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International Series in Operations Research & Management Science

Outsourcing

Cases and Studies in Using Operations Research and Management Science Methods

Energy and Sustainable Analytics, Volume 2

Machine Learning Technologies on Energy Economics and Finance

Energy and Sustainable Analytics, Volume 1

Innovation at the Interface

University-Industry Collaboration

From Theory to Practice

Outsourcing Using Operations Research and Management Science Methods

Challenges in Economics and Management Science

The Unaffordable Price of Static Decision-making Models

Applications to Large-Scale Engineering Problems

Optimization via Relaxation and Decomposition

This book highlights the major features of the ripple effect and introduces methodologies to mitigate its adverse impact on supply chain resilience and to recover from severe disruptions. It brings fresh insights into the fields of supply chain management and engineering, addressing three fundamental questions: “In what circumstance does one failure trigger others?” “Which supply chain structures are especially susceptible to the ripple effect?” “What are the typical ripple effect scenarios and the most efficient ways to respond to them?”In this new edition, recent advancements are incorporated, particularly in areas such as supply chain viability, digital supply chains, artificial intelligence, and epidemiological models. Furthermore, it introduces new methodologies with a particular emphasis on data-driven and AI-based approaches.This comprehensive book provides innovative optimization and simulation models to address real-world challenges. With examples from industrial and service sectors, it offers actionable decision-making recommendations for tackling disruption risks in the supply chain proactively and reactively. As such the book is a comprehensive source for diverse readerships.

Handbook of Ripple Effects in the Supply Chain

This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty. Each method is accompanied by rigorous mathematical analysis, ensuring a deep understanding of the underlying principles. The theoretical discussions included are essential for comprehending the mechanics of various algorithms and the nature of the solutions they provide-whether they are global, local, stationary, or critical. The book begins by introducing fundamental tools from set-valued analysis, optimization, and probability theory. It then transitions from deterministic to stochastic optimization, starting with a thorough discussion of modeling, understanding uncertainty, and incorporating it into optimization problems. Following this foundation, the book explores numerical algorithms for nonsmooth optimization, covering well-known decomposition techniques and algorithms for convex optimization, mixed-integer convex programming, and nonconvex optimization. Additionally, it introduces numerical algorithms specifically for stochastic programming, focusing on stochastic programming with recourse, chance-constrained optimization, and detailed algorithms for both risk-neutral and risk-averse multistage stochastic programs.

The book guides readers through the entire process, from defining optimization models for practical problems to presenting implementable algorithms that can be applied in practice. It is intended for students, practitioners, and scholars who may be unfamiliar with stochastic programming and nonsmooth optimization. The analyses provided are also valuable for practitioners who may not be interested in convergence proofs but wish to understand the nature of the solutions obtained.

From Conceptual Algorithms to Real-World Applications

Methods of Nonsmooth Optimization in Stochastic Programming

This book demonstrates how decision-making models can be applied to solve specific real-life problems, with a particular emphasis on wind energy. In a step-by-step manner, it guides the reader through decision-making, the formulation of optimization models, and the methods for solving them. After providing an overview of various models for the design of wind farms, it presents an optimization model for deciding which economy (country) to invest in and models for selecting suppliers. A dedicated chapter focuses on different models for monitoring and predictive maintenance for wind turbines (farms) due to the construction of turbine blades and vibration. It shows how combinatorial optimization models can help to make optimal decisions for one-dimensional cutting stock of blanks, their processing, and determining the optimal composition for production. Moreover, it discusses how the energy consumption balance index formed by conventional and renewable sources can be determined and presents a means of identifying the relative share of wind energy consumption among the other renewable sources.&nbsp;Operations research professionals, students, and decision-makers alike will find this book to be a valuable resource for tackling real-world challenges and driving sustainable advances in wind energy solutions.

Decision-Making in Design, Maintenance, Planning, and Investment of Wind Energy

This book examines multiple criteria decision making (MCDM) and presents the Sequential Iterative Modelling for Urban Systems (SIMUS) as a method to be used for strategic decision making. It emphasizes the necessity to take into account aspects related to real world scenarios and incorporating possible real-life aspects for modelling. The book also highlights the use of sensitivity analysis and presents a method for using criteria marginal values instead of weights, which permits the drawing of curves that depicts the variations of the objective function due to increments/decrements of criteria values. In this way, it also gives quantitative values of the objective function allowing stakeholders to perform a comprehensive risk analysis for a solution when it is affected by exogenous variables.&nbsp;Strategic Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios is divided into four parts. Part 1 is devoted to exploring the history and development of the discipline and the way it is currently used. It highlights drawbacks and problems that scholars have identified in different MCDM methods and techniques. Part 2 refers to what can be done using the MCDM process. Part 3 proposes the SIMUS method as a strategic procedure to deal with MCDM problems, and addressing how to approach complicate scenarios. Part 4 is entirely devoted to support practitioners through more than 100 questions a user may ask, and their corresponding answers, as well as a collection of solved six complex real-life scenarios. The decision-making process can be a complex task, especially with multi-criteria problems. With large amounts of information, it can be an extremely difficult to make a rational decision, due to the number of intervening variables, their interrelationships, potential solutions that might exist, diverse objectives envisioned for a project, etc. The SIMUS method has been designed to offer a strategy to help organize, classify, and evaluate this information effectively.

