Urban association rules: uncovering linked trips for shopping behavior

TL;DR

This paper introduces urban association rules using the Apriori algorithm to analyze city-wide shopping behaviors from transaction data, revealing linked trips and store visit patterns to aid urban planning and retail strategies.

Contribution

The study presents a novel application of association rules to urban shopping data, enabling city-wide analysis of linked trips and store visit patterns from anonymized bank transactions.

Findings

Identified common linked shopping trips across the city.

Quantified the edge weights of store-to-store transitions.

Provided insights for urban management and retail optimization.

Abstract

In this article, we introduce the method of urban association rules and its uses for extracting frequently appearing combinations of stores that are visited together to characterize shoppers' behaviors. The Apriori algorithm is used to extract the association rules (i.e., if -> result) from customer transaction datasets in a market-basket analysis. An application to our large-scale and anonymized bank card transaction dataset enables us to output linked trips for shopping all over the city: the method enables us to predict the other shops most likely to be visited by a customer given a particular shop that was already visited as an input. In addition, our methodology can consider all transaction activities conducted by customers for a whole city in addition to the location of stores dispersed in the city. This approach enables us to uncover not only simple linked trips such as transition movements between stores but also the edge weight for each linked trip in the specific district. Thus, the proposed methodology can complement conventional research methods. Enhancing understanding of people's shopping behaviors could be useful for city authorities and urban practitioners for effective urban management. The results also help individual retailers to rearrange their services by accommodating the needs of their customers' habits to enhance their shopping experience.