# Using Large Language Models to Construct Virtual Top Managers: A Method for Organizational Research

arXiv: https://arxiv.org/abs/2601.18512 · HTML: https://mlsanity.com/paper/2601.18512/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jan 2026.

## Built on by (most cited first, 1 of 1)

- [An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction](https://mlsanity.com/paper/2608.20320/) (2026)

## Abstract (arXiv)

This study introduces a methodological framework that uses large language models to create virtual personas of real top managers. Drawing on real CEO communications and Moral Foundations Theory, we construct LLM-based participants that simulate the decision-making of individual leaders. Across three phases, we assess construct validity, reliability, and behavioral fidelity by benchmarking these virtual CEOs against human participants. Our results indicate that theoretically scaffolded personas approximate the moral judgements observed in human samples, suggesting that LLM-based personas can serve as credible and complementary tools for organizational research in contexts where direct access to executives is limited. We conclude by outlining implications for future research using LLM-based personas in organizational settings.