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

Journal of Marketing(2022)

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摘要
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, we make a case for an “empirics-first” approach. Empirics-first refers to research that (i) is grounded in (originates from) a real-world marketing phenomenon, problem, or observation, (ii) involves obtaining and analyzing data, and (iii) 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 surface novel research questions untethered to theory. The present paper 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 present paper offers guidance on how to implement empirics-first research and how it can lead to valuable knowledge development. Advice is also offered to authors on how to report EF research and to reviewers and to editorial teams on how to evaluate it. Our ultimate objective is to pave a way for empirics-first to enter the mainstream of academic marketing research.
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关键词
empirical research,marketing theory,relevance,empirical generalizations,research methods
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