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The Human Perils of Scaling Smart Technologies: Evidence from Field Experiments

Author

Listed:
  • Alec Brandon
  • Christopher M. Clapp
  • John A. List
  • Robert D. Metcalfe
  • Michael Price

Abstract

Smart-home technologies have been heralded as an important way to increase energy conservation. While in vitro engineering estimates support optimism, little has been done to explore whether such estimates scale beyond the lab. We estimate the causal impact of smart thermostats on energy use via two novel framed field experiments in which a random subset of treated households have a smart thermostat installed in their home. Examining 18 months of associated high-frequency data on household energy consumption, yielding more than 16 million hourly electricity and daily natural gas observations, we find little evidence that smart thermostats have a statistically or economically significant effect on energy use. Using almost four million observations of system events including human interactions with their smart thermostat, we find that user behavior dampens energy savings and explains the discrepancy between estimates from engineering models, which assume a perfectly compliant subject, and actual households, who are occupied by users acting in accord with behavioral economists’ conjectures. In this manner, our data document a keen threat to the scalability of new user-based technologies.

Suggested Citation

  • Alec Brandon & Christopher M. Clapp & John A. List & Robert D. Metcalfe & Michael Price, 2022. "The Human Perils of Scaling Smart Technologies: Evidence from Field Experiments," NBER Working Papers 30482, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:30482
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    Cited by:

    1. John A. List, 2024. "Optimally generate policy-based evidence before scaling," Nature, Nature, vol. 626(7999), pages 491-499, February.
    2. Löschel, Andreas & Rodemeier, Matthias & Werthschulte, Madeline, 2023. "Can self-set goals encourage resource conservation? Field experimental evidence from a smartphone app," European Economic Review, Elsevier, vol. 160(C).
    3. John A. List, 2026. "The Economics of Scaling Early Childhood Programs: Lessons from the Chicago School," Journal of Political Economy, University of Chicago Press, vol. 134(1), pages 1-48.
    4. Joshua Blonz & Karen Palmer & Casey J. Wichman & Derek C. Wietelman, 2025. "Smart Thermostats, Automation, and Time-Varying Prices," American Economic Journal: Applied Economics, American Economic Association, vol. 17(1), pages 90-125, January.
    5. Dritjon Gruda & Paul Hanges, 2024. "Turn down for watt: Community fit and thermal comfort habituation predict average household heating energy consumption," PLOS Climate, Public Library of Science, vol. 3(7), pages 1-16, July.

    More about this item

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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