بررسی تاثیر بازخورد محیط زیست نمایندگی اطلاعات بر روی رفتار و صرفه جویی مصرف انرژی ساکنان ساختمانی

In response to rising energy costs and concerns over environmental emissions, researchers and practitioners have developed eco-feedback systems to provide building occupants with information on their energy consumption. While such eco-feedback systems have been observed to drive significant reductions in energy consumption, little is known as to what specific design features of these systems are most motivational. One common feature of eco-feedback systems is the way in which energy consumption is represented to users. In this study, we empirically examine the impact that information representation has on energy consumption behavior by comparing the effectiveness of direct energy feedback versus feedback represented as an environmental externality. A one month empirical study with 39 participants in an urban residential building was conducted. Participants were divided into two different study groups; one group was provided with feedback in direct energy units and a second group was provided feedback in environmental externality units. Results revealed that information representation has a statistically significant impact on the energy consumption behavior of users, and that users receiving eco-feedback as an environmental externality reduced their consumption more than their counterparts who received feedback in direct energy units. This study represents a crucial first step towards gaining a deeper understanding of how information representation can be leveraged to maximize energy savings.

The built environment is responsible for over 40% of energy consumption in the United States [1] making it a prime target for the application of energy efficiency measures. Pressure is rising to reduce energy consumption in buildings amid increasing energy costs and concerns over environmental emissions. Most efforts to improve energy efficiency in buildings focus on physical “green” retrofits and other energy saving technologies (e.g. energy efficient appliances, upgrades to HVAC systems, energy-efficient lighting). While such physical measures and upgrades can boost energy efficiency substantially, concerns over the long-term effectiveness of such capital intensive retrofits exist due to the “take back effect” [2]. The “take back effect” occurs when a building occupant adopts inefficient consumption behavior that could reduce or nullify the efficiency gains associated with a retrofit. The installation of energy saving technologies must be accompanied by energy efficient occupant behavior to ensure sustained reductions in energy consumption. Several studies [3], [4] and [5] have concluded that occupant behavior can have a substantial impact on building energy consumption, and that occupant energy savings have the potential to reduce US emissions by 7.4% with little or no impact on household well-being [6]. Moreover, behavior-based efficiency programs have been proven to be among the most cost effective energy efficiency strategies on the market [7].

Overall, this work empirically establishes that information representation in eco-feedback systems can have a significant impact on energy consumption behavior and establishes the environmental proxy of “trees needed to offset emissions” as a viable alternative to current units (e.g., kWh, CO2 emissions) utilized in eco-feedback systems. This study represents a crucial first step to settle the current discord in the eco-feedback literature regarding information representation by analyzing empirical energy consumption data. The methodology established in this paper provides a first pathway toward a more holistic analysis of eco-feedback system design by incorporating empirical energy consumption data. It also allowed for the validation of conclusions from previous user surveys and laboratory experiments. The results of this study have important implications for how we approach eco-feedback system design and the use of information representation in eco-feedback systems. Information representation has been acknowledged to be an important aspect of eco-feedback systems, yet little research exists that empirically and explicitly tests it. The authors hope that the findings from this paper will spark dialog among researchers and practitioners regarding information representation leading to future studies that will extend and expand the results and methodology presented in this paper. Future research should aim to simultaneously employ user surveying techniques, empirical experimentation and real energy consumption data to analyze not only information representation but other aspects of eco-feedback system design. Through the use of empirical experimentation and observed energy savings data we can validate currently established design heuristics and begin to resolve the current discord in the eco-feedback design literature.