Evidence map›Paper›PMID 39729485›Full record

ArticlePloS one2024

Exploring pathways to digital transformation: fsQCA analysis based on the AMO framework.

Jun Liu, Ziwei Wang, Changjin Li, Ruofan Xu

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jun LiuSchool of Business Administration, Shandong University of Finance and Economics, Jinan, Shandong, China.
Ziwei WangSchool of Business Administration, Shandong University of Finance and Economics, Jinan, Shandong, China.ORCID 0009-0003-8050-9121
Changjin LiSchool of Business Administration, Shandong University of Finance and Economics, Jinan, Shandong, China.
Ruofan XuSchool of Business Administration, Shandong University of Finance and Economics, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, China has significantly increased its global competitiveness in digital technologies, emphasizing the importance of the digital economy during the high-quality development stage. The question of how firms in traditional industries can achieve digital transformation, which is critical for participating in the digital economy, is still understudied. Using the ability-motivation-opportunity (AMO) framework, this research developed a model and identified six factors' ability, motivation, and opportunity dimensions. It used fuzzy-set qualitative comparative analysis (fsQCA) to investigate their synergistic effect on digital transformation. With manufacturing firms in China as examples, the findings were as follows. First, no single factor could provide the necessary conditions for digital transformation, implying that the synergistic effect of multiple conditions must be considered. Second, four configurations with three paths for high digital transformation, namely motivation-opportunity-oriented, total factor-oriented, and motivation-oriented, showed different approaches to digital transformation under different conditions. These findings shed light on the complex causal relationships among antecedents of digital transformation and provide theoretical and practical recommendations for businesses looking to implement the digital process.

Indexed as

Digital TechnologyChinaFuzzy LogicHumansMotivation

Identifiers

PMID39729485
PMCPMC11676893

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.