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This book includes a selection of refereed papers presented at the'Annual International Conference of the German Operations Research Society (OR2016),'which took place at the Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg, Germany, Aug. 30 - Sept. 2, 2016. Over 700 practitioners and academics from mathematics, computer science, business/economics, and related fields attended the conference. The scientific program included around 475 presentations on the theme Analytical Decision Making, focusing on the process of researching complex decision problems and devising effective solution methods towards better decisions. The book presents papers discussing classical mathematical optimization, statistics and simulation techniques. Such approaches are complemented by computer science methods and tools for the processing of data and the design and implementation of information systems. The book also examines recent advances in information technology, which allow big data volumes to be treated and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Further, it includes problems modeled and treated under consideration of uncertainty, risk management, behavioral issues, and strategic decision situations.

In this volume, Dean Shepherd focuses on the varying topics of entrepreneurship unified through conjoint analysis. Although the topic of entrepreneurial decision making is broad, in doing so, he reveals the mechanisms that come into play during the entrepreneurial decision-making process.Scholars of entrepreneurship and organizational behavior will find this collection an essential resource for understanding how decision making is achieved in entrepreneurial settings.

In two volumes, Planning Production and Inventories in the Extended Enterprise: A State of the Art Handbook examines production planning across the extended enterprise against a backdrop of important gaps between theory and practice. The early chapters describe the multifaceted nature of production planning problems and reveal many of the core complexities. The middle chapters describe recent research on theoretical techniques to manage these complexities. Accounts of production planning system currently in use in various industries are included in the later chapters. Throughout the two volumes there are suggestions on promising directions for future work focused on closing the gaps. Included in Volume 1 are papers on the Historical Foundations of Manufacturing Planning and Control; Advanced Planning and Scheduling Systems; Sustainable Product Development and Manufacturing; Uncertainty and Production Planning; Demand Forecasting; Production Capacity; Data in Production and Supply Chain Planning; Financial Uncertainty in SC Models; Field Based Research in Production Control; Collaborative SCM; Sequencing and Coordination in Outsourcing and Subcontracting Operations; Inventory Management; Pricing, Variety and Inventory Decisions for Substitutable Items; Perishable and Aging Inventories; Optimization Models of Production Planning Problems; Aggregate Modeling of Manufacturing Systems; Robust Stability Analysis of Decentralized Supply Chains; Simulation in Production Planning; and Simulation-Optimization in Support of Tactical and Strategic Enterprise Decisions. Included in Volume 2 are papers on Workload and Lead-Time Considerations under Uncertainty; Production Planning and Scheduling; Production Planning Effects on Dynamic Behavior of A Simple Supply Chain; Supply and Demand in Assemble-to-Order Supply Chains; Quantitative Risk Assessment in Supply Chains; A Practical Multi-Echelon Inventory Model with Semiconductor Application; Supplier Managed Inventory for CustomItems with Long Lead Times; Decentralized Supply Chain Formation; A Cooperative Game Approach to Procurement Network Formation; Flexible SC Contracts with Options; Build-to-Order Meets Global Sourcing for the Auto Industry; Practical Modeling in Automotive Production; Discrete Event Simulation Models; Diagnosing and Tuning a Statistical Forecasting System; Enterprise-Wide SC Planning in Semiconductor and Package Operations; Production Planning in Plastics; SC Execution Using Predictive Control; Production Scheduling in The Pharmaceutical Industry; Computerized Scheduling for Continuous Casting in Steelmaking; and Multi-Model Production Planning and Scheduling in an Industrial Environment.

This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.

This book is about elicitation: the facilitation of the quantitative expression of subjective judgement about matters of fact, interacting with subject experts, or about matters of value, interacting with decision makers or stakeholders. It offers an integrated presentation of procedures and processes that allow analysts and experts to think clearly about numbers, particularly the inputs for decision support systems and models. This presentation encompasses research originating in the communities of structured probability elicitation/calibration and multi-criteria decision analysis, often unaware of each other's developments.Chapters 2 through 9 focus on processes to elicit uncertainty from experts, including the Classical Method for aggregating judgements from multiple experts concerning probability distributions; the issue of validation in the Classical Method; the Sheffield elicitation framework; the IDEA protocol; approaches following the Bayesian perspective; themain elements of structured expert processes for dependence elicitation; and how mathematical methods can incorporate correlations between experts.Chapters 10 through 14 focus on processes to elicit preferences from stakeholders or decision makers, including two chapters on problems under uncertainty (utility functions), and three chapters that address elicitation of preferences independently of, or in absence of, any uncertainty elicitation (value functions and ELECTRE). Two chapters then focus on cross-cutting issues for elicitation of uncertainties and elicitation of preferences: biases and selection of experts.Finally, the last group of chapters illustrates how some of the presented approaches are applied in practice, including a food security case in the UK; expert elicitation in health care decision making; an expert judgement based method to elicit nuclear threat risks in US ports; risk assessment in a pulp and paper manufacturer in the Nordic countries; and elicitation of preferences for crop planning in a Greek region.

This book gathers a selection of refereed papers presented at the 4th International Symposium and 26th National Conference of the Hellenic Operational Research Society. It highlights recent scientific advances in operational research and management science (OR/MS), with a focus on linking OR/MS with other areas of quantitative methods in a multidisciplinary framework. Topics covered include areas such as business process modeling, supply chain management, organization performance and strategy planning, revenue management, financial applications, production planning, metaheuristics, logistics, inventory systems, and energy systems.

