Data Availability

The Journal of Business Strategy and Management Review requires authors to make the data, code, and other research artifacts that support the conclusions of their work available to readers, subject to clearly stated and legitimate restrictions. The Journal aligns its policy with the FAIR principles (Findable, Accessible, Interoperable, Reusable).

Mandatory Data Availability Statement

Every manuscript must include a Data Availability Statement, placed in a dedicated section between the Conclusions and the References. The statement specifies what data underlie the findings reported in the article and how those data may be accessed.

Acceptable forms of data availability

Authors should select the option below that best fits their study. Multiple options may apply.

  1. Data in a public repository. The data are deposited in a public repository (Zenodo, Figshare, Dryad, the Open Science Framework, the Harvard Dataverse, or a discipline-specific repository) with a persistent identifier. Provide the repository name, the persistent identifier or URL, and the access terms.
  2. Data included in the article and supplementary information. The data are fully reported in the article and its supplementary files; no separate dataset is required.
  3. Data available on reasonable request. The data are available from the corresponding author on reasonable request, subject to specified conditions (for example, institutional data-sharing agreement, ethics committee approval).
  4. Restricted data. The data are subject to restrictions (for example, commercial confidentiality, personal data protection, ethics approval limits). Specify the nature of the restriction and the conditions under which the data may be obtained.
  5. No new data created. The study used only previously published data; cite the original sources.

Code and analysis availability

Where the study uses or produces analysis code, scripts, or statistical syntax, authors are required to:

  • Cite all third-party software used, with version numbers, in the methods section (for example, R, Stata, SPSS, Python, or NVivo);
  • Make any custom code or analysis syntax that is essential to reproducing the reported results available in a public repository (GitHub, GitLab, Zenodo, or the Open Science Framework) with a persistent identifier;
  • Specify the license under which the code is released. Recommended licenses are MIT, Apache 2.0, GPL, or BSD for code, and CC BY for data.

Materials availability

For studies that involve specific research materials such as survey instruments, interview protocols, coding schemes, or experimental stimuli, authors should describe the materials in sufficient detail for replication and indicate whether the materials are available on request.

Reproducibility

The Journal encourages submissions to include a Reproducibility section describing the software environment (package and version numbers), any random seeds used in simulation or resampling, and the steps required to reproduce the reported results from the published data and analysis files. This is particularly relevant for quantitative work involving statistical modeling, econometric analysis, and simulation, where full specification of the data preparation and analysis steps is essential to independent verification.

Example statements

Example 1: public repository. "The dataset analyzed in this study is available in the Zenodo repository at https://doi.org/10.5281/zenodo.EXAMPLE under a CC BY 4.0 license. Custom analysis code is available at https://github.com/EXAMPLE under an MIT license."

Example 2: reasonable request. "The data that support the findings of this study are available from the corresponding author on reasonable request. Restrictions apply to the availability of these data, which were used under license for the present study and are not publicly available."

Example 3: no new data. "No new data were created or analyzed in this study. All data referenced in this work are publicly available from the cited sources."