How do bureaucracies remember? The conventional view is that institutional memory is static and singular, the sum of recorded files and learned procedures. There is a growing body of scholarship that suggests contemporary bureaucracies are failing at this core task. This Element argues that this diagnosis misses that memories are essentially dynamic stories. They reside with people and are thus dispersed across the array of actors that make up the differentiated polity. Drawing on four policy examples from four sectors (housing, energy, family violence and justice) in three countries (the UK, Australia and New Zealand), this Element argues that treating the way institutions remember as storytelling is both empirically salient and normatively desirable. It is concluded that the current conceptualisation of institutional memory needs to be recalibrated to fit the types of policy learning practices required by modern collaborative governance.

This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book's closing section, several case studies are presented, helping students apply the theory covered to practical problems. The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide.

In this edited volume, we present the state-of-the-art views of the perspective of enterprise risk management, to include frameworks and controls in the ERM process with respect to supply chains, constructions, and project, energy, environmental and sustainable development risk management. The bulk of this volume is devoted to presenting a number of modeling approaches that have been (or could be) applied to enterprise risk management in construction.

This book studies diverse categories of venture capital (VC) firms in India based on their ownership type (domestic vs foreign), stage of investment (early vs growth stage) and VC investment team composition (entrepreneurial experience vs investing experience). For each category of VC firms, the nuances in their investment, portfolio involvement and exit strategies are separately analysed. Employing the framework of information asymmetry, the book studies how different categories of VC firms rely on distinct mechanisms such as deal syndication and domain specialization to address the ensuing adverse selection and agency risks. It also delves into the macro context by assessing whether the emergence of VC in India has been driven by 'pull' or 'push' factors. This is accomplished by analysing in depth the supply and demand of VC funds. Finally, it critically reviews the existing policies of entrepreneurial finance and arrives at recommendations for future directions of the same.

The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random processes, the authors not only meet the demand for a solid theoretical account but also develop a stochastic processes counterpart of the classical copula theory that exists for finite-dimensional random variables. Presenting both the technical aspects and the applications of the theory, this is a valuable reference for researchers and practitioners in the field, as well as for graduate students in pure and applied mathematics programs. Numerous theoretical examples are included, alongside examples of both current and potential applications, aimed at helping those who need to model structured dependence between dynamic random phenomena.

Analysis, assessment, and data management are core tools required for operation research analysts. The April 2011 conference held at the Helenic Military Academy addressed these issues with efforts to collect valuable recommendations for improving analysts' capabilities to assess and communicate the necessary qualitative data to military leaders. This unique volume is an outgrowth of the April conference and comprises of contributions from the fields of science, mathematics, and the military, bringing Greek research findings to the world. Topics cover a wide variety of mathematical methods used with application to defense and security. Each contribution considers directions and pursuits of scientists that pertain to the military as well as the theoretical background required for methods, algorithms, and techniques used in military applications. The direction of theoretical results in these applications is conveyed and open problems and future areas of focus are highlighted. A foreword will be composed by a member of N.A.T.O. or a ranking member of the armed forces. Topics covered include: applied OR and military applications, signal processing, scattering, scientific computing and applications, combat simulation and statistical modeling, satellite remote sensing, and applied informatics - cryptography and coding. The contents of this volume will be of interest to a diverse audience including military operations research analysts, the military community at large, and practitioners working with mathematical methods and applications to informatics and military science.

This Element deals with the know-how and show-how to accomplish high velocity business operations. The basis of these operations is real-time data and low latency processing. Relevant applications are pervasive due to the emerging technologies of IoT, 5G, AI and data analytics. This Element explores theories and methods of configuring, formulating and implementing high velocity business operations with properly designed and developed platforms and processes. Current mobile transformation is enabling the unwiring of businesses, de-territorializing them, and creating more opportunities for these operations. High velocity business processes increase throughput and efficiency, offering first-mover advantage. They also provide location-independence due to use of mobile platforms and devices (smartphones, tablets and wearables). This Element present mobility as a critical attribute of high velocity business operations, taking advantage of world-wide resources and expertise with well-designed mobile platforms and their data.

Content of this proceedings discusses emerging trends in structural reliability, safety and disaster management, covering topics like total quality management, risk maintenance and design for reliability. Some papers also address chemical process reliability, reliability analysis and engineering applications in chemical process equipment systems and includes a chapter on reliability evaluation models of chemical systems. Accepted papers from 2019 International Conference on Reliability, Risk Maintenance and Engineering Management (ICRRM 2019) are part of this conference proceeding. It offers useful insights to road safety engineers, disaster management professionals involved in product design and probabilistic methods in manufacturing systems.