This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics. It includes theoretically oriented contributions as well as papers from various application areas, where knowledge from different research directions is needed to find the best possible interpretation of data for the underlying problem situations. Beside traditional classification research, the book focuses on current interests in fields such as the analysis of social relationships as well as statistical musicology.

In the knowledge economy, teams play a central role in decisions made within and across organisations. The reason why teams with diverse compositions are often used is arguably their ability to develop solutions that none of their members could have produced alone. Systems design, strategy and policy development, risk management, and innovation are just a few of the areas that call for team decisions. Unfortunately, a considerable number of behavioural research studies show that teamwork is fraught with difficulties. Teams often underestimate their fallibility, struggle with conflict, or are unable to share and integrate critical information effectively. Indeed, the evidence shows that two out of three teams do not achieve their goals and half of organisational decisions – many of which are team decisions – fail.In this book, the authors draw from research in psychology, decision and systems sciences – as well as their own research and consulting work that spans more than 20 years – to show how designed interventions can enable team decision making to become rigorous, transparent, and defensible. They cover theory and practice regarding the design, delivery, and evaluation of interventions to support team decision making in situations of varied complexity. Written as an applied resource for researchers and advanced students in particular, this book offers a guide to proven interventions that enhance the process of making team decisions and increase the chances of superior team results.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

This research-based book critically examines the complex interplay of power relations in decision-making in megaprojects. This book is tailored for academics, students, practitioners, clients, and policymakers and addresses a significant gap in understanding how formal and informal power influences decision-making. Through applying governmentality theory and narrative inquiry from thirty-nine interviews, this book presents over sixty-five detailed stories offering a series of real-life narratives that expose the diverse forms of power at play in megaprojects. The stories reveal how deviations from norms can significantly impact project outcomes. This book uncovers the complex web of power relations, institutional norms, and individual actions driving decisions.This book provides a framework illustrating four behavioural contexts, entrepreneurial, box-ticking, deception, and recklessness, as manifestations of megaproject decision-making, providing readers with a tool to understand and navigate the intricate power dynamics in megaprojects.Readers will benefit from practical insights and strategies for fostering conducive decision-making environments, tailoring interventions to promote constructive behaviours, and mitigating harmful actions. This book is a resource for anyone seeking to grasp the complexities of megaproject management in the context of power relations, shaping their decision-making leading to success.

In the last few decades, managerial and business studies have shown an increasing inability to explain and forecast emergent dynamics in society, economics, and the environment.Consolidated managerial approaches and business theories seem to be incapable of communicating and depicting the ongoing evolution, and new perspectives are required to support both researchers and practitioners in tracing new paths for development. Building upon the constructivist approach, this book illustrates the multiple advantages that systems thinking can offer in supporting a holistic understanding of social and economic phenomena.The book proposes a representation of the firm as a viable system and represents its functioning and decision-making processes trough a recursive depiction that can be applied for each of the multiple levels through which socio-economic environments are defined. As a result of the focus on the differences between decision making and problem-solving processes, the book enriches current knowledge about systems thinking and provides useful instruments through which both researchers and practitioners can effectively understand the multiple variables able to influence decisions and actions within a firm's configuration.The book is aimed at both postgraduate students and researchers interested in the multiple dimensions of systems thinking.

Why successful leaders must embrace simple strategies in an increasingly uncertain and complex world.Making decisions is one of the key tasks of managers, leaders, and professionals. In Smart Management, Jochen Reb, Shenghua Luan, and Gerd Gigerenzer demonstrate how business leaders can utilize heuristics—simple decision-making strategies adapted to the task at hand. In a world that has become increasingly volatile, uncertain, complex, and ambiguous (VUCA), the authors make the case against complex analytical methods that quickly reach their limits. This against-the-grain approach leads to decisions that are not only faster but also more accurate, transparent, and easier to learn about, communicate, and teach. Smart Management offers an evidence-based yet practical discussion of how business leaders can use smart heuristics to make good decisions in a VUCA world.Building on the fast-and-frugal heuristics program, Smart Management demonstrates the efficacy of heuristic decision making in a twofold approach. First, it introduces the concept of ecological rationality, which prescribes the environmental conditions under which specific heuristics work well. Second, the book describes a repertoire of heuristics, referred to as the adaptive toolbox, that leaders, managers, and professionals can develop and rely on to make a variety of decisions, such as on business strategy, negotiation, and personnel selection. The toolbox not only showcases the practical usefulness of these heuristics but also inspires readers to discover and develop their own smart heuristics.

