Evidence map›Paper›PMID 41417844›Full record

ArticlePloS one2025

How similar should collaborators be in inter-organizational learning: Optimal cognitive proximity and knowledge complexity.

Yeokyung Hwang, Junseok Hwang, Junmin Lee

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yeokyung HwangTechnology Management, Economics, and Policy Program, Seoul National University, Seoul, South Korea.ORCID https://orcid.org/0009-0009-0620-6003
Junseok HwangTechnology Management, Economics, and Policy Program, Seoul National University, Seoul, South Korea.
Junmin LeeDepartment of Public Policy and Management, Pusan National University, Busan, South Korea.ORCID https://orcid.org/0000-0003-3245-4851

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective knowledge exchange is critical for innovation in knowledge-intensive sectors, yet the relationship between cognitive proximity and collaborative innovation remains underexplored in complex knowledge environments. While prior studies confirm a non-linear, inverted U-shaped relationship where moderate similarity balances absorptive capacity and novelty, how this relationship changes with increasing knowledge complexity is poorly understood. This study investigates how knowledge complexity moderates the cognitive proximity-innovation relationship in the U.S. biotechnology sector using a comprehensive dataset of over 650,000 patents from over 57,000 unique assignee organizations spanning 1976 to 2024. We distinguish between two dimensions of collaborative innovation: collaboration volume and collaboration quality. Cognitive proximity was measured through CPC-based Jaccard similarity, while knowledge complexity was operationalized using a structural complexity framework based on knowledge combination networks. Negative binomial regressions reveal that knowledge complexity moderates the proximity-innovation relationship differently across the two dimensions. For collaboration volume, higher complexity shifts the optimal proximity point rightward and flattens the curve while maintaining the inverted U-shape. For collaboration quality, complexity produces a leftward shift and, remarkably, leads to a complete breakdown of the curvilinear relationship at high complexity levels, where the relationship becomes nearly horizontal. These contrasting patterns indicate that cognitive proximity operates through fundamentally different mechanisms in partner selection versus innovation realization. While absorptive capacity considerations dominate partnership decisions even under high complexity, novelty-generating mechanisms become disconnected from proximity effects as complexity rises. The findings refine proximity theory by demonstrating that knowledge complexity serves as a structural moderator and offer actionable insights for partner selection strategies in advanced innovation ecosystems.

Indexed as

CognitionCooperative BehaviorKnowledgeLearningHumansUnited States

Identifiers

PMID41417844
PMCPMC12716722

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.