Research keywords: behavior change, decision making, psychology, intervention, technology adoption, smart grid, energy use, power systems, electric vehicles, transportation behavior, sustainability, behavioral spillover, food-energy-water nexus, self-perception, symbolic attributes, cognitive attribution, cognitive bias, social influence
Biography
As an environmental psychologist, my work strives to advance psychological theory while producing insights that can be applied to benefit the environment and society. Broadly, I am interested in:
(1) illuminating the psychological, social, and contextual factors that influence individual-level behavior pertaining to environmental resource consumption
(2) developing and evaluating interventions aimed at promoting sustainable behavior
(3) investigating the cognitive, emotional, and social factors that influence intervention effectiveness.
My work takes an interdisciplinary approach grounded in behavioral science with a focus on quantitative methods (e.g., experimental, survey), often involving collection of high-resolution consumption (e.g., smart electric meter) and other consumer data. Key areas of interest include how individuals use energy in households, the adoption and use of energy efficient technologies (e.g., electric cars), and behavioral spillover across the food-energy-water nexus. My work has been supported by the National Science Foundation, US Department of Energy, Los Angeles Department of Water and Power, World Wildlife Fund, and US Army Research Office. I hold a B.S. in Psychology / Ecology from the University of California, San Diego, and a Master’s in Psychology, graduate certificate in Sustainable Cities, and Ph.D. in Psychology from the University of Southern California. For information on current projects in my lab, click here.
Selected Publications
(*denotes student I have mentored)
*White, L.V., & Sintov, N. D. (2018). Inaccurate consumer perceptions of monetary savings in a demand-side response programme predict programme acceptance. Nature Energy, 1101–1108. https://doi.org/10.1038/s41560-018-0285-y
Sintov, N.D., & Schuitema, G. (2018). Odd couple or perfect pair? Tensions and opportunities in academia-industry collaborations. Energy Policy, 117, 247-251. https://doi.org/10.1016/j.enpol.2018.03.021
White, L., & Sintov, N. (2017). You are what you drive: Environmentalist and social innovator symbolism drive electric vehicle adoption intentions. Transportation Research Part A: Policy and Practice, 99, 94-113. doi.org/10.1016/j.tra.2017.03.008
Sintov, N.D., & Schultz, P.W. (2017). Making smart homes more sustainable with adjustable green defaults. Sustainability special issue on the Advent of Smart Homes, 9(4), doi:10.3390/su9040622
Schuitema, G., & Sintov, N. (2017). Should we quit our jobs? Challenges, barriers, and recommendations for interdisciplinary energy research. Energy Policy, 101, 246-250.
Sintov, N., *Kar, D., Nguyen, T., Fang, F., Hoffman, K., Lyet, A., & Tambe, M. (2017). Keeping it real: Using real-world problems to teach AI to Diverse Audiences. Artificial Intelligence Magazine.
Schuitema, G., & Sintov, N. (2017). Should we quit our jobs? Challenges, barriers, and recommendations for interdisciplinary energy research. Energy Policy, 101, 246-250.
*Chen, B., & Sintov, N.D. (2016). Bridging the gap between technology adoption and protecting natural resources: Predicting intentions to adopt energy management technologies in California. Energy Research and Social Science, 22, 210-223.
*Merrill, R. & Sintov, N.D. (2016). An affinity to commons model of public support for clean energy policy. Energy Policy, 99, 88-99.
Sintov, N.D., Dux, E., *Tran, A., & Orosz, M. (2016). What goes on behind closed doors? How college dormitory residents change to save energy during a competition-based energy reduction intervention. International Journal for Sustainability in Higher Education, 17, 451-470.
Konis, K., Orosz, M., & Sintov, N. (2016). A window into occupant-driven energy outcomes: leveraging sub-metering infrastructure to examine psychosocial factors driving long-term outcomes of short-term competition-based energy interventions. Journal of Energy & Buildings, doi:10.1016/j.enbuild.2016.01.005
Sintov, N.D. & Schultz, P.W. (2015). Unlocking the potential of smart grid technologies with behavioral science. Frontiers in Psychology, 6. doi: 10.3389/fpsyg.2015.00410
Kwac, J., Tan, C.-W., Sintov, N., Flora, J., & Rajagopal, R. (2013). Utility customer segmentation based on smart meter data: Empirical study. Proceedings of the IEEE SmartGrid Comm meeting (pp. 720-725).
Sintov, N.D., Desario, G., & Prescott, C.A. (2010). Effectiveness of a Web-based Intervention in Promoting Energy Conservation in a University Residential Setting. The climate for energy efficiency is now (pp.7-322 – 7-336). Washington, DC: American Council for an Energy Efficient Economy.
Sintov, N., *Kar, D., Nguyen, T., Fang, F., Hoffman, K., Lyet, A., & Tambe, M. (2016). From the lab to the classroom and beyond: Extending a Game-Based Research Platform for Teaching AI to Diverse Audiences. Proceedings of the Association for the Advancement of Artificial Intelligence 6th Symposium on Educational Advances in Artificial Intelligence.
*Kar, D., Fang, F., Delle Fave, F. M., Sintov, N., Tambe, M., and Lyet, A. (2016). Comparing Human Behavior Models in Repeated Stackelberg Security Games: An Extended Study. Journal of Artificial Intelligence, 240, 65-103. doi.org/10.1016/j.artint.2016.08.002
Fang, F., Nguyen, T., *Ford, B., Sintov, N., & Tambe, M. (2015). Introduction to Green Security Games. Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Cognitive Knowledge Acquisition and Applications.
*Kar, D., Fang, F., Delle Fave, F. M., Sintov, N., & Tambe, M. (2015). A game of thrones: When human behavior models compete in repeated stackelberg security games. Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
*Kar, D., Fang, F., Delle Fave, F. M., Sintov, N., Tambe, M., & van Wissen, A. (2015). Effectiveness of Probability Perception Modeling and Defender Strategy Generation Algorithms in Repeated Stackelberg Games. Proceedings of the 29th annual Conference for the Advancement of Artificial Intelligence (AAAI).
