Evidence map›Paper›PMID 42034657›Full record

ArticleScientific reports2026

Mechanisms of employability development for applied talents in the artificial intelligence era.

Liguo Wu, Chanti Wu, Jinzhou Geng, Haitao Zhao, Zongtuan Liu

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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

5 authors.

Liguo WuCollege of Management, Ningbo University of Finance & Economics, Ningbo, 315175, Zhejiang, P.R. China.
Chanti WuCollege of Management, Ningbo University of Finance & Economics, Ningbo, 315175, Zhejiang, P.R. China.
Jinzhou GengCollege of Management, Ningbo University of Finance & Economics, Ningbo, 315175, Zhejiang, P.R. China.
Haitao ZhaoSchool of Humanities, Ningbo University of Finance & Economics, Ningbo, 315175, Zhejiang, P.R. China.
Zongtuan LiuCollege of Management, Ningbo University of Finance & Economics, Ningbo, 315175, Zhejiang, P.R. China. ztliu@nbufe.edu.cn.

Funding

Teaching Reform Project of Zhejiang Provincial Regular Undergraduate Universities during the "14th Five-Year Plan" Period jg20220635
6 · The paper itself

Abstract

Rapid AI integration is transforming global labor markets while widening the digital skills gap. Despite existing efforts, research remains limited by ambiguous AI-driven dimensions, a lack of systematic exploration into factor hierarchies, and methodological constraints that leave deep-seated causal mechanisms underexplored. Integrating the COTE (Customer-Organization-Technology-Environment) value co-creation framework with TOE and UTAUT models, this study employs a multi-stage mixed-methods design centered on a pivotal cross-border e-commerce enterprise. Utilizing a tripartite research design comprising Grounded Theory (n = 15), DEMATEL (n = 6), and Interpretive Structural Modeling (ISM), we develop a holistic Macro-Micro framework to identify and deconstruct 15 critical factors influencing the employability of applied talents. The findings reveal a multi-layered Environment-Organization-Competency (E-O-C) transmission path where corporate culture acts as the foundational driver, triggering a recursive feedback loop among workplace mindset, communication, and career development, which ultimately facilitates the top-level outcome of AI technology acceptance. This systematic framework provides actionable guidance for stakeholders to optimize talent cultivation models in the era of AI.

Indexed as

Artificial intelligenceCOTE frameworkEmployabilityMixed methods

Identifiers

PMID42034657
PMCPMC13279778

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.