Extracting Consumer Purchase Value from Consumer Signalling: The Case of Country of Origin
(A2023-114228)

AUTHORS

Rafid Ur Rahman, Leeds University Business School, University of Leeds; Martin Heinberg, Leeds University Business School, University of Leeds; Sourindra Banerjee, University of Leeds; Constantine Katsikeas, Leeds University Business School

ABSTRACT

Abundant consumer data have complicated rather than simplified decision making for marketers. A plethora of data raises the question of which variables–readily accessible for retailers–contain reliable information about future consumer purchase value to guide strategic decisions. To address this issue, this study builds on signalling theory and explores Country of Origin (COO) and COO diversity as analytical tools to extract insights from consumer purchase data. Importantly, authors theorize that a specific COO as well as COO diversity in a consumer’s purchase basket can predict future consumer purchase value for retailers. This study observes over a million transactions of 327,863 consumers across 600 brands. Our findings suggest that COO and COO diversity allow retailers to successfully distinguish high from low purchase value consumers. Furthermore, this study identifies boundary conditions related to high-involvement product categories and purchase frequency.