The ALPS research collaboration is a joint effort between the Transitions to New Technologies (TNT) Program, the Energy Program (ENE), and colleagues at the Research Institute for Innovative Technologies for the Earth, Japan. Significant progress was achieved by ALPS in 2015, with a new research focus on linking technological change (diffusion) processes to social behavioral variables. Using a multiple-methods approach, research explored the impacts of two alternative, but complementary, ways of representing social and behavioral heterogeneity: discrete choice modeling (explored by ENE’s David McCollum), and agent-based modeling (explored by TNT’s Tieju Ma and Arnulf Grubler).
These two approaches promise to significantly improve the representation of social and behavioral heterogeneity in IAMs, which is currently extremely coarse. For instance, new agent-based model simulations have revealed that from all social actor interactions, the knowledge feedbacks between technology adopters (users) and technology producers (firms) assume a particularly significant role. Conversely, traditional social network and peer effects exercise a much smaller role in the rapid diffusion of advanced, environmentally friendly technologies. This key importance of knowledge feedbacks that arise endogenously (even when referred to in traditional economics simply as a knowledge externality) echoes earlier findings from the ALPS project on international knowledge spillovers . Knowledge flows were also a novel aspect in the research on innovation metrics under an innovation systems approach conducted by Rui Hu, who worked in TNT as a participant in the IIASA Young Scientist Summer Program in 2015.
 Leibowicz BD, Krey V & Grubler A (2016). Representing spatial technology diffusion in an energy system optimization model. Technological Forecasting and Social Change, 103:350-363.
Energy Program (ENE)
Research Institute for Innovative Technologies for the Earth, Japan
Last edited: 23 March 2016
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