Evidence map›Paper›PMID 40920781›Full record

ArticlePloS one2025

When automation hits jobs: Entrepreneurship as an alternative career path.

Daehyun Kim, Taekyun Kim, Wonjoon Kim, Hyejin Youn

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

4 authors.

Daehyun KimMax Planck Institute for Innovation and Competition, München, Germany.ORCID https://orcid.org/0009-0009-4557-727X
Taekyun KimSchool of Business, Chungnam National University, Daejeon, South Korea.ORCID https://orcid.org/0009-0001-1586-3752
Wonjoon KimSchool of Business and Technology Management, KAIST, Daejeon, South Korea.
Hyejin YounCollege of Business Administration, Seoul National University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the relationship between occupational automation risks and workers' transitions to entrepreneurship using data from the Current Population Survey. We find that employees facing automation-related job displacement are inclined to shift toward unincorporated entrepreneurship, emphasizing entrepreneurship as a viable alternative career path. Noteworthy variations emerge when examining specific automation technologies, revealing a positive association between industrial robots and entrepreneurial transitions, whereas artificial intelligence displays a negative relationship. Gender disparities are observed, with female workers exhibiting a lower likelihood than males of transitioning into entrepreneurship. This study also shows a heightened prominence of entrepreneurial transitions during the early stages of the COVID-19 pandemic. By illuminating entrepreneurship as a response to job displacement, our results offer crucial policy insights into the labor market implications of automation.

Indexed as

AutomationCOVID-19EntrepreneurshipAdultArtificial IntelligenceEmploymentFemaleHumansMaleMiddle AgedSARS-CoV-2Surveys and Questionnaires

Identifiers

PMID40920781
PMCPMC12416648

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.