NeuroManagement was first proposed in 2006 by Professor Qingguo Ma from Zhejiang University in China. In the past ten years, neuroManagement has emerged as an interdisciplinary field studying human behavior in economic and managerial settings using cognitive neuroscience approaches. NeuroManagement researchers bring together very different fields of research, such as neuroscience, psychology, economy, and sociology, among others, to understand the socioeconomic and environmental factors that drive managerial decisions.
New advances in intelligent computing technologies, such as machine learning and brain-like simulations, are used to observe and study the neural mechanisms behind management decisions. They provide data that can be used to establish the neural models to describe human psychology and predict behavioral outcomes under different management scenarios. NeuroManagement can also provide important knowledge for other types of intelligent computation, such as affective computing, cognitive computing, and online behavior data mining, etc., and help to reduce the computational cost as well as to improve the computational efficiency and accuracy of the current techniques.
Due to the diversity and complexity of management scenarios, novel theories, methodologies, and technologies will improve our understanding of neuroManagement and, as a consequence, will improve the intelligent computing design.
This Research Topic aims to publish cutting-edge research on intelligent computing systems for neuroManagement from a multidisciplinary perspective. In order to construct a systematic paradigm for synthesizing research outcomes, we propose the PIMT framework to describe research objectives into the four layers: L1-new phenomena and features(P), L2-influence factors(I), L3-systematic mechanism(M), and L4-new theory and methods(T). The above framework can help reduce repetitive research work, gather results at different levels, and build new theories and methods by the ascending process from L1 to L4.
The scope of this topic includes neural studies and intelligent computing for management. Authors are encouraged to submit original research articles or reviews addressing the following themes:
• Recent advances in neuroManagement
• Neuroscience of managerial behaviors
• Socioeconomic factors influencing management, from a neuroscience perspective
• Intelligent computing on neural experimental data
• Affective and cognitive computing guiding managerial decision-making
• Intelligent simulation of neural mechanisms to explain neuroManagement
• Managerial applications of intelligent computing
NeuroManagement was first proposed in 2006 by Professor Qingguo Ma from Zhejiang University in China. In the past ten years, neuroManagement has emerged as an interdisciplinary field studying human behavior in economic and managerial settings using cognitive neuroscience approaches. NeuroManagement researchers bring together very different fields of research, such as neuroscience, psychology, economy, and sociology, among others, to understand the socioeconomic and environmental factors that drive managerial decisions.
New advances in intelligent computing technologies, such as machine learning and brain-like simulations, are used to observe and study the neural mechanisms behind management decisions. They provide data that can be used to establish the neural models to describe human psychology and predict behavioral outcomes under different management scenarios. NeuroManagement can also provide important knowledge for other types of intelligent computation, such as affective computing, cognitive computing, and online behavior data mining, etc., and help to reduce the computational cost as well as to improve the computational efficiency and accuracy of the current techniques.
Due to the diversity and complexity of management scenarios, novel theories, methodologies, and technologies will improve our understanding of neuroManagement and, as a consequence, will improve the intelligent computing design.
This Research Topic aims to publish cutting-edge research on intelligent computing systems for neuroManagement from a multidisciplinary perspective. In order to construct a systematic paradigm for synthesizing research outcomes, we propose the PIMT framework to describe research objectives into the four layers: L1-new phenomena and features(P), L2-influence factors(I), L3-systematic mechanism(M), and L4-new theory and methods(T). The above framework can help reduce repetitive research work, gather results at different levels, and build new theories and methods by the ascending process from L1 to L4.
The scope of this topic includes neural studies and intelligent computing for management. Authors are encouraged to submit original research articles or reviews addressing the following themes:
• Recent advances in neuroManagement
• Neuroscience of managerial behaviors
• Socioeconomic factors influencing management, from a neuroscience perspective
• Intelligent computing on neural experimental data
• Affective and cognitive computing guiding managerial decision-making
• Intelligent simulation of neural mechanisms to explain neuroManagement
• Managerial applications of intelligent computing
