Daniel Czamanski – författare
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Chapters delve into specific applications of big data and AI including mobility, tourism, and land use, drawing on case studies from diverse urban environments across Europe and North America. Expert authors evaluate future opportunities for leveraging these technologies, addressing the integration of machine learning into spatial econometric models, the use of self-organizing maps to study demographic shifts, and novel approaches to simulating contagion patterns during pandemics. Ultimately, the Handbook emphasizes the potential of AI to contribute to social good.
Academics and students in human geography, regional and urban studies, economics, sociology, and management will benefit from this multidisciplinary and comprehensive Handbook. Combining theoretical insights with practical applications, it is also a valuable resource for policymakers and practitioners interested in the ongoing digital transformation of urban spaces.
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With the help of leading experts worldwide, the Handbook examines how and to what extent entropic and non-entropic forces and processes in complex spatial socio-economic systems shape and are shaped by their structure and dynamics. Moreover, considering current concerns that big data and related data-driven methods may signal an end to theory, this Handbook is intended to investigate the potential and possibilities for complexity science to engage, revitalize, and advance theory in spatial economics. Overall, this Handbook reaches beyond qualitative generalizations, contributing to the identification of fundamental structural and dynamic properties of the complex space-economy.
Drawing upon diverse foundations and perspectives, the Handbook on Entropy, Complexity and Spatial Dynamics: A Rebirth of Theory? will be an essential resource for researchers and students of many fields and disciplines, including economics, urban planning and geography, regional science, information science, physics, and biology.