Intelligent technologies are increasingly facilitating
sustainable water management strategies in Australia. While this
innovation can present clear cost benefits to utilities through
immediate leak detection and deference of capital costs, the impact of
this technology on households is less distinct. By offering real-time
engagement and detailed end-use consumption breakdowns, there is
significant potential for demand reduction as a behavioural response
to increased information. Despite this potential, passive
implementation without well-planned residential engagement
strategies is likely to result in a lost opportunity. This paper begins
this research process by exploring the effect of smart water meters
through the lens of three behaviour change theories. The Theory of
Planned Behaviour (TPB), Belief Revision theory (BR) and Practice
Theory emphasise different variables that can potentially influence
and predict household water engagements. In acknowledging the
strengths of each theory, the nuances and complexity of household
water engagement can be recognised which can contribute to
effective planning for residential smart meter engagement strategies.
<p>[1] D.P. Giurco, S.B. White, S.B. and R. Stewart, “Smart metering and
water end-use data: Conservation benefits and privacy risks”, Water,
vol. 2, no. 3, pp.461-467, 2010.
[2] I. Azjen, “The theory of planned behavior”,Organisational Behaviour
and Human Decision Processes, vol. 50, no. 2, pp.179-211, 1991.
[3] G. Godin and G. Kok, “The theory of planned behavior: A review of its
applications to health-related behaviors”, American Journal of Health
Promotion, vol. 11, no. 2, pp.87-98, 1996.
[4] P. Sheeran, M. Conner. and P. Norman, “Can the Theory of Planned
Behavior explain patterns of health behavior change? Health
Psychology, vol. 20, no. 1, pp.12-19, 2001.
[5] P. Norman, M. Conner and R. Bell, “The theory of planned behavior and
smoking cessation” Health Psychology, vol. 18, no. 1, pp.89-94, 1999.
[6] M. Conner, P. Norman, P. and R. Bell, R, “The theory of planned
behavior and healthy eating” Health Psychology, 22(2), pp.194-201,
2002.
[7] D.E. Schifter and I. Ajzen, “Intention, perceived control, and weight
loss: An application of the theory of planned behavior”, Journal of
Personality and Social Psychology, vol. 49, no. 3, pp.843-851, 1985.
[8] K.S. Courneya and E. McAuley, “Cognitive mediators of the social
influence-exercise adherence relationship: A test of the theory of
planned behavior”, Journal of Behavioral Medicine, vol. 18, no.5,
pp.499-515, 1995.
[9] C.J. Armitage, “Can the Theory of Planned Behavior Predict the
Maintenance of Physical Activity?”, Health Psychology, vol. 24, no. 3,
pp.235-245, 2005.
[10] C.J. Armitage and M. Conner, “Efficacy of the Theory of Planned
Behaviour: A meta-analytic review” British Journal of Social
Psychology, vol. 40, no. 4, pp.471-499, 2001.
[11] S. Munro, S. Lewin, T. Swart and J. Volmink, “A review of health
behaviour theories: how useful are these for developing interventions to
promote long-term medication adherence for TB and HIV/AIDS?” BMC
Public Health, vol.7, no.104, 2007.
[12] S. Sutton, S, “Predicting and Explaining Intentions and Behavior: How
Well Are We Doing?” Journal of Applied Social Psychology, vol.28,
no.15, pp.1317-1338, 1998.
[13] J.B.F. de Wit, W. Stroebe, E.M.M. Vroome, T.G.M. Sandfort, G.J.P. van
Griensven, “Understanding AIDS preventive behavior with casual and
primary partners in homosexual men: The Theory of Planned Behavior
and the information-motivation-behavioral-skills model” Psychology &
Health, vol. 15, no. 3, pp.325-340, 2000.
[14] V. Strang, The meaning of water, Berg, Oxford, 2004.
[15] L.M. Gibbs, “Valuing water: Variability and the Lake Eyre Basin,
Central Australia”, Australian Geographer, vol.37, no.1, pp.73-85,
2006.
[16] S. Jackson, N. Stoeckl, A. Straton and O. Stanley, “The changing value
of australian tropical rivers”Geographical Research, Vol.46, no.3,
pp.275-290, 2008.
[17] E. Shove, Comfort, Cleanliness and Convenience: The Social
Organization of Normality, Oxford: Berg, 2003.
[18] M. Kaika, M, City of flows: modernity, nature, and the city, New York:
Routledge, 2005.
[19] G. Davison, “Down the gurglerQ: Historical influences on Australian
domestic water consumption” in Troubled Waters: Confronting the
water crisis in Australian cities, P. Troy and P. Nicol, Canberra: ANU E
Press, pp. 37-65, 2008.
