Evidence map›Paper›PMID 40570048›Full record

ArticlePloS one2025

Diversity in knowledge search paths and breakthrough technological innovation: Evidence from new energy vehicle firms.

Xiao Yin, Le Song, Ying Pan

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.

Xiao YinSchool of Business Administration, South China University of Technology, Guangzhou, China.ORCID 0009-0008-4939-8546
Le SongSchool of Business, Shandong Normal University, Jinan, China.ORCID 0000-0001-9425-9395
Ying PanSchool of Business Administration, South China University of Technology, Guangzhou, China.ORCID 0009-0006-4300-0061

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breakthrough technological innovations have heralded a transformative era within the automotive industry. Knowledge search diversity, as the key to acquiring the raw materials for knowledge recombination, enables firms to overcome resource constraints and accelerate the realization of breakthrough technological innovations. This paper integrates the theories of organizational search and knowledge recombination theory and draws upon the relationship between knowledge and industry to distinguish between basic knowledge search diversity and applied knowledge search diversity. It further investigates the distinct relationships between these two forms of knowledge search diversity and their respective contributions to breakthrough technological innovations. We develop research hypotheses and employ a negative binomial fixed-effects regression model to empirically test data from 280 Chinese new energy vehicle (NEV) manufacturers. The results demonstrate that: (1) knowledge search diversity exhibits an inverted U-shaped relationship with breakthrough technological innovation; (2) the inverted U-shaped relationship is steeper for basic knowledge search diversity compared to applied knowledge search diversity; (3) organizational proximity positively moderates the inverted U-shaped relationship between knowledge search diversity and breakthrough technological innovation. The findings provide practical insights into optimizing knowledge search strategies for technological convergence and accelerating the internalization of external resources to foster innovative transformation and upgrading.

Indexed as

AutomobilesIndustryInventionsKnowledgeTechnologyChinaHumans

Identifiers

PMID40570048
PMCPMC12201647

What OpenQuestion holds

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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.