Explaining Heterogeneity in the Organization of Scientific Work
Name
SSRN-id3084070.pdf
Description
Accepted version
Size
1.13 MB
Format
Adobe PDF
Checksum (MD5)
db29d097d3442de39f69101d8f3d8695
Author(s)
Rahmandad, Hazhir
Vakili, Keyvan
Date Issued
2019
Journal
Organization Science
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Version
Author's final manuscript
Abstract
© 2019 INFORMS. Prior studies of academic science have largely focused on researchers in life sciences or engineering. However, while academic researchers often work under similar institutions, norms, and incentives, they vary greatly in how they organize their research efforts across different scientific domains. This heterogeneity, in turn, has important implications for innovation policy, the relationship between industry and academia, the scientific labor market, and the perceived deficit in the relevance of social sciences and humanities research. To understand this heterogeneity, we model scientists as publication-maximizing agents, identifying two distinct organizational patterns that are optimal under different parameters. When the net productivity of research staff (e.g., PhD students and postdocs) is positive, the funded research model with an entrepreneurial scientist and a large team dominates. When the costs of research staff exceed their productivity benefits, the hands-on research approach is optimal. The model implies significant heterogeneity across the two modes of organizing in research funding, supply of scientific workforce, team size, publication output, and stratification patterns over time. Exploratory empirical analysis finds consistent patterns of time allocation and publication in a prior survey of faculty in U.S. universities. Using data from an original survey, we also find causal effects consistent with the model's prediction on how negative shocks to research staff-due to visa or health problems, for example-differentially impact research output under the two modes of organization.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1287/ORSC.2019.1303
