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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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    References listed on IDEAS

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    1. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    2. Thomas Covert & Michael Greenstone & Christopher R. Knittel, 2016. "Will We Ever Stop Using Fossil Fuels?," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 117-138, Winter.
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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. Blonz, Joshua & Palmer, Karen & Wichman, Casey & Wietelman, Derek C., 2021. "Smart Thermostats, Automation, and Time-Varying Prices," RFF Working Paper Series 21-20, Resources for the Future.

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    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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