Practice Paper—AI-Driven Behavioral Nudges for Organizations: An Integrative System for Sustainable Resource Management
Christopher Amaral, Ceren Kolsarici, Iina Ikonen, Nicole Robitaille
Marketing Science · 2026 · Volume 45 · Issue 3
Abstract
In today’s business environment, organizations face increasing pressure to manage resources efficiently while meeting financial and sustainability goals. This paper presents a novel integrative approach that combines artificial intelligence-driven forecasting with behavioral interventions to help businesses optimize energy consumption under critical peak pricing schemes, reduce costs, and align with sustainability initiatives. We conducted a multiphase longitudinal study with large organizations leveraging neural network time-series modeling to improve peak energy demand predictions and behaviorally informed communications leveraging planning prompts to enhance compliance with curtailment recommendations. The proposed intervention reduces energy consumption during critical peaks by 42%, yielding average net annual savings of approximately $230,000 per organization. Through a nationwide rollout, we estimate that hourly peak-period carbon dioxide emissions could be reduced by approximately 6,500 tonnes, equivalent to roughly 1 million Canadian households’ daily energy consumption. The results demonstrate significant financial savings and reduced environmental impact, benefiting organizations, regulators, service providers, and society. We contribute to research on resource management, systems thinking, and nudging in an organizational context by aligning technological tools with human processes. This work offers a practical, business-oriented solution to real-world challenges, creating value for multiple stakeholders and positioning firms for long-term success in an increasingly resource-constrained world. History: Olivier Touba served as the senior editor. This paper was accepted through the Marketing Science Practice Paper Publication Process. Funding: This work was supported by the Natural Sciences and Engineering Research Council of Canada [Grant ALLRP 592457-2023]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mksc.2024.1154 .
Keywords
artificial intelligence, behavioral nudging, sustainability, dynamic pricing, critical peak pricing, energy consumption
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