A Practical Guide for Complex Scenarios

Strategic Approach in Multi-Criteria Decision Making

This book applies Multicriteria Decision Making (MCDM) tools and techniques to problems in location analysis. It begins with a generic model for MCDM and subsequently develops specific versions of the technique for particular location problems. Throughout the book, MCDM is understood to encompass all tools and techniques that choose or rank existing or feasible solutions, including discrete multi-attribute decision making (MADM) problems, which typically include an attribute table that specifies the consequences of each decision with regard to the given criteria, as well as multi-objective linear problems (MOLPs), which incorporate all objectives in a single optimization problem.&nbsp; 

The book is organized as follows: the first four chapters introduce readers to the basic tools and techniques used in single-objective optimization, multicriteria decision making, location analysis, and other tools, such as statistical regression and geographical information systems. This is followed by ten chapters on model applications, each of which introduces readers to a specific location problem and applies one technique to solve it. The book is then wrapped up in a closing chapter that looks at the location process from a practitioner’s point of view.&nbsp; This book is intended as a textbook for upper-undergraduate and master-level courses on location analysis. It will also benefit decision-makers who actually need to locate facilities.&nbsp;

Multicriteria Location Analysis

This book brings Data Envelopment Analysis (DEA) based techniques and big data together to explore the novel uses and potentials of DEA under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.&nbsp;Over the past four decades, DEA models have been applied in almost every major field of study. However, DEA has not been used to its fullest extent. As the inter- and intra-disciplinary research grows, DEA could be used in potentially many other ways; for instance, DEA could be viewed as a data mining tool for data-enabled analytics. One opportunity is brought by the existence of big data. Although big data has existed for a while now, gaining popularity among insight seekers, we are still in incipientstages when it comes to taking full advantage of its potential. Generally, researchers have either been interested in examining its origin or in developing and using big data technology.As the amount of (big) data is growing every day in an exponential manner, so does its complexity; in this sense, various types of data are surfacing, whose study and examination could shed new light on phenomena of interest. A quick review of existing literature shows that big data is a new entrant within the DEA framework. Recently, there has been an increasing interest in bringing the two concepts together, with research studies aiming to integrate DEA and big data concepts within a single framework. But, more work is needed to fully explore the value of their intersection—it is time to view DEA in light of its potential usage in new fields or new usage within the existing fields, under the big data umbrella. It is time to view DEA models beyond their present scope and mine new insights for better data-driven decision-making.

DEA for Big Data

Data-Enabled Analytics

Das Buch bietet eine systematische Übersicht über das Logistikrecht. Grundgedanke der Logistik ist die Steigerung der Effektivität bei der raum- und zeitlichen Gütertransformation im Zusammenwirken einer Vielzahl von Beteiligten, oft in Form von Logistikketten. Das Zusammenwirken von Beteiligten mit wirtschaftlicher Zielsetzung kann vielfach jedoch auch zu Interessenkonflikten führen. Deren rechtliche Einordnung und juristische Lösungsmöglichkeiten sind Gegenstand dieses Buches. Dabei trägt der Autor den verschiedensten Bereichen, in welchen wir heute auf Logistik treffen, Rechnung – von der Großhandelslogistik über die direkte Belieferung der Endverbraucher bis hin zur Produktions- und Entsorgungslogistik.

Logistikrecht

Systems Thinking

This book offers an assessment of Pondy's contribution, through critical reflection on what happened to the relationship between conflict theory and 'beyond open systems'.

Reclaiming the Enthinkment Path

The Management Thought of Louis R. Pondy

Tourism, Hospitality & Event Management

This book provides a critical, systemic analysis of the challenge of food waste and its drivers in hospitality operations. It reviews existing approaches to mitigating food waste in catering services and highlights best practices in effective mitigation. It also discusses the determinants of the broader adoption of effective approaches to food-waste management across the sector and within the various geographical markets of out-of-home food consumption.This book is suitable for academics in the hospitality and tourism field as well as for professionals such as hotel and restaurant managers. It can also be used in undergraduate and postgraduate classes in hospitality management.