'Data-driven decision making is crucial for ensuring the long-term sustainability of businesses and economic growth. While rapid technological advancements have enabled the collection and analysis of data on an unprecedented scale, businesses face challenges in adopting evidence-based decision making. Data-Driven Intelligent Business Sustainability is a comprehensive guide that examines the challenges and opportunities presented by data-driven decision making. It covers new technologies like blockchain, IoT, and AI, explores their potential for sustainable business success, and provides guidance on managing cybersecurity threats.The book also includes case studies and examples of successful implementations of data-driven decision making, making it a practical resource for those seeking to upskill or reskill in this field. Targeted at computer science and engineering professionals, researchers, and students, the book provides valuable insights into the role of data-driven decision making in business sustainability, helping businesses achieve long-term success.'--

In today's rapidly evolving world, traditional management approaches often fail to address the complexities of modern challenges. Decision-makers frequently encounter unpredictable environments where Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) reign; this poses a significant obstacle to achieving sustainable outcomes and can lead to ineffective decision-making. By presenting cutting-edge research and theoretical frameworks, Chaos, Complexity, and Sustainability in Management equips seasoned professionals, researchers, and students with the tools to navigate the complexities of adaptive systems and make informed decisions in a VUCA world. It delves into decision-making in strenuous environments, systems thinking, and sustainable management practices, providing practical insights and strategies for addressing these challenges. Through a comprehensive exploration of these concepts, readers will understand how to thrive in turbulent times.

Rethinking Decision-Making Strategies and Tools: Emerging Research and Opportunities analyses established decision-making tools, and on the necessity to re-arrange and re-evaluate some of them. The authors propose a new matrix with eight quadrants of the dynamic SWOT analysis. The new tool also considers three dimensions: (1) Actual – Potential, (2) Positive – Negative and (3) Internal – External. Applications for this revised matrix are offered in a range of relevant case studies, along with examples from a wide range of industries and firms to illustrate the many dimensions of decision-making tools and theories. Readers will be able to compare, contrast and comprehend whether the ‘decision making strategies and tools'from different lenses are delivered similarly, or otherwise, in different parts of the world. The text includes an interesting mix of theory, primary research findings, and practice that will appeal to students, academics, and practitioners alike.

This book deals with an often-neglected feature of location problems, namely uncertainty, by combining two related fields: location theory and optimization. Written by leading researchers and practitioners in these fields, each chapter examines one aspect of the location process in different contexts, such as supply chains; location decisions under congestion; disaster management; design of resilient facilities; uncertainty in the health sector; and facility location in the retail sector under uncertainty. The book also addresses methodological aspects, such as chance-constrained approaches, heuristic algorithms, scenario approaches, and simulation. As such, it provides decision-makers with essential methods, tools and approaches to help them deal with these uncertainties. It is mainly intended for graduate students in the fields of operations research and logistics, as well as professionals in logistics and supply chain management.

This book offers a fresh approach to strategy by examining the idea of Optionality. Optionality is the right, but not the obligation, to take an action. Built on historic military tactics, static engineering principles, and equilibrium-seeking economics, conventional strategic-thinking suffers some weaknesses, principal of which is its inability to deal with conditions of high uncertainty. This book begins by dividing the business landscape into three distinct domains; (1) Fragile, (2) Robust, and (3) Long-shot (FRL), which alert us to the context-specificity of strategy tools, before suggesting that theoretical lenses are required to understand and implement strategy in VUCA (Volatile, Uncertain, Complex, and Ambiguous) domains. The authors explore the concept and methodology of Optionality in order to demonstrate how it can be used in conjunction with existing strategy tools in order to achieve competitive success. It will be of great interest to academics and students of strategyand innovation.

This book comprises a set of stories about being an engineer for many decades and the lessons the author learned from research and practice. These lessons focus on people and organizations, often enabled by technology. The settings range from airplanes, power plants, and communication networks to ecosystems that enable education, healthcare, and transportation. All of these settings are laced with behavioral and social phenomena that need to be understood and influenced. The author's work in these domains has often led to the question:'Well, why does it work like that?'He invariably sought to understand the bigger picture to find the sources of requirements, constraints, norms, and values. He wanted to understand what could be changed, albeit often with much effort to overcome resistance. He found that higher levels of an ecosystem often provide the resources and dictate the constraints imposed on lower levels. These prescriptions are not just commands. They also reflect values and cultural norms. Thus, the answers to the question were not just technical and economic. Often, the answers reflected eons of social and political priorities. The endeavors related in the book frequently involved addressing emerging realities rather than just the status quo. This book is an ongoing discovery of these bigger pictures. The stories and the lessons related in this book provide useful perspectives on change. The understanding of people and organizations that emerges from these lessons can help to enable transformative change. Fundamental change is an intensely human-centric endeavor, not just for the people and organizations aspiring to change, but also for the people helping them. You will meet many of these people in this book as the stories unfold. The genesis of this book originated in a decision made early in the author's career. He had developed a habit of asking at the end of each day,'What did I really accomplish today?'This was sometimes frustrating as he was not sure the day had yielded any significant accomplishments. One day it dawned on him that this was the wrong question – He needed to ask,'What did I learn today?'It is always possible to learn, most recently about public health and climate change. In planning this book, the author first thought in terms of accomplishments such as projects conducted, systems built, and articles and books published. He could not imagine this being interesting to readers. Then, it struck him – It is much more interesting to report on what he learned about people and organizations, including how he helped them accomplish their goals. This is a book of stories about how these lessons emerged.In planning this book, the author first thought in terms of accomplishments such as projects conducted, systems built, and articles and books published. He could not imagine this being interesting to readers. Then, it struck him – It is much more interesting to report on what he learned about people and organizations, including how he helped them accomplish their goals. This is a book of stories about how these lessons emerged.

