Guenther, P., Guenther, M., Misra, S. et al. (2 more authors) (Accepted: 2025) Propensity score modeling for business marketing research. Industrial Marketing Management. ISSN 0019-8501 (In Press)
Abstract
Propensity score modeling (PSM) is a powerful statistical technique that, in the appropriate data contexts, addresses biases from confounding and selection, which can otherwise distort results and lead to erroneous inferences. However, while the number of PSM applications in business marketing research is growing, many studies mistakenly assume that PSM is a universal solution for all endogeneity issues. Often, studies lack sufficient detail about the specific endogeneity problem they aim to address, which is a critical issue, as PSM is appropriate only for certain types of endogeneity. Additionally, essential tests to confirm the validity and robustness of PSM results are frequently overlooked or insufficiently reported, raising concerns about the reliability of findings. This article aims to enhance the rigor of PSM applications in business marketing research by offering updated practical guidance on its appropriate use, key aspects to report, and common misconceptions and errors to avoid. A practical example of PSM implementation in Stata is included, along with a comprehensive checklist of justifications and best practices to guide business marketing researchers in their future PSM-based studies.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author produced version of an article accepted for publication in Industrial Marketing Management, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | propensity score modeling; review; results assessment; guidelines |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Marketing Division (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Mar 2025 14:09 |
Last Modified: | 26 Mar 2025 14:09 |
Status: | In Press |
Publisher: | Elsevier |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:224838 |