality management, product development, strategy and organizational engineering, knowledge and information management, sustainability, and disaster management, to name a few. These topics broadly involve fields like operations, manufacturing, industrial and production engineering, and management. This book can be a valuable resource for researchers and practitioners in optimization research, operations research, and correlated fields.

Cognition-driven decision support system (DSS) has been recognized as a paradigm in the research and development of business intelligence (BI). Cognitive decision support aims to help managers in their decision making from human cognitive aspects, such as thinking, sensing, understanding and predicting, and fully reuse their experience. Among these cognitive aspects, decision makers situation awareness (SA) and mental models are considered to be two important prerequisites for decision making, particularly in ill-structured and dynamic decision situations with uncertainties, time pressure and high personal stake. In today s business domain, decision making is becoming increasingly complex. To make a successful decision, managers SA about their business environments becomes a critical factor.

This book presents theoretical models as well practical techniques of cognitiondriven DSS. It first introduces some important concepts of cognition orientation in decision making process and some techniques in related research areas including DSS, data warehouse and BI, offering readers a preliminary for moving forward in this book. It then proposes a cognition-driven decision process (CDDP) model which incorporates SA and experience (mental models) as its central components. The goal of the CDDP model is to facilitate cognitive decision support to managers on the basis of BI systems. It also presents relevant techniques developed to support the implementation of the CDDP model in a BI environment. Key issues addressed of a typical business decision cycle in the CDDP model include: natural language interface for a manager s SA input, extraction of SA semantics, construction of data warehouse queries based on the manger s SA and experience, situation information retrieval from data warehouse, how the manager perceives situation information and update SA, how the manager s SA leads to a final decision. Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed."

This book focuses on the adoption of a Dynamic Performance Management (DPM) approach to support the planning and management of urban transportation systems. DPM allows one to embrace a dynamic and systemic perspective and, as a result, to frame the contribution of different stakeholders, in terms of outcome-based performance, at an inter-institutional level. The discussed DPM approach allows one to focus on the causal relationships and feedback processes that characterize urban transportation systems' governance. Particularly, through the adoption of such an approach, it is possible to identify outcome-based performance measures that help to monitor and drive the governance network toward the creation of public value for the reference communities.Strategic Planning for Urban Transportation: A Dynamic Performance Management Approach begins with an examination of urban transportation, highlighting the main criticalities and future challenges of managing it. Next, the book examines the governance of urban transportation including how to identify and engage stakeholders. Finally, the book introduces the main application of DPM and system dynamics to urban areas, with specific regards to transportation. The framework is outlined, and a case study is provided as a practical example of how to apply the model. This book should be useful to urban transportation decision-makers at both the managerial and political level.

30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries.

This book discusses corporate citizenship, corporate responsibility and business ethics across Africa generally, and Botswana specifically. It begins by contextualizing Botswana within the broader context of Africa, using nine other countries - Angola, Cameroon, Ghana, Kenya, Nigeria, South Africa, Zambia and Zimbabwe - to provide a comparative perspective, examining the common factor: that weak legalization makes it challenging for corporate social responsibility to be actualized.From this background, the book then discusses Botswana as a key study. Botswana has been described as 'Africa's economic miracle' due to its growing economy since independence This puts it in a unique position for the implementation and study of corporate social responsibility. The interdisciplinary team of authors employ various research methods to examine the complex relationship between business, society, corporations and social justice issues.This book will be valuable reading for any academic working on corporate social responsibility in Africa, and will present an interesting insight to an often neglected area of study. France Maphosa is a Professor of Sociology at the University of Botswana. His research interests include migration and transnationalism, the sociology of entrepreneurship, corporate social responsibility, urban and rural livelihoods, labour studies and alternative dispute resolution (ADR). Langtone Maunganidze is a Senior Lecturer in the Faculty of Social Sciences at the Midlands State University in Zimbabwe. His research interests include industrial sociology, business and society, rural livelihoods and sustainable development, and entrepreneurship.

This book summarizes years of research in the field of fuzzy relational programming, with a special emphasis on geometric models. It discusses the state-of-the-art in fuzzy relational geometric problems, together with key open issues that must be resolved to achieve a more efficient application of this method. Though chiefly based on research conducted by the authors, who were the first to introduce fuzzy geometric problems, it also covers important findings obtained in the field of linear and non-linear programming. Thanks to its balance of basic and advanced concepts, and its wealth of practical examples, the book offers a valuable guide for both newcomers and experienced researcher in the fields of soft computing and mathematical optimization.

Understanding the concept of Entrepreneurial Orientation (EO) is of critical importance as organizations and individuals manage a world that is defined by increasing uncertainty and complexity. The need for organizations of all types and sizes to survive and thrive in such an environment demonstrates a clear need for both managers and academics to really understand EO. Building upon this foundational need to better understand EO and with both a scholarly desire to synthesize and the practical need to execute, this volume convenes some of the world's leading experts on EO to address some of the most pressing issues facing scholars and leaders in the world of practice. Within this volume, you'll discover cutting edge insights ranging from theorizing on the future of EO to an empirical investigation of its measurement. There are chapters that focus on international ventures and EO and a detailed call for a global, multidimensional view of EO. Other contributions provide contextual views of EO that examine its connections to digital work environments, family business, and more. Taken together, this volume provides readers with an overview of the current state of EO research and sets a compelling agenda for its future.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP's performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.