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Health Administration; Quality Control, Reliability, Safety and Risk; Quality of Life Research; Practice and Hospital Management

Summary: Health Administration; Quality Control, Reliability, Safety and Risk; Quality of Life Research; Practice and Hospital Management

Business Analytics (BA) is an evolving phenomenon that showcases the increasing importance of using huge volumes of data to generate value for businesses. Advances in BA have offered great opportunities for organisations to improve, innovate, and develop existing or new processes, products, and services. BA is the process of transforming data into actionable insight by using statistical and mathematical analysis, descriptive, prescriptive, and predictive models, machine learning, information systems and network science methods, among others, along with a variety of data, expert knowledge, and fact-based management to support better and faster decision-making.BA and Business Intelligence (BI) generate capabilities for companies to compete in the market effectively and has become one of the main functional areas in most companies. BA tools are used in diverse ways, for example, to identify consumer behaviour patterns and market trends, to derive valuable insights on the performance of stocks, to find information on the attrition rate of employees, to analyse and solve healthcare problems, to offer insight into inventory management and supply chain management, to analyse data from social networks, and to infer traffic behaviour and develop traffic management policy, among others.BA and BI have become one of the most popular research areas in academic circles, as well as in the industry, driven by the increasing demand in the business world. This book aims to become a stimulus for innovative business solutions covering a wide range of aspects of business analytics, such as management science, information technology, descriptive, prescriptive, and predictive models, machine learning, network science, mathematical and statistical techniques. The book will encompass a valuable collection of chapters exploring and discussing computational frameworks, practices, and applications of BA that can assist industries and relevant stakeholders in decision-making and problem-solving exercises, with a view to driving competitive advantage.

This book provides a comprehensive and practical introduction to Data Envelopment Analysis (DEA). It explains how this non-parametric technique is used to measure performance and extract efficiency from homogeneous entities within a production procedure. It situates DEA within a growing field of productivity analysis and performance measurement, for which numerous models have been proposed. This book encapsulates all of the advances in DEA models proposed in the literature. These models are presented in the context of the GAMS software, which is a powerful tool for mathematical programming models. This book serves two educational purposes: it introduces readers to DEA models and provides examples using GAMS. In addition, the reader is introduced to GAMS programming, as well as innovative and practical applications. GAMS codes are available for free, allowing readers to test and expand the models to meet their specific needs.

Composite indices are used by national and international organisations, as well as governments and corporations, to track various performance aspects of a country's economy and its people, evaluate progress, and engage constructively in policy dialogue; and they have long proven useful as communication tools and inputs into decision-making and policymaking. Modern Indices for International Economic Diplomacy compiles a spectrum of relevant indices for development and well-being used in benchmarking across nations, namely the OECD Better Life Index, the Gini Index, the Gender Equality/Inequality Index, the International Energy Security Risk Index, the Big Mac Index, the Country Risk Index, the Corruption Perceptions Index, and the Global Terrorism Index. The book will be relevant to practitioners, policymakers, researchers, and students interested in the topic of international economic relationships.

This book aims to provide the necessary background to work with big data blockchain by introducing some novel applications in service operations for both academics and interested practitioners, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book intends to cover theory, research, development, and applications of big data and blockchain, as embedded in the fields of mathematics, engineering, computer science, physics, economics, business, management, and life sciences, to help service operations management.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

This book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs. It focuses on the application of theories and interpretations of the mathematical programs, which are combined with economic and organizational thinking. The book's main purpose is to shed light on the advantages of the different methods in deterministic and stochastic environments and thoroughly prepare readers to properly use these methods in various cases. Simple examples, along with graphical illustrations and real-world applications in industry, are provided for a better understanding. The models introduced here can be easily used in both theoretical and real-world evaluations. This book is intended for graduate and PhD students, advanced consultants, and practitioners with an interest in quantitative performance evaluation.

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, Naïve 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 doubtthat 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 highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks – many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes.

Measuring and managing the performance of a business is one of the main requirements of the management of any organization. This book introduces new contexts and themes of application and presents emerging research areas related to business performance measurement and management. It draws authors from all around the globe from a variety of functional disciplines, all of whom are working in the field of business performance measurement and management, thus resulting in a variety of perspectives on performance measurement from various functional areas – accounting, finance, economics, marketing, and operations management – in a single volume.

Data envelopment analysis (DEA), a non-parametric technique, has emerged as a popular management tool for measuring the performance of a set of entities, known as decision making units. This book, Data Envelopment Analysis and Its Applications to Management, is a collection of contributions from DEA experts from various countries. It covers a wide range of research papers from the theoretical development of DEA to its applications in various sectors such as economy, banking, education, revenue management, sports, branch networks, cities, and live stock production systems. The book is useful for researchers as well as practitioners who intend to apply DEA to their strategic and managerial decisions.

Les produits naturels sont de plus en plus recherchés pour une agriculture durable, l'utilisation sans discernement des pesticides conventionnels de synthèse ayant eu un impact écologique et sanitaire néfaste (résistance des ravageurs, contamination de l'environnement et des écosystèmes, perte de la biodiversité…). Le recours au monde végétal et aux molécules qui ont permis aux plantes de se protéger contre les ennemis naturels devient donc indispensable. À côté de molécules susceptibles d'avoir des actions insecticides, fongicides ou herbicides, les recherches récentes ont souligné les activités des composés végétaux dans les mécanismes de défense des plantes. Elles ont ouvert de nouveaux horizons en matière de stimulation des défenses des plantes ou de nouveaux procédés chimiques et biologiques d'ordre industriel pour valoriser ces molécules en tant que produits ou stratégies phytosanitaires. Ces avancées ont conduit à des réflexions sur leur réglementation et leur homologation qui s'inscrivent dans des perspectives renouvelées. Cette deuxième édition augmentée de Biopesticides d'origine végétale fait état des dernières découvertes au niveau fondamental et appliqué. Fruit des travaux de spécialistes provenant de plusieurs horizons disciplinaires (entomologie, allélopathie, écologie chimique, botanique, chimie des substances naturelles) et de trois continents (Afrique, Amérique du Nord et Europe), elle s'adresse plus spécifiquement aux praticiens et professionnels de la protection des végétaux ainsi qu'aux chercheurs, enseignants et étudiants des 2e et 3e cycles universitaires.

The aim of this book is to reduce the risks of medical treatment and enhance the safety of patients in all areas of healthcare. The first section discusses human error, the incidence of harm to patients, and the development or risk management. Chapters in the second section discuss the reduction of risk in clinical practice in key medical specialties. The third section discusses features of the healthcare systems that are essential to safe practice, such as communication of risk to patients, the design of equipment, supervision and training, and effective teamwork. The fourth section describes how to put risk management into practice, including the effective and sensitive handling of complaints and claims, the care of injured patients and the staff involved, and the reporting, investigation and analysis of serious incidents.