This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization. Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.

Demography as a discipline is now at the point where its relevance to business decision making is indisputable--and top business management knows this. People who lack an understanding of state-of-the-art demographic techniques, and who cannot adapt to new ways of thinking prompted by demography and demographers, will find themselves significantly disadvantaged in today's competitive business environment. Pol and Thomas thus provide practitioners and students alike with a concise but intensive introduction to the concepts and methods of business demography. They chronicle current demographic trends and explain their meaning for business. With numerous examples drawn from business and industry, they make clear that business demography is truly a decision-making science.

Pol and Thomas introduce basic concepts, then present an overview of recent and future demographic trends. They elaborate on the application of current demographic methods to planning and marketing in the contemporary business environment, and illustrate their points with numerous charts, maps, and sidebars. Pol and Thomas provide many examples of real world situations in which demographic methods, data, perspective, and theory are actively applied. With sections on sources of health care data, the calculation of demographic rates, the demographic resources available and up-to-date statistics on current demographic trends, their book becomes not only a unique resource for professionals, but also a useful text and reference for their colleagues in the academic community.

In this groundbreaking book, Tim Harford, the Undercover Economist, shows us a new and inspiring approach to solving the most pressing problems in our lives. When faced with complex situations, we have all become accustomed to looking to our leaders to set out a plan of action and blaze a path to success. Harford argues that today's challenges simply cannot be tackled with ready-made solutions and expert opinion; the world has become far too unpredictable and profoundly complex. Instead, we must "adapt."

Deftly weaving together psychology, evolutionary biology, anthropology, physics, and economics, along with the compelling story of hard-won lessons learned in the field, Harford makes a passionate case for the importance of adaptive trial and error in tackling issues such as climate change, poverty, and financial crises--as well as in fostering innovation and creativity in our business and personal lives.

Taking us from corporate boardrooms to the deserts of Iraq, "Adapt "clearly explains the necessary ingredients for turning failure into success. It is a breakthrough handbook for surviving--and prospering-- in our complex and ever-shifting world.

Risk Analysis: Foundations, Models, and Methods fully addresses the questions of "What is health risk analysis?" and "How can its potentialities be developed to be most valuable to public health decision-makers and other health risk managers?" Risk analysis provides methods and principles for answering these questions. It is divided into methods for assessing, communicating, and managing health risks. Risk assessment quantitatively estimates the health risks to individuals and to groups from hazardous exposures and from the decisions or activities that create them. It applies specialized models and methods to quantify likely exposures and their resulting health risks. Its goal is to produce information to improve decisions. It does this by relating alternative decisions to their probable consequences and by identifying those decisions that make preferred outcomes more likely. Health risk assessment draws on explicit engineering, biomathematical, and statistical consequence models to describe or simulate the causal relations between actions and their probable effects on health. Risk communication characterizes and presents information about health risks and uncertainties to decision-makers and stakeholders. Risk management applies principles for choosing among alternative decision alternatives or actions that affect exposure, health risks, or their consequences.

This book presents a rich collection of studies on the analysis of sustainable development from a multiple criteria decision-making (MCDM) perspective, written by some of the most prominent authors in the field of MCDM/A. The book constitutes a unique international reference guide to the analysis, measurement, and management of sustainability in a multidimensional decision analysis context. Chiefly intended for academics and policymakers, it reflects some of the latest methodological advances in decision-making, which are illustrated in real-life applications to sustainability-related topics in both the private and public sector.

Semiorder is probably one of the most frequently ordered structures in science. It naturally appears in fields like psychometrics, economics, decision sciences, linguistics and archaeology. It explicitly takes into account the inevitable imprecisions of scientific instruments by allowing the replacement of precise numbers by intervals. The purpose of this book is to dissect this structure and to study its fundamental properties. The main subjects treated are the numerical representations of semiorders, the generalizations of the concept to valued relations, the aggregation of semiorders and their basic role in a general theoretical framework for multicriteria decision-aid methods. Audience: This volume is intended for students and researchers in the fields of decision analysis, management science, operations research, discrete mathematics, classification, social choice theory, and order theory, as well as for practitioners in the design of decision tools.

