Systems Thinking and Complexity Science and the Relevance of Big Data Analytics, Intelligence Functions, and Simulation Models

  • Simon Elias BibriEmail author
Part of the The Urban Book Series book series (UBS)


Smart sustainable cities are complex systems par excellence. This is manifested in a variety of ways to think of and define the underlying many subsystems as connected and joined together by a web of relationships that interact to produce collective behavior that cannot easily be explained in terms of interactions between the individual constituent elements. As such, they involve special conundrums, intractable problems, and complex challenges pertaining to sustainability and urbanization. It follows that to deal with such systems requires newfangled ways founded on more innovative solutions and sophisticated methods with respect to how cities can be monitored, understood, managed, planned, and developed. This necessitates leveraging the advance and prevalence of ICT in the transition toward the needed sustainable urban development in an increasingly urbanized and computerized world. Importantly, smart sustainable cities require advanced thinking approaches to be well understood and illuminated so as to enable more effective actions necessary for enhancing their functioning and adaptation in ways that guide their development toward sustainability. The aim of this chapter is twofold. Grounded in systems thinking and complexity science as theoretic approaches, this chapter endeavors to systematically explore the key underlying structures, behavioral patterns, conditions, relationships, and interactions pertaining to smart sustainable cities as complex systems, and to elucidate the related principles in terms of methods, mechanisms, and goals. The intent of offering the knowledge to describe and analyze such systems accordingly is to surface noteworthy relationships as well as their implications for sustainability so as to provoke thought, foster deeper understanding, and create fertile insights, with the primary purpose of making visible possible places for actions that improve the contribution of smart sustainable cities to the goals of sustainable development. This can be accomplished by means of devising powerful urban intelligence functions and robust urban simulation models for strategic decision-making based on big data analytics in conjunction with urban design concepts and planning principles of sustainability. Accordingly, this chapter also discusses the potential of big data analytics and related urban intelligence functions and urban simulation models for, and the role of urban design in, catalyzing and advancing the strategic process of sustainable development by proposing innovative approaches and solutions for monitoring, managing, planning, and designing smart sustainable cities of the future. The main argument is that the systems thinking and complexity science are integral to the understanding of smart sustainable cities, which is a moving target in that they are becoming more complex through the very technologies being used to understand them. Moreover, advanced ICT is founded on the application of complexity theory to urban problems in terms of tracking the changing dynamics, disentangling the intractable problems, and tackling the challenges pertaining to urban systems, which are in and of themselves becoming ever more complex. As high-performance computers have become an indispensable source of information, complex systems cannot be understood and studied without the use of computers and big data analytics.


Smart sustainable cities Systems thinking Systems theory Complexity science Big data analytics Urban intelligence functions Urban simulation models Intractable problems Complex systems Urban sustainability 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer and Information Science, Department of Urban Design and PlanningNorwegian University of Science and TechnologyTrondheimNorway

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