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“How do people make decisions in organizations?” is the question at the core of this book. Do people act rationally? Under what conditions can information and knowledge be shared to improve decision making? Davide Secchi applies concepts and theories from cognitive science, organizational behavior, and social psychology to explore the dynamics of decision making. In particular, he integrates “bounded rationality” (people are only partly rational; they have (a) limited computational capabilities and (b) limited access to information) and “distributed cognition” (knowledge is not confined to an individual, but is distributed across the members of a group) to build upon the pioneering work of Herbert Simon (1916-2001) on rational decision making and contribute fresh insights. This book is divided into two parts. The first part (Chapters 2 to 5) explores how recent studies on biases, prospect theory, heuristics, and emotions provide the so-called “map” of bounded rationality. The second part (Chapter 6 to 8) presents the idea of extendable rationality. In this section, Secchi identifies the limitations of bounded rationality and focuses more heavily on socially-based decision processes and the role of “docility” in teaching, managing, and executing decisions in organizations. The practical implications extend broadly to issues relating to change and innovation, as organizations adapt to evolving market conditions, implementing new systems, and effectively managing limited resources. The final chapter outlines an agenda for future research to help understand the decision making characteristics and capabilities of an organization.
Decision making. --- Organization. --- Decision making --- Organizational behavior --- Management --- Business & Economics --- Management Theory --- Behavior in organizations --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Business. --- Planning. --- Industrial psychology. --- Business and Management. --- Industrial, Organisational and Economic Psychology. --- Strategic planning. --- Organizational behavior. --- Organization --- Psychology, Industrial --- Social psychology --- Goal setting (Strategic planning) --- Planning, Strategic --- Strategic intent (Strategic planning) --- Strategic management --- Planning --- Business planning --- Applied psychology. --- Industrial and Organizational Psychology. --- Applied psychology --- Psychagogy --- Psychology, Practical --- Social psychotechnics --- Psychology --- Organisation --- Business psychology --- Industrial psychology --- Psychotechnics --- Industrial engineering --- Personnel management --- Psychology, Applied --- Industrial psychologists --- Creation (Literary, artistic, etc.) --- Executive ability
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The book addresses the rigorous foundations of mathematical analysis. The first part presents a complete discussion of the fundamental topics: a review of naive set theory, the structure of real numbers, the topology of R, sequences, series, limits, differentiation and integration according to Riemann. The second part provides a more mature return to these topics: a possible axiomatization of set theory, an introduction to general topology with a particular attention to convergence in abstract spaces, a construction of the abstract Lebesgue integral in the spirit of Daniell, and the discussion of differentiation in normed linear spaces. The book can be used for graduate courses in real and abstract analysis and can also be useful as a self-study for students who begin a Ph.D. program in Analysis. The first part of the book may also be suggested as a second reading for undergraduate students with a strong interest in mathematical analysis.
Mathematical analysis. --- Analysis. --- 517.1 Mathematical analysis --- Mathematical analysis --- Anàlisi matemàtica --- Teoria de conjunts --- Agregats (Matemàtica) --- Classes (Matemàtica) --- Conjunts (Matemàtica) --- Matemàtica --- Àlgebra de Boole --- Aritmètica --- Conjunts analítics --- Conjunts convexos --- Conjunts ordenats --- Espais mètrics --- Forcing (Teoria de models) --- Funcions --- Morfismes (Matemàtica) --- Nombres ordinals --- Teoria axiomàtica de conjunts --- Teoria combinatòria de conjunts --- Teoria dels reticles --- Teoria descriptiva de conjunts --- Topologia --- Lògica matemàtica --- Àlgebra lineal --- Anàlisi combinatòria --- Anàlisi de Fourier --- Anàlisi estocàstica --- Anàlisi matemàtica no-estàndard --- Anàlisi numèrica --- Matemàtica per a enginyers --- Sèries infinites --- Teoria del potencial (Matemàtica) --- Teories no lineals --- Rutes aleatòries (Matemàtica) --- Àlgebra --- Càlcul --- Teoria de conjunts.
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The aim of this book is to demonstrate how Agent-Based Modelling (ABM) can be used to enhance the study of social agency, organizational behavior and organizational management. It derives from a workshop, sponsored by the Society for the Study of Artificial Intelligence and the Simulation of Behavior (AISB), held at Bournemouth University Business School in 2014 on “Modelling Organizational Behavior and Social Agency”. The contents of this book are divided into four themes: Perspectives, Modeling Organizational Behavior, Philosophical and Methodological Perspective, and Modeling Organized Crime and Macro-Organizational Phenomena. ABM is a particular and advanced type of computer simulation where the focus of modeling shifts to the agent rather than to the system. This allows for complex and more realistic representations of reality, facilitating an innovative socio-cognitive perspective on organizational studies. The editors and contributing authors claim that the use of ABM may dramatically expand our understanding of human behavior in organizations. This is made possible because of (a) the computational power made available by technological advancements, (b) the relative ease of the programming, (c) the ability to borrow simulation practices from other disciplines, and (d) the ability to demonstrate how the ABM approach clearly enables a socio-cognitive perspective on organizational complexity. Showcasing contributions from academics and researchers of various backgrounds and discipline, this volumes provides a global, interdisciplinary perspective.