The theory of value structure concerns the meaning of "better than" and "good," as well as the way in which values serve as a basis for rational decision making. Drawing methodologically from economics and theories of decision making, the aim of serious axiology in metaethics is to do justice to problems that have puzzled philosophers of value for centuries. Can value comparisons be cyclic? Are all values comparable with each other and can decision makers just add up different aspects of an evaluation to determine the best course of action? A Theory of Value Structure: From Values to Decisions starts with a thorough introduction to the modeling of "better than" comparisons from a normative perspective. In the philosophical part of the book, Erich H. Rast argues that aspects of "better than" comparisons can differ qualitatively so much that one aspect may outrank another. Consequently, the classical weighted sum aggregation model fails. Values cannot always be summed up and comparisons may be fundamentally noncompensatory, an indeterminacy that explains problems like the apparent nontransitivity of "better than" and hard cases in decision making. Using a lexicographic method of value comparisons, Rast develops a multidimensional theory of "better than" and shows how and to which extent it can be combined with standard methods of decision making under uncertainty by using rank-dependent utility theory.

In recent years there has been substantial interest in benefits assessment methods, especially as these methods are used to assess health, safety, and environmental issues. At least part of this interest can be traced to Executive Order 12291, issued by President Ronald Reagan in 1981. This Executive Order requires Federal agencies to perform benefits assessments of pro posed major regulations and prohibits them from taking regulatory action unless potential benefits exceed potential costs to society. Heightened interest in benefits assessment methods has in tum given rise to greater recognition of the inherent difficulties in performing such assess ments. For example, many benefits that are intuitively felt to be most important are also among the most difficult to measure. It can be difficult to identify the full range of both benefits and costs. The choice of an appro priate discount rate for comparing benefits and costs over time is proble matic. Even when benefits are quantifiable in principle and agreement can be reached on their valuation, required d, ata may not be available. Thus considerable uncertainty is built into most benefit estimates, even when they are based on the best available data. In light of the complexities and difficulties associated with the perform ance of a benefits assessment, this book reviews the current state of theoretical and methodological knowledge in the field. The review is extensive in that it covers over fifty years of research, theoretical develop ment, and practice."

The numerous advances in mathematical programming have opened up new insights about sensitivity analysis. The paradigm What if...?' question is no longer the only question of interest. Often, we want to know Why...?' and Why not...?' Such questions were not analyzed in the early years of mathematical programming to the same extent that they are now, and we have not only expanded our thinking about post-optimal analysis', but also about solution analysis', even if the solution obtained is not optimal. Therefore, it is now time to examine all the recent advances on sensitivity analysis and parametric programming. This book combines the origins of sensitivity analysis with the state of the art. It covers much of the traditional approaches with a modern perspective, and shows recent results using the optimal partition approach, stemming from interior methods, for both linear and quadratic programming. It examines the special case of network models. It presents a neglected topic, qualitative sensitivity analysis, as well as elements of mixed integer programming and gives a modern perspective of nonlinear programming. It provides recent advances in multi-criteria mathematical programming and also describes the state-of-the-art in stochastic programming. It covers recent advances in understanding redundancy in quadratic programs, considers an approach to diagnosing infeasibility in linear and nonlinear programs, and gives an overview of sensitivity analysis for fuzzy mathematical programming.

This book presents the human, cultural, and scientific contributions of professor Eliano Pessa, who recently passed away. His research interests and activities were varied, some of which included quantum physics, cognitive science and psychology, systems science, artificial intelligence, and alpinism. They were never disciplinary-separated issues, but rather some coherent dimensions of his interests in life. He lived and not only practiced interdisciplinarity and multiple dimensions; he considered it unacceptable to do only one thing in life. The contributors in this volume consider, discuss, interpret, and represent the multiplicity and interdisciplinarity experienced, lived and applied by Pessa. The chapters are inspired by, rebuild, and retrace such networked interests lived by him from the personal, cultural, and scientific points of view of the authors. This is true interdisciplinarity and usage of non-equivalences, honoring the richness of Pessa's contributions.

Life after Boris is a quick-to-read fable that should encourage any partner - or indeed anyone aspiring to partnership - in a professional services firm, to make sure that the succession planning issue is addressed in their firm. It seeks to demonstrate that with good planning, collaboration and proactive discussion, options can be found that will be acceptable to all. Without such an approach, the consequences could be serious. Succession planning is not inherently difficult or intellectually complex. It does, however, strike many raw nerves, both with those who are currently at the top of their firms and are contemplating retirement (or not), and also with those in the early stages of their careers who are anxious to know what the future holds for them in their current firm. The frustration, of course, is that many stakeholders in the succession planning process (of which there are far more than one might originally envisage) rush into decisions because of the apparent lack of a succession plan, thereby simply exacerbating the problem for all the other stakeholders. It is therefore critical that all firms, and the stakeholders within those firms, address the succession planning question before it becomes an issue. Closing the stable door after the horse has bolted is simply not an option. Initiating the succession planning process need not necessarily come from the current leaders. Indeed, their failure to do so is often at the root of the problem. The bright leaders of tomorrow have much at stake and although a great deal of tact and sensitivity will be needed, it is often these future leaders of a firm who are best positioned to bring about change. In the author's experience over the last 12 years of working with professional services firms around the world, one of the most frequently recurring catalysts for discussion has been succession management. Firms that got it right developed and prospered. Those that didn't struggled and often ended up having to merge and ultimately disappear into oblivion.

