Human-social choices and decisions with application to sustainability transition
Global change is recognized by most as real and significant, yet there is a growing discrepancy between actual human action from individual to social levels, and the actions that would be needed for effective mitigation. It is only recently that psychological reasons for this discrepancy are being understood. Moreover, general ideas on how to overcome the psychological obstacles to enhance action and engagement are also becoming more apparent.
The goal of this project is to formulate a quantitative and dynamic framework for human-social behavior that unifies relevant known quantitative social-psychological behavior theories.The framework is to be used for exploring different factors that affect human–social action and engagement for mitigating global change in particular related to energy use
The approach integrates the following theories: i) social networks, opinion and consensus building; ii) conditioning and associative learning, and iii) prospect theory on framing and risk-taking. As has been thoroughly discussed and documented in e.g., Per Espen Stoknes (”What We Think About When We (Try Not to) Think About Global Warming,” 2017) and more recently in mass media, e.g.,http://www.bbc.com/future/story/20190304-human-evolution-means-we-can-tackle-climate-change the narrative or framing are key factors influencing human decisions. Moreover, the social networks in the modern society affect individual decision more or less, and are one means of enhancing action and engagement. Thus providing a quantitative framework that links social networks influences and opinion building, with biases related to risk-taking and framing as summarized by prospect theory are key factors for a more realistic description of human-social behavior, here set in the context of energy use and global change mitigation.
Human-social behaviour, global change mitigation, social networks and consensus building, conditioning and learning, prospect theory
Work in progress. Basic results at https://ieeexplore.ieee.org/abstract/document/8062680 and at https://arxiv.org/abs/1809.08474v1
Vladimir Cvetkovic, SEED, School of Architecture and the Built Environment (ABE), KTH.
Other project members
Karl-Henrik Johansson, School of Electrical Engineering and Computer Science.