The 2022 World Economic Forum surveyed 1,000 experts and leaders who indicated their risk perception that the earth's conditions for humans are a main concern in the next 10 years. This means environmental risks are a priority to study in a formal way. At the same time, innovation risks are present in theminds of leaders, newknowledge brings new risk, and the adaptation and adoption of risk knowledge is required to better understand the causes and effects can have on technological risks. These opportunities require not only adopting new ways of managing and controlling emerging processes for society and business, but also adapting organizations to changes and managing new risks.Risk Analytics: Data-Driven Decisions Under Uncertainty introduces a way to analyze and design a risk analytics system (RAS) that integrates multiple approaches to risk analytics to deal with diverse types of data and problems. A risk analytics system is a hybrid system where human and artificial intelligence interact with a data gathering and selection process that uses multiple sources to the delivery of guidelines to make decisions that include humans and machines. The RAS system is an integration of components, such as data architecture with diverse data, and a risk analytics process and modeling process to obtain knowledge and then determine actions through the new knowledge that was obtained. The use of data analytics is not only connected to risk modeling and its implementation, but also to the development of the actionable knowledge that can be represented by text in documents to define and share explicit knowledge and guidelines in the organization for strategy implementation.This book moves from a review of data to the concepts of a RAS. It reviews RAS system components required to support the creation of competitive advantage in organizations through risk analytics. Written for executives, analytics professionals, risk management professionals, strategy professionals, and postgraduate students, this book shows a way to implement the analytics process to develop a risk management practice that creates an adaptive competitive advantage under uncertainty.

This book explores all aspects of the new and emerging area of behavioural business. This book identifies behavioural business as a powerful application of the latest insights and tools from psychology and behavioural science to decision-making in business, management and policy. This book uniquely positions behavioural business as different from both behavioural economics and psychology. This book instead applies a fresh focus on behavioural interventions in policy and business. This book introduces this new area and showcases what it contributes to a number of important contemporary business and policy issues. These include behavioural insights for managers in diverse and multi-cultural workplaces, designers of organisations, interventions, products and services, financial advisors, public policy makers, business creatives and entrepreneurs as well as charity and NGO practitioners. This book summarises state-of-the-art knowledge in the areas of expertise of the authors, who are members of the Behavioural Business Lab at RMIT University in Australia. This book will interest advanced students in related subjects as well as academics and policy makers hoping to learn and apply behavioural insights to their areas of expertise.

Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligence Data analytics and consumer behavior The role of big data analytics in organizational decision-making This book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analytics Web analytics for digital marketing Smart retailing Leveraging web analytics for optimizing digital marketing strategies Big Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.

Turbulence is not new to the business world. In fact, turbulence is increasing, and managers are seeing teams spinning their wheels. Management systems are in a state of crisis and operations are more complex. The old top-down operations mode no longer suffices. Today's businesses demand speed and increased accuracy, forcing everyone to re-evaluate chains of command and tear down the walls between functions. Amid the responsibilities of traditional management lies problem solving. The push is toward moving decision-making authority down the ladder to all levels. Managers are no longer equipped to or capable of making the number and variety of necessary decisions in a vacuum. The current mode is to have employees deal directly with workplace issues and take corrective action without complaint and without management involvement. Coping with this reality and preparation for these improvements in workplace problem solving requires interest and motivation.Strategic Decision Making for Successful Planning can facilitate this by demystifying and simplifying the process. The book bridges philosophy and theory and puts together a practical integration of all the tools necessary to get results from your investment of time, energy, and money. What is unique about this book is while it's based on a strong academic foundation, it does not get bogged down in the human-planning or psychological process of solving problems. It doesn't provide'pie-in-the-sky'creative solutions or a five-year process for solving problems and planning for the future. Numerous techniques and tools are included to make the book the right balance between practical and academic. The book also includes an extensive case study to illustrate points made in the text.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises'productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

This book presents a consistent methodology for making decisions under uncertain conditions, as is almost always the case. Tools such as value of information and value of flexibility are explored as a means to make more complex and nuanced decisions.The book develops the complete formalism for assessing the value of acquiring information with two novel approaches. Firstly, it integrates the fuzzy characteristics of data, and secondly develops a methodology for assessing data acquisition actions that optimize the value of projects from a holistic perspective. The book also discusses the formalism for including flexibility in the project decision assessment. Practical examples of oil- and gas-related decision problems are included and discussed to facilitate the learning process.This book provides valuable advice and case studies applicable to engineers, researchers, and graduate students, particularly in the oil and gas industry and pharmaceutic industry.

Managers in organisations must make rational decisions. Rational decision making is the opposite of intuitive decision making. It is a strict procedure utilising objective knowledge and logic. It involves identifying the problem to solve, gathering facts, identifying options and outcomes, analysing them, considering all the relationships and selecting the decision. Rational decision making requires support: methods and software tools. The identification of the problem to solve needs methods that would measure and evaluate the current situation. Identification and evaluation of options and analysis of the available possibilities involves analysis and optimisation methods. Incorporating intuition into rational decision making needs adequate methods that would translate ideas or observed behaviours into hard data. Communication, observation and opinions recording is hardly possible today without adequate software. Information and data that form the input, intermediate variables and the output must be stored, managed and made accessible in a user-friendly manner. Rational Decisions in Organisations: Theoretical and Practical Aspects presents selected recent developments in the support of the widely understood rational decision making in organisations, illustrated through case studies. The book shows not only the variety of perspectives involved in decision making, but also the variety of domains where rational decision support systems are needed. The case studies present decision making by medical doctors, students and managers of various universities, IT project teams, construction companies, banks and small and large manufacturing companies. Covering the richness of relationships in which the decisions should and must be taken, the book illustrates how modern organisations operate in chains and networks; they have multiple responsibilities, including social, legal, business and ethical duties. Nowadays, managers in organisations can make transparent decisions and consider a multitude of stakeholders and their diverse features, incorporating diverse criteria, using multiple types and drivers of information and decision-making patterns, and referring to numerous lessons learned. As the book makes clear, the marriage of theoretical ideas with the possibilities offered by technology can make the decisions in organisations more rational and, at the same time, more human.