[20] S.J Kantola, G.J Syme and N.A. Campbell, “The role of individual
differences and external variables in a test of the sufficiency of
fishbein’s model to explain behavioral intentions to conserve
water”,Journal of Applied Social Psychology, vol.12, no.1, pp.70-83,
1982.
[21] C. Seligman, D. Hall and J. Finegan, “Predicting home energy
consumption: An application of the Fishbein-Ajzen model”Advances in
Consumer Research, vol. 10, pp.647-651, 1983.
[22] M. Tongleta, P.S. Phillips and A.D. Read, “Using the Theory of Planned
Behaviour to investigate the determinants of recycling behaviour: a case
study from Brixworth”, Resources, Conservation and Recycling, vol.41,
no.3, pp.191-214, 2004.
[23] A. Hurlimann, S. Dolnicar and P. Meyer, “Understanding behaviour to
inform water supply management in developed nations – A review of
literature, conceptual model and research agenda”. Journal of
Environmental Management, Vol.91, pp.47-56.
[24] G. Tselekidis, P. Peppas and M. Williams, “Belief revision and
organisational knowledge dynamics”. Journal of the Operational
Research Society, vol.54, no.9, pp.914-923, 2003.
[25] Z. Sofoulis, Z, “Big Water, Everyday Water: A Sociotechnical
Perspective”, Continuum: Journal of Media & Cultural Studies, vol.19,
no.4, pp.445-463, 2005.
[26] A. Warde, “Consumption and Theories of Practice”, Journal of
Consumer Culture, vol.5, no.2, pp.131-135, 2005.
[27] Y. Strengers, “Challenging comfort & cleanliness norms through
interactive in-home feedback systems”, Green Pervasive Workshop at
Persuasive 2008, Sydney, 19 May, 2008.
[28] S.Darby, The Effectiveness of Feedback on Energy Consumption: A
Review for DEFRA on the Literature on Metering, Billing and Direct
Displays, Oxford: Environmental Change Institute, University of
Oxford, 2006.
[29] Y. Strengers, Y., 2009, “Bridging the divide between resource
management and everyday life”, Social Science, September, 2009.
[30] T. Hargreaves, M. Nye, J. Burgess, J, “Making energy visible: A
qualitative field study of how householders interact with feedback from
smart energy monitors”, Energy Policy, vol.38, no.10, pp.6111-6119,
2010.
[31] C. Fischer, “Feedback on household electricity consumption: a tool for
saving energy?”,Energy Efficiency, vol.1, no.1, pp.79-104, 2008.
[32] M. Chetty, D. Tran and R.E Grinter, “ Getting to GreenQ:
Understanding Resource Consumption in the Home”, UbiComp '08
Proceedings of the 10th international conference on Ubiquitous
computing, pp.242-251, 2008.
[33] S.S. Intille, “Designing a home of the future”, IEEE Pervasive
Computing, vol.1, no.2, pp.76-82, 2002.
[34] H. Wilhite, and R. Ling, R, “Measured energy savings from a more
informative energy bill”, Energy and Buildings, vol.22, pp.145-155,
1995.
[35] R. Willis, R. Stweart, L. Chen, L. Rutherford, “Water end use
consumption analysis into Gold Coat dual retriculated households:
Pilot”, Australia’s National Water Conference and Oz Water 09’,
Melbuourne Convention Centre, March 2009.
[36] J.M. Bohli, C. Sorge, and O. Ugus, “A Privacy Model for Smart
Metering”, In Commuincations Workshops (ICC), 2010 IEEE
International Conference on. pp. 1-5, 2010.
[37] Sydney Water, “The history of Water Wise rules”, Available at:
http://www.sydneywater.com.au/water4life/waterwise/WhenWereWater
RestrictionsIntroduced.cfm (Accessed March 8, 2012).
[38] Bureau of Meteorolgy, Annual Australian Climate Statement 2011.
http://www.bom.gov.au/announcements/media_releases/climate/change/
20120104.shtml (Accessed March 5, 2012).
[39] ABC News, Smart meters causing havoc. Inside Business. Available at:
http://www.abc.net.au/insidebusiness/content/2011/s3259653.htm, 2011
(Accessed March 8, 2012).
[40] P. Newman, P,“Sustainable Cities of the Future: The Behavior Change
Driver”,Sustainable Development, Law & Policy, vol.11, no.1, 2010.</p>
<p>[1] D.P. Giurco, S.B. White, S.B. and R. Stewart, “Smart metering and
water end-use data: Conservation benefits and privacy risks”, Water,
vol. 2, no. 3, pp.461-467, 2010.