Were you looking for the book with access to MyLab Math Global? This product is the book alone and does NOT come with access to MyLab Math Global. Students, if MyLab Math Global is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyLab Math Global should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. There's no doubt that a manager's job is getting tougher. Do it better, do it faster, do it cheaper are the pressures every manager faces. And at the heart of every manager's job is decision-making: deciding what to do and how to do it. This well-respected text looks at how quantitative analysis techniques can be used effectively to support such decision making. As a manager, developing a good understanding of the quantitative analysis techniques at your disposal is crucial. Knowing how, and when, to use them and what their results really mean can be the difference between making a good or bad decision and, ultimately, between business success and failure. Appealing both to students on introductory-level courses and to MBA and postgraduate students, this internationally successful text provides an accessible introduction to a subject area that students often find difficult. Quantitative Analysis for Decision Makers (formerly known as Quantitative Methods for Decision Makers) helps students to understand the relevance of quantitative methods of analysis to management decision-making by relating techniques directly to real-life business decisions in public and private sector organisations and focuses on developing appropriate skills and understanding of how the techniques fit into the wider management process. Key features: The use of real data sets to show how analytical techniques are used in practice "QADM in Action" case studies illustrating how organisations benefit from the use of analytical techniques Articles from the Financial Times illustrating the use of such techniques in a variety of business settings Fully worked examples and exercises supported by Excel data sets Student Progress Check activities in each chapter with solutions A 300+ page Tutors Solutions Manual

The encounter, in the late seventies, between the theory of triangular norms, issuing frorn stochastic geornetry, especially the works of Menger, Schweizer and Sklar, on the one band, and the theory of fuzzy sets due to Zadeh, 10n the other band has been very fruitful. Triangular norms have proved to be ready-rnade mathematical rnodels of fuzzy set intersections and have shed light on the algebraic foundations of fuzzy sets. One basic idea behind the study of triangular norms is to solve functional equations that stern frorn prescribed axioms describing algebraic properties such as associativity. Alternative operations such as rneans have been characterized in a similar way by Kolmogorov, for instance, and the rnethods for solving functional equations are now weil established thanks to the efforts of Aczel, among others. One can say without overstaternent that the introduction of triangular norms in fuzzy sets has strongly influenced further developrnents in fuzzy set theory, and has significantly contributed to its better acceptance in pure and applied rnathematics circles. The book by Fodor and Roubens systematically exploits the benefits of this encounter in the- analysis of fuzzy relations. The authors apply functional equation rnethods to notions such as equivalence relations, and various kinds of orderings, for the purpose of preference rnodelling. Centtal to this book is the rnultivalued extension of the well-known result claiming that any relation expressing weak preference can be separated into three cornponents respectively describing strict preference, indifference and incomparability.

This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.

Resilient people are happier, healthier, and more productive. Psychologist and business writer Adrian Furnham takes a sideways and entertaining look at the challenges of being a leader, demonstrating how resilience can be honed, developed, and used as a personal life raft to keep afloat in the face of adversity.

This new edition Workbook has been fully updated for 2019 and covers Theme 3 Business behaviour and the labour market A-level Paper 1 Markets and business behaviour, and A-level Paper 3 Microeconomics and Macroeconomics will both draw on topics from Theme 3. Up-to-date and focused to help students practice their skills and improve their subject knowledge both inside and outside the classroom, this Practice Workbook: - Covers specific aspects of the course, providing targeted support for complex and challenging topics - Reinforces students' understanding, with more new practice questions and exam-style questions to develop their skills and improve their confidence - Includes more sample answers with commentary to help students meet the demands of the specification - Adapts easily and flexibly to existing textbooks and schemes of work - Provides opportunities for self-directed learning and self-testing, helping students revise on their own terms

