Corporate Diversity Statements and Employees' Online DEI Ratings: An Unsupervised Machine-Learning Text-Mining Analysis

Following the deaths of many Black Americans in spring 2020, public consciousness rose around the societal mega-threat of racism. In response, many organizations released public statements to condemn racism and affirm their stance on diversity, equity, and inclusion (DEI). However, little is known about the specific thematic contents covered in such diversity statements and their implications on important organizational outcomes. Taking both inductive and deductive approaches, we conducted two studies to advance our understanding in this area. Study 1 employed structural topic modeling (STM)-an advanced unsupervised machine-learning text-mining technique-and comprehensively analyzed the latent semantic topics underlying the diversity statements publicly released by Fortune 1000 companies in late May and early June 2020. The results uncovered six underlying latent semantic topics: (1) general DEI terms, (2) supporting Black community, (3) acknowledging Black community, (4) committing to diversifying the workforce, (5) miscellaneous words, and (6) titles and companies. Furthermore, drawing from the identity-blindness and identity-consciousness theoretical frameworks and leveraging millions of data points of employees' DEI ratings retrieved from Glassdoor.com, Study 2 further tested and supported hypotheses that companies were more positively rated by their employees on organizational diversity and inclusion if they (1) released (vs. did not release) diversity statements and (2) emphasized identity-conscious (vs. identity-blind) topics in their diversity statements. Our findings shed light on important theoretical implications for the current research and offer practical recommendations for organizational scientists and practitioners in diversity management.

Automated summary

This study comprehensively analyzed the thematic contents of diversity statements released by Fortune 1000 companies in response to the rising public consciousness around racism. It uncovered six latent semantic topics and found that companies emphasizing identity-conscious topics in their diversity statements were more positively rated on organizational diversity and inclusion by their employees. The findings have important theoretical implications and practical recommendations for diversity management.