A case for the empirics-first approach that develops marketing-relevant insights from real-world problems

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Researchers from Dartmouth College, Tilburg University, University of Technology Sydney, University of New South Wales, University of Sydney, and University of Florida published a new article in the Journal of Marketing that advocates for an empirics-first (EF) approach for research in marketing.

The study, forthcoming in the Journal of Marketing, is titled "Learning from Data: An Empirics-First Approach to Relevant Knowledge Generation" and is authored by Peter N. Golder, Marnik G. Dekimpe, Jake T. An, Harald J. van Heerde, Darren S. U. Kim, and Joseph W. Alba.

Over 50 years ago, academic across several business disciplines was criticized for falling short of scientific standards. This led to a away from description and toward theory—a shift that was entirely appropriate and broadly successful. But has the pendulum moved too far? Is scientific legitimacy viewed so narrowly that it suppresses real-world relevance and limits the novelty of ideas that might be captured from starting with real-world observations?

It is time to entertain another paradigm shift, one where is revered more than theory. This new article makes the case for an empirics-first (EF) approach for research in marketing as opposed to the dominant theory-first (TF) approach. EF refers to research that:

  • is grounded in (and originates from) a real-world marketing phenomenon, problem, or observation,
  • involves obtaining and analyzing data, and
  • produces valid marketing-relevant insights without necessarily developing or testing theory.

In most published academic marketing research, a theory is borrowed, refined, or developed and then tested empirically. As a result, many papers published in leading marketing journals (especially in consumer research and strategy) follow a typical template: introduction → prior literature → overarching theoretical framework → hypotheses → empirical test → discussion.

The research team advocates for EF research that starts with a real-world marketing phenomenon, problem, or observation; exploits data; and develops valid marketing-relevant insights—with or without making an overture to theory. Several developments contribute to the timeliness (and timelessness) of the EF approach. One key driver is the quest for research relevance. "EF research is often sparked by "data" from the real world, which means research can start down a fresh path, asking new questions unburdened by the demands of existing theory. In other words, the natural arc of the EF approach more easily bends back to real-world implications," they say. Other developments contributing to the need for EF research include the availability of new data and analytical methods, the need for marketing to address critical real-world issues such as vaccine acceptance, , and disinformation, and the confidence crises plaguing the social sciences around replicability and data manipulation.

Why Has EF Research Failed to Gain Traction?

The fields of strategy and experimental are most likely to abide by a TF approach. One possible reason is that TF research is well-represented in Ph.D. education and uses a series of well-defined steps while EF research, which tends to be open-ended and unstructured, appears to lack rigor.

The research team explains that EF research consists of three stages. In the first stage—called "Identify Opportunity"—a meaningful, real-world issue with broad appeal to marketing stakeholders is selected. In the second stage—"Explore Terrain"—researchers use initial empirical insights to broaden and deepen the research scope. Finally, the third stage—"Advance Understanding"—aims to provide empirical regularities, conceptual and theoretical insights, and stakeholder advice.

The success of EF research rests both on proper execution and effective communication. EF scholars should be mindful of the expectations of the journal review team, many of whom may be steeped in the TF tradition. It should be made clear why the EF approach is appropriate for the particular research problem. Also, EF scholars are advised to justify the variables they study, explain their exact steps, report what worked and what did not, test robustness, and report the results fully.

Challenge of Reporting EF Research

The research team says that "To effectively report the nonlinear process that makes up EF research, we recommend paying special attention to communicating the paper's structure and narrative. Suggested tools include a flowchart to orient the reader at the start, structuring the paper based on the research questions, using section, table, and figure headings that guide the reader, and providing explanatory bridges between the steps in the process."

Journal reviewers and editors should be open-minded and informed when evaluating EF research. Rather than demanding an overarching , a single theoretical lens, or perfectly clean results, they should be realistic about which robustness checks are feasible. Even if a robustness check does not confirm all findings, reviewers should view it as a learning opportunity. Reviewers also should not demand traditional theoretical implications or expect EF research to be reported as TF research as this can lead to HARKing (hypothesizing after results are known).

"The EF path, when ambitiously and rigorously pursued, offers a way to address demands for relevance, novelty, replicability, and generalizability. The shift requires changes in the mindsets of authors, a more even balance between TF research and EF research in Ph.D. education, and a journal review process that accepts the inherent tradeoffs in pursuing EF research. Our ultimate objective is to pave the way for EF to enter the mainstream of academic marketing research," the researchers claim.

More information: Peter N. Golder et al, EXPRESS: Learning from Data: An Empirics-First Approach to Relevant Knowledge Generation, Journal of Marketing (2022). DOI: 10.1177/00222429221129200

Journal information: Journal of Marketing

Citation: A case for the empirics-first approach that develops marketing-relevant insights from real-world problems (2022, November 2) retrieved 27 January 2023 from https://phys.org/news/2022-11-case-empirics-first-approach-marketing-relevant-insights.html
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