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Reproducibility in Management Science

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dc.contributor.authorSomasundaram, Jeeva
dc.contributor.authorGreiner, Ben
dc.contributor.authorHuber, Christoph
dc.contributor.authorKatok, Elena
dc.contributor.authorIhsan Ozkes, Ali
dc.contributor.rorhttps://ror.org/02jjdwm75
dc.date.accessioned2025-02-19T11:21:30Z
dc.date.available2025-02-19T11:21:30Z
dc.date.issued2023-12-22
dc.description.abstractWith the help of more than 700 reviewers, we assess the reproducibility of nearly 500 articles published in the journal Management Science before and after the introduction of a new Data and Code Disclosure policy in 2019. When considering only articles for which data accessibility and hardware and software requirements were not an obstacle for reviewers, the results of more than 95% of articles under the new disclosure policy could be fully or largely computationally reproduced. However, for 29% of articles, at least part of the data set was not accessible to the reviewer. Considering all articles in our sample reduces the share of reproduced articles to 68%. These figures represent a significant increase compared with the period before the introduction of the disclosure policy, where only 12% of articles voluntarily provided replication materials, of which 55% could be (largely) reproduced. Substantial heterogeneity in reproducibility rates across different fields is mainly driven by differences in data set accessibility. Other reasons for unsuccessful reproduction attempts include missing code, unresolvable code errors, weak or missing documentation, and software and hardware requirements and code complexity. Our findings highlight the importance of journal code and data disclosure policies and suggest potential avenues for enhancing their effectiveness.
dc.description.peerreviewedyes
dc.description.statusPublished
dc.formatapplication/pdf
dc.identifier.citationFišar, M., Greiner, B., Huber, C., Katok, E., Ozkes, A. I., & Management Science Reproducibility Collaboration. (2024). Reproducibility in Management Science. Management Science, 70(3), 1343-1356. https://doi.org/10.1287/mnsc.2023.03556.
dc.identifier.doihttps://doi.org/10.1287/mnsc.2023.03556
dc.identifier.issn0025-1909
dc.identifier.urihttps://hdl.handle.net/20.500.14417/3581
dc.issue.number3
dc.journal.titleManagement Science
dc.language.isoen
dc.page.total14
dc.publisherInforms
dc.relation.departmentOperations & Business Analytics
dc.relation.entityIE University
dc.relation.schoolIE Business School
dc.rightsAttribution 4.0 International
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed
dc.subject.keywordReproducibility
dc.subject.keywordReplication
dc.subject.keywordCrowd science
dc.titleReproducibility in Management Science
dc.typeinfo:eu-repo/semantics/article
dc.version.typeinfo:eu-repo/semantics/publishedVersion
dc.volume.number70
dspace.entity.typePublication
relation.isAuthorOfPublication2c764812-5db7-4867-b0a2-42f42e12bfa3
relation.isAuthorOfPublication.latestForDiscovery2c764812-5db7-4867-b0a2-42f42e12bfa3
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