Using Market Basket Analysis in Management Research

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, pharmacoepidemiology, immunology, and geophysics. 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 theorizing; can address contingency (i.e., moderated) relationships; does not rely on assumptions such as linearity, normality, and residual equal variance, which are often violated when using general linear model–based techniques; allows for the use of data often considered “unusable” and “messy” in management research (e.g., data not collected specifically for research purposes); can help build dynamic theories (i.e., theories that consider the role of time explicitly); is suited to examine relationships across levels of analysis; and is practitioner friendly. We explain how the adoption of MBA is likely to help bridge the much-lamented micro–macro and science–practice divides. We also illustrate that use of MBA can lead to insights in substantive management domains, such as human resource management (e.g., employee benefits), organizational behavior (e.g., dysfunctional employee behavior), entrepreneurship (e.g., entrepreneurs’ identities), and strategic management (e.g., corporate social responsibility). We hope our article will serve as a catalyst for the adoption of MBA as a novel methodological approach in management research.

An Ounce of Prevention Is Worth a Pound of Cure: Improving Research Quality Before Data Collection

“…As noted by Locke (2007), inductive theorizing can lead to important theoretical progress. Evidence of such was provided by Aguinis et al (2013a), who noted that, compared with theory-testing elements, theory-building elements in an empirical article lead to a greater number of citations (Colquitt & Zapata-Phelan 2007). Despite inductive research's ability to facilitate theoretical progress, the fact remains that few of our mainstream journals regularly publish or directly recognize this type of research in their general calls for papers (Eby et al 2009).…”

“…Opening avenues for inductive research is an appropriate step in the right direction. Such research is likely to be facilitated given the vast stores of data being collected by firms in response to the analytics (i.e., Big Data) movement as well as the sharp decrease in the cost of data storage technology (Aguinis et al 2013a). Although the advice in the following sections addresses more specific issues, it is given with the overall goal of facilitating meaningful theoretical progress.…”

Data Mining Model Performance of Sales Predictive Algorithms Based on Rapidminer Workflows

“…Concerning business intelligence processes related to large-scale retail (GDO), in literature are analysed data mining algorithms able to optimize sales by analysing special dashboards for monitoring products in stock, for product facing strategies, and for the activation of promotional activities [15]. The business intelligence tools could be implemented by analysing Market Basket Analysis -MBA-indicators and marketing strategies related to the layout of products in the stores [16]- [20], while the sales activity targeted by type of customers could be carried out by profiling and segmenting customers by processing data from a CRM. Data mining algorithms can be implemented through the use of graphical user interfaces -GUIs-easy to use and compatible with several operating systems [15].…”

A new optimization model for market basket analysis with allocation considerations: A genetic algorithm solution approach

“…In another research, Coscia et al (2016) were used market basket analysis approach to explore cultural consumer behaviours. Obviously, the conducted research on the market basket analysis are not limited to those reviewed papers and for more information interested reader may refer to Holý et al (2017), Olson (2016), Aguinis et al (2013), Kaur and Kang (2016). However, reviewing the related research reveals that the main goal of the market basket analysis and its application is optimization.…”