LLM-based iterative personalization boosted electricity conservation by 0.56 kWh per room-day (18.3 percentage-point higher adjusted saving rate) versus text nudges in a three-arm field trial.
Potential of large language model-powered nudges for promoting daily water and energy conservation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2roles
background 1polarities
background 1representative citing papers
Many LLMs exhibit stronger environmental cognition, affect, and behavioral recommendations than human survey averages and shift with persona prompts.
citing papers explorer
-
Enhancing behavioral nudges with large language model-based iterative personalization: A field experiment on electricity and hot-water conservation
LLM-based iterative personalization boosted electricity conservation by 0.56 kWh per room-day (18.3 percentage-point higher adjusted saving rate) versus text nudges in a three-arm field trial.
-
Greener Than Humans? Environmental Attitudes in Large Language Models
Many LLMs exhibit stronger environmental cognition, affect, and behavioral recommendations than human survey averages and shift with persona prompts.