Measuring Corporate Culture Using Machine Learning

104 Pages Posted: 21 Oct 2018 Last revised: 29 Jun 2020

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

Stevens Institute of Technology

Rui Shen

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

Xinyan Yan

University of Dayton

Date Written: June 28, 2020

Abstract

We create a culture dictionary using one of the latest machine learning techniques—the word embedding model—and 209,480 earnings call transcripts. We score the five corporate cultural values of innovation, integrity, quality, respect, and teamwork for 62,664 firm-year observations over the period 2001–2018. We show that an innovative culture is broader than the usual measures of corporate innovation – R&D expenses and the number of patents. Moreover, we show that corporate culture correlates with business outcomes, including operational efficiency, risk-taking, earnings management, executive compensation design, firm value, and deal making, and that the culture-performance link is more pronounced in bad times. Finally, we present suggestive evidence that corporate culture is shaped by major corporate events, such as mergers and acquisitions.

Keywords: machine learning; word embedding; semi-supervised learning; corporate culture; cultural fit; acculturation; mergers and acquisitions

JEL Classification: C45; G34

Suggested Citation

Li, Kai and Mai, Feng and Shen, Rui and Yan, Xinyan, Measuring Corporate Culture Using Machine Learning (June 28, 2020). Available at SSRN: https://ssrn.com/abstract=3256608 or http://dx.doi.org/10.2139/ssrn.3256608

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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China Academy of Financial Research (CAFR)

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European Corporate Governance Institute (ECGI) ( email )

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Canadian Sustainable Finance Network (CSFN) ( email )

Queens University
Kingston, ON
Canada

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Feng Mai

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
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 )

Xinyan Yan

University of Dayton ( email )

300 College Park
Dayton, OH 45469
United States

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