Opportunities for Sustainable Management

Food Waste in Hospitality Operations

Dieses Buch untersucht eine prozessorientierte Perspektive auf Design und Entwicklung, basierend auf Forschung in den Bereichen Designstudien, Ingenieurdesign und Systemdesign. 
Der Design- und Entwicklungsprozess ist von großer Bedeutung – er schafft alle künstlichen Produkte und Systeme und bestimmt, wie gut sie menschliche Bedürfnisse erfüllen. Die in diesem Buch dargelegte Prozessperspektive ist wertvoll für die Praxis und Ausbildung im Bereich Design und Entwicklung und stellt zugleich ein faszinierendes Forschungsgebiet dar. 
Das Buch baut auf den Grundlagen der Prozessperspektive auf und erörtert deren Umsetzung in zahlreichen Prozessmodellen, Theorien und Ansätzen, die im Laufe der Jahre entwickelt wurden. Die Kapitel bieten verknüpfte Übersichten zu zentralen Konzepten und führen neue konzeptionelle Rahmenwerke ein, um die Beziehungen zwischen den diskutierten Beiträgen zu verdeutlichen. Darüber hinaus werden praktische Überlegungen und die notwendigen Kompetenzen zur Realisierung der greifbaren Vorteile einer Prozessperspektive thematisiert. 
Ein einzigartiger Aspekt dieses Buches ist, dass es viele Perspektiven auf den Design- und Entwicklungsprozess vereint: von solchen, die sich auf individuelle Designaktivitäten konzentrieren, bis hin zu solchen, die groß angelegte Entwicklungsprojekte betreffen; von wissenschaftlich relevanten Ansätzen bis hin zu praxisorientierten Aspekten; und von Kontexten, die vom menschenzentrierten Design über Ingenieurdesign bis hin zum Systemdesign reichen. Die Kapitelbibliographien enthalten sorgfältig ausgewählte Empfehlungen für weiterführende Literatur zu den jeweils behandelten Themen. Zudem enthält das Buch zahlreiche Abbildungen in Farbe, die die Beziehungen der Themen zu den neu eingeführten Organisationsrahmen visuell widerspiegeln. 
Die Übersetzung wurde mit Hilfe von künstlicher Intelligenz durchgeführt. Eine anschließende menschliche Überarbeitung erfolgte vor allem in Bezug auf den Inhalt.&nbsp;&nbsp;&nbsp;&nbsp; This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Perspektiven, Ansätze und Modelle

Der Design- und Entwicklungsprozess

Schriftenreihe des Deutschen Instituts für Interdisziplinäre Sozialpolitikforschung (DIFIS)

Empirische Sozialpolitikforschung und evidenzbasierte Sozialpolitikberatung sind auf qualitativ hochwertige Daten sowie eine Dateninfrastruktur angewiesen, die einen einfachen Zugang zu Daten und die sichere Nutzung für die wissenschaftliche Forschung ermöglichen. Die bestehende Dateninfrastruktur steht jedoch in der Kritik. So werden unter anderem die Intransparenz des Datenökosystems, uneinheitliche Datenschutzstandards, die Anpassungsprobleme amtlicher Statistik an aktuelle Fragen und fehlende Verknüpfungsmöglichkeiten von Mikrodaten aus unterschiedlichen Quellen beanstandet. 
Dieses Buch bietet einen Überblick über die sozialpolitische Forschungsdateninfrastruktur in Deutschland mit besonderem Augenmerk auf Daten zu sozialpolitischen Leistungen. Es thematisiert Lücken und Bedarfe in der Dateninfrastruktur und entwickelt Empfehlungen zu deren Weiterentwicklung vor dem Hintergrund positiver Beispiele verschiedener europäischer Länder.

Stand und Perspektiven

Dateninfrastrukturen für die Sozialpolitikforschung

Series on Innovation and Knowledge Management

Communication And Knowledge Transfer: Theories And Cases In Journalism, Public Relations And Advertising

SpringerBriefs in Business

This open access book offers a structured approach that aligns indicators of social value and provides a stable foundation amidst the dynamic and ever-changing social complexities. From detailed system scales of participation to an overview of how it works, this book presents a roadmap for automating data in systemic alignment with social value. With its adaptability to changing societal structures, it provides a pragmatic solution within existing systems while paving the way for future advancements. It is valuable for researchers and business leaders.

Leveraging Collective Intelligence

Unifying Sustainability Information for Societal Automation

Contributions to Finance and Accounting

This book discusses the evolution of technical features in decentralized finance and focuses on machine-learning finance in emerging economies. As technological advancement evolves at an unpredictable pace, the financial industry, like every other sector, must adapt accordingly.. Furthermore, the rapid expansion of diverse financial products and services is creating new applications and markets. Alongside technological progress, the exploration of complex patterns in vast amounts of data, known as big data, is facilitated by its commonly acknowledged characteristics: volume, variety, veracity, value, and velocity.Overall, machine learning has become crucial in the financial industry, allowing businesses to automate operations, gain insights from data, and make more informed decisions in real time. This edited book&nbsp;covers algorithmic trading, risk management, fraud detection, customer service and personalization, portfolio management, credit scoring, sentiment analysis, and algorithmic pricing. The book connects theoretical concepts with practical real-world applications, benefiting professionals looking to enhance their proficiency in using these methods efficiently. It offers insightful guidance for theorists, market participants, and policymakers by exploring financial theories and practices in light of contemporary machine-learning approaches, with a special emphasis on emerging economies.

Trends, Developments and Business Practices in the Financial Sector

Machine Learning in Finance

Routledge Companions in Business, Management and Marketing

This volume examines the progress made in the field of Information Systems in recent years in and presents a forward-looking perspective that can help to shape future scholarly conversations both in the field of Information Systems but also in cognate fields where information technology is having profound effects.

Outsourcing

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