Cross-cultural assessment of the effectiveness of eco-feedback in building energy conservation

Abstract To reduce energy consumption in buildings, researchers have in the recent decade explored the potential of changing occupants’ energy consumption behaviors using eco-feedback technologies. Energy consumption behavior is a type of consumer behavior, which has been proven culture-specific in prior research. This paper aims to assess the impact of culture on the effectiveness of eco-feedback technologies in reshaping building occupants’ energy consumption behaviors, and to examine the mechanism of such impact. A total of 39 students from 10 different countries who shared four university dormitories were recruited in an experiment. A web-based eco-feedback system was developed in this study, and implemented in these dormitories. The eco-feedback system was responsible for sending weekly email reminders to students participating in the study and, upon their login, providing them with their detailed energy consumption data as well as those of their peers on a daily basis. Subsequent changes in the students’ energy consumption behaviors were analyzed, and correlated with their cultural background, which was assessed using a survey instrument designed based on Hofstede's cultural dimensions model. The experiment results showed that the mean and variance of changes in energy consumption, in response to the provision of eco-feedback information, differed significantly between participants from different countries. The results also showed that all cultural dimensions were statistically correlated to the effectiveness of the eco-feedback system, which explained how different aspects of culture could influence the energy consumption behaviors of building occupants. The results suggested that eco-feedback technologies should be tailored to specific cultural context to improve their effectiveness in building energy conservation.

[1]  G. Hofstede Culture′s Consequences: Comparing Values, Behaviors, Institutions and Organizations Across Nations , 2001 .

[2]  Douglas D. Gransberg,et al.  Comparative Analysis of Owner Goals for Design/Build Projects , 2008 .

[3]  I. Vassileva,et al.  Energy consumption feedback devices’ impact evaluation on domestic energy use , 2013 .

[4]  S. Karjalainen Consumer preferences for feedback on household electricity consumption , 2011 .

[5]  Craig Whittington,et al.  Using theory to synthesise evidence from behaviour change interventions: the example of audit and feedback. , 2010, Social science & medicine.

[6]  Vladislav Kantchev Shunturov,et al.  Dormitory residents reduce electricity consumption when exposed to real‐time visual feedback and incentives , 2007 .

[7]  Brian Orland,et al.  Saving energy in an office environment: A serious game intervention , 2014 .

[8]  Yoshikuni Yoshida,et al.  Determining the relationship between a household’s lifestyle and its electricity consumption in Japan by analyzing measured electric load profiles , 2016 .

[9]  Barbara Schlomann,et al.  Characterization of the household electricity consumption in the EU, potential energy savings and sp , 2011 .

[10]  John E. Taylor,et al.  Investigating the impact eco-feedback information representation has on building occupant energy consumption behavior and savings , 2013 .

[11]  John E. Taylor,et al.  The impact of place-based affiliation networks on energy conservation: An holistic model that integrates the influence of buildings, residents and the neighborhood context , 2012 .

[12]  Gert Jan Hofstede,et al.  Cultures and Organizations - Software of the Mind: Intercultural Cooperation and its Importance for Survival (3. ed.) , 2010 .

[13]  Hans Auer,et al.  The impact of consumer behavior on residential energy demand for space heating , 1998 .

[14]  A. Kluger,et al.  The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. , 1996 .

[15]  Alex Pentland,et al.  The Influence of Reference Frame and Population Density on the Effectiveness of Social Normative Feedback on Electricity Consumption , 2012, ICIS.

[16]  Rishee K. Jain Building Eco-Informatics: Examining the Dynamics of Eco-Feedback Design and Peer Networks to Achieve Sustainable Reductions in Energy Consumption , 2013 .

[17]  Peter Kerkhof,et al.  Using feedback through digital technology to disrupt and change habitual behavior: A critical review of current literature , 2016, Comput. Hum. Behav..

[18]  M. Newborough,et al.  Energy-use information transfer for intelligent homes : Enabling energy conservation with central and local displays , 2007 .

[19]  Rishee K. Jain,et al.  Can social influence drive energy savings? Detecting the impact of social influence on the energy consumption behavior of networked users exposed to normative eco-feedback , 2013 .