This book constitutes the refereed proceedings of the 19th International Conference on Group Decision and Negotiation, GDN 2019, held in Loughborough, UK, in June 2019. The field of Group Decision and Negotiation focuses on decision processes with at least two participants and a common goal but conflicting individual goals. Research areas of Group Decision and Negotiation include electronic negotiations, experiments, the role of emotions in group decision and negotiations, preference elicitation and decision support for group decisions and negotiations, and conflict resolution principles. The 17 full papers presented in this volume were carefully reviewed and selected from 98 submissions. They were organized in topical sections named: preference modeling for group decision and negotiations; collaborative decision making processes; conflict resolution; behavioral OR, and negotiation support systems and studies.

This volume contains a selection consisting of the best papers presented at the FUR XII conference, held at LUISS in Roma, Italy, in June 2006, organized by John Hey and Daniela Di Cagno. The objectives of the FUR (Foundations of Utility and Risk theory) conferences have always been to bring together leading academics from Economics, Psychology, Statistics, Operations Research, Finance, Applied Mat- matics, and other disciplines, to address the issues of decision-making from a g- uinely multi-disciplinary point of view. This twelfth conference in the series was no exception. The early FUR conferences - like FUR I (organized by Maurice Allais and Ole Hagen) and FUR III (organized by Bertrand Munier) - initiated the move away from the excessively rigid and descriptively-inadequate modelling of beh- iour under risk and uncertainty that was in vogue in conventional economics at that time. More than twenty years later, things have changed fundamentally, and now - novations arising from the FUR conferences, and manifesting themselves in the new behavioural economics, are readily accepted by the profession. Working with new models of ambiguity, and bounded rationality, for example, behavioural decision making is no longer considered a sign of mere non-standard intellectual diversi?- tion. FUR XII was organised with this new spirit. In the sense that the behavioural concerns initiated by the ?rst FUR conferences are now part of conventional e- nomics, and the design and organisation of FUR XII re?ects this integration, FUR XII represents a key turning point in the FUR conference series.

Research and development infrastructures are a critical success factor in the platform of science and technology. In turn, an R&D preliminary feasibility study is essential to establish fairness and social credibility of a plan, including expert review, information disclosure and alternative setting. Preliminary Feasibility for Public Research & Development Projects explains how to evaluate R&D business by exploring the five key features of policy implication, policy improvement, preliminary feasibility study, R&D evaluation, and R&D strategy. Presenting policy measures to ensure the sustainability of R&D projects, Preliminary Feasibility for Public Research & Development Projects will help develop strategic measures for R&D preliminary feasibility studies while proposing ways to enhance the effectiveness of these studies, promote efficiency in public investment projects, and enhance the financial efficiency of large investment projects.

Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research. Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil) Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium) This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France)

We are now entering a new phase in the establishment of historical organization studies as a distinctive methodological paradigm within the broad field of organization studies. This book serves both as a landmark in the development of the field and as a key reference tool for researchers and students. For two decades, organization theorists have emphasized the need for more and better research recognizing the importance of the past in shaping the present and future. By historicizing organizational research, the contexts and forces bearing upon organizations will be more fully recognized, and analyses of organizational dynamics improved. But how, precisely, might a traditionally empirically oriented discipline such as history be incorporated into a theoretically oriented discipline such as organization studies? This book evaluates the current state of play, advances it and identifies the possibilities the new emergent field offers for the future. In addition to providing an important work of reference on the subject for researchers, the book can be used to introduce management and organizational history to a student audience at both undergraduate and postgraduate levels. The book is a valuable source for wider reading, providing rich reference material in tutorials across organizational studies, or as recommended or required reading on courses with a connection to business or management history.

An accessible introduction to optimization analysis using spreadsheets Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft(R) Office Excel(R) Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software. The Third Edition includes many practical applications of optimization models as well as a systematic framework that illuminates the common structures found in many successful models. With focused coverage on linear programming, nonlinear programming, integer programming, and heuristic programming, Optimization Modeling with Spreadsheets, Third Edition features: * An emphasis on model building using Excel Solver as well as appendices with additional instructions on more advanced packages such as Analytic Solver Platform and OpenSolver * Additional space devoted to formulation principles and model building as opposed to algorithms * New end-of-chapter homework exercises specifically for novice model builders * Presentation of the Sensitivity Toolkit for sensitivity analysis with Excel Solver * Classification of problem types to help readers see the broader possibilities for application * Specific chapters devoted to network models and data envelopment analysis * A companion website with interactive spreadsheets and supplementary homework exercises for additional practice Optimization Modeling with Spreadsheets, Third Edition is an excellent textbook for upper-undergraduate and graduate-level courses that include deterministic models, optimization, spreadsheet modeling, quantitative methods, engineering management, engineering modeling, operations research, and management science. The book is an ideal reference for readers wishing to advance their knowledge of Excel and modeling and is also a useful guide for MBA students and modeling practitioners in business and non-profit sectors interested in spreadsheet optimization.

