Evidence map›Paper›PMID 40595210›Full record

ArticleScientific reports2025

Factors influencing the intention of textile and garment SMEs to adopt digital technologies and its impact on performance.

Aries Susanty, Nia Budi Puspitasari, Geovany Sondang Siahaan, Sigit Setiawan, Muhammad Syafrudin

Abstract read
In one paragraph

Article in Scientific reports, 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

5 authors.

Aries SusantyDepartment of Industrial Engineering, Diponegoro University, Semarang, Central Java, Indonesia. ariessusanty@gmail.com.
Nia Budi PuspitasariDepartment of Industrial Engineering, Diponegoro University, Semarang, Central Java, Indonesia.
Geovany Sondang SiahaanDepartment of Industrial Engineering, Diponegoro University, Semarang, Central Java, Indonesia.
Sigit SetiawanNational Research and Innovation Agency, Jakarta, Indonesia.
Muhammad SyafrudinDepartment of Artificial Intelligence and Data Science, Sejong University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to identify the factors influencing textile and garment SMEs' intentions to adopt digital technology. A survey of owners of textile and garment SMEs respondents was conducted to explore the determinants that shape SMEs' decisions to adopt digital technology using the Unified Theory of Acceptance and Use of Technology (UTAUT), which was extended with six additional variables: trust and perceived risk for internal of SMEs, competitive pressure and government support for external of SMEs, and non-financial and financial performance for the impact of digital technology on SMEs business. The findings indicate a significant influence of performance expectancy, effort expectancy, trust, government support, and competitive pressure on digital technology adoption by textile and garment SMEs. Then, facilitating condition and behavioural intention significantly influence actual behavior to use, impacting both financial and non-financial performance. The study's findings provide vital insights for owners of SMEs and government (policymakers) for the successful adoption of digital technology. The integration of digital technologies requires specialized skills. Governments and industry associations can implement training programs to equip workers with the necessary skills for operating digital machinery and managing digital systems.

Indexed as

Behavioural intentionDigital technologyExtension of the UTAUT modelTextile and garment SMEs

Identifiers

PMID40595210
PMCPMC12215705

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.