Effects of the AI-Driven Design Process on Pleasure and Self-Expansion: Focusing on Perceived Originality and Attractiveness

This study examined the perceived originality and attractiveness of design output in the AI-driven design process and their impact on self-expansion through pleasure. Furthermore, this study examined whether individuals’ creative consumer efficacy moderates the effects of perceived originality and attractiveness on pleasure. The volunteers participated in a design process to collect data using a generative AI program within an experimental setting. Seventy-seven complete responses were collected. The data were analyzed using SPSS 26.0 for exploratory factor analysis, reliability analysis, and the PROCESS macro for mediation analysis. Bootstrapping analysis using the PROCESS macro (Model 8, with 5,000 bootstrap samples) showed that perceived originality increased self-expansion, with this effect mediated by pleasure. The effect of perceived originality on pleasure was moderated by creative consumer efficacy. Specifically, individuals with low creative consumer efficacy exhibited a stronger positive relationship between the perceived originality and pleasure. In addition, the direct effect of perceived attractiveness on self-expansion was significant, but this relationship was not mediated by pleasure. By identifying pleasure as a mediator between perceived originality and self-expansion, this study extends existing theories on the emotional aspects of innovation processes. Furthermore, exploring creative consumer efficacy as a moderator enriches the theoretical frameworks by recognizing the role of individual differences.

Authors

Publication Details

Journal
The Korean Journal of Community Living Science
Published
2025-02-28
DOI
https://doi.org/10.7856/kjcls.2025.36.1.47
Primary Topic
Consumer Perception and Purchasing Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of the AI-Driven Design Process on Pleasure and Self-Expansion: Focusing on Perceived Originality and Attractiveness

Ha Kyung Lee
The Korean Journal of Community Living Science
Consumer Perception and Purchasing Behavior
article

Effects of the AI-Driven Design Process on Pleasure and Self-Expansion: Focusing on Perceived Originality and Attractiveness

Ha Kyung Lee
article en

Abstract

This study examined the perceived originality and attractiveness of design output in the AI-driven design process and their impact on self-expansion through pleasure. Furthermore, this study examined whether individuals’ creative consumer efficacy moderates the effects of perceived originality and attractiveness on pleasure. The volunteers participated in a design process to collect data using a generative AI program within an experimental setting. Seventy-seven complete responses were collected. The data were analyzed using SPSS 26.0 for exploratory factor analysis, reliability analysis, and the PROCESS macro for mediation analysis. Bootstrapping analysis using the PROCESS macro (Model 8, with 5,000 bootstrap samples) showed that perceived originality increased self-expansion, with this effect mediated by pleasure. The effect of perceived originality on pleasure was moderated by creative consumer efficacy. Specifically, individuals with low creative consumer efficacy exhibited a stronger positive relationship between the perceived originality and pleasure. In addition, the direct effect of perceived attractiveness on self-expansion was significant, but this relationship was not mediated by pleasure. By identifying pleasure as a mediator between perceived originality and self-expansion, this study extends existing theories on the emotional aspects of innovation processes. Furthermore, exploring creative consumer efficacy as a moderator enriches the theoretical frameworks by recognizing the role of individual differences.

The Korean Journal of Community Living ScienceVol. 36(1)
Openalex Percentile: Top 95%
Consumer Perception and Purchasing Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.