Agent-based simulation of policy induced diffusion of smart meters

Martin Rixen and Jürgen Weigand

Technological Forecasting and Social Change, 2014, vol. 85, issue C, 153-167

Abstract: How can policy makers influence the path of innovation diffusion effectively and efficiently? We tackle this question in an agent-based model that integrates demand and supply for Smart Meters. Consumers adopt due to awareness and attainment of price thresholds. Suppliers act strategically upon Cournot competition. We add different policies to the simulation and analyze effects on speed and level of Smart Meter adoption. The tested interventions are: Market liberalization, information policies, and monetary grants. From our results we conclude that “One size does not fit all”. The best-suited intervention depends on the regulator's objective. Information policies speed-up adoption, but are ineffective in monopolies and if the timing is late. Monetary grants boost speed and level, but policy costs as well. Market structure is critical: Interventions in closed markets primarily favor the monopolist, while intensifying competition raises effectiveness and efficiency. Regulators may combine policies to gain synergies and utilize strategic decision making of suppliers.

Keywords: Induced diffusion; Innovation adoption; Agent-based modeling; Smart Metering; Competitive dynamics (search for similar items in EconPapers)
JEL-codes: C63 D43 O33 O38 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162513001790
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:85:y:2014:i:c:p:153-167

DOI: 10.1016/j.techfore.2013.08.011

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().