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INTEREST CATEGORY: MARKETING RESEARCH
POSTING TYPE: Calls: Journals

Posted by: Maria Petrescu

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CALL FOR PAPERS

Journal of Marketing Analytics

Special Issue on

The Significance of Nothing: Null Results in Business Research

Guest Editors:

Dr. Anjala Krishen, University of Nevada, Las Vegas
Dr. Maria Petrescu, Embry-Riddle Aeronautical University

Submission window: January 1^st 2026-May 1^st 2026

The ���file-drawer problem��� has long warned that literatures overstate effects because studies with nonsignificant results are less likely to be written up, submitted, or accepted (Rosenthal, 1979). Marketing is no exception: in a classic audit of three flagship journals (1974���1989), only 7.8% of papers using significance tests failed to reject the null; the share halved from the 1970s to the 1980s, and this pattern could not be explained by low power (Hubbard & Armstrong, 1992). More recently, experimental evidence documents a null-result penalty: holding design and precision constant, experts rate null-result studies as less publishable, lower quality, and less important, penalties observed among both PhD students and editors; pre-results review is highlighted as a promising remedy (Chopra et al., 2023). Together, these studies imply biased literatures, mis-estimated effects, and misallocation of analytic effort in business settings that rely on evidence for high-stakes decisions.

A null result, an empirical outcome that fails to confirm the focal hypothesis, is not ���no result,��� but evidence about the (non-)existence, magnitude, or boundary conditions of effects (Knight, 2003; Springer Nature, 2025). Such findings reduce research waste, sharpen theory by ruling out relationships, and improve practice when ���no difference��� supports cheaper or simpler options (survey implementation choices) ( Kozlov, 2024; Landis et al., 2014). Far from being peripheral, nulls are essential inputs to meta-analysis, measurement invariance checks, and cumulative knowledge building in analytics-driven domains (Landis et al., 2014, Springer Nature, 2025).

Informative nulls are those where (a) theory is explicit and strong, (b) design is adequately powered and well-measured, (c) analysis uses appropriate tools (equivalence testing), and (d) results are fully reported (Landis et al., 2014). In analytics contexts, especially survey-based field experiments, researchers should pre-specify hypotheses and decisions, avoid post-hoc pooling across heterogeneous studies, and adopt design/analysis practices that render nonsignificant outcomes diagnostic rather than ambiguous (Kane, 2025). Importantly, empirics-first frameworks in marketing emphasize documenting all empirical outcomes (including nulls) as the basis for relevant, cumulative knowledge prior to theorizing, a philosophy that normalizes, rather than penalizes, null findings (Golder, Dekimpe & Van Heerde, 2023; Kozlov, 2024).

For analytics-heavy marketing problems (experimentation, uplift modeling, causal inference, segmentation), the literature points to a few priorities:

1. Design for inference about no meaningful effect: Power for minimum detectable effects and apply equivalence or minimal-effect tests so that nulls can speak to managerial irrelevance, not merely statistical uncertainty (Landis et al., 2014; Kane, 2025).
2. Pre-specification and transparency: Pre-register hypotheses, analysis plans, and decision rules; avoid undisclosed flexibility and after-the-fact pooling across heterogeneous studies or segments (Kane, 2025; Kozlov, 2024).
3. Comprehensive reporting: Retain nonsignificant coefficients, intervals, diagnostics, and robustness checks; do not ���trim for brevity���, meta-analysis and decision models need the full empirical surface (Landis et al., 2014).
4. Editorial innovation: Consider pre-results review/registered reports to neutralize the null-penalty at submission time (Chopra et al., 2023), and adopt review rubrics that explicitly assess the informativeness of nulls (Landis et al., 2014).

Taken together, evidence on bias (Hubbard & Armstrong, 1992; Rosenthal, 1979), experimental estimates of a null-penalty (Chopra et al., 2023), empirics-first norms (Golder et al., 2023), and editorial exemplars (Landis et al., 2014) make a strong case that business analytics needs more visible, methodologically rigorous null results. In this context, a JMA special issue can contribute by (a) publishing substantive nulls that refine or overturn accepted effects in analytics-relevant domains; (b) advancing methodological notes (power for heterogeneity, equivalence testing in uplift/AB tests, design analysis, principled pooling); and (c) foregrounding editorial/process innovations (pre-results review; structured reporting checklists) that reduce bias and increase the cumulative value of our analytics evidence base.

The combined historical and contemporary evidence argues for a dedicated venue where nulls are first-class citizens when they meet rigorous standards. This Journal of Marketing Analytics special issue can advance the field by including some of these topics:

1. Substantive nulls that reset priors in core analytics domains (channel lift, personalization intensity, ad-creative features, attention metrics), especially where conventional wisdom predicts sizable gains.
2. Method notes and tutorials on design analysis for equivalence/minimal-effect tests, power for heterogeneity, sequential testing with null-sensitive stopping, and transparent multi-study pooling that preserves nulls.
3. Process and infrastructure papers evaluating registered reports, preregistration, and negative-results repositories in marketing-industry settings (product experimentation platforms, ad-tech, CRM).

Instructions

Manuscripts submitted for consideration must be unique and not be reviewed for publication by any other source. The journal���s standard evaluation process involves independent referees reviewing the manuscripts. The editors’ final decision will consider the manuscript���s relevance to the special issue, its technical merit, the novelty of its content, and the originality of its research approaches and findings.

Submissions should be uploaded via Editorial Manager (see

).

To have your paper reviewed for inclusion in this special issue, select ���yes��� when asked if it is intended for a special issue during submission and choose the appropriate title from the list provided. It may also be helpful to mention the special issue in your cover letter. Authors should adhere to the journal���s publication guidelines, which can be found at:

Optional extended abstracts can be submitted to one of the Guest Editors via email at: petrescm@erau.edu

References

Chopra F, Haaland I, Roth C, Stegmann A (2023) The null result penalty, The Economic Journal 134:193���219

Golder PN, Dekimpe MG, An JT, et al (2023) Learning from Data: An Empirics-First Approach to Relevant Knowledge Generation. J Mark 87:319���336.

Hubbard R, Armstrong JS (1992) Are null results becoming an endangered species in marketing? Mark Lett 3:127���136.

Kane J V. (2024) More than meets the ITT: A guide for anticipating and investigating nonsignificant results in survey experiments. J Exp Polit Sci 110���125.

Knight J (2003) Null and void. Nature 422:554���555.

Kozlov BM (2024) How to give null results the airtime they deserve. Nature 631:738���730

Landis RS, James LR, Lance CE, et al (2014) When is Nothing Something? Editorial for the Null Results Special Issue of Journal of Business and Psychology. J Bus Psychol 29:163���167.

Rosenthal R (1979) The file drawer problem and tolerance for null results. Psychol Bull 86:638���641.

Springer Nature (2025) The state of null results: Insights from 11,000 researchers on negative or inconclusive results (white paper), Springer Nature, 2025.