This book provides a blend of quantitative and qualitative approaches to decision making, while also bridging the gap between the theory of how to make good decisions versus how people actually make decisions. The authors present the tools and techniques of decision analysis to learn how to become a FOCCUSSED decision maker: Identify and properly Frame the decision or problem at handSpecify the goals, Objectives, and values that you are trying to achieveDevelop creative, meaningful Choices from among which you can chooseEvaluate the Consequences of selecting each alternative using your goals, objectives, and valuesThink about the key Uncertainties that could impact the decisionUnderstand the Swaps and trade-offs that you are willing to makeDevelop an approach for implementing your SolutionElicit the data you'll need from a variety of sourcesand Disseminate and communicate your decisions to others. The authors define a decision as the choice among alternatives, based on how we value and trade-off their pros and cons, made in the face of uncertainty about what will actually happen. The decision-making process is presented as having three pillars to support the decision maker: Preferences–what we prefer, what meets our goals and objectives, and the recognition that preferences are personal to the one making the decision; Alternatives–the choices, options, or courses of action that we have, and over which we have some degree of control; and Information–what we know about the situation, what we don't know, how we connect choices to outcomes, and how we deal with uncertainty. Key components of good decision-making include how to define your goals and objectives, how to incorporate uncertainties that we all face, and how to develop better alternatives, all of which are discussed. Sophisticated techniques are presented in a way that is accessible to the average decision maker. Probability theory is utilized to improve decisions, and uncertainties are captured in decision trees. Risk avoidance, risk transfer, and risk mitigation are also discussed. Readers will gain a clear understanding of how to articulate the goals and objectives that should be the focal point of any decision.

Applications of Management Science showcases current studies in the application of management science, contributing to the solution of significant managerial decision-making problems. To those involved in the applications of multi-criteria decision making, data envelopment analysis, and decision making, in a realistic managerial problem-solving environment through the use of state-of-the-art management science modeling, this is a must read. The research presented by academics in Volume 13 significantly aids in the deconstruction of managerial decision-making problems with management science methodologies. Specifically focusing on the applications of management science methodologies data envelopment analysis and multi-criteria decision making, this collection is split into three sections: Data Envelopment Analysis, Optimization Modeling, Business Analytical Modeling. Applications of Management Science is core for those academics, researchers, and practitioners of management science in mitigating significant managerial decision-making problems, for both the public and the private sectors.

We are told from a young age that we should strive to make the right decisions, but we aren't taught exactly how to do this. Every day, we make over 35,000 decisions in our personal and professional lives. How many of those decisions do we get right? This book will help business executives systematically tackle these 35,000 decisions. Executives are forced to make critical decisions that impact their lives, their employees'lives, and the lives of their customers. Decisions like what products to create, who should be hired, and what divisions to shut down are all commonplace in the executive suite. This book offers three strategies for dealing with decisions: problem-solving techniques, routines, and decision-making frameworks. Each strategy is designed to help readers achieve more clarity, gain time back, and improve the quality of their decisions. The first one focuses on helping readers solve the right problem instead of wasting time on the wrong one. The second strategy helps deal with decisions that need to be made once but can then be executed regularly. The third and final strategy provides a three-step framework for making the most important decisions in their lives. The focus of the author's work is on helping readers use data to make better decisions. This book gives readers the tools to convert the insights they learn from their data into actionable decisions.

Even senior people, business owners, and board members are unaware of the nuances of influence on a daily basis. They think in a straight line and try to'strike deals,'use hierarchical power, make'trade-offs,'or bargain as if at a flea market. They unwittingly sacrifice vital needs to gain minor and temporary bright, shiny things. Influence is not about fast-talking, it's about fast-thinking and carefully constructed language that one applies within a specific context. Influence is thought to be programmable—that is, it can create scarcity or consistency of positive responses. In reality, it's about accountability, innovation, and leverage. No pre-pandemic strategy is worth a cent in a post-pandemic world. There is no'new normal'or'return to normal.'There are only new realities. In this book, one of the boldest, most aggressive, most successful consultants in the world makes his predictions and provides recommendations that may frighten and stun, but ultimately can lead to market domination. Million-dollar influencers understand that influence doesn't mean kissing up to everyone. While we may all be equal as human beings, not everyone has a stake in the outcomes in the business of influence. Some will resist change for the sake of resisting change. They lack imagination or let fear hold them in place. Recognizing actual stakeholders will guide your positioning of stakes in the ground that will mark critical positions leading to your desired outcome. Features How consensus building is something to live with, not something to die for The fundamental difference between accountability and authority The need for innovation and even improvisation in wielding influence The scientific and magical contrasts of language How to effectively maneuver within political environments How to rally the right stakeholders at the right time The powerful role of consequence

