Abstract

Market basket analysis (MBA), also known as association rule mining or affinity analysis, is a data-mining technique that originated in the field of marketing and more recently has been used effectively in other fields such as bioinformatics, nuclear science, and immunology. The goal of MBA is to identify relationships (i.e., association rules) between groups of products, items, or categories. We describe MBA and explain that it allows for inductive and deductive theorizing, can model contingency theories, does not rely on assumptions that are often untenable (as general linear model–based techniques do), allows for the use of data often considered “unusable” in management research, is uniquely suited to handle data considered “messy” and also data collected at different levels of analysis, and is practitioner-friendly. We explain how the adoption of MBA is likely to help bridge the micro–macro and science–practice divides and illustrate that its use can lead to important insights in substantive managemen...

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