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The automotive industry ranks among the most significant business phenomena of the 20th century and remains vitally important today, accounting for almost 11% of the GDP of North America, Europe and Japan and one in nine jobs. In economic and social terms alike, its products have had a fundamental impact on modern society - for better and worse. Yet the industry has found it hard to adjust to recent challenges and is no longer much valued by the capital markets. It is riven with internal contradictions that inhibit reform, and faces a stark choice between years of strife or radical change. This book is a wake-up call for those who work in the automotive business. It highlights the challenges and opportunities that exist for managers, legislators, financial institutions and potential industry entrants. Most of all, it gives us all cause to reflect on the value of our mobility, today and tomorrow.
The automotive industry ranks among the most significant business phenomena of the 20th century and remains vitally important today, accounting for almost 11% of the GDP of North America, Europe and Japan and one in nine jobs. Although its products have had a fundamental impact on modern society in economic and social terms, the industry has found it hard to adjust to contemporary conditions and is thus no longer esteemed in capital markets. Riven with internal contradictions that inhibit reform, it now faces a stark choice between years of strife or radical change. Highlighting the challenges and opportunities that exist for managers, legislators, financial institutions and potential industry entrants, this book is a wake-up call for those who work in the automotive industry. Most of all, it gives us all cause to reflect on the value of mobility, today and tomorrow. Graeme Maxton is director of AutoPolis, a firm that specializes in the structures and dynamics of the world automotive industry and helps clients position themselves for profitable growth. He is responsible for its activities in Asia and since 1992, has been closely affiliated with the Economist Newspaper Group and chairs all of The Economist's automotive industry conferences throughout the world. He writes for Business China, Business Asia, and various other Group publications, as well as for numerous newspapers throughout Europe and Asia. He is also a television, radio, and press commentator on the industry. Maxton and Wormald were co-authors of Driving Over a Cliff? Business Lessons from the World's Car Industry (Addison Wesley, 1994), which was nominated for the Financial Times Best Book about Business Award. John Wormald is a director and co-founder of Autopolis. He has worked in and for the automotive industry for over 25 years. He advises vehicle manufacturers, component suppliers, distribution and service companies, and financial and government institutions, with a particular emphasis on the downstream distribution and service sectors of the industry. He regularly lectures about the industry, speaks at industry conferences, writes for automotive and general publications, and is quoted and interviewed in the media. He is a co-author of Driving Over a Cliff?
“Top agricultural scientists from around the world have taken up the challenge of sustainable agriculture, with the specific focus on integrating agronomic, climatological, biophysical and socio-economic perspectives and processes. Every chapter (of the Handbook) contributes to addressing the growing food-security challenges facing the world.”Foreword by Jeffrey Sachs, Director of the Earth Institute at Columbia UniversityClimate effects on agriculture are of increasing concern in both the scientific and policy communities because of the growing population and the greater uncertainty in the weather during growing seasons. Changes in production are directly linked to variations in temperature and precipitation during the growing season and often to the offseason changes in weather because of soil water storage to replenish the soil profile. This is not an isolated problem but one of worldwide interest because each country has concerns about their food security.The Agricultural Model Intercomparison and Improvement Project (AgMIP) was developed to evaluate agricultural models and intercompare their ability to predict climate impacts. In sub-Saharan Africa and South Asia, South America and East Asia, AgMIP regional research teams (RRTs) are conducting integrated assessments to improve understanding of agricultural impacts of climate change (including biophysical and economic impacts) at national and regional scales. Other AgMIP initiatives include global gridded modeling, data and information technology (IT) tool development, simulation of crop pests and diseases, site-based crop-climate sensitivity studies, and aggregation and scaling.
In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change.