[20]  G. Hofstede,et al.  Culture′s Consequences: International Differences in Work-Related Values , 1980 .

[21]  Francisco Argüello,et al.  An eco-feedback system for improving the sustainability performance of universities , 2011, 2011 IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems Proceedings.

[22]  Siaw Kiang Chou,et al.  Achieving better energy-efficient air conditioning - A review of technologies and strategies , 2013 .

[23]  I. Vassileva,et al.  The impact of consumers’ feedback preferences on domestic electricity consumption , 2012 .

[24]  G. Hofstede,et al.  Cross-Cultural Consumer Behavior: A Review of Research Findings , 2011 .

[25]  Rebecca Ford,et al.  Energy feedback technology: a review and taxonomy of products and platforms , 2014 .

[26]  Michael Wilke,et al.  First German-Austrian case-mix comparison with real life data , 2008, BMC Health Services Research.

[27]  Yong Yan,et al.  A persuasive feedback support system for energy conservation and carbon emission reduction in campus residential buildings , 2014 .

[28]  J. M. Twati The Influence of Societal Culture on the Adoption of Information Systems: The Case of Libya , 2014, Communications of the IIMA.

[29]  G. T. Gardner,et al.  The Short List: The Most Effective Actions U.S. Households Can Take to Curb Climate Change , 2008 .

[30]  W. Henry Cultural Values do Correlate with Consumer Behavior , 1976 .

[31]  John E. Taylor,et al.  Response–relapse patterns of building occupant electricity consumption following exposure to personal, contextualized and occupant peer network utilization data , 2010 .

[32]  Jeannet H. Van Houwelingen,et al.  The Effect of Goal-Setting and Daily Electronic Feedback on In-Home Energy Use , 1989 .

[33]  Willett Kempton,et al.  Comparison groups on bills : Automated, personalized energy information , 2006 .

[34]  William J. Kaiser,et al.  Real-time, appliance-level electricity use feedback system: How to engage users? , 2014 .

[35]  S. S. van Dam,et al.  Home energy monitors: impact over the medium-term , 2010 .

[36]  F. Siero,et al.  Changing organizational energy consumption behaviour through comparative feedback , 1996 .

[37]  John E. Taylor,et al.  Assessing Eco-Feedback Interface Usage and Design to Drive Energy Efficiency in Buildings , 2012 .

[38]  H. Wilhite,et al.  A cross-cultural analysis of household energy use behaviour in Japan and Norway , 1996 .

[39]  J. Hattie,et al.  The Power of Feedback , 2007 .

[40]  J. Taylor,et al.  The impact of peer network position on electricity consumption in building occupant networks utilizing energy feedback systems , 2012 .

[41]  Peirong Che,et al.  Cross-Culture Study on the Consumption Behavior in Mobile Data Services , 2009, 2009 International Conference on Management and Service Science.

[42]  Geert Hofstede,et al.  Are cultural dimensions relevant for explaining cross-national differences in antibiotic use in Europe? , 2008, BMC health services research.

[43]  Sigal Segev,et al.  Modelling household conservation behaviour among ethnic consumers: the path from values to behaviours , 2015 .

[44]  David Luna,et al.  An integrative framework for cross‐cultural consumer behavior , 2001 .

[45]  Julian Di Stefano,et al.  Energy efficiency and the environment: the potential for energy efficient lighting to save energy and reduce carbon dioxide emissions at Melbourne University, Australia , 2000 .

[46]  Paul Raftery,et al.  A review of methods to match building energy simulation models to measured data , 2014 .

[47]  Burcin Becerik-Gerber,et al.  Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures , 2015 .

[48]  Aviv Shoham,et al.  Hofstede's dimensions of culture in international marketing studies , 2007 .

[49]  Nan Li,et al.  The Impact of Eco-Feedback on Energy Consumption Behavior: A Cross-Cultural Study , 2016 .

[50]  Riccardo Russo,et al.  The question of energy reduction: The problem(s) with feedback , 2015 .

[51]  D.M.N.S.W. Dissanayake,et al.  Does the Innate Culture make all Failures to Entrepreneurs? An Existing Context Specific Problem , 2014 .