TY - JOUR
T1 - Reproducibility in Management Science
AU - the Management Science Reproducibility Collaboration
AU - Fišar, Miloš
AU - Greiner, Ben
AU - Huber, Christoph
AU - Katok, Elena
AU - Ozkes, Ali I.
AU - Abraham, Diya
AU - Adams, Gabrielle S.
AU - Adbi, Arzi
AU - Addoum, Jawad M.
AU - Adena, Maja
AU - Akella, Laxminarayana Yashaswy
AU - Akey, Pat
AU - Akmansoy, Olivier
AU - Alban, Andres
AU - Alexeev, Vitali
AU - Alimov, Azizjon
AU - Aman, Argun
AU - Aouad, Ali
AU - Appel, Gil
AU - Arnosti, Nick
AU - Arora, Kashish
AU - Arpinon, Thibaut
AU - Artinger, Florian M.
AU - Arts, Joachim
AU - Baardman, Lennart
AU - Babutsidze, Zakaria
AU - Bahrami, Golnaz
AU - Banerjee, Somnath
AU - Bao, Chenzhang
AU - Bao, Te
AU - Baron, Opher
AU - Barriola, Xabier
AU - Monteiro e Silva Barroso, Pedro
AU - Baskin, Ernest
AU - Batt, Robert J.
AU - Batta, George
AU - Bauer, Anahid
AU - Bauman, Konstantin
AU - Bazley, William
AU - Becker-Peth, Michael
AU - Begen, Mehmet
AU - Begen, Nazire
AU - Benoit, Sylvain
AU - Berger, Loic
AU - Berlin, Noémi
AU - Berling, Lars Peter
AU - Bernard, Anna
AU - Bertomeu, Jeremy
AU - Białkowski, Jędrzej
AU - Bilinski, Pawel
AU - Bischof, Jannis
AU - Black, Jeffrey R.
AU - Blunden, Hayley
AU - Bongaerts, Dion
AU - Bönisch, Felix
AU - Bos, Marieke
AU - Bosch-Rosa, Ciril
AU - Bourjade, Sylvain
AU - Boysen, Andrew
AU - Brimhall, Craig
AU - Brokesova, Zuzana
AU - Brooks, J. Paul
AU - Bruns, Stephan B.
AU - Buckle, Georgia
AU - Buenstorf, Guido
AU - Burtch, Gordon
AU - Bushong, Benjamin
AU - Buti, Sabrina
AU - Callery, Patrick
AU - Canayaz, Mehmet
AU - Cao, Jie
AU - Cao, Wei
AU - Cao, Xinyu
AU - Carree, Martin
AU - Castellani, Vincent
AU - Cerasi, Yann Joel
AU - Chang, Hannah H.
AU - Chang, Jin Wook
AU - Chang, Michelle
AU - Chang, Yanru
AU - Chaturvedi, Aadhaar
AU - Chauvin, Jasmina
AU - Chavez, Daniel E.
AU - Chen, Christopher
AU - Chen, Fadong
AU - Chen, Josie I.
AU - Chen, Peng Chu
AU - Chen, Roy
AU - Chen, Wei
AU - Chen, Wei James
AU - Chen, Yuanyuan
AU - Chen, Zepeng
AU - Chen, Zhuoqiong
AU - Chew, Lydia
AU - Chhabra, Param Pal Singh
AU - Chintala, Sai Chand
AU - Choi, Ga Young
AU - Choi, Seungho
AU - Choudhary, Vivek
AU - Chow, Vincent Tsz Fai
AU - Christensen, Katherine L.
AU - Chung, Doug J.
AU - Cinelli, Melissa
AU - Cingl, Lubomír
AU - Cire, Andre Augusto
AU - Clark, Jeffrey
AU - Clement, Jeffrey
AU - Clithero, John
AU - Cloléry, Héloïse
AU - Clough, David R.
AU - Clyde, Nicholas
AU - Coali, Andrea
AU - Comeig, Irene
AU - Cook, Nikolai
AU - Correia-Da-Silva, Joao
AU - Costa, Elaine
AU - Coutts, Alexander
AU - Cribben, Ivor
AU - Cuculiza, Carina
AU - Cui, Zimeng
AU - Cunningham, Colleen
AU - Cziraki, Peter
AU - Dagorn, Étienne
AU - Dai, Rui
AU - Dana, Jason
AU - Danks, Nicholas Patrick
AU - Darendeli, Alper
AU - Dato, Simon
AU - Davcik, Nebojsa
AU - de Grazia, Charles
AU - De Sousa, Jose
AU - De Vries, Jelle
AU - De Vries, Martijn
AU - Deev, Oleg
AU - DeFronzo, Ryan
AU - Dekker, Lennart
AU - Delarue, Arthur
AU - Demiral, Elif E.
AU - Demiroglu, Cem
AU - Deore, Aishwarrya
AU - Detzel, Andrew
AU - Devonaev, Azamat
AU - Bala, Archana Dhinakar
AU - Dimant, Eugen
AU - Dimmery, Drew
AU - Dimmock, Stephen G.
AU - Ding, Cheng
AU - Ding, Likang
AU - Ding, Tingting
AU - Ding, Yuheng
AU - Dong, Lu
AU - Donohue, Karen
AU - Drichoutis, Andreas
AU - Du, Shaoyin
AU - Duan, Ying
AU - Duevski, Teodor
AU - Duong, Huu Nhan
AU - Ederhof, Merle
AU - El Hajj, Hussein
AU - Ellison, Martin
AU - Eriksen, Jonas Nygaard
AU - Espinosa, Miguel
AU - Fallucchi, Francesco
AU - Fang, Xiaohua
AU - Fanghella, Valeria
AU - Faralli, Matilde
AU - Farham, Saleh
AU - Fattinger, Felix
AU - Feiereisen, Stephanie
AU - Feng, Yiding
AU - Ferracuti, Elia
AU - Filippin, Antonio
AU - Fillon, Adrien
AU - Fiorin, Stefano
AU - Fisher, Geoffrey
AU - Fisher, Matthew
AU - Flath, Christoph
AU - Foerderer, Jens
AU - Frey, Vincenz
AU - Fuchs, Christoph
AU - Fugger, Nicolas
AU - Gabel, Sebastian
AU - Gaessler, Fabian
AU - Ganglmair, Bernhard
AU - Gangwar, Manish
AU - Ares, Pedro Angel Garcia
AU - Garg, Rajiv
AU - Gaspar, José Miguel
AU - Gastaldi, Chiara
AU - Gauriot, Romain
AU - De Genaro, Alan
AU - Geng, Yuxin
AU - Georgalos, Konstantinos
AU - Geraldes, Diogo
AU - Gerhards, Leonie
AU - Gerken, William
AU - Gibson, Mike
AU - Gijsbrechts, Joren
AU - Goerg, Sebastian
AU - Goetz, Daniel
N1 - Publisher Copyright:
© 2023 INFORMS.
PY - 2024/3/1
Y1 - 2024/3/1
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.
KW - crowd science
KW - replication
KW - reproducibility
UR - https://www.scopus.com/pages/publications/85187694519
U2 - 10.1287/mnsc.2023.03556
DO - 10.1287/mnsc.2023.03556
M3 - Article
AN - SCOPUS:85187694519
SN - 0025-1909
VL - 70
SP - 1343
EP - 1356
JO - Management Science
JF - Management Science
IS - 3
ER -