This book is about the behaviour of systems. Systems are important, for we interact with them all the time, and many of the actions we take are influenced by a system – for example, the system of performance measures in an organisation influences, often very strongly, how individuals within that organisation behave. Furthermore, sometimes we are involved in the design of systems, as is any manager contributing to the definition of what those performance measures might be. That manager will want to ensure that all the proposed performance measures will drive the ‘right'behaviours rather than (inadvertently) encouraging dysfunctional ‘game playing', and so anticipating how the performance measurement system will work in practice is a vital part of a wise design process. Some of the systems with which we interact are local, such as your organisation's performance measurement system. Some systems, however, are distant, but nonetheless very real, such as the healthcare system, the education system, the legal system and the climate system. Systems, therefore, exist on all scales, from the local to the global. And all systems are complex, some hugely so. That's why understanding how systems behave can be very helpful. Systems are complex for two main reasons. First, the manner in which they behave over time can be very hard to anticipate – and anticipating the future sensibly is of course a key objective of management. Second, the ‘entities'within a system can be connected together in very complex ways, so that an intervention ‘here'can result in an effect ‘there', perhaps a long time afterward. Sometimes this can be surprising, and so we talk of ‘unintended consequences'– but this is of course a euphemism for ‘because I didn't understand how this system behaves, I had not anticipated that'. Systems thinking, the subject matter of this book, is the disciplined study of systems, and causal loop diagrams – the ‘pictures'of this ‘picture book'– are a very insightful way to represent the connectedness of the entities from which any system is composed, so taming that system's complexity.

The book covers the domain of multi-criteria decision making, a topic which has gained significant attention of researchers and practitioners spanning a variety of disciplines for enhancing their decision making in real life situation. The topics in this volume help readers understand the techniques in the model building and analysis stage. The chapters cover a variety of techniques and their applications for interesting problems. This book will be of interest to readers in diverse disciplines such as engineering, business, management, humanities, psychology and law. ^

Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of'It's All Analytics!'series, we describe two primary things: 1) What this'most important aspect'consists of, and 2) How to get this'most important aspect'at the center of the analytics effort and thus make your analytics program successful.This Book II in the series is divided into three main parts:Part I, Organizational Design for Success, discusses ……. The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture – the company culture culture!!! To be successful, the CEO's and Decision Makers of a company / organization must be fully cognizant of the cultural focus on ‘establishing a center of excellence in analytics'. Simply,'culture – company culture'is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses ….. Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy.Part III, Analytics Technology Design for Success, discusses …. Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.

Papers presented at a conference held Jan. 5-10, 1973, Maui, Hawaii, and sponsored by the Joint Committee on Japanese Studies of the Social Science Research Council and the American Council of Learned Societies.

It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690)Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term,'analytics,'is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology?This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.

This book discusses how to build optimization tools able to generate better future studies. It aims at showing how these tools can be used to develop an adaptive learning environment that can be used for decision making in the presence of uncertainties. The book starts with existing fuzzy techniques and multicriteria decision making approaches and shows how to combine them in more effective tools to model future events and take therefore better decisions. The first part of the book is dedicated to the theories behind fuzzy optimization and fuzzy cognitive map, while the second part presents new approaches developed by the authors with their practical application to trend impact analysis, scenario planning and strategic formulation. The book is aimed at two groups of readers, interested in linking the future studies with artificial intelligence. The first group includes social scientists seeking for improved methods for strategic prospective. The second group includes computer scientists and engineers seeking for new applications and current developments of Soft Computing methods for forecasting in social science, but not limited to this.

This book examines how to develop the main traits that are necessary to become an “informed intuitant”. Case studies and examples of successful “informed intuitants” are a major component of the book. “Intuitant” is someone who has the intuitive awareness to be successful. “Informed intuitant” indicates that the individual/decision maker not only applies his/her intuition but also verifies it through using data-driven approaches (such as data analytics). Some of this work resulted from research examining how well do executives trust their intuition.

This book presents the multi-criteria approach to decision support, as well as the various multi-criteria tools to help avoid multi-objective optimization. The book is intended as a tool for understanding the multi-criteria tools for decision support and modeling in mathematical programming. It helps to structure models, to easily model complex constraints, to have a basic modeling guide for any multi-criteria system and to better understand models already existing in the literature.The book is structured in the same order as components of the methodology, established in a multi-criteria optimization problem. It introduces the elements of the actors, the decision-making activity under criteria, calculations, specifications and objective criterion.

This book offers a comprehensive introduction to decision-making in an MCDM framework. Designed as a tutorial, it presents the main concepts and methods to be applied, together with essential background information. This includes the concept of nondominance, Simon's bounded rationality, Tversky and Kahneman's prospect theory, and the concepts of behavioral vs. mathematical convergence and premature stopping put forward by Korhonen, Moskowitz and Wallenius. The book concludes with a non-technical review of many popular decision algorithms, including the Analytic Hierarchy Process (AHP), VIMDA, and a number of classic interactive man-machine algorithms. In essence, the book is a “one-stop” source on everything you need to know about managerial decision-making in the multiple-criteria setting.