Commerce - General --- Commerce --- Business & Economics --- Organizational behavior --- Intelligent agents (Computer software) --- Computer simulation --- Behavior in organizations --- Management --- Organization --- Psychology, Industrial --- Social psychology --- Information technology. --- Management. --- Organization. --- IT in Business. --- Innovation/Technology Management. --- Organizational Studies, Economic Sociology. --- Organisation --- Administration --- Industrial relations --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Business—Data processing. --- Industrial management. --- Planning. --- Economic sociology. --- Economic sociology --- Economics --- Socio-economics --- Socioeconomics --- Sociology of economics --- Sociology --- Creation (Literary, artistic, etc.) --- Executive ability --- Business administration --- Business enterprises --- Business management --- Corporate management --- Corporations --- Industrial administration --- Management, Industrial --- Rationalization of industry --- Scientific management --- Business --- Industrial organization --- Social aspects
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The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets, .... The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statisticians working at the forefront of statistical analysis.
Mathematical statistics -- Data processing -- Congresses. --- Mathematical statistics -- Data processing. --- Mathematical statistics. --- Mathematical statistics --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Data processing --- Database design --- Statistical methods. --- Data base design --- Mathematics. --- Data mining. --- Computer software. --- Statistics. --- Mathematical Software. --- Statistics and Computing/Statistics Programs. --- Statistical Theory and Methods. --- Data Mining and Knowledge Discovery. --- System design --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Software, Computer --- Computer systems --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Statistics and Computing. --- Data processing.
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In a world on the brink of a global recession caused by the COVID-19 global pandemic, the infrastructure efforts of today and tomorrow are more crucial than ever. For one, they are an indispensable countercyclical tool to mitigate the negative effects of the economic paralysis. But they also constitute a pivotal component for a country’s development, raising its competitiveness in the long term. That is why infrastructure will continue to play a critical role even when the pandemic crisis has been tamed. Rapid demographic growth, increasing urbanization, especially in developing countries, coupled with the ounting challenge posed by climate change, are trends that are not going to disappear with the virus. How to cope with these global, long-term trends? How to finance the increasing need for infrastructure? Which major international actors will take the lead? And what role will technology play in shaping the future of infrastructure?
Economic development. --- Development, Economic --- Economic growth --- Growth, Economic --- Economic policy --- Economics --- Statics and dynamics (Social sciences) --- Development economics --- Resource curse --- Economic history --- Business & economics
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In the aftermath of the pandemic, global demand for infrastructure is booming. National plans around the world show that infrastructure is likely to provide the backbone for a resurgence in public expenditure, and to support growth in economies badly hit by the pandemic. As all the biggest powers and blocs (the EU, the US, China, and Japan) have recently announced their plans for climate or carbon neutrality, the room and need for green and sustainable infrastucture are greatly expanding. Decarbonisation and digitalisation will be underpinning this latest investment drive in infrastructure, with sustainability and ESG principles at its core.
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In today's tumultuous and fast-changing times, digitalisation and technology are game changers in a wide range of sectors and have a tremendous impact on infrastructure. Roads, railways, electricity grids, aviation, and maritime transport are deeply affected by the digitaland technological transition, with gains in terms of competitiveness, cost-reduction, and safety. Digitalisation is also a key tool for fostering global commitment towards sustainability, but the race for digital infrastructure is also a geopolitical one. As the world's largest economies are starting to adopt competitive strategies, a level playing field appears far from being agreed upon.Why are digitalisation and technology the core domains of global geopolitical competition? How are they changing the way infrastructure is built, operated, and maintained? To what extent will road, rail, air, and maritime transport change by virtue of digitalisation, artificial intelligence, and the Internet of Things? How to enhance cyber protection for critical infrastructure? What are the EU's, US' and China'sdigital strategies?
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The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
Mathematical statistics --- Statistique mathématique --- Data processing. --- Informatique --- Engineering. --- Mathematical statistics. --- Mathematics. --- Software engineering. --- Statistical methods. --- Statistics. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Numerical analysis --- Data structures (Computer science) --- Statistique mathématique --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B --- Statistical inference --- Statistics, Mathematical --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Statistical methods --- Biostatistics. --- Applied mathematics. --- Engineering mathematics. --- Complexity, Computational. --- Statistical Theory and Methods. --- Applications of Mathematics. --- Complexity. --- Software Engineering/Programming and Operating Systems. --- Statistics --- Probabilities --- Sampling (Statistics) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Computer software engineering --- Engineering --- Construction --- Industrial arts --- Technology --- Math --- Science --- Statistics . --- Computational complexity. --- Complexity, Computational --- Machine theory --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Engineering analysis --- Mathematical analysis --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics
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