This book explores the evolving dynamics of market competition in an age defined by rapid technological advancements and globalization. Drawing from interdisciplinary research across evolutionary theory, economics, computer science, and biology, it provides strategies for businesses, both large and small, to thrive in fiercely competitive environments. This book will interest scholars, businesspeople and economists.
Chapter 1: The Entrenchment of Traditional Industries and the
Winner-Takes-All Phenomenon.
Chapter 2: The Dark Horse of New Tracks and the
Life-Death Cycle.
Chapter 3: Dont Put All Your Eggs in One Basket vs. Going
All-In on a Single Venture.
Chapter 4: Top-Down Management vs. Bottom-Up
Innovation.
Chapter 5: Efficient Traditional Industries vs. Inefficient
Emerging Industries.
Chapter 6: The Contraction of Primary and Secondary
Industries vs. The Expansion of the Tertiary Industry.
Chapter 7: Moore's
Law and Endless Desires.
Chapter 8: The Moore's Law in the Field of
Artificial Intelligence.
Chapter 9: Lessons from the Extinction of
Dinosaurs.
Chapter 10: The Boundaries of AI Capabilities.
Chapter 11: The
Evolution from Mental Labor Today to Physical Labor Tomorrow.
Chapter 12:
One Step Ahead is a Pioneer, Two Steps Ahead is a Martyr.
Chapter 13: A
Makeshift Troupe Performing a Grand Opera: The Startup Path of Emerging
Companies.
Chapter 14: Company Strategy Choices: Rapid Expansion vs. Quality
Over Quantity.
Chapter 15: Re-thinking the Theory of Evolution.
Dr. Xinwei Cao is presently a full professor at the School of Business, Jiangnan University, China, with a distinguished interdisciplinary background in both management and computing. She earned her PhD through a joint program between the School of Management at Fudan University and the School of Business at the Chinese University of Hong Kong. Over the years, Dr. Cao has actively collaborated with experts in computing and artificial intelligence to seamlessly integrate AI into management practices.
Dr. Cao has published over 50 peer-reviewed scientific papers, reflecting her significant contributions to academia. In addition to her academic work, she serves as a consultant and an independent director on audit committees for listed companies. These practical roles offer her valuable insights that enrich the content of this book.
Her research primarily focuses on applying AI and computational tools to address real-world challenges in finance, economics, and management. She has pioneered the use of machine learning in accounting and auditing, notably advancing the detection of financial fraud. Furthermore, she has utilized optimization theory to improve portfolio management for high frequency trading and developed early-warning systems for management issues based on statistical analysis. Dr. Caos interdisciplinary expertise enables her to approach modern entrepreneurial management with a comprehensive and insightful perspective.
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