Examining the generalizability of research findings from archival data

概化理论 背景(考古学) 匹配(统计) 集合(抽象数据类型) 计量经济学 心理学 数据科学 统计 计算机科学 地理 考古 数学 发展心理学 程序设计语言
作者
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,Matúš Adamkovič,Елена Агадуллина,Jungsoo Ahn,Çinla Akinci,Handan Akkaş,David Albrecht,Shilaan Alzahawi,Marcio Alves 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 Bavoľár,Seçil Bayraktar,S. Beckman,Aaron S. Benjamin,Stephanie Brown,Jeffrey Buckley,Ricardo E. Buitrago R.,Jefferson Luiz Bution,Nick Byrd,Clara Carrera,Eugene M. Caruso,Minxia Chen,Chen Lin,Eyyub Ensari Cicerali,Eric David Cohen,Marcus Credé,J. David Cummins,Linus Dahlander,David P. Daniels,Lea Liat Daskalo,Ian Dawson,Martin V. Day,Erik Dietl,Artur Domurat,Jacinta Dsilva,Christilene du Plessis,Dmitrii Dubrov,Sarah Edris,Christian T. Elbæk,Mahmoud Medhat Elsherif,Thomas Rhys Evans,Martin R. Fellenz,Susann Fiedler,Mustafa Firat,Raquel Meister Ko. Freitag,Rémy A. Furrer,Richa Gautam,Dhruba Kumar Gautam,Brian Gearin,Stephan Gerschewski,Omid Ghasemi,Zohreh Ghasemi,Anindya Ghosh,Cinzia Giani,Matthew H. Goldberg,Manisha Goswami,Lorenz Graf‐Vlachy,Jennifer A. Griffith,Dmitry Grigoryev,Jingyang Gu,H Rajeshwari,Allègre L. Hadida,Andrew Hafenbrack,Sebastian Hafenbrädl,Jonathan Hammersley,Hyemin Han,Jason L. Harman,Andree Hartanto,Alexander P. Henkel,Yen-Chen Ho,Benjamin C. Holding,Felix Holzmeister,Alexandra Horobeţ,Tina Huang,Yiming Huang,Jeffrey R. Huntsinger,Katarzyna Idzikowska
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:119 (30) 被引量:35
标识
DOI:10.1073/pnas.2120377119
摘要

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.

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