Fixed effects models versus mixed effects models for clustered data: Reviewing the approaches, disentangling the differences, and making recommendations.
Clustered data are common in many fields. Some prominent examples of clustering are
employees clustered within supervisors, students within classrooms, and clients within …
employees clustered within supervisors, students within classrooms, and clients within …
Marketing analytics for data-rich environments
The authors provide a critical examination of marketing analytics methods by tracing their
historical development, examining their applications to structured and unstructured data …
historical development, examining their applications to structured and unstructured data …
Addressing endogeneity in international marketing applications of partial least squares structural equation modeling
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 …
international marketing research. Users of PLS-SEM have, however, largely overlooked the …
Marketing analytics capability, artificial intelligence adoption, and firms' competitive advantage: Evidence from the manufacturing industry
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 …
today's industrial marketing management. Although many firms have embraced analytics …
Revisiting Gaussian copulas to handle endogenous regressors
Marketing researchers are increasingly taking advantage of the instrumental variable (IV)-
free Gaussian copula approach. They use this method to identify and correct endogeneity …
free Gaussian copula approach. They use this method to identify and correct endogeneity …
How and when do big data investments pay off? The role of marketing affordances and service innovation
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 …
with superior performance. However, firms investing in big data often fail to attain those …
Handling endogenous regressors by joint estimation using copulas
We propose a new statistical instrument-free method to tackle the endogeneity problem. The
proposed method models the joint distribution of the endogenous regressor and the error …
proposed method models the joint distribution of the endogenous regressor and the error …
Instrumental variables estimation: Assumptions, pitfalls, and guidelines
Researchers striving to ensure rigor in their scientific findings face a common pitfall:
Endogeneity. To tackle this problem, scholars have increasingly adopted instrumental …
Endogeneity. To tackle this problem, scholars have increasingly adopted instrumental …
Addressing endogeneity without instrumental variables: An evaluation of the gaussian copula approach for management research
The availability and quality of instrumental variables (IV) are frequent concerns in empirical
management research when trying to overcome endogeneity problems. For endogeneity …
management research when trying to overcome endogeneity problems. For endogeneity …
Addressing endogeneity in marketing models
The marketing literature uses regression models based on observational data for causal
inferences. Endogeneity issues are a threat to inferring causal effects. Endogeneity—the …
inferences. Endogeneity issues are a threat to inferring causal effects. Endogeneity—the …