There is both a need and an opportunity to develop analytics-driven approaches to address
many significant challenges facing society. Toward this end, this article presents an “ESG …

abstract Research Summary Researchers increasingly use unstructured text data to
construct quantitative variables for analysis. This goal has traditionally been achieved using …

When managing major disasters, authorities may ask residents to comply with certain
guidelines that change community members' daily routines. In these situations, authorities …

Topic models are becoming a frequently employed tool in the empirical methods repertoire
of information systems and management scholars. Given textual corpora, such as consumer …

Topic modeling methods such as latent Dirichlet allocation (LDA) are powerful tools for
analyzing massive amounts of textual data. They have been used extensively in information …

On digital platforms, thumbnails are omnipresent promotion tools for hedonic media goods.
However, thumbnail designs still constitute a black box regarding their effects on …

Although social media has helped online newspapers by allowing users to organically share
articles, some have argued that it has cannibalized and hurt newspapers through reduced …

Abstract Machine learning is a growing method for causal inference. In machine learning
settings, prediction errors are a commonly overlooked problem that can bias results and …

When organizations adopt artificial intelligence (AI) to recognize individuals' negative
emotions and accordingly allocate limited resources, strategic users are incentivized to …

Researchers are increasingly leveraging machine learning (ML) or artificial intelligence
technologies (AI) to predict feature variables and use them as regressors in subsequent …