This paper reviews the literature examining how costs of monitoring for, acquiring, and
analyzing firm disclosures–collectively,“disclosure processing costs”–affect investor …

Natural language processing (NLP) is gaining momentum in management research for its
ability to automatically analyze and comprehend human language. Yet, despite its extensive …

We develop FinBERT, a state‐of‐the‐art large language model that adapts to the finance
domain. We show that FinBERT incorporates finance knowledge and can better summarize …

We develop a method that identifies the attention paid by earnings call participants to firms'
climate change exposures. The method adapts a machine learning keyword discovery …

Increasingly, management researchers are using topic modeling, a new method borrowed
from computer science, to reveal phenomenon-based constructs and grounded conceptual …

Natural language is a key form of business communication. Textual analysis is the
application of natural language processing (NLP) to textual data for automated information …

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 …

This study tests the impact of enterprise digital transformation on the information
environment. The results show that while analyst coverage increase significantly and the …

We adapt simple tools from computational linguistics to construct a new measure of political
risk faced by individual US firms: the share of their quarterly earnings conference calls that …

After fitting a topic model to 40,927 COVID-19–related paragraphs in 3,581 earnings calls
over the period Jan. 22–Apr. 30, 2020, we obtain firm-level measures of exposure and …