More is less: multidisciplinarity and the dynamics of scientific knowledge

This paper develops a simple model of academic research to analyze knowledge flows within a research system, when demand for multi-disciplinarity varies. Scientists are embedded in departments, linked to all others in the department, as well as to a small number of others outside the department. Pairs of scientists collaborate to produce 'papers'. They can collaborate successfully with their direct links provided the distances in knowledge space between partners are within specified upper and lower bounds. By creating new knowledge, co-authors converge in their knowledge endowments, and the distance between them can fall below the lower bound. This is mitigated in two ways: extra-departmental links; and an intermittent job market in which scientists can change departments. In a simulation model we find that increasing the extent of extra-departmental links, and increasing job market activity both improve aggregate knowledge production. These two modes of knowledge diffusion are, however, substitutes rather than complements: increasing both does not improve performance over increasing only one. In addition, we find that increasing demands for multi-disciplinarity (essentially increasing the lower bound on knowledge distance for effective collaboration) generally decreases knowledge production.

Authors

Institutions

Publication Details

Journal
Economics of Innovation and New Technology
Published
2025-03-14
DOI
https://doi.org/10.1080/10438599.2025.2475335
Primary Topic
Interdisciplinary Research and Collaboration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

More is less: multidisciplinarity and the dynamics of scientific knowledge

Robin Cowan, Nicolas Jonard
Economics of Innovation and New Technology
Interdisciplinary Research and Collaboration
article

More is less: multidisciplinarity and the dynamics of scientific knowledge

Robin Cowan, Nicolas Jonard
article en

Abstract

This paper develops a simple model of academic research to analyze knowledge flows within a research system, when demand for multi-disciplinarity varies. Scientists are embedded in departments, linked to all others in the department, as well as to a small number of others outside the department. Pairs of scientists collaborate to produce 'papers'. They can collaborate successfully with their direct links provided the distances in knowledge space between partners are within specified upper and lower bounds. By creating new knowledge, co-authors converge in their knowledge endowments, and the distance between them can fall below the lower bound. This is mitigated in two ways: extra-departmental links; and an intermittent job market in which scientists can change departments. In a simulation model we find that increasing the extent of extra-departmental links, and increasing job market activity both improve aggregate knowledge production. These two modes of knowledge diffusion are, however, substitutes rather than complements: increasing both does not improve performance over increasing only one. In addition, we find that increasing demands for multi-disciplinarity (essentially increasing the lower bound on knowledge distance for effective collaboration) generally decreases knowledge production.

Economics of Innovation and New Technology
University of Luxembourg (LU), Stellenbosch University (ZA), Maastricht University (NL), Université de Strasbourg (FR)
Quality Education
Openalex Percentile: Top 95%
Interdisciplinary Research and Collaboration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.