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1. Measuring higher-order rationality with belief control

   https://doi.org/10.1017/eec.2025.5  

   Chen, Wei James; Fong, Meng-Jhang; Lin, Po-Hsuan (May 2025, Experimental Economics)

   Determining an individual’s strategic reasoning capability based solely on choice data is a complex task. This complexity arises because sophisticated players might have non-equilibrium beliefs about others, leading to non-equilibrium actions. In our study, we pair human participants with computer players known to be fully rational. This use of robot players allows us to disentangle limited reasoning capacity from belief formation and social biases. Our results show that, when paired with robots, subjects consistently demonstrate higher levels of rationality, compared to when paired with human players. Furthermore, players’ rationality levels are relatively stable across games when paired with robot players, even though those with intermediate rationality levels exhibit inconsistency across games. Leveraging our experimental design, we identify and document potential causes of this inconsistency. 

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2. Consumer-Based Carbon Costs: Integrating Consumer Carbon Preferences in Electricity Markets

   https://doi.org/10.1109/TEMPR.2026.3671642  

   Jiang, Wenqian; Rangarajan, Aditya; Roald, Line (January 2026, IEEE Transactions on Energy Markets, Policy and Regulation)

   An increasing share of consumers care about the carbon footprint of their electricity. This paper analyzes a method to integrate consumer carbon preferences in the electricity market-clearing by introducing consumer-based carbon costs and a carbon allocation mechanism. Specifically, consumers submit not only bids for power but also assign a cost to the carbon emissions incurred by their electricity use. The carbon allocation mechanism then assigns emissions from generation to consumers to minimize overall carbon costs. Our analysis starts from a previously proposed centralized market clearing formulation that maximizes social welfare under consideration of generation costs, consumer utility, and consumer carbon costs. We then derive an equivalent equilibrium formulation that incorporates a carbon allocation problem and gives rise to a set of carbonadjusted electricity prices for both consumers and generators. We prove that the carbon-adjusted prices are higher for lowemitting generators and consumers with high carbon costs. Further, we prove that this new paradigm satisfies the same desirable market properties as standard electricity markets based on locational marginal prices, namely revenue adequacy and individual rationality, and demonstrate that a carbon tax on generators is equivalent to imposing a uniform carbon cost on consumers. Using a simplified three-bus system and the RTSGMLC system, we illustrate that consumer-based carbon costs contribute to greener electricity market clearing both through generation redispatch and demand reductions. 

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3. Informational nudges in conservation auctions: A field experiment with U.S. farmers

   https://doi.org/10.1016/j.foodpol.2023.102504  

   Wallander, Steven; Paul, Laura A; Ferraro, Paul J; Messer, Kent D; Iovanna, Richard (October 2023, Food Policy)

   In the U.S., the fifth largest ‘‘crop’’ is vegetation dedicated to environmental conservation. Over 22 million acres of perennial covers are planted on environmentally sensitive land enrolled in U.S. Department of Agriculture’s Conservation Reserve Program (CRP), one of the largest agricultural conservation programs in the world. About half of CRP lands are enrolled through a complex reverse auction called the General Signup. The communication of program options to participants could have an important behavioral impact. Psychologists have found that information presentation in complex decision environments can interact with the bounded rationality and cognitive biases of decision makers. We tested two changes in the status quo CRP decision environment using an incentivized, lab-in-the-field experiment with 701 prior General Signup participants. First, program participants typically make an active choice over which cover practice to plant and how much of a discount to offer, where the discount is a reduction in their annual program payment. Changing that default to an opt-out, high-scoring offer resulted in a 13 percentage point increase in selection of the best practice and a 48 percent increase in the average discount. In the actual CRP, that increase in discounting would reduce total program costs by about $30 million per signup. Second, shifting to real-time updating of offer scores modestly reduced the frequency with which participants revised their offers, suggesting a reduction in transaction costs. From a policy perspective, these results suggest that small changes in conservation auctions could both improve the quality of conservation practices and reduce program costs. 

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4. Understanding inspiration: Insights into how designers discover inspirational stimuli using an AI-enabled platform

   https://doi.org/10.1016/j.destud.2023.101202  

   Kwon, Elisa; Rao, Vivek; Goucher-Lambert, Kosa (September 2023, Design Studies)

   Throughout the design process, designers encounter diverse stimuli that influence their work. This influence is particularly notable during idea generation processes that are augmented by novel design support tools that assist in inspiration discovery. However, fundamental questions remain regarding why and how interactions afforded by these tools impact design behaviors. This work explores how designers search for inspirational stimuli using an AI-enabled multi-modal search platform, which supports queries by text and non-text-based inputs. Student and professional designers completed a think-aloud design exploration task using this platform to search for stimuli to inspire idea generation. We identify expertise and search modality as factors influencing design exploration, including the frequency and framing of searches, and the evaluation and utility of search results. 

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5. Exploring the Effectiveness of Interactive Preference Learning for Adapting Designs to Abstract Semantic Attributes

   https://doi.org/10.1115/1.4069687  

   Nandy, Ananya; Goucher-Lambert, Kosa (April 2026, Journal of Mechanical Design)

   Abstract semantic attributes of designs (e.g., comfortable, luxurious, and durable) play a significant role in the assessment of user-facing products, capturing intangible factors that people may consider aside from performance requirements. However, due to the difficulty of mapping highly subjective and varying perceptions to specific design features, it remains a challenge to quickly and accurately translate these qualities into designs using computational design tools. Seeking to align computational and human representations of subjective design information, we investigate the utility of adapting representations of semantic attributes to designers’ perceptions through interactive models. A study is conducted in which users evaluate parameterized drinking mugs, indicating their perceptions of how comfortable each is to hold. Interactive Bayesian optimization is used to adaptively arrive at a design that optimizes this subjective quantity for each participant individually. Participants (N = 31) guide the model by providing their own decisions or building off of empirical data from a prior group of participants (N = 25). The resulting designs are evaluated across different scenarios, demonstrating the extent to which outputs of noninteractive models can be used to represent a subjective, semantic attribute and how interactive models may improve perceived alignment between human intent and computionally generated outputs. 

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