This book presents a range of qualitative and quantitative analyses in areas such as cybersecurity, sustainability, multivariate analysis, customer satisfaction, parametric programming, software reliability growth modeling, and blockchain technology, to name but a few. It also highlights integrated methods and practices in the areas of machine learning and genetic algorithms. After discussing applications in supply chains and logistics, cloud computing, six sigma, production management, big data analysis, satellite imaging, game theory, biometric systems, quality, and system performance, the book examines the latest developments and breakthroughs in the field of science and technology, and provides novel problem-solving methods. The themes discussed in the book link contributions by researchers and practitioners from different branches of engineering and management, and hailing from around the globe. These contributions provide scholars with aplatform to derive maximum utility in the area of analytics by subscribing to the idea of managing business through system sciences, operations, and management. Managers and decision-makers can learn a great deal from the respective chapters, which will help them devise their own business strategies and find real-world solutions to complex industrial problems.

How organizations—including Google, StubHub, Airbnb, and Facebook—learn from experiments in a data-driven world.Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of different online experiences. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream. No tech company worth its salt (or its share price) would dare make major changes to its platform without first running experiments to understand how they would influence user behavior. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world. Luca and Bazerman describe the central role experiments play in the tech sector, drawing lessons and best practices from the experiences of such companies as StubHub, Alibaba, and Uber. Successful experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget—or bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts. Moving beyond tech, Luca and Bazerman consider experimenting for the social good—different ways that govenments are using experiments to influence or “nudge” behavior ranging from voter apathy to school absenteeism. Experiments, they argue, are part of any leader's toolkit. With this book, readers can become part of “the experimental revolution.”

Becoming a Supervisor tells the story of Trevor who works as one of the production team in a small company that makes toy boats. He is thrust into the role of supervisor unexpectedly when his general manager reacts to his constant suggestions of how things could be better. When the GM becomes ill, Trevor struggles to take up the slack for several months until a new GM arrives. The core of the book follows Trevor's growth under the coaching of Julie, his new GM. As Trevor deals with one challenge after another, Julie guides him on a journey to learn the core skills needed by all front-line leaders.The reader takes away four key ideas: (1) Front-line leadership skills are not too complicated to learn. (2) These skills are something that they can develop in themselves, regardless of what their organization does. (3) Tools and skills are there to help solve real business problems; implementing the tools is not a strategy. (4) In your role as supervisor (directing or responsible for others) you have to look after the mission of the company AND look after your people – doing only one is not an option.Essentially, this book is intended to give hope to a new supervisor or team lead. They will finish the book knowing that the skills they need can be learned and aren't that difficult to acquire. It is designed to introduce the central skills that any supervisor has to be able to master at least with a basic working competency: instructing, leading, and making improvements in their own area. It introduces some of the more widely used tools that a new supervisor may need. More importantly, it ties these tools and skills to solving particular problems. Readers will understand that the tools are not important for their own sake, but only to the extent that the tools serve the larger objective of the organization. This book is designed to give the reader an entertaining and hopeful story about the very difficult transition from worker to supervisor, from being one of the crew to directing the crew. It is an emotionally tough transition, and the idea that someone could see a model of how it can work out will be helpful to folks new in a leadership role. Finally, the book provides a reference to other sources of information that will let the reader extend their learning about each of the tools or skills referenced in the contents.

This book examines relationships between pairwise comparisons matrices. It first provides an overview of the latest theories of pairwise comparisons in decision making, discussing the pairwise comparison matrix, a fundamental tool for further investigation, as a deterministic matrix with given elements. Subsequent chapters then investigate these matrices under uncertainty, as a matrix with vague elements (fuzzy and/or intuitionistic fuzzy ones), and also as random elements. The second part of the book describes the application of the theoretical results in the three most popular multicriteria decision-making methods: the Analytic Hierarchy Process (AHP), PROMETHEE and TOPSIS. This book appeals to scholars in areas such as decision theory, operations research, optimization theory, algebra, interval analysis and fuzzy sets.

Pertinent to modern industry, administration, finance and society, the most pressing issue for firms today is how to reapproach the way we think and work in business. With topics ranging from improving productivity and coaxing economic growth after periods of market inactivity, Complex Decision-Making in Economy and Finance offers pragmatic solutions for dealing with the critical levels of disorder and chaos that have developed throughout the modern age. This book examines how to design complex products and systems, the benefits of collective intelligence and self-organization, and the best methods for handling risks in problematic environments. It also analyzes crises and how to manage them. This book is of benefit to companies and public bodies with regards to saving assets, reviving fortunes and laying the groundwork for robust, sustainable societal dividends. Examples, case studies, practical hints and guidelines illustrate the topics, particularly in finance.

Systems Thinking for a Turbulent World will help practitioners in any field of change engage more effectively in transformative innovation. Such innovation addresses the paradigm shift needed to meet the diverse unfolding global challenges facing us today, often summed up as the Anthropocene. Fragmentation of local and global societies is escalating, and this is aggravating vicious cycles. To heal the rifts, we need to reintroduce the human element into our understandings – whether the context is civic or scientific – and strengthen truth-seeking in decision-making. Aided by appropriate concepts and methods, this healing will enable a switch from reaction to anticipation, even in the face of discontinuous change and high uncertainty. The outcome is to privilege the positive human skills for collaborative navigation through uncertainty over the disjointed rationality of mechanism and artificial intelligence, which increasingly alienates us. The reader in search of new ways of thinking will be introduced to concepts new to systems thinking that integrate systems thinking and futures thinking. The concept of anticipatory present moment (APM) serves as a basis for learning the cognitive skills that better enable navigation through turbulent times. A key personal and team practice is participative repatterning, which is the basis for transformative innovation. This practice is aided by new methods of visual facilitation. The reader is guided through the unfolding of the ideas and practices with a narrative based on the metaphor of search portrayed in the tradition of ox herding, found in traditional Far Eastern consciousness practice.

