Building Eco-Informatics: Examining the Dynamics of Eco-Feedback Design and Peer Networks to Achieve Sustainable Reductions in Energy Consumption

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Autor/in	Jain, Rishee K.
Titel	Building Eco-Informatics: Examining the Dynamics of Eco-Feedback Design and Peer Networks to Achieve Sustainable Reductions in Energy Consumption
Quelle	(2013), (121 Seiten) PDF als Volltext Verfügbarkeit Ph.D. Dissertation, Columbia University
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	978-1-3033-8542-1
Schlagwörter	Hochschulschrift; Dissertation; Energy Conservation; Social Networks; Feedback (Response); Costs; Building Design; Construction (Process); Climate; Efficiency; Computer Software; Information Systems; Incentives; Behavior Change; Electronic Mail; Information Sources; Responses; Social Influences; Users (Information); Metropolitan Areas; New York + Suchen Sie Ihr Suchwort? Thesis; Dissertations; Academic thesis; Energieerhaltung; Energiespeicherung; Social network; Soziales Netzwerk; Cost; Kosten; Baugestaltung; Aufbau; Konstruktion; Klima; Effectiveness; Effektivität; Wirkungsgrad; Anreiz; Elektronischer Briefkasten; Information source; Informationsquelle; Sozialer Einfluss; Benutzerprofil; Nutzer; Ballungsraum
Abstract	The built environment accounts for a substantial portion of energy consumption in the United States and in many parts of the world. Due to concerns over rising energy costs and climate change, researchers and practitioners have started exploring the area of eco-informatics to link information from the human, natural and built environments. Specifically, they have begun exploring the use of normative eco-feedback systems to encourage energy efficient behavior and reduce building energy consumption. A normative eco-feedback system provides building occupants with information regarding their own energy consumption and the energy consumption of others in their peer network. While such eco-feedback systems have been observed to drive significant reductions in energy consumption, little is known about the specific system and peer network dynamics that are driving observed reductions. Without this deeper understanding, researchers run the risk of designing eco-feedback systems with low efficacy and may therefore fail to capitalize on potential energy savings. The central aim of this dissertation is to investigate the impact eco-feedback system design and peer network dynamics have on occupant energy consumption behavior. To enable both energy consumption and network data collection, I developed a web-based of an eco-feedback system prototype for an 69 unit residential building in New York City and utilized the system in three empirical experiments. The first experiment was designed to ascertain the effect eco-feedback interface design components have on energy consumption behavior. Analysis of time stamped interface usage and energy consumption data revealed evidence that providing users with incentives and information on their historical consumption levels encourages conservation behavior. Results also suggested that penalizing users for using more energy is not effective in driving energy reductions and instead discourages user engagement. To further understand the effect eco-feedback system design has on energy consumption behavior, a second experiment was conducted using an email-based eco-feedback system. The aim of this study was to examine the role feedback representation plays in encouraging reductions in energy consumption. Participants were broken into two different study groups; one group was provided with feedback in kWh, while a second group was provided with feedback in the equivalent trees required to offset emissions associated with their kWh energy usage. Results revealed that users who received feedback in the form of equivalent trees were more likely to reduce their consumption and had a less dramatic response-relapse effect to feedback emails than their counterparts who received feedback in kWh. The third experiment aimed to characterize the impact peer networks have on modifying energy consumption behavior. Specifically, the experiment was designed to determine if social influence drives energy savings in eco-feedback systems. Analysis of user interaction and energy consumption data was conducted by developing an algorithmic approach based on stochastic and social network test procedures. Social influence was found to impact energy consumption behavior and results indicated the potential of utilizing social influence and peer networks as a means to encourage energy conservation. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided).
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Update	2020/1/01