Case Studies
Sustainable smart cities are a globally shared vision of urban-regional development intended to reduce urban carbon footprints, by taking full advantage of evolving digital technology. In spite of significant technological challenges of integrating physical-cyber systems to reduce resource use while maintaining or improving functionality, the key challenge is harmonizing technical design with human-social behavior and choices. The focus of this project is to improve the quantitative description and predictability of human choices that are relevant for sustainable development in particular related to smart cities. Our basic conceptualization distinguishes three scales: meso scale (individuals making decisions that they view is in their best personal interest; this is the scale considered e.g. in behavioral economics), micro scale (neuro-cognitive processes with a number of internal constraints that include material, emotional and social/moral valuations), macro scale (interactions between individuals within social networks that exist on multiple levels).
The research in HiSS is conducted within six case studies, [a] to [f], whose topical relationship is illustrated in the figure.
A general objective of the project is to link dominant mechanisms of decision-making and choice between the micro, meso and macro scales that are most relevant for advancing the sustainability agenda in smart cities. The specific objectives are related to theoretical and experimental studies of different aspects of decision-making at micro, meso and macro scales, that help answer the following questions:
Which human choice/decision models are suitable for understanding decision processes, policy making, etc., in the sustainable smart city context?
Case Study [a] is central to this question, which also relates to Case Studies [b] and [c].
What aspects of human choices and decisions in the present context can be related to and explained by neuro-cognitive processes?
Case Study [d] is central to this question and Case Study [e] offers some extra insights.
How do social network interactions (e.g. collaboration and competition) affect human choices from smart homes to smart cities?
This question will mainly be explored in Case Study [b], with experimental components discussed in Case Studies [c] and [f].
Vladimir Cvetkovic, Angela Fontan, Cecilia Katzeff, Marco Molinari, Jeremy Pitt, and Stacy Vallis
The goal of this case study is to examine how digital tools are being developed and applied at various scales to produce new insights about urban dynamics.
Angela Fontan, Vladimir Cvetkovic, Karl H. Johansson, Mikael Skoglund
The goal of this case study is to examine cities as social networks, how human-social choices define these networks and how digital tools applied at various levels shape urban interactions and change.
Mahsa Farjadnia, Karl H. Johansson, Hedvig Kjellström, Marco Molinari, and Ruibo Tu
The goal of this case study is to apply to a real building scenario automated approaches to isolate correlations among large set of sensors and showcase the possibility to find causality.
Pawel Herman, Hedvig Kjellström, Vladimir Cvetkovic, and Ricky Molen
The aim of this case study is to gain better understanding how decision making and its behavioral consequences at a population level can be modelled as an emergent effect of different interactions between individuals with their own goals, motivations and experiences.
Pawel Herman, Arvind Kumar, Movitz Lenninger, and Mikael Skoglund
The aim of this case study is to gain novel insights into computational principles of representing and processing neural information in the brain. Despite a relatively large body of experimental data, there is no well-established theory how populations of neural cells in the brain reliably encode information about complex environmental stimuli and how neural network circuits are optimized to make this information behaviorally relevant.
Cecilia Katzeff, Stacy Ann Vallis, Joe Llewellyn, Marco Molinari, Loove Broms, Karin Ehrnberger
The aim of this case study is to analyze the role of households' and their practices in relation to digitalization of the energy system and in the transition to a sustainable society. As the development of the energy system is dominated by technology development, social aspects of the energy system tend to fall into the background. With its focus on citizens, communities, practices and design, this case study will bring social aspects of the sustainable smart city to the foreground. Through the use of research methods from behavior science and design research, the case study will collect empirical data from existing real world city environments as well as from experimental environments.