This is an exciting new edition of a core textbook that explores innovation management from a global perspective. Innovation management is increasingly significant, both as an academic discipline and as an integral part of the way businesses seek to change and grow. However the key factors behind successful innovation and the process by which innovation is turned into profit in the global arena remain largely undefined. The new edition provides a unique answer to these questions and offers a step-by-step guide to innovation strategy development, taking into account the global context in which businesses today operate. Written by a highly experienced instructor, this is an ideal companion for undergraduate students of innovation as well as postgraduate and MBA students taking modules with an innovation component. New to this Edition: - Completely rewritten and restructured to explore in more depth how innovative ideas are identified and strategized in an increasingly globalized world - Fully updated and extended case studies on world-leading companies - Increased attention to commercialized innovation, including factors such as intellectual property laws, technology acceleration and the competition for venture capital and finance - Coverage of new topics such as open innovation and service innovation - Expanded coverage of the tools and methods needed to understand financial gain and risk
This new edition surveys the full range of available structural equation modeling (SEM) methodologies. The book has been updated throughout to reflect the arrival of new software packages, which have made analysis much easier than in the past. Applications in a broad range of disciplines are discussed, particularly in the social sciences where many key concepts are not directly observable. This book presents SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that are growing in importance. SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained and methods are presented for extending their power, including guidelines for data preparation, sample size calculation and the special treatment of Likert scale data. Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.
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