University research buildings are significant energy consumers in the United States. There is therefore a need to reduce energy use on the nation's campuses, not only cutting their carbon footprints but also saving money. Universities' efforts to reduce energy use include updating older facilities, implementing renewable energy systems, and encouraging energy saving behavior. This study evaluated the differential effects of two forms of feedback on electricity consumption in two groups of research buildings on a college campus to determine whether providing feedback to energy users has an impact on energy conservation behavior. A control group of buildings received no feedback regarding their electricity use. In the first study group of buildings, occupants received information about their electricity consumption with some electricity saving tips, distributed via email. The same procedure was followed with building occupants in the second study group, who received additional information showing their electricity consumption performance in comparison to other buildings within the study group. The baseline reading was conducted a week before the experiment began in August, 2012. Over the course of the five week study, the daily adjusted average reductions in electricity usage compared to the control group were less than 1 percent for both study groups, with study group 1 achieving an average reduction of 0.2 percent and study group 2 an average reduction of 0.8 percent. Although the reduction observed for study group 2 was 4 times greater than that for study group 1, the saving was not continuous over the study period. Accordingly, the result was deemed to be not statistically significant and the effectiveness of comparative energy use feedback in university research buildings was not supported. However, even small savings in the energy used in university research buildings can be very important in terms of the total amount of energy saved because research buildings use significantly more energy than other buildings on campus such as academic buildings and residence blocks. This study concludes with a consideration of potentially fruitful directions for future research into developing new ways to reduce the energy consumption on university campuses. / Master of Science

Industry is one of the major energy consumers resulting in negative environmental impacts in the world. In this context, industrial energy management becomes critically important when improving industrial energy savings. Emphasized is the careful energy treatment in the Sustainable Development Goals of the United Nations. The dominance of a technical approach in current research of industrial energy management suppresses significant potentials of human behavior for energy efficiency. Societal problems such as the energy efficiency gap and the rebound effect may be tackled by involving energysaving behavior in interventions. This thesis aims to explain characteristics of energy-saving behavior in the industrial settings of an automobile producer in Central Europe. The manufacturer utilizes an energy management program, named QUEST, which is facilitated by the external advisor HE Consulting s.r.o. Questions of particular interest are therefore related to perceived organizational readiness to engage in energy-saving behavior. Data gathering include a structured-questionnaire of perceptions on energy savings at the plants with managers of the automobile producer. Additionally, a semi-structured interview with the CEO of HE Consulting s.r.o. offers a more in-depth view on practical implications of energysaving behavior. As a base for data collection serves a psychological perspective of perceptional theories. Strongly related is that approach to the change management discipline. Results of the study show that, indeed, managers in the QUEST program tend to perceive organizational readiness on energy savings re latively more positive than managers outside the program. Resistance to change can be marginally observed in lower management levels. However, the managers emphasize a lack of time to engage in energy savings. Indicators of perceived organizational readiness on energy savings alone do not show the actual energy-saving behavior. This means that this thesis does not directly observe energy-saving behavior. Nevertheless, the impact of such indicators on the actual performed energy-saving behavior may be seen in combination with quantified energy savings. All findings can only be interpreted in the frame of this study.

The IoT-embedded smart homes have a high level of home automation and could change many aspects of the residents' daily lives, such as control, convenience, comfort, and energy-saving. The rise of voice-based virtual assistants like Amazon's Alexa, Google assistants in the past five years has brought new potentials to provide occupants with a convenient and intuitive interface to interact with smart homes through conversations. However, the one-way communications in the form of user commands to control building systems does not result in the optimal course of actions. As such, in this thesis, we proposed the concept of proactive smart home assistants and explored the occupants' perception towards smart home assistants proactively providing suggestions to adapt them into energy-saving behaviors. We also investigated the impact of occupants' personal features on their intention in taking energy-saving behaviors. A comprehensive data collection was conducted through online surveys, in which 307 valid responses with participant's personal profile information, their perceptions of smart home assistants, and their feedback to our designed messages were collected. The first manuscript compared participants' responses to traditional plain-text energy-saving suggestions and suggestions provided by smart home assistants. The nudging effect of smart home assistants was justified to be significant in affecting occupant's energy-saving behaviors. Occupant's thermal comfort range, smart home device previous experience, values and beliefs were then proved to have significant impact on their intention in taking the smart home assistant's suggestions. The second manuscript fitted 21 personal characteristics features in machine learning models (SVM, Random Forest, Logistic Regression) to predict occupant's intention and attitude towards energy-saving suggestions. The results indicated that occupant's beliefs about interests in taking actions and beliefs about energy expenses, occupant's education level, residence occupancy type, thermal comfort ranges, and smart home device experiences are important features in occupants' energy-saving behavior intention prediction. This research demonstrates the effect of proactive smart home assistants in human-building interaction as well as the impact of personal characteristic features on occupant's energy-saving behaviors, paving a path to the future development of bi-directional human-building communication. / Master of Science / With the technology development in the fields of the Internet of Things (IoT), smart homes have made it possible to help occupants conserve energy in an efficient way without sacrificing the occupants' comfort. The rise of voice-based virtual assistants like Amazon's Alexa, Google assistants accompany the proliferation of smart speaker products in the past five years has brought new potentials to provide occupants with a convenient and intuitive interface to interact with smart homes through conversations. Based on IoT, the virtual assistants are able to control a broad range of Wi-Fi connected home devices like thermostats, lighting systems, and security systems. As such, through the simple wake words (e.g., "Alexa", "Hey, Google"), occupants can easily control the home environment with their voice commands. Despite the potentials brought by these voice-based virtual assistants, it has been shown that users might not know about all the supported features and limit their interaction with smart home assistants to simple daily tasks. The one-way communications in the form of user commands to control building systems do not result in the optimal course of actions. Therefore, in this study, we have envisioned that these virtual assistants, coupled with their corresponding smart home ecosystems could act proactively as a bridge to facilitate human-building interaction and achieve goals like nudging occupants to adopt sustainable and healthy behaviors. A comprehensive data collection was conducted through online surveys, in which 307 valid responses with participant's personal profile information, their perceptions of smart home assistants, and their feedback to our designed messages were collected. The first manuscript compared participants' responses to traditional plain-text energy-saving suggestions and suggestions provided by smart home assistants. The nudging effect of smart home assistants was justified to be significant in affecting occupant's energy-saving behaviors. Occupant's thermal comfort range, smart home device previous experience, values and beliefs were then proved to have significant impact on their intention in taking the smart home assistant's suggestions. The second manuscript fitted 21 personal characteristics features in machine learning models (SVM, Random Forest, Logistic Regression) to predict occupant's intention and attitude towards energy-saving suggestions. The results indicated that occupant's beliefs about interests in taking actions and beliefs about energy expenses, occupant's education level, residence occupancy type, thermal comfort ranges, and smart home device experiences are important features in occupants' energy-saving behavior intention prediction. This research demonstrates the effect of proactive smart home assistants in human-building interaction as well as the impact of personal characteristic features on occupant's energy-saving behaviors, paving a path to the future development of bi-directional human-building communication.