This book presents essential information on modern location science – in a word, all you need to know about location. The second edition of this handbook has been fully revised throughout, with numerous updates and chapters added, to offer an even more comprehensive overview of methods and applications. The book is divided into three parts: basic concepts, advanced concepts and applications. Written by the most respected specialists in the field and thoroughly reviewed by the editors, it first lays out the fundamental problems in location science and provides readers with basic background information on location theory. Part II covers advanced models and concepts, broadening and expanding on the content presented in Part I. It also discusses important tools to help readers grasp and solve real-world location problems. Part III focuses on the links between location science and other areas like GIS, telecommunications, healthcare, rapid transit networks, districting problems and disaster events, and presents a wide range of applications to allow readers to understand the role of facility location in such areas and learn how to handle real-world location problems. The book is intended for researchers working on theory and applications involving location problems and models. It is also suitable as a textbook for graduate courses on facility location.

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book's chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. The book's twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja–Bretones–Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes. Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot's stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem. The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.

This book presents 27 methods of the Multiple Attribute Decision Making (MADM), which are not discussed in the existing books, nor studied in details, using more applications. Nowadays, decision making is one of the most important and fundamental tasks of management as an organizational goal achievement that depends on its quality. Decision making includes the correct expression of objectives, determining different and possible solutions, evaluating their feasibility, assessing the consequences, and the results of implementing each solution, and finally, selecting and implementing the solution. Multiple Criteria Decision Making (MCDM) is sum of the decision making techniques. MCDM is divided into the Multiple Objective Decision Making (MODM) for designing the best solution and MADM for selecting the best alternative. Given that the applications of MADM are mostly more than MODM, wide various techniques have been developed for MADM by researchers over the last 60 years, and the currentbook introduces some of the other new MADM methods.

This book examines multiple criteria decision making (MCDM) and presents the Sequential Interactive 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 variations of these marginal 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. Strategic Approach in Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios is divided into three 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 addresses best practices to assure quality MCDM process. Part 3 introduces the concept of Linear Programming and the proposed SIMUS method as techniques to deal with MCDM. It also includes case studies in order to help document and illustrate difficult concepts, especially related to demands from a scenario and also in their modelling. 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 thisinformation effectively.

Tear down the obstacles to creative innovation in your organization Unlocking Creativity is an exploration of the creative process and how organizations can clear the way for innovation. In many organizations, creative individuals face stubborn resistance to new ideas. Managers and executives oftentimes reject innovation and unconventional approaches due to misplaced allegiance to the status quo. Questioning established practices or challenging prevailing sentiments is frequently met with stiff resistance. In this climate of stifled creativity and inflexible adherence to conventional wisdom, potentially game-changing ideas are dismissed outright. Senior leaders claim to value creativity, yet often lack the knowledge to provide a creative framework. Unlocking Creativity offers effective methods and real-world examples of how the most successful organizations create cultures of innovation and experimentation. Best-selling author and scholar Michael Roberto presents a thorough investigation of organizational obstacles to creative thought. Highly relevant to the growth crises many enterprises face in today's economic landscape, this book examines how to break barriers to spark creativity and foster new ideas. This insightful and informative work allows business executives, senior managers, and organization leaders to: Recognize the six organizational mindsets that impede creativity and innovation Learn how to tear down the barriers that obstruct the creative process Create an environment that allows talented people to thrive Encourage creative collaboration in teams throughout an organization Leaders do not have to conceive innovative ideas, but rather open the path for curious and creative employees within their organization. Unlocking Creativity: How to Solve Any Problem and Make the Best Decisions aids organizations in removing obstacles to the creative process and helps to form an atmosphere of imagination and innovation.

In this volume, the authors'two-fold objective is to lay out a methodology and approach that allows the reader to learn how to utilize existing technology in the form of computer software and hardware for forecasting and decision-making and to discuss factors that affect upcoming events that, in turn, shape future paradigms. With the sheer volume of information available and the ever-greater ease of access, it is becoming increasingly difficult to introduce an appropriate methodology of decision-making that is fast enough to be effective. The demand for real-time information processing and related data—both structured and unstructured—is on the rise. This rise makes it challenging to implement correct decision-making within enterprises at a level that keeps organizations robust and resilient against natural and man-made disasters. This volume provides an understanding of these factors and will help decision-makers be better prepared to face future challenges and will assist them in coping with unexpected circumstances. This volume is divided into two parts. Part one discusses a'technological infrastructure'so that readers can gain a greater understanding based on the knowledge of tomorrow's computing functionality. The second part goes on to discuss the key indicators in the areas of population, culture, economics, climate change, and the impacts of technology in commerce and socially—which all need to be considered when forecasting a future paradigm. The authors will follow this introductory volume with additional volumes that review and analyse other critical indicators in the areas of geopolitics, the nature of political power around the globe, and other applications of technology and energy.