Dissecting Corporate Culture Using Generative AI – Insights from Analyst Reports

88 Pages Posted: 1 Sep 2023 Last revised: 16 Feb 2024

See all articles by Kai Li

Kai Li

University of British Columbia (UBC) - Sauder School of Business; Asian Bureau of Finance and Economic Research (ABFER); China Academy of Financial Research (CAFR); European Corporate Governance Institute (ECGI); Canadian Sustainable Finance Network (CSFN)

Feng Mai

University of Iowa - Department of Business Analytics

Rui Shen

The Chinese University of Hong Kong, Shenzhen - School of Management and Economics; Shenzhen Finance Institute

Chelsea Yang

University of British Columbia (UBC) - Sauder School of Business

Tengfei Zhang

Rutgers University - Rutgers School of Business-Camden

Date Written: February 15, 2024

Abstract

Our study is among the first in finance, accounting, and economics to apply generative AI models as reasoning agents on analyst reports to gain insights into analysts’ views of corporate culture. We employ generative AI (ChatGPT) to analyze 2.4 million analyst reports between 2000 and 2020. Generative AI organizes analysts’ views into a knowledge graph that links different cultural values to their perceived causes and effects. In terms of influencing factors for corporate culture, analysts identify business strategy as a key factor for a large number of cultural values – customer-oriented, operations-oriented, innovation, results-oriented, adaptability, integrity, and risk control; and management team for teamwork, innovation, results-oriented, adaptability, integrity, risk control, and people-oriented values. In terms of business outcomes shaped by corporate culture, analysts identify innovation and adaptability as affecting almost all aspects of business operations, ranging from market share and growth to corporate ESG practices, while other values such as customer-oriented, operation-oriented, or people-oriented have less impact on business outcomes. We further provide evidence that analysts’ views of culture are distinct from values presented on corporate websites, and/or from the views of executives and employees. Finally, we show that analysts’ views of corporate culture are reflected in their stock recommendations and target price forecasts as well as impact price reactions to the release of their reports. We conclude that analysts’ research on corporate culture offers new insights into its causes and effects, and that we are closer to establishing the culture-firm value link.

Keywords: corporate culture; equity analysts; analyst reports; large language models; generative AI; ChatGPT; cause-effect knowledge graph

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

Suggested Citation

Li, Kai and Mai, Feng and Shen, Rui and Yang, Chelsea and Zhang, Tengfei, Dissecting Corporate Culture Using Generative AI – Insights from Analyst Reports (February 15, 2024). Available at SSRN: https://ssrn.com/abstract=4558295 or http://dx.doi.org/10.2139/ssrn.4558295

Kai Li (Contact Author)

University of British Columbia (UBC) - Sauder School of Business ( email )

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Asian Bureau of Finance and Economic Research (ABFER) ( email )

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Singapore

China Academy of Financial Research (CAFR) ( email )

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Shanghai P.R.China, 200030
China

European Corporate Governance Institute (ECGI) ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels
Belgium

Canadian Sustainable Finance Network (CSFN) ( email )

Queens University
Kingston, ON
Canada

HOME PAGE: http://https://smith.queensu.ca/centres/isf/research/network.php

Feng Mai

University of Iowa - Department of Business Analytics ( email )

Iowa City
United States

Rui Shen

The Chinese University of Hong Kong, Shenzhen - School of Management and Economics ( email )

2001 Longxiang Road, Longgang District
Shenzhen, 518172
China

Shenzhen Finance Institute ( email )

Chelsea Yang

University of British Columbia (UBC) - Sauder School of Business ( email )

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada

Tengfei Zhang

Rutgers University - Rutgers School of Business-Camden ( email )

227 Penn Street
Camden, NJ 08102
United States

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