This proceedings volume contains selected papers presented at the 2014 International Conference on Education Management and Management Science (ICEMMS 2014), held August 7-8, 2014, in Tianjin, China. The objective of ICEMMS2014 is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the wo
Change of Time and Change of Measure provides a comprehensive account of two topics that are of particular significance in both theoretical and applied stochastics: random change of time and change of probability law.Random change of time is key to understanding the nature of various stochastic processes, and gives rise to interesting mathematical results and insights of importance for the modeling and interpretation of empirically observed dynamic processes. Change of probability law is a technique for solving central questions in mathematical finance, and also has a considerable role in insurance mathematics, large deviation theory, and other fields.The book comprehensively collects and integrates results from a number of scattered sources in the literature and discusses the importance of the results relative to the existing literature, particularly with regard to mathematical finance.In this Second Edition a Chapter 13 entitled 'A Wider View' has been added. This outlines some of the developments that have taken place in the area of Change of Time and Change of Measure since the publication of the First Edition. Most of these developments have their root in the study of the Statistical Theory of Turbulence rather than in Financial Mathematics and Econometrics, and they form part of the new research area termed 'Ambit Stochastics'.
Noted for its crystal clear explanations, this book is considered the most comprehensive introductory text to structural equation modeling (SEM). Noted for its thorough review of basic concepts and a wide variety of models, this book better prepares readers to apply SEM to a variety of research questions. Programming details and the use of algebra are kept to a minimum to help readers easily grasp the concepts so they can conduct their own analysis and critique related research. Featuring a greater emphasis on statistical power and model validation than other texts, each chapter features key concepts, examples from various disciplines, tables and figures, a summary, and exercises. Highlights of the extensively revised 4th edition include: -Uses different SEM software (not just Lisrel) including Amos, EQS, LISREL, Mplus, and R to demonstrate applications. -Detailed introduction to the statistical methods related to SEM including correlation, regression, and factor analysis to maximize understanding (Chs. 1 – 6). -The 5 step approach to modeling data (specification, identification, estimation, testing, and modification) is now covered in more detail and prior to the modeling chapters to provide a more coherent view of how to create models and interpret results (ch. 7). -More discussion of hypothesis testing, power, sampling, effect sizes, and model fit, critical topics for beginning modelers (ch. 7). - Each model chapter now focuses on one technique to enhance understanding by providing more description, assumptions, and interpretation of results, and an exercise related to analysis and output (Chs. 8 -15). -The use of SPSS AMOS diagrams to describe the theoretical models. -The key features of each of the software packages (Ch. 1). -Guidelines for reporting SEM research (Ch. 16). -www.routledge.com/9781138811935 which provides access to data sets that can be used with any program, links to other SEM examples, related readings, and journal articles, and more. Reorganized, the new edition begins with a more detailed introduction to SEM including the various software packages available, followed by chapters on data entry and editing, and correlation which is critical to understanding how missing data, non-normality, measurement, and restriction of range in scores affects SEM analysis. Multiple regression, path, and factor models are then reviewed and exploratory and confirmatory factor analysis is introduced. These chapters demonstrate how observed variables share variance in defining a latent variables and introduce how measurement error can be removed from observed variables. Chapter 7 details the 5 SEM modeling steps including model specification, identification, estimation, testing, and modification along with a discussion of hypothesis testing and the related issues of power, and sample and effect sizes.Chapters 8 to 15 provide comprehensive introductions to different SEM models including Multiple Group, Second-Order CFA, Dynamic Factor, Multiple-Indicator Multiple-Cause, Mixed Variable and Mixture, Multi-Level, Latent Growth, and SEM Interaction Models. Each of the 5 SEM modeling steps is explained for each model along with an application. Chapter exercises provide practice with and enhance understanding of the analysis of each model. The book concludes with a review of SEM guidelines for reporting research. Designed for introductory graduate courses in structural equation modeling, factor analysis, advanced, multivariate, or applied statistics, quantitative techniques, or statistics II taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. Prerequisites include an introduction to intermediate statistics that covers correlation and regression principles.
Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.
Experts report the state of the art in the study of global climate change using remote sensing techniques. Topics covered include the principles of remote sensing, the management of data, data requirements in climatology, the principles of modelling, the input of data into models, and the application of remote sensing to the atmosphere, ice and snow, seas and land. The book is highly topical given the current great public and scientific awareness of possible man-made changes to the climate. It is essential reading for anyone new to the field, and invaluable as a reference work to those already working in it.