FIŠAR, Miloš, Ben GREINER, Christoph HUBER, Elena KATOK, Ali OZKES and Management Science REPRODUCIBILITY COLLABORATION. Reproducibility in Management Science. MANAGEMENT SCIENCE. UNITED STATES: INFORMS, 2024, vol. 70, No 3, p. 1343-1356. ISSN 0025-1909. Available from: https://dx.doi.org/10.1287/mnsc.2023.03556.
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Basic information
Original name Reproducibility in Management Science
Authors FIŠAR, Miloš (203 Czech Republic, guarantor, belonging to the institution), Ben GREINER, Christoph HUBER (40 Austria), Elena KATOK (840 United States of America), Ali OZKES and Management Science REPRODUCIBILITY COLLABORATION.
Edition MANAGEMENT SCIENCE, UNITED STATES, INFORMS, 2024, 0025-1909.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50200 5.2 Economics and Business
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW Article
Impact factor Impact factor: 5.400 in 2022
Organization unit Faculty of Economics and Administration
Doi http://dx.doi.org/10.1287/mnsc.2023.03556
UT WoS 001132639700001
Keywords in English reproducibility; replication; crowd science
Tags International impact, Reviewed
Changed by Changed by: Mgr. Pavlína Kurková, učo 368752. Changed: 27/3/2024 14:55.
Abstract
With 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 hard- 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 dataset 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 to the period before the introduction of the disclosure policy, where only 12\% of articles voluntarily provided replication materials, out of which 55 % could be (largely) reproduced. Substantial heterogeneity in reproducibility rates across different fields is mainly driven by differences in dataset accessibility. Other reasons for unsuccessful reproduction attempts include missing code, unresolvable code errors, weak or missing documentation, but also soft- 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.
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