Learning from Data: An Empirics-First Approach to Relevant Knowledge Generation

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Abstract

A theory-first paradigm tends to be the dominant approach in much academic marketing research. In this approach, a theory is borrowed, refined, or developed and then tested empirically. In this challenging-the-boundaries article, the authors make a case for an empirics-first approach. “Empirics-first” refers to research that (1) is grounded in (originates from) a real-world marketing phenomenon, problem, or observation, (2) involves obtaining and analyzing data, and (3) produces valid marketing-relevant insights without necessarily developing or testing theory. The empirics-first approach is not antagonistic to theory but rather can serve as a stepping-stone to theory. The approach lends itself well to today’s data-rich environment, which can reveal novel research questions untethered to theory. The present article describes the underlying principles of an empirics-first approach, which consists of exploring a domain purposefully without preconceptions. Using a rich set of published examples, the authors offer guidance on how to implement empirics-first research and how it can lead to valuable knowledge development. Advice is also offered to scholars on how to report empirics-first research and to reviewers and to editorial teams on how to evaluate it. The ultimate objective is to pave a way for the empirics-first approach to enter the mainstream of academic marketing research.

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APA

Golder, P. N., Dekimpe, M. G., An, J. T., van Heerde, H. J., Kim, D. S. U., & Alba, J. W. (2023). Learning from Data: An Empirics-First Approach to Relevant Knowledge Generation. Journal of Marketing, 87(3), 319–336. https://doi.org/10.1177/00222429221129200

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