[2] I. Azjen, “The theory of planned behavior”,Organisational Behaviour
and Human Decision Processes, vol. 50, no. 2, pp.179-211, 1991.
[3] G. Godin and G. Kok, “The theory of planned behavior: A review of its
applications to health-related behaviors”, American Journal of Health
Promotion, vol. 11, no. 2, pp.87-98, 1996.
[4] P. Sheeran, M. Conner. and P. Norman, “Can the Theory of Planned
Behavior explain patterns of health behavior change? Health
Psychology, vol. 20, no. 1, pp.12-19, 2001.
[5] P. Norman, M. Conner and R. Bell, “The theory of planned behavior and
smoking cessation” Health Psychology, vol. 18, no. 1, pp.89-94, 1999.
[6] M. Conner, P. Norman, P. and R. Bell, R, “The theory of planned
behavior and healthy eating” Health Psychology, 22(2), pp.194-201,
2002.
[7] D.E. Schifter and I. Ajzen, “Intention, perceived control, and weight
loss: An application of the theory of planned behavior”, Journal of
Personality and Social Psychology, vol. 49, no. 3, pp.843-851, 1985.
[8] K.S. Courneya and E. McAuley, “Cognitive mediators of the social
influence-exercise adherence relationship: A test of the theory of
planned behavior”, Journal of Behavioral Medicine, vol. 18, no.5,
pp.499-515, 1995.
[9] C.J. Armitage, “Can the Theory of Planned Behavior Predict the
Maintenance of Physical Activity?”, Health Psychology, vol. 24, no. 3,
pp.235-245, 2005.
[10] C.J. Armitage and M. Conner, “Efficacy of the Theory of Planned
Behaviour: A meta-analytic review” British Journal of Social
Psychology, vol. 40, no. 4, pp.471-499, 2001.
[11] S. Munro, S. Lewin, T. Swart and J. Volmink, “A review of health
behaviour theories: how useful are these for developing interventions to
promote long-term medication adherence for TB and HIV/AIDS?” BMC
Public Health, vol.7, no.104, 2007.
[12] S. Sutton, S, “Predicting and Explaining Intentions and Behavior: How
Well Are We Doing?” Journal of Applied Social Psychology, vol.28,
no.15, pp.1317-1338, 1998.
[13] J.B.F. de Wit, W. Stroebe, E.M.M. Vroome, T.G.M. Sandfort, G.J.P. van
Griensven, “Understanding AIDS preventive behavior with casual and
primary partners in homosexual men: The Theory of Planned Behavior
and the information-motivation-behavioral-skills model” Psychology &
Health, vol. 15, no. 3, pp.325-340, 2000.
[14] V. Strang, The meaning of water, Berg, Oxford, 2004.
[15] L.M. Gibbs, “Valuing water: Variability and the Lake Eyre Basin,
Central Australia”, Australian Geographer, vol.37, no.1, pp.73-85,
2006.
[16] S. Jackson, N. Stoeckl, A. Straton and O. Stanley, “The changing value
of australian tropical rivers”Geographical Research, Vol.46, no.3,
pp.275-290, 2008.
[17] E. Shove, Comfort, Cleanliness and Convenience: The Social
Organization of Normality, Oxford: Berg, 2003.
[18] M. Kaika, M, City of flows: modernity, nature, and the city, New York:
Routledge, 2005.
[19] G. Davison, “Down the gurglerQ: Historical influences on Australian
domestic water consumption” in Troubled Waters: Confronting the
water crisis in Australian cities, P. Troy and P. Nicol, Canberra: ANU E
Press, pp. 37-65, 2008.
[20] S.J Kantola, G.J Syme and N.A. Campbell, “The role of individual
differences and external variables in a test of the sufficiency of
fishbein’s model to explain behavioral intentions to conserve
water”,Journal of Applied Social Psychology, vol.12, no.1, pp.70-83,
1982.
[21] C. Seligman, D. Hall and J. Finegan, “Predicting home energy
consumption: An application of the Fishbein-Ajzen model”Advances in
Consumer Research, vol. 10, pp.647-651, 1983.
[22] M. Tongleta, P.S. Phillips and A.D. Read, “Using the Theory of Planned
Behaviour to investigate the determinants of recycling behaviour: a case
study from Brixworth”, Resources, Conservation and Recycling, vol.41,
no.3, pp.191-214, 2004.
[23] A. Hurlimann, S. Dolnicar and P. Meyer, “Understanding behaviour to
inform water supply management in developed nations – A review of
literature, conceptual model and research agenda”. Journal of
Environmental Management, Vol.91, pp.47-56.
