Application of Bass Diffusion Theory to Simulate the Impact of Feedback and Word of Mouth on Occupants’ Behavior in Commercial Buildings: An Agent-Based Approach
Publication: Journal of Architectural Engineering
Volume 22, Issue 4
Abstract
In their assumption of a static nature for occupants’ energy-use characteristics, the conventional energy-simulation tools have failed to bring about a reliable prediction regarding changes in occupants’ behavior and the resulting impact on energy consumption. Thus, this study investigated an agent-based approach to simulating the diffusion of energy-saving policies among the occupants and the related impact on energy consumption and emission production of commercial buildings. Two different strategies were implemented in the agent-based environment to track the changes in occupants’ behavioral patterns and the consequential energy conservation by providing informational feedback to the occupants. Compared to the results obtained from energy-simulation software, the first model showed a 13% variation/reduction in building energy consumption from Year 1 to Year 3; the second model, inspired by Bass diffusion theory, showed 20% variation/reduction in the same period. The results indicate that the adoption of energy-saving policies or positive changes in occupants’ behavioral patterns of energy use may follow Bass diffusion theory in simulation of product adoption. Also, the results of both agent-based models show that there is considerable potential in energy preservation and emission reduction by providing feedback to the occupants. However, the resulting word-of-mouth effect among the occupants had a stronger influence on persuading the occupants to save energy.
Get full access to this article
View all available purchase options and get full access to this article.
References
Andersen, R. V., Toftum, J., Andersen, K. K., and Olesen, B. W. (2009). “Survey of occupant behaviour and control of indoor environment in Danish dwellings.” Energy Build., 41(1), 11–16.
AnyLogic [Computer software]. AnyLogic Company, Chicago.
Azar, E., and Menassa, C. (2012). “Agent-based modeling of occupants and their impact on energy use in commercial buildings.” J. Comput. Civ. Eng., 506–518.
Bass, F. M. (1969). “A new product growth for model consumer durables.” Manage. Sci., 15(5), 215–227.
eGRID. (2015). Emissions & generation resource integrated database. Environmental Protection Agency, Washington, DC.
EIA (Energy Information Administration). (2010). “Annual energy review.” DOE/EIA–0384, U.S. Dept. of Energy, Washington, DC.
eQuest 3.63 [Computer software]. U.S. Dept. of Energy, Washington, DC.
Inyim, P., and Zhu, Y. (2014). “Application of Monte Carlo simulation and optimization to multi-objective analysis of sustainable building designs.” Proc., Int. Conf. on Computing in Civil and Building Engineering, ASCE, Reston, VA.
Mahajan, V., Muller, E., and Bass, F. M. (1995). “Diffusion of new products: Empirical generalizations and managerial uses.” Market. Sci., 14(3), G79–G88.
Mahdavi, A., Mohammadi, A., Kabir, E., and Lambeva, L. (2008). “Occupants' operation of lighting and shading systems in office buildings.” J. Build. Perform. Simul., 1(1), 57–65.
Mahdavi, A., and Pröglhöf, C. (2009). “Toward empirically-based models of people’s presence and actions in buildings.” Proc., Building Simulation, International Building Performance Simulation Association, 〈http://www.ibpsa.org/proceedings/BS2009/BS09_0537_544.pdf〉.
Masoso, O. T., and Grobler, L. J. (2010). “The dark side of occupants’ behaviour on building energy use.” Energy Build., 42(2), 173–177.
Meier, A. (2006). “Operating buildings during temporary electricity shortages.” Energy Build., 38(11), 1296–1301.
Ouyang, J., and Hokao, K. (2009). “Energy-saving potential by improving occupants’ behavior in urban residential sector in Hangzhou City, China.” Energy Build., 41(7), 711–720.
Peschiera, G., Taylor, J. E., and Siegel, J. A. (2010). “Response–relapse patterns of building occupant electricity consumption following exposure to personal, contextualized and occupant peer network utilization data.” Energy Build., 42(8), 1329–1336.
Raaij, V., Fred, W., and Verhallen, T. M. M. (1983). “A behavioral model of residential energy use.” J. Econ. Psych., 3(1), 39–63.
Seryak, J., and Kissock, K. (2003). “Occupancy and behavioral effects on residential energy use.” Proc., Solar Conference, American Solar Energy Society, Boulder, CO.
Soebarto, V. I., and Williamson, T. J. (2001). “Multi-criteria assessment of building performance: Theory and implementation.” Build. Environ., 36(6), 681–690.
Srinivasan, V., and Mason, C. H. (1986). “Technical note: Nonlinear least squares estimation of new product diffusion models.” Market. Sci., 5(2), 169–178.
Staats, H., Leeuwen, E. V., and Wit, A. (2000). “A longitudinal study of informational interventions to save energy in an office building.” J. Appl. Behav. Anal., 33(1), 101–104.
Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world, McGraw-Hill, Boston.
Tianzhen, H., and Hung-Wen, L. (2013). “Occupant behavior: Impact on energy use of private offices.” Proc., ASim 2012, International Building Performance Simulation Association. 〈http://www.ibpsa.org/proceedings/asim2012/0050.pdf〉.
Wang, W., Rivard, H., and Zmeureanu, R. (2005). “A Framework for simulation-based optimization with application to green building design.” Proc., Computing in Civil Engineering, ASCE, Reston, VA, 1–8.
Yudelson, J. (2010). Greening existing buildings, Island Press, Washington, DC.
Zhang, T., Siebers, P. O., and Aickelin, U. (2011). “Modelling electricity consumption in office buildings: An agent based approach.” Energy Build., 43(10), 2882–2892.
Information & Authors
Information
Published In
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Aug 10, 2015
Accepted: Apr 26, 2016
Published online: Jun 1, 2016
Discussion open until: Nov 1, 2016
Published in print: Dec 1, 2016
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.