Examining the generalizability of research findings from archival data
Autor
Delios, Andrew
Clemente, Elena Giulia
Wu, Tao
Tan, Hongbin
Wang, Yong
Gordon, Michael
Viganola, Domenico
Chen, Zhaowei
Dreber, Anna
Johannesson, Magnus
Pfeiffer, Thomas
Uhlmann, Eric Luis
Al-Aziz, Ahmad M.Abd
Abraham, Ajay T.
Trojan, Jais
Adamkovic, Matus
Agadullina, Elena
Ahn, Jungsoo
Akinci, Cinla
Akkas, Handan
Albrecht, David
Alzahawi, Shilaan
Amaral-Baptista, Marcio
Anand, Rahul
Ang, Kevin Francis U.
Anseel, Frederik
Aruta, John Jamir Benzon R.
Ashraf, Mujeeba
Baker, Bradley J.
Bao, Xueqi
Baskin, Ernest
Bathula, Hanoku
Bauman, Christopher W.
Bavolar, Jozef
Bayraktar, Secil
Beckman, Stephanie E.
Benjamin, Aaron S.
Brown, Stephanie E.V.
Buckley, Jeffrey
Buitrago, Ricardo E.
Bution, Jefferson L.
Byrd, Nick
Carrera, Clara
Caruso, Eugene M.
Chen, Minxia
Chen, Lin
Cicerali, Eyyub Ensari
Cohen, Eric D.
Crede, Marcus
Cummins, Jamie
Dahlander, Linus
Daniels, David P.
Daskalo, Lea Liat
Dawson, Ian G.J.
Day, Martin V.
Dietl, Erik
Domurat, Artur
Dsilva, Jacinta
Du Plessis, Christilene
Dubrov, Dmitrii I.
Edris, Sarah
Elbaek, Christian T.
Elsherif, Mahmoud M.
Evans, Thomas R.
Fellenz, Martin R.
Fiedler, Susann
Firat, Mustafa
Freitag, Raquel
Furrer, Rémy A.
Gautam, Richa
Gautam, Dhruba Kumar
Gearin, Brian
Gerschewski, Stephan
Ghasemi, Omid
Ghasemi, Zohreh
Ghosh, Anindya
Giani, Cinzia
Goldberg, Matthew H.
Goswami, Manisha
Graf-Vlachy, Lorenz
Rajeshwari, H.
Griffith, Jennifer A.
Grigoryev, Dmitry
Gu, Jingyang
Hadida, Allegre L.
Hafenbrack, Andrew C.
Hafenbrädl, Sebastian
Hammersley, Jonathan J.
Han, Hyemin
Harman, Jason L.
Hartanto, Andree
Henkel, Alexander P.
Ho, Yen Chen
Holding, Benjamin C.
Holzmeister, Felix
Horobet, Alexandra
Huang, Tina S.T.
Huang, Yiming
Huntsinger, Jeffrey R.
Datum vydání
2022Publikováno v
Proceedings of the National Academy of Sciences of the United States of AmericaRočník / Číslo vydání
119 (30)ISBN / ISSN
ISSN: 0027-8424ISBN / ISSN
eISSN: 1091-6490Metadata
Zobrazit celý záznamKolekce
Tato publikace má vydavatelskou verzi s DOI 10.1073/pnas.2120377119
Abstrakt
This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability-for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples.
Klíčová slova
archival data, context sensitivity, generalizability, reproducibility, research reliability
Trvalý odkaz
https://hdl.handle.net/20.500.14178/2446Licence
Licence pro užití plného textu výsledku: Creative Commons Uveďte původ-Neužívejte dílo komerčně-Nezpracovávejte 4.0 International