[24] G. Tselekidis, P. Peppas and M. Williams, “Belief revision and
organisational knowledge dynamics”. Journal of the Operational
Research Society, vol.54, no.9, pp.914-923, 2003.
[25] Z. Sofoulis, Z, “Big Water, Everyday Water: A Sociotechnical
Perspective”, Continuum: Journal of Media & Cultural Studies, vol.19,
no.4, pp.445-463, 2005.
[26] A. Warde, “Consumption and Theories of Practice”, Journal of
Consumer Culture, vol.5, no.2, pp.131-135, 2005.
[27] Y. Strengers, “Challenging comfort & cleanliness norms through
interactive in-home feedback systems”, Green Pervasive Workshop at
Persuasive 2008, Sydney, 19 May, 2008.
[28] S.Darby, The Effectiveness of Feedback on Energy Consumption: A
Review for DEFRA on the Literature on Metering, Billing and Direct
Displays, Oxford: Environmental Change Institute, University of
Oxford, 2006.
[29] Y. Strengers, Y., 2009, “Bridging the divide between resource
management and everyday life”, Social Science, September, 2009.
[30] T. Hargreaves, M. Nye, J. Burgess, J, “Making energy visible: A
qualitative field study of how householders interact with feedback from
smart energy monitors”, Energy Policy, vol.38, no.10, pp.6111-6119,
2010.
[31] C. Fischer, “Feedback on household electricity consumption: a tool for
saving energy?”,Energy Efficiency, vol.1, no.1, pp.79-104, 2008.
[32] M. Chetty, D. Tran and R.E Grinter, “ Getting to GreenQ:
Understanding Resource Consumption in the Home”, UbiComp '08
Proceedings of the 10th international conference on Ubiquitous
computing, pp.242-251, 2008.
[33] S.S. Intille, “Designing a home of the future”, IEEE Pervasive
Computing, vol.1, no.2, pp.76-82, 2002.
[34] H. Wilhite, and R. Ling, R, “Measured energy savings from a more
informative energy bill”, Energy and Buildings, vol.22, pp.145-155,
1995.
[35] R. Willis, R. Stweart, L. Chen, L. Rutherford, “Water end use
consumption analysis into Gold Coat dual retriculated households:
Pilot”, Australia’s National Water Conference and Oz Water 09’,
Melbuourne Convention Centre, March 2009.
[36] J.M. Bohli, C. Sorge, and O. Ugus, “A Privacy Model for Smart
Metering”, In Commuincations Workshops (ICC), 2010 IEEE
International Conference on. pp. 1-5, 2010.
[37] Sydney Water, “The history of Water Wise rules”, Available at:
http://www.sydneywater.com.au/water4life/waterwise/WhenWereWater
RestrictionsIntroduced.cfm (Accessed March 8, 2012).
[38] Bureau of Meteorolgy, Annual Australian Climate Statement 2011.
http://www.bom.gov.au/announcements/media_releases/climate/change/
20120104.shtml (Accessed March 5, 2012).
[39] ABC News, Smart meters causing havoc. Inside Business. Available at:
http://www.abc.net.au/insidebusiness/content/2011/s3259653.htm, 2011
(Accessed March 8, 2012).
[40] P. Newman, P,“Sustainable Cities of the Future: The Behavior Change
Driver”,Sustainable Development, Law & Policy, vol.11, no.1, 2010.</p>
@article{"International Journal of Business, Human and Social Sciences:55971", author = "Candice Moy and Damien Guirco and Thomas Boyle", title = "Can Smart Meters Create Smart Behaviour?", abstract = "Intelligent technologies are increasingly facilitating
sustainable water management strategies in Australia. While this
innovation can present clear cost benefits to utilities through
immediate leak detection and deference of capital costs, the impact of
this technology on households is less distinct. By offering real-time
engagement and detailed end-use consumption breakdowns, there is
significant potential for demand reduction as a behavioural response
to increased information. Despite this potential, passive
implementation without well-planned residential engagement
strategies is likely to result in a lost opportunity. This paper begins
this research process by exploring the effect of smart water meters
through the lens of three behaviour change theories. The Theory of
Planned Behaviour (TPB), Belief Revision theory (BR) and Practice
Theory emphasise different variables that can potentially influence
and predict household water engagements. In acknowledging the
strengths of each theory, the nuances and complexity of household
water engagement can be recognised which can contribute to
effective planning for residential smart meter engagement strategies.
", keywords = "Behaviour, information, household, smart meters,
water.", volume = "7", number = "7", pages = "2028-8", }
