skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: PowerPlay: Exploring decision making behaviors in energyefficiency markets

Abstract

Computer models are widely used to analyze decisions aboutenergy efficiency improvements in the residential and commercial sectors.Few models exist that can actually be run interactively by decisionmakers to play out alternative future scenarios. None are available thatinteractively capture the dynamics, subtleties and complexities ofinterdependent decisions by utilities, households and firms in anever-changing technological and economic environment. This paper presentsthe features and experiences of PowerPlay, a computer-facilitated gamewhich fills that gap and does more: it is a game to be played by at leasta dozen player groups who interact with each other, make deals (or breakthem), plan for the future and revise decisions. The computer modelfunctions like a game board to trace actions and offer choices. Theobserved behaviors can be analyzed to advance understanding of investmentstrategies and consumer choices; to generate experimentally-based data onenergy efficiency changes; and to provide the basis for analyses that cansubstantiate or complement historical, time-series driven specificationsof energy models.

Authors:
; ; ;
Publication Date:
Research Org.:
COLLABORATION - University ofMaryland
OSTI Identifier:
929493
Report Number(s):
LBNL-63381
Journal ID: ISSN 0040-1625; TFSCB3; R&D Project: E50901; TRN: US200813%%215
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Journal Article
Resource Relation:
Journal Name: Technological Forecasting&Social Change; Journal Volume: 74; Related Information: Journal Publication Date: 2007
Country of Publication:
United States
Language:
English
Subject:
29; COMMERCIAL SECTOR; COMPUTERS; DECISION MAKING; ECONOMICS; ENERGY EFFICIENCY; ENERGY MODELS; HOUSEHOLDS; SPECIFICATIONS

Citation Formats

Ruth, Matthias, Bernier, Clark, Meier, Alan, and Laitner, John. PowerPlay: Exploring decision making behaviors in energyefficiency markets. United States: N. p., 2007. Web. doi:10.1016/j.techfore.2006.05.012.
Ruth, Matthias, Bernier, Clark, Meier, Alan, & Laitner, John. PowerPlay: Exploring decision making behaviors in energyefficiency markets. United States. doi:10.1016/j.techfore.2006.05.012.
Ruth, Matthias, Bernier, Clark, Meier, Alan, and Laitner, John. Mon . "PowerPlay: Exploring decision making behaviors in energyefficiency markets". United States. doi:10.1016/j.techfore.2006.05.012.
@article{osti_929493,
title = {PowerPlay: Exploring decision making behaviors in energyefficiency markets},
author = {Ruth, Matthias and Bernier, Clark and Meier, Alan and Laitner, John},
abstractNote = {Computer models are widely used to analyze decisions aboutenergy efficiency improvements in the residential and commercial sectors.Few models exist that can actually be run interactively by decisionmakers to play out alternative future scenarios. None are available thatinteractively capture the dynamics, subtleties and complexities ofinterdependent decisions by utilities, households and firms in anever-changing technological and economic environment. This paper presentsthe features and experiences of PowerPlay, a computer-facilitated gamewhich fills that gap and does more: it is a game to be played by at leasta dozen player groups who interact with each other, make deals (or breakthem), plan for the future and revise decisions. The computer modelfunctions like a game board to trace actions and offer choices. Theobserved behaviors can be analyzed to advance understanding of investmentstrategies and consumer choices; to generate experimentally-based data onenergy efficiency changes; and to provide the basis for analyses that cansubstantiate or complement historical, time-series driven specificationsof energy models.},
doi = {10.1016/j.techfore.2006.05.012},
journal = {Technological Forecasting&Social Change},
number = ,
volume = 74,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}