Dissecting Corporate Culture Using Generative AI

Abstract

We conduct the first large-scale study of how different stakeholder groups assess corporate culture and quantify the economic implications of those differences. We employ generative AI to analyze analyst reports, call transcripts, and employee reviews, and organize the extracted information into a knowledge graph that links a culture type to its perceived causes and effects. We demonstrate that the divergence in different stakeholder groups’ assessment of culture aligns with their distinct roles and economic incentives. Moreover, we show that analysts’ culture analyses are incorporated into stock recommendations and target prices, and investors react to divergence in stakeholders’ assessment of culture.

Keywords: corporate culture, equity analysts, analyst reports, earnings calls, employee reviews, lange language models, generative AI, cause-effect knowledge graph, GPT

JEL Classification: C45, C55, G32, G34, Z1