Examining the generalizability of research findings from archival data

Generalizability Tests Forecasting Collaboration, Andrew Delios*, Elena Giulia Clemente, Tao Wu, Hongbin Tan, Yong Wang, Michael Gordon, Domenico Viganola, Zhaowei Chen, Anna Dreber, Magnus Johannesson, Thomas Pfeiffer, Eric Luis Uhlmann*, Ahmad M.Abd Al-Aziz, Ajay T. Abraham, Jais Trojan, Matus Adamkovic, Elena Agadullina, Jungsoo Ahn, Cinla AkinciHandan Akkas, David Albrecht, Shilaan Alzahawi, Marcio Amaral-Baptista, Rahul Anand, Kevin Francis U. Ang, Frederik Anseel, John Jamir Benzon R. Aruta, Mujeeba Ashraf, Bradley J. Baker, Xueqi Bao, Ernest Baskin, Hanoku Bathula, Christopher W. Bauman, Jozef Bavolar, Secil Bayraktar, Stephanie E. Beckman, Aaron S. Benjamin, Stephanie E.V. Brown, Jeffrey Buckley, Ricardo E. Buitrago, Jefferson L. Bution, Nick Byrd, Clara Carrera, Eugene M. Caruso, Minxia Chen, Lin Chen, Eyyub Ensari Cicerali, Eric D. Cohen, Marcus Crede, Amanda Rotella

*Corresponding author for this work

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Abstract

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.

Original languageEnglish
Article numbere2120377119
Number of pages9
JournalProceedings of the National Academy of Sciences of the United States of America
Volume119
Issue number30
DOIs
Publication statusPublished - 26 Jul 2022
Externally publishedYes

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