The ALPS project—Alternative Pathways to sustainable development and climate Stabilization— is a collaboration between TNT, the Energy Program, and the Research Institute for Innovative Technologies for the Earth (RITE), Japan.
ALPS aims to foster innovative methodological concepts and translate them into improved models and better informed policy choices. The Project represents the cumulative effects of a long-term mutual commitment to pushing the research frontier under a stable, long-term funding strategy. The TNT and ENE Programs are grateful for the continuous interest, support and most valuable input of our RITE colleagues to this research.
Significant research progress was achieved in 2014. Prototype model formulations were consolidated by ENE’s Volker Krey into a novel multi-regional modeling framework; new and improved model parametrizations were also prepared based on extensive meta-analysis of expanding data and a comprehensive literature review and meta-analysis by Charlie Wilson and Arnulf Grubler. As part of the ALPS research project TNT was also able to update its unique data set underlying the research into the Scaling Dynamics of Energy Technologies (SD-ET).
An entirely new research field was also opened within the ALPS project in 2014: the improved modeling representation of decentralized consumer decisions. Unlike discrete, large-scale technology adoption decisions made by energy supply firms, energy-end use technologies and consumers “tick” quite differently. Millions of adoption decisions are made under imperfect information, vastly heterogeneous consumer preferences, and under presence of social network (or so-called peer) effects, which to date have eluded representation in IAMs.
To improve the state of the art in this field, a novel agent-based model of decentralized consumer technology adoption decisions was developed by TNT researcher Tieju Ma in collaboration with Arnulf Grubler . An agent-based modeling strategy is particularly salient, as agent interactions are at the core of social network, or peer effects, to which companies, policymakers and energy and climate modelers have recently become increasingly attentive. Following the TNT research tradition of rapid prototyping of new modeling formulations, illustrative simulations were performed with the new model. Preliminary results suggest that the peer effect, while real, might be less significant in a transition to low carbon technologies on the consumer side, compared to traditional targets of centralized technology policy, such as technological performance and prices or technology standards.
 Chen H, Ma T (2014). Technology adoption with limited foresight and uncertain technological learning. European Journal of Operational Research, 239(1):266-275
Last edited: 01 April 2015
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