AIM2026

UPDATE

The 6th AIM Conference in 2026 was a success with about 135 high-quality presentations. We would like to express our heartfelt gratitude to all the presenters, participants, and sponsors who made it possible. As we conclude the conference, we are delighted to announce this year's award winners.

The selection process began with session chairs nominating standout papers they believed merited award consideration. In parallel, several conference co-chairs reviewed the presented papers and added their own nominations. Some award sponsors also identified noteworthy contributions during the sessions.

From this pool of nominees, the co-chairs carefully reviewed the papers and cast their individual votes for those they deemed most deserving. These became our Finalists. Among the finalists, those receiving strong support from the co-chairs were named our Winners.

Congratulations to all Winners and Finalists!

WINNERS

Dominique Hanssens Best PhD Paper Award ($5,000)

• Zhuoyan Ma (Boston University), “Collaborate to Elevate: Leveraging Social Capital in Digital Creator Collaborations.”

• Cyrille Grumbach (ETH Zurich), “The Innovation-Diversity Tradeoff in AI-Augmented Evaluations.”

• Ruben R Salas (Wharton), “AI-Mediated Marketing: Constrained Content Optimization for LLM Visibility”

Vithala Rao Best PhD Paper Award ($5,000)

• Binglu Wang (Northwestern), “Human–AI Collaboration in Science at Scale: A Large-scale Randomized Field Experiment”

• Ruru Hoong (Harvard), “Calibrated Coarsening: Designing Information for AI-Assisted Decisions.”

• Jingwei Dai, “Algorithmic Illusion? An Empirical Study of Generative AI Image Ban on a Food Delivery Platform.”

Steven Shugan Best Junior Faculty Paper Award ($5,000)

• Francesca Bonetti (HEC), “Do LLMs Succumb to Neutrality Bias? Evidence from LLMs Predicting the Future from CEO Letters.”

Cheryl and Gerard Tellis Best Junior Faculty Award ($5,000)

• Pan Li (Georgia Tech), “All Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanations with Large Language Models.”

• Andrea Contigiani (Ohio State), “Experimentation in the Age of Generative AI: Evidence from ChatGPT.”

FINALISTS

Winners excluded. Only the presenting author is listed. Finalists are listed in alphabetical order.

• Pooria Assadi, "Beyond Accuracy: A Cost-of-Error Framework for Economic Evaluation of AI"

• Adrien Audoin, "When Humans Lead and AI Supports:  Task Allocation and Performance in Entrepreneurial Social Media Engagement"

• Chengxin Cao, "AI-Augmented Green Jobs and Corporate Climate Performance: Evidence from U.S. Firms and Facilities"

• Winston Chen, "AI and Appropriation Risk"

• Shon Hiatt, "Decoding the Role of AI Human and Structural Capital in Novel Drug Discoveries using a Configurational Approach"

• Zijing "Jimmy" Hu, "Discovery Design in Long-Tail Marketplaces: Evidence from a Digital Music Platform"

• Jibin Jun, "When Innovation Gets Hollow: The Impact of Generative AI on Patent Quality"

• Leonard Kinzinger, "Synthetic Personalities: How Well Can LLMs Mimic Individual Respondents Using Socio-Economic Microdata?"

• Seungcheol Austin Lee, "How AI Refines Authorship: Evidence from Text and Content Analysis"

• Samuel Levy, "Profit-Preserving Privacy for Recommender Systems"

• Yufan (Frank) Lin, "A Standardized Protocol for Text-Based Construct Classification Using Large Language Models"

• Giacomo Mantegazza, "Artificial Intelligence and Spontaneous Collusion"

• Raveesh Mayya, "Mitigating Spoken Language Barriers in AI-Assisted Programming: Evidence from a Field Experiment"

• Patryk Perkowski, "When Can We Trust Experiments on Digital Twins? A Potential Outcomes Framework for Causal Inference with LLM Simulations"

• Yuqing Tang, "Pay Equity and the Decentralization of AI Innovation"

• Matteo Tranchero, "Misleading Science Maps: Firms’ Strategic Responses to Data Malpractice in Alzheimer’s Research"

• Wenyan Tuo, "Platform Brands Rising: The Competitive and Perceptual Consequences of Amazon Brand Entry"

• Mengxin Wang, "Large Language Models for Market Research: A Data-augmentation Approach"

• Yuyan Wang, "Can Explanations Improve Recommendations? A Joint Optimization with LLM Reasoning"

• Linhui Wu, "Redistributing Errors: How AI Transforms the Omission-Commission Trade-off in Hierarchical Organizations"

• Miao Ben Zhang, "The  Household Impact of Generative AI: Evidence from Internet Browsing Behavior"