Clustered data are common in many fields. Some prominent examples of clustering are
employees clustered within supervisors, students within classrooms, and clients within …

Data-driven analytics and artificial intelligence (AI) have become the most crucial aspects of
today's industrial marketing management. Although many firms have embraced analytics …

Marketing researchers are increasingly taking advantage of the instrumental variable (IV)-
free Gaussian copula approach. They use this method to identify and correct endogeneity …

Partial least squares structural equation modeling (PLS-SEM) has become a key method in
international marketing research. Users of PLS-SEM have, however, largely overlooked the …

Researchers striving to ensure rigor in their scientific findings face a common pitfall:
Endogeneity. To tackle this problem, scholars have increasingly adopted instrumental …

The availability and quality of instrumental variables (IV) are frequent concerns in empirical
management research when trying to overcome endogeneity problems. For endogeneity …

The authors provide a critical examination of marketing analytics methods by tracing their
historical development, examining their applications to structured and unstructured data …

Big data technologies and analytics enable new digital services and are often associated
with superior performance. However, firms investing in big data often fail to attain those …

The marketing literature uses regression models based on observational data for causal
inferences. Endogeneity issues are a threat to inferring causal effects. Endogeneity—the …

Endogeneity bias represents a critical issue for the analysis of cause and effect
relationships. Although the existence of endogeneity can produce severely biased results, it …