Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Exploring fashion designers' acceptance of AIGC: A dual-pathway analysis from the stimulus-organism-response perspective.

Created on 18 Aug 2026

Authors

Tingting Ma, Mengyun Yang

Published in

PloS one. Volume 21. Issue 8. Pages e0356536. Epub Aug 17, 2026.

Abstract

Artificial Intelligence Generated Content (AIGC) is increasingly used in creative design. Understanding fashion designers' willingness to adopt these tools has therefore become important for both research and practice. Drawing on the Stimulus-Organism-Response (SOR) model, this study integrates Self-Determination Theory (SDT) with perceived risk, social influence, and facilitating conditions. It examines how these contextual stimuli shape designers' basic psychological need satisfaction and behavioral intention. We analyzed 318 valid responses with complete data for all 21 measurement items from Chinese fashion-design practitioners using partial least squares structural equation modeling (PLS-SEM). Perceived risk negatively predicted autonomy, competence, and relatedness, whereas social influence and facilitating conditions positively predicted these organismic states. Autonomy, competence, and relatedness each positively predicted behavioral intention, with competence showing the largest coefficient (β = 0.520, p < 0.001). Bootstrapped analyses confirmed all nine specific indirect effects from the three stimuli to behavioral intention through the three psychological needs. These findings clarify how SOR and SDT jointly explain technology adoption among fashion designers. They also provide practical guidance for copyright governance, prompt training, and collaboration between designers and AI.

PMID:
42607085
Bibliographic data and abstract were imported from PubMed on 18 Aug 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 9
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement