Journal of Management Scientific Reports Mission, Aims, and Scope


JOMSR focuses on submissions that test previously published theory either as its first test, replication, or generalizability test. A theory is only as strong as its supporting evidence, however, much theory in management research goes untested and theory tests are often not replicated. JOMSR seeks methodologically strong contributions that draw on existing theory or hypotheses and either 1) present a compelling case for why (these elements of) the theory warrant testing, or 2) in the case of replication or a generalizability test, why replication or testing generalizability is warranted. Further, papers should clearly delineate how the empirical test of the theory (or some of its propositions) makes a contribution to management research.

Aims and scope

JOMSR’s unique aim is to publish original empirical work that tests existing theory in management rather than proposing and testing new theory. JOMSR is not open to submissions building new theory ahead of the methods and results (though, it is possible that new theoretical insights or clarifications can be garnered based on the study’s conclusions). Such studies aimed at building new theory are better submitted to the majority of empirical journals in management that see new theory as a core element in the contributions they seek. Submissions that do not report unambiguous tests of published theory (e.g., because they concern dependent variables to which published statements of the theory do not refer) must include a persuasive argument for how the study constitutes a test of existing theory and is not a novel theoretical extension of the theory.

Submissions can draw on a single theory or integrative framework as previously published in a theory paper, integrative review, meta-analysis, or empirical study. Submissions can also draw on more than one theory. For instance, this may occur when different theories make alternative or competing predictions about the same outcome, and the theory test in the paper submitted to JOMSR speaks to their relative merits. Alternatively, it can occur when different theories make the same or very similar predictions but seem to use different labels for the same or very similar constructs, and the theory test in the submitted paper speaks to construct consolidation.

Importantly, whether a first test, replication, or generalizability study, finding support for a theory or a particular hypothesis is not a requirement for publication in JOMSR, but contributing to the advancement of management research is required. Contributions are judged in two ways. First, papers will be gauged in terms of how important the reported tests are to building a strong knowledge base in management research, given that some theories are more important and/or central than others in advancing the field, and some elements of a theory are more important to test than others (e.g., because they are more central to the theory). Second, quality of the evidence (i.e., methods, analyses), be it qualitative or quantitative, will be key; although new theory will not be generated, the methods should still be highly rigorous. Studies reporting null findings, specifically, must advance a convincing argument as to the validity and statistical power of the tests reported.

Paper Types

Tests of theories (or, more typically, parts of a theory) can take different forms. The following captures paper types that are appropriate for JOMSR. This is neither meant to be exhaustive or restrictive as to what specific form papers should take. Rather, it is intended to clarify that theory testing also includes replication studies, generalizability studies, and tests of competing theories, and that theory testing is not exclusively the domain of quantitative research but can also be accomplished in qualitative research.

Reproducibility, Replication, and Generalizability Studies

JOMSR welcomes reproducibility, replication, and generalizability studies. Authors of reproducibility studies re-analyze the same data used in the original study with the same (direct reproducibility) or improved analytical techniques (constructive reproducibility). Replications engage in an empirical test of the same effect or model, but with new data. Generalizability studies aim to extend findings from previous studies to new contexts or populations. Below are more specific elaborations on relevant submissions of these types of papers for JOMSR.

(1) Reproducibility studies

  • Direct reproducibility studies analyze the same data as the original study, following the original study’s analysis strategy as closely as possible. This type of study needs a strong motivation and rationale for how the reanalysis contributes new knowledge above and beyond the original study.
  • Constructive reproducibility studies analyze the same data as the original study but with superior analysis methods. This type of study needs to demonstrate methodological improvements and argue how these improvements lead to new or changed insights beyond the original study.

(2) Replication studies

  • Direct replication studies test the same effect and model using the same methods in a sample that differs from the original study but is from the same population. The purpose of such direct replications is to examine whether past results are sample-specific. Authors of a direct replication should provide justification for how the replication advances knowledge beyond the original study. In addition, the samples used by such studies must be constructed in such a way as to assure high confidence in the replication results.
  • Constructive replication studies test the same effect or model as a previous study, but with gradual improvement(s) upon the original study/studies with regard to the methods, measures, design, or analytical techniques employed. Authors of a constructive replication study must provide rationale for how the improved research methods either lead to a substantially deeper understanding of the studied phenomenon or evaluate to what degree past results were an artefact of a specific approach by testing the same effect or model but using a promising alternative. Authors must justify the value of using these alternatives, including but not limited to changes to:
  • Measures/proxies
  • Sampling process
  • Statistical analyses
  • Control variables
  • Experimental treatments

(3) Generalizability studies

  • Generalizability studies test the boundary conditions of past work by gradually altering the population or empirical context to obtain a deeper understanding of the generalizability of the studied effects. The study’s objective is to test the same effect or model as the original study, but, for example:
  • Sample subjects with at least one systematically different characteristic from subjects in the original study.
  • Sample subjects from a subpopulation of the original study (e.g., specific age groups).
  • Execute the study in a different empirical context (e.g., different industry, time, country, culture, etc.).

Authors should explicitly justify the value of using these constructive changes to the design of the original studies.

Testing Competing Theories

An evaluation of competing theories applies two (or more) different theoretical perspectives to test the same phenomenon. These papers focus on both common ground and differences between theories with regard to (a) assumptions, (b) levels of analysis, (c) constructs, and/or (d) methods. The goal of these studies is, through empirics, to jointly demonstrate the relative strengths and weaknesses of the theoretical perspectives and should be focused on providing evidence of where the theories apply to a greater or lesser degree.

Types of Competing Theories Studies:







Type A





Type B





Type C





Type D





  • The “Assumptions” column refers to the possibility of strengthening/weakening of assumptions. In other words, as the assumptions of one theory is strengthened or loosened, the explanatory power of the other theory may be strengthened or weakened. Another permutation of this could be “adding or dropping” assumptions.
  • A potential extension (abstraction) of competing theories is competing epistemologies (ways of knowing) or competing ontologies (classification systems). These probably manifest through different theoretical perspectives, but we could allow for the higher level as well.

Testing Previously Untested Theories

Tests of previously published, but untested, theories should focus on rigorous research design and execution with appropriate samples. Authors must state whether they test the entire theory or only parts of the theory and, if the latter, should justify their focus on that part of the theory. Authors further must explain how their test of the theory constitutes a rigorous test and provides strong empirical evidence for evaluating the theory. Providing a transparent description of this initial theory test is paramount so that it can be replicated in the future.

Theory Testing With Qualitative Methods

JOMSR also welcomes papers that test theory using qualitative methods. As qualitative methods are much more frequently used for theory generation, there will be a very narrow scope for theory testing with qualitative methods. We do not view theory testing with qualitative methods as converting qualitative data via a form of content coding into numbers, which can then be tested with quantitative techniques: this would be considered a quantitative theory test. Rather, we envision papers that use traditional qualitative methods (e.g., case study method) in innovative ways to systematically test patterns in the qualitative data. It is unlikely that qualitative methods focused predominantly on theory-building or theory elaboration (such as grounded theory, ethnography, narrative analysis, or discourse analysis) can be successfully used for theory testing.

Examples of theory testing with qualitative methods can be found in case study designs, which can use systematic case comparisons to test alternative theoretical explanations for observed phenomena. Other examples may include features of process analysis, which compare process patterns (such as patterns unfolding over time) to evaluate alternative theoretical explanations. Further examples may include linguistic pattern analysis (as long as the data are analyzed in qualitative form, not in quantitative form) or specific context comparisons.

Naturally, theory testing with qualitative methods takes a very different form from theory testing with quantitative methods. There are no significance tests or other quantitatively derived tests that apply to qualitative methods. As such, the application of qualitative methods for theory testing must follow qualitative criteria for trustworthiness of the findings relevant to the respective qualitative method employed, and to the epistemological grounding chosen for the research.

Qualitative theory testing is a relatively novel and rare application of qualitative methods in the management field. As such, we also look forward to submissions that employ innovative theory testing using qualitative methods. These papers must demonstrate the appropriateness of their qualitative theory testing approach without the generation of new theory.

Theory Testing Methodology Papers

JOMSR also publishes papers that discuss and outline methodological issues related to the design, execution, and interpretation of theory testing studies. Possible types of papers include:

  • Evaluations and elaborations of the foundations of theory testing approaches (including epistemological and ontological foundations, core differences in approaches to theory testing).
  • Advocacy and outline of best practices for theory testing (including replication and generalizability studies).
  • Introduction and discussion of important methodological opportunities or challenges.
  • Stimulation of discussions and debates about controversial methodological topics.

In the end, scientific progress in our field depends not only on conducting and publishing more theory testing studies, but also on enhancing our field’s capability to design and execute high-quality theory testing studies.