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Modern business management

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modern business managementby Xinwei Cao.
Author:	Cao, Xinwei.
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xvi, 150 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Management.
Online resource:	https://doi.org/10.1007/978-981-96-0594-1
ISBN:	9789819605941$q(electronic bk.)

Modern business management
Cao, Xinwei.

Modern business management[electronic resource] /by Xinwei Cao. - Singapore :Springer Nature Singapore :2025. - xvi, 150 p. :ill. (some col.), digital ;24 cm.

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: Don't 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.

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. 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. Cao's interdisciplinary expertise enables her to approach modern entrepreneurial management with a comprehensive and insightful perspective.

ISBN: 9789819605941$q(electronic bk.)

Standard No.: 10.1007/978-981-96-0594-1doiSubjects--Topical Terms:

180005
Management.

LC Class. No.: HD31.2

Dewey Class. No.: 658

Modern business management
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505 0 $a 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: Don't 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.
520 $a 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. 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. Cao's interdisciplinary expertise enables her to approach modern entrepreneurial management with a comprehensive and insightful perspective.
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