Evidence map›Paper›PMID 42651517›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

The Impact of Psychological Resilience on Digital Transformation: A Resource Orchestration Perspective.

Gejun Wang, Xingqiu Hu

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 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

2 authors.

Gejun WangSchool of Business, Hohai University, Nanjing 211100, China.ORCID 0009-0004-7393-7053
Xingqiu HuSchool of Business, Hohai University, Nanjing 211100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of economic turbulence, pursuing new development opportunities through digital transformation has become an inevitable choice for Chinese firms, with top executives serving as core decision-makers. Drawing on resource orchestration theory and the too-much-of-a-good-thing effect, this study examines the relationship between executive psychological resilience and enterprise digital transformation, as well as its boundary conditions, using panel data from Chinese A-share listed firms from 2011 to 2024. The results provide evidence of an inverted U-shaped relationship between executive psychological resilience and enterprise digital transformation, suggesting that an optimal level of psychological resilience exists for digital transformation. Beyond this level, manifestations of bounded rationality, including an underestimation of transformation risks and attentional biases, lead to inefficient resource orchestration. Industry capital intensity weakens this nonlinear relationship, while slack resources appear to shift the turning point to an earlier stage. By questioning the cognitive inertia that treats resilience as a universally beneficial personality trait, this study shifts the perspective on the relationship between executive psychological resilience and enterprise digital transformation from a linear to a nonlinear framework. It further extends the application of the resource orchestration theory in the digital transformation context and contributes to research on the micro-level drivers of digital transformation-specifically executive psychological traits.

Indexed as

enterprise digital transformationexecutive psychological resiliencemanagerial discretionresource orchestration theorytoo-much-of-a-good-thing effect

Identifiers

PMID42651517
PMCPMC13509346

What OpenQuestion holds

Textmetadata
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.