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Reproducibility in Management Science

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Reproducibility in Management Science. / Fišar, Miloš ; Greiner, Ben ; Huber, Christoph et al.
In: Management Science, Vol. 70, No. 3, 22.12.2023, p. 1343-1356.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Fišar, M, Greiner, B, Huber, C, Katok, E, Ozkes, AI & Management Science Reproducibility Collaboration 2023, 'Reproducibility in Management Science', Management Science, vol. 70, no. 3, pp. 1343-1356. https://doi.org/10.1287/mnsc.2023.03556

APA

Fišar, M., Greiner, B., Huber, C., Katok, E., Ozkes, A. I., & Management Science Reproducibility Collaboration (2023). Reproducibility in Management Science. Management Science, 70(3), 1343-1356. Advance online publication. https://doi.org/10.1287/mnsc.2023.03556

Vancouver

Fišar M, Greiner B, Huber C, Katok E, Ozkes AI, Management Science Reproducibility Collaboration. Reproducibility in Management Science. Management Science. 2023 Dec 22;70(3):1343-1356. Epub 2023 Dec 22. doi: 10.1287/mnsc.2023.03556

Author

Fišar, Miloš ; Greiner, Ben ; Huber, Christoph et al. / Reproducibility in Management Science. In: Management Science. 2023 ; Vol. 70, No. 3. pp. 1343-1356.

Bibtex

@article{efd2d2d3728642008cf1db6d3dc10bf5,
title = "Reproducibility in Management Science",
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 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",
author = "Milo{\v s} Fi{\v s}ar and Ben Greiner and Christoph Huber and Elena Katok and Ozkes, {Ali I.} and Grzegorz Pawlina and {Management Science Reproducibility Collaboration}",
year = "2023",
month = dec,
day = "22",
doi = "10.1287/mnsc.2023.03556",
language = "English",
volume = "70",
pages = "1343--1356",
journal = "Management Science",
issn = "0025-1909",
publisher = "INFORMS Inst.for Operations Res.and the Management Sciences",
number = "3",

}

RIS

TY - JOUR

T1 - Reproducibility in Management Science

AU - Fišar, Miloš

AU - Greiner, Ben

AU - Huber, Christoph

AU - Katok, Elena

AU - Ozkes, Ali I.

AU - Pawlina, Grzegorz

AU - Management Science Reproducibility Collaboration

PY - 2023/12/22

Y1 - 2023/12/22

N2 - 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 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

AB - 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 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

U2 - 10.1287/mnsc.2023.03556

DO - 10.1287/mnsc.2023.03556

M3 - Journal article

VL - 70

SP - 1343

EP - 1356

JO - Management Science

JF - Management Science

SN - 0025-1909

IS - 3

ER -