This book presents practical approaches for facilitating the achievement of excellence in the management and leadership of organizational resources. It shows how the principles of creating shared value can be applied to ensure faster learning, training, business development, and social renewal. In particular, it presents novel methods and tools for tackling the complexity of management and learning in both business organizations and society. Discussing ontologies, intelligent management systems, methods for creating knowledge and value added, it offers novel insights into time management and operations optimization, as well as advanced methods for evaluating customers' satisfaction and conscious experience. Based on two conferences, the AHFE 2019 International Conference on Human Factors, Business Management and Society, and the AHFE 2019 International Conference on Human Factors in Management and Leadership, held in July 24-28, 2019, Washington D.C., USA, the book provides both researchers and professionals with new tools and inspiring ideas for achieving excellence in various business activities.

This book surveys new algorithmic approaches and applications to natural and man-made disasters such as oil spills, hurricanes, earthquakes and wildfires. Based on the "Third International Conference on Dynamics of Disasters" held in Kalamata, Greece, July 2017, this Work includes contributions in evacuation logistics, disaster communications between first responders, disaster relief, and a case study on humanitarian logistics. Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

This book discusses reliability applications for power systems, renewable energy and smart grids and highlights trends in reliable communication, fault-tolerant systems, VLSI system design and embedded systems. Further, it includes chapters on software reliability and other computer engineering and software management-related disciplines, and also examines areas such as big data analytics and ubiquitous computing. Outlining novel, innovative concepts in applied areas of reliability in electrical, electronics and computer engineering disciplines, it is a valuable resource for researchers and practitioners of reliability theory in circuit-based engineering domains.

This book introduces the basic concepts of fuzzy collaborative forecasting and clustering, including its methodology, system architecture, and applications. It demonstrates how dealing with disparate data sources is becoming more and more popular due to the increasing spread of internet applications. The book proposes the concepts of collaborative computing intelligence and collaborative fuzzy modeling, and establishes several so-called fuzzy collaborative systems. It shows how technical constraints, security issues, and privacy considerations often limit access to some sources. This book is a valuable source of information for postgraduates, researchers and fuzzy control system developers, as it presents a very effective fuzzy approach that can deal with disparate data sources, big data, and multiple expert decision making.

"There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available." Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. "The book by Gallego and Topaloglu provides a fresh, up-to-date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in-depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it." Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. "This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field." Robert L. Phillips, Director of Pricing Research at Amazon "At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference." Richard Ratliff, Research Scientist at Sabre "This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers." Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK.

This book brings together studies broadly addressing human error from different disciplines and perspectives. It discusses topics such as human performance; human variability and reliability analysis; medical, driver and pilot error, as well as automation error; root cause analyses; and the cognitive modeling of human error. In addition, it highlights cutting-edge applications in safety management, defense, security, transportation, process controls, and medicine, as well as more traditional fields of application. Based on the AHFE 2019 International Conference on Human Error, Reliability, Resilience, and Performance, held on July 24-28, 2019, Washington D.C., USA, the book includes experimental papers, original reviews, and reports on case studies, as well as meta-analyses, technical guidelines, best practice and methodological papers. It offers a timely reference guide for researchers and practitioners dealing with human error in a diverse range of fields.

Markus Hammer investigates a time-based and analytics-supported operations management approach. He explores five perspectives: 1) the needs of industry, in particular manufacturing in process industries, 2) the impact of digitization, with focus on Big Data and analytics, 3) the management of operations through time-based performance metrics, 4) how operations improvement methods and advanced process control help achieve resource-productive operations and 5) learning from practice based on two empirical case studies. The author conceives, explains, and tests an implementation methodology. The final case study proves that the developed implementation methodology works in practice.

This book discusses an emerging area in computer science, IT and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the International Conference on Decision Science and Management 2018 (ICDSM 2018), held at the Interscience Institute of Management and Technology (IIMT), Bhubaneswar, India.

Consumer co-operatives provide a different approach to organizing business through their ideals of member ownership and democratic practice. Every co-operative member has an equal vote regardless of his or her own personal capital investment. The co-operative movement can also be an important force in promoting development and self-sufficiency in poorer areas, particularly in non-industrialised countries. This book explores in depth the fortunes of the Berkeley Consumer Co-operative, which became the largest consumer co-operative in the United States with 116,000 members in 1984 and viewed nationally as a leader in innovative retail practices and a champion of consumer rights. The Berkeley Consumer Co-operative is promoted by both supporters and opponents of the co-operative business model as a significant example of what can go wrong with the co-operatives. This book will provide the first in depth analysis of the history of the Berkeley Co-operative using its substantial but little used archives and oral histories to explore what the Berkeley experience means for the co-operative business model. The specific chapters relating to Berkeley will be organised around particular themes to highlight the issues relating to the co-operative business model and the local context of Berkeley. The themes relate to developments in Berkeley and the Bay Area in terms of the economy, politics and the retail environment; the management of the Berkeley co-operative, looking at governance, financial management and strategic decisions; relationship of management with members and employees; and finally, the relationship of the Berkeley Co-operative with the community. The core message of the book is that it is not inevitable that consumer co-operatives fail, but that the story of Berkeley story can provide insights that can strengthen the co-operative business model and minimise failures on the scale of Berkeley occurring in the future.