Framework to investigate energy conservation motivation and actions of building occupants: The case of a green campus in Abu Dhabi, UAE

Significant energy savings can be achieved in buildings by altering how occupants use and operate various building systems. The first step to successfully inducing such change requires a thorough assessment and understanding of the actual drivers and motivators of existing behaviors. The current literature on energy conservation behaviors in buildings presents significant limitations including: (1) the availability of data on human behavior in buildings; (2) the lack of consideration of various behavioral drivers (e.g., social, environmental, and economic); (3) simplified data analysis methods, which overlook combined effects of behavioral drivers; and (4) limited scopes of work to either residential or commercial buildings, overlooking potential synergies between the two. This paper aims to fill the stated gaps in the literature by proposing a comprehensive data collection and analysis framework to investigate the energy conservation motivation and actions of people in individual or groups of buildings (e.g., community or city). The framework is illustrated through a case study on a green campus located in Abu Dhabi, United Arab Emirates (UAE). Data was collected from a total of 227 campus users or residents, followed by descriptive and statistical analyses using Principal Components Analysis (PCA) and multiple linear regression models. Results indicate that energy saving awareness and motivation do not directly translate to actions, particularly at the workplace where a correlation coefficient of only 0.083 is observed. Factors such as respondents’ demographics, the level of control over building systems, and motivation drivers (e.g., financial, social, and environmental) highly affect energy saving actions and need through consideration for effective human-focused energy conservation strategies.

[1]  Tianzhen Hong,et al.  Advances in research and applications of energy-related occupant behavior in buildings ☆ , 2016 .

[2]  SangHyun Lee,et al.  An empirically grounded model for simulating normative energy use feedback interventions , 2016 .

[3]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[4]  G. Nigel Gilbert,et al.  Agent-Based Models , 2007 .

[5]  John E. Taylor,et al.  Modeling building occupant network energy consumption decision-making: The interplay between network structure and conservation , 2012 .

[6]  G. Dunteman Principal Components Analysis , 1989 .

[7]  Sylvain Robert,et al.  State of the art in building modelling and energy performances prediction: A review , 2013 .

[8]  C. Vlek,et al.  Encouraging pro-environmental behaviour : An integrative review and research agenda , 2009 .

[9]  Frédéric Magoulès,et al.  A review on the prediction of building energy consumption , 2012 .

[10]  Mithra Moezzi,et al.  Behavioral Assumptions in Energy Efficiency Potential Studies , 2009 .

[11]  Liu Yang,et al.  Thermal comfort and building energy consumption implications - A review , 2014 .

[12]  Elizabeth A. Peck,et al.  Introduction to Linear Regression Analysis , 2001 .

[13]  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 .

[14]  Alan J. Miller Subset Selection in Regression , 1992 .

[15]  P. Wargocki,et al.  Literature survey on how different factors influence human comfort in indoor environments , 2011 .

[16]  Brad J. Sagarin,et al.  Managing social norms for persuasive impact , 2006 .

[17]  Elie Azar,et al.  A comprehensive analysis of the impact of occupancy parameters in energy simulation of office buildings , 2012 .

[18]  A. Carrico,et al.  Motivating energy conservation in the workplace: An evaluation of the use of group-level feedback and peer education , 2011 .

[19]  P. Stern New Environmental Theories: Toward a Coherent Theory of Environmentally Significant Behavior , 2000 .

[20]  Jessica Granderson,et al.  Energy Information Handbook: Applications for Energy-Efficient Building Operations , 2013 .

[21]  Ying Hua,et al.  Completing the missing link in building design process: Enhancing post-occupancy evaluation method for effective feedback for building performance , 2015 .

[22]  Elie Azar,et al.  A comprehensive framework to quantify energy savings potential from improved operations of commercial building stocks , 2014 .

[23]  Dino Bouchlaghem,et al.  Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap , 2012 .

[24]  Nora El-Gohary,et al.  Energy-related values and satisfaction levels of residential and office building occupants , 2016 .

[25]  Scott Glick,et al.  Reducing electrical energy consumption through behaviour changes , 2014 .

[26]  Elie Azar,et al.  Optimizing the Performance of Energy-Intensive Commercial Buildings: Occupancy-Focused Data Collection and Analysis Approach , 2016 .

[27]  Stephanie E. Chang,et al.  Effective and persistent changes in household energy-saving behaviors: Evidence from post-tsunami Japan , 2016 .

[28]  Marcella Ucci,et al.  Behaviour change potential for energy saving in non-domestic buildings: Development and pilot-testing of a benchmarking tool , 2014 .

[29]  Koen Steemers,et al.  Behavioural, physical and socio-economic factors in household cooling energy consumption , 2011 .

[30]  John E. Taylor,et al.  Network synergy effect: Establishing a synergy between building network and peer network energy conservation effects , 2014 .

[31]  Fred A. Mael,et al.  Social identity theory and the organization , 1989 .

[32]  D. Dillman,et al.  How to conduct your own survey , 1994 .

[33]  Furong Li,et al.  A novel time-of-use tariff design based on Gaussian Mixture Model , 2016 .

[34]  David S. C. Thompson,et al.  A guide to knowledge translation theory , 2006, The Journal of continuing education in the health professions.

[35]  Elie Azar,et al.  Evaluating the impact of extreme energy use behavior on occupancy interventions in commercial buildings , 2015 .

[36]  O. T. Masoso,et al.  The dark side of occupants’ behaviour on building energy use , 2010 .

[37]  S. Mullainathan,et al.  Behavior and Energy Policy , 2010, Science.

[38]  S. Svendsen,et al.  Residential and commercial buildings , 2012 .

[39]  I. Vassileva,et al.  Analytical comparison between electricity consumption and behavioral characteristics of Swedish households in rented apartments , 2012 .

[40]  Ian Ridley,et al.  The potential of increasing cooling set-points in air-conditioned offices in the UK , 2011 .

[41]  C. Vlek,et al.  A review of intervention studies aimed at household energy conservation , 2005 .

[42]  Carol C. Menassa,et al.  Impact of Social Network Type and Structure on Modeling Normative Energy Use Behavior Interventions , 2014, J. Comput. Civ. Eng..

[43]  Elie Azar,et al.  Integrating building performance simulation in agent-based modeling using regression surrogate models: A novel human-in-the-loop energy modeling approach , 2016 .

[44]  Tianzhen Hong,et al.  An insight into actual energy use and its drivers in high-performance buildings , 2014 .

[45]  Jerry Yudelson,et al.  Greening Existing Buildings , 2009 .

[46]  Muhammad Imran,et al.  Individual energy use and feedback in an office setting: A field trial , 2013 .

[47]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[48]  Gaye Teksöz,et al.  University Students' Behaviors Pertaining to Sustainability: A Structural Equation Model with Sustainability-Related Attributes. , 2012 .

[49]  W. Abrahamse,et al.  How do socio-demographic and psychological factors relate to households' direct and indirect energy use and savings? , 2009 .

[50]  Craig Brown,et al.  Assessing occupant satisfaction and energy behaviours in Toronto’s LEED gold high-rise residential buildings , 2014 .

[51]  P. McCullagh,et al.  Generalized Linear Models , 1984 .

[52]  Francesco Asdrubali,et al.  Human-based energy retrofits in residential buildings: A cost-effective alternative to traditional physical strategies , 2014 .

[53]  Isaac A. Meir,et al.  Post-Occupancy Evaluation: An Inevitable Step Toward Sustainability , 2009 .