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This book offers a comprehensive exploration of the transformative trajectory undertaken by Chinese domestic enterprises, with a particular focus on Geely Automobile. Comprising five chapters and totaling 13 sections, the study delves into Geely's remarkable progression from a state of catch-up to surpassing established competitors. The initial chapter chronicles Geely's entry into the automotive industry amidst resource and technological scarcity, shedding light on the strategies employed to achieve breakthroughs during the nascent stages. The subsequent section elucidates Geely's transition from a late entrant to a prominent player in the global automotive market, facilitated by innovative practices across organizational, technological, talent-driven, quality-oriented, and cultural dimensions. The third chapter examines Geely's successful foray into globalization, offering a comprehensive analysis of its non-linear growth trajectory, overseas mergers and acquisitions, and strategic expansion efforts. The fourth part explores Geely's approach to embracing uncertainty and navigating cyclical challenges in the automotive industry, seeking determinative opportunities for future growth. Finally, the concluding chapter draws insights from Geely's non-linear growth and advances the "C theory," an enriched local innovation management framework grounded in China's unique developmental context.
A personal growth roadmap guiding you into the future of relationships in work, life, play, and giving Curve Benders is a personal growth roadmap. It will guide you through the complicated intersection of work, life, play, and giving. Countless new forces will shape the future, so the strategic relationships we form in these areas of life are, of necessity, changing. This book will show you how to move into the future and dramatically alter your growth trajectory in both its direction and ultimate destination. David Nour, the author of Relationship Economics and a top thought leader on business relationships, has identified 15 forces that will heavily influence what we do and how and where we engage our current and prospective relationships to create value and make a difference in the lives of others. This book aims to provide you with a step-by-step guide for personal, professional, and organizational growth. The author highlights how certain relationships enable a non-linear growth trajectory. These relationships, in addition to augmenting what we can accomplish, often shape who we become. These relationships are “curve benders,” and this book will show you who and where they are, how to find and engage them, and, equally valuable, how you can become a curve bender to impact the lives and livelihoods of others profoundly. Gain insight into the value of your current strategic relationships and how they help you achieve your work, life, and giving goals Reconceptualize relationships to identify the people with the power, not only to help you achieve but to change who you become Learn how to become a “curve bender” who makes an outsized impact in the lives of others Become better at finding and engaging people, navigating the 15 forces that are reshaping our world This book is about strategic relationship planning, personal growth, and, ultimately, about you. Read Curve Benders to launch yourself into your best future.
Optimal growth theory studies the problem of efficient resource allocation over time, a fundamental concern of economic research. Since the 1970s, the techniques of nonlinear dynamical systems have become a vital tool in optimal growth theory, illuminating dynamics and demonstrating the possibility of endogenous economic fluctuations. Kazuo Nishimura's seminal contributions on business cycles, chaotic equilibria and indeterminacy have been central to this development, transforming our understanding of economic growth, cycles, and the relationship between them. The subjects of Kazuo's analysis remain of fundamental importance to modern economic theory. This book collects his major contributions in a single volume. Kazuo Nishimura has been recognized for his contributions to economic theory on many occasions, being elected fellow of the Econometric Society and serving as an editor of several major journals. Chapter “Introduction” is available open access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License via link.springer.com.
This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.
Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.
This interdisciplinary book argues that the economy has an underlying non-linear structure and that business cycles are endogenous, which allows a greater explanatory power with respect to the traditional assumption that dynamics are stochastic and shocks are exogenous. The first part of this work is formal-methodological and provides the mathematical background needed for the remainder, while the second part presents the view that signal processing involves construction and deconstruction of information and that the efficacy of this process can be measured. The third part focuses on economics and provides the related background and literature on economic dynamics and the fourth part is devoted to new perspectives in understanding nonlinearities in economic dynamics: growth and cycles. By pursuing this approach, the book seeks to (1) determine whether, and if so where, common features exist, (2) discover some hidden features of economic dynamics, and (3) highlight specific indicators of structural changes in time series. Accordingly, it is a must read for everyone interested in a better understanding of economic dynamics, business cycles, econometrics and complex systems, as well as non-linear dynamics and chaos theory.
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of Nonlinear Regression "A very good book and an important one in that it is likely to become a standard reference for all interested in nonlinear regression; and I would imagine that any statistician concerned with nonlinear regression would want a copy on his shelves." –The Statistician "Nonlinear Regression also includes a reference list of over 700 entries. The compilation of this material and cross-referencing of it is one of the most valuable aspects of the book. Nonlinear Regression can provide the researcher unfamiliar with a particular specialty area of nonlinear regression an introduction to that area of nonlinear regression and access to the appropriate references . . . Nonlinear Regression provides by far the broadest discussion of nonlinear regression models currently available and will be a valuable addition to the library of anyone interested in understanding and using such models including the statistical researcher." –Mathematical Reviews
- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.
This book collects recent advances in the field of nonlinear dynamics in biological systems. Focusing on medical applications as well as more fundamental questions in biochemistry, it presents recent findings in areas such as control in chemically driven reaction-diffusion systems, electrical wave propagation through heart tissue, neural network growth, chiral symmetry breaking in polymers and mechanochemical pattern formation in the cytoplasm, particularly in the context of cardiac cells. It is a compilation of works, including contributions from international scientists who attended the “2nd BCAM Workshop on Nonlinear Dynamics in Biological Systems,” held at the Basque Center for Applied Mathematics, Bilbao in September 2016. Embracing diverse disciplines and using multidisciplinary approaches – including theoretical concepts, simulations and experiments – these contributions highlight the nonlinear nature of biological systems in order to be able to reproduce their complex behavior. Edited by the conference organizers and featuring results that represent recent findings and not necessarily those presented at the conference, the book appeals to applied mathematicians, biophysicists and computational biologists.
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.