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

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

This book illustrates how to access the right information for making the best decisions during turbulent times. It is written from an experienced-based perspective that is beneficial for those looking for the development and improvement of the decision-making process. The approach is centered on the author's experience in developing and implementing effective and efficient approaches to decision-making in business and government. Based on those experiences, this book provides insights into how to improve the decision making process of your organization, whether it be large or small. For decision makers and those providing market information for making decisions, this book provide guidelines for a framework which includes systems thinking. For those interested in change management and corporate governance, the book presents examples where it was done well and some examples where it was not and the ensuring consequences. Praise for Systems Thinking Decision-Making Process... "This is an absolutely incredible book by a distinguished practitioner. The range of knowledge and experience that Vince Barabba has had is astounding. I urge everyone who is interested in complex, messy problems to read this amazing book." --Ian I. Mitroff "...Vince has masterfully blended the art of organizational respect with the science of data inquiry to drive change and realize strategic vision. A master storyteller, he does not just teach, his book brings his learnings to life in a meaningful way that if carefully listened to, can change the course of a career." -- Paul D'Alessandro Principal, Health Industries, PwC US "In his latest book, Vince Barabba integrates his vast knowledge from 50 years of dedicated work in both the public and private sectors in order to provide leaders with an actionable framework for radically improving how their organizations collect and use information to make the best decisions for all the wicked messes that now appear in our global village... This book can save your company from living in the dark with false assumptions about all your key stakeholders." -- Ralph H. Kilmann, Ph.D. CEO, Kilmann Diagnostics Co-Author, The Thomas-Kilmann Conflict Mode Instrument (TKI) "Absorbing just a few of the many smart ideas in this book will make you a better leader and decision maker. Thinking systemically about how the hard-earned lessons from Vince Barabba's brilliant career apply to your enterprise could make you a great one." - Chunka Mui Co-Author, A Brief History of a Perfect Future and Billion Dollar Lessons "...if you are interested in 'thinking in systems,' this book is for you. The 'On Star' story demonstrates to you how the initial product-centered thinking was proselytized to 'thinking in systems'." -- John Pourdehnad Visiting Professor, IESE Business School and Faulty of Systems Leadership, Thomas Jefferson University "In writing Systems Thinking Decision-Making Process: How to Avoid Burnt Toast, Vince Barabba is addressing the limits of knowledge management systems which enable 'organizations as usual' to share best practices on how to scrape toast faster and cheaper... The examples shared by Vince, from his first-hand experiences in corporate America or his services as a marketing consultant, contribute invaluable clarity to his goal of providing a "sketch of an Inquiry Center Learning and Support System" for those with the ambition to lead efforts to work smarter, not harder, firmly against the grain of 'organizations as usual'..." -- Bill Bellows, Ph.D., President, InThinking Services Adjunct Professor, California State University, Northridge and Southern Utah University Advisory Council Member and Former Deputy Director, The W. Edwards Deming Institute (R) "In his 'last book', Vince weaves the experiences and learning of a lifetime into whole cloth of insight and wisdom. He helps us to find relevant information from a rapidly changing world and apply it to making good decisions. This is a masterpiece of knowledge presented in a very entertaining way." -- Carl Spetzler Chairman, Strategic Decisions Group International LLC "This is a truly inspiring and mind changing book directly relevant for our times... Vince has shown through his remarkable work that business and government are a force for good when leaders think long term, work with, not against nature, and use their influence and resources for the many, not the few..." -- Osvald Bjelland Founder and President, Xynteo Founder, The Performance Theatre Foundation

This book has resulted from the activities of IFAC TC 5.2 "Manufacturing Modelling for Management and Control". The book offers an introduction and advanced techniques of scheduling applications to cloud manufacturing and Industry 4.0 systems for larger audience. This book uncovers fundamental principles and recent developments in the theory and application of scheduling methodology to cloud manufacturing and Industry 4.0. The purpose of this book is to present recent developments in scheduling in cloud manufacturing and Industry 4.0 and to systemize these developments in new taxonomies and methodological principles to shape this new research domain. This book addresses the needs of both researchers and practitioners to uncover the challenges and opportunities of scheduling techniques' applications to cloud manufacturing and Industry 4.0. For the first time, it comprehensively conceptualizes scheduling in cloud manufacturing and Industry 4.0 systems as a new research domain. The chapters of the book are written by the leading international experts and utilize methods of operations research, industrial engineering and computer science. Such a multi-disciplinary combination is unique and comprehensively deciphers major problem taxonomies, methodologies, and applications to scheduling in cloud manufacturing and Industry 4.0.