@article{ART003335453},
author={Jeong Woo Hwang and Seung In Kim},
title={A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner},
journal={Industry Promotion Research},
issn={2466-1139},
year={2026},
volume={11},
number={2},
pages={261-273},
doi={10.21186/IPR.2026.11.2.261}
TY - JOUR
AU - Jeong Woo Hwang
AU - Seung In Kim
TI - A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner
JO - Industry Promotion Research
PY - 2026
VL - 11
IS - 2
PB - Industrial Promotion Institute
SP - 261
EP - 273
SN - 2466-1139
AB - This study aims to empirically examine the acceptance process of Generation Z users who perceive text-based generative AI as a collaborative partner. While generative AI is increasingly utilized as an agent of cooperative interaction rather than a mere tool, structural explanations of how such perceptions are formed in actual usage contexts remain limited. To address this gap, the study proposes a research model that incorporates performance expectancy from UTAUT and shared goal recognition from collaboration theory as key antecedents, with trust and engagement as serial mediators. A mixed-method approach combining surveys and in-depth interviews with Generation Z users experienced in text-based generative AI was employed. Quantitative analysis revealed that collaborative usage intention is more directly shaped by performance expectancy than relational factors, while trust and engagement function as conditional process variables depending on context. Qualitative findings further support these results, showing that users adjust their perception of collaboration situationally. By extending AI acceptance beyond technology adoption to the formation of collaborative recognition, this study provides meaningful implications for AI service design and user experience development.
KW - Generative AI;Human–AI Collaboration;Collaborative User Experience;Technology Acceptance;Generation Z
DO - 10.21186/IPR.2026.11.2.261
ER -
Jeong Woo Hwang and Seung In Kim. (2026). A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner. Industry Promotion Research, 11(2), 261-273.
Jeong Woo Hwang and Seung In Kim. 2026, "A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner", Industry Promotion Research, vol.11, no.2 pp.261-273. Available from: doi:10.21186/IPR.2026.11.2.261
Jeong Woo Hwang, Seung In Kim "A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner" Industry Promotion Research 11.2 pp.261-273 (2026) : 261.
Jeong Woo Hwang, Seung In Kim. A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner. 2026; 11(2), 261-273. Available from: doi:10.21186/IPR.2026.11.2.261
Jeong Woo Hwang and Seung In Kim. "A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner" Industry Promotion Research 11, no.2 (2026) : 261-273.doi: 10.21186/IPR.2026.11.2.261
Jeong Woo Hwang; Seung In Kim. A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner. Industry Promotion Research, 11(2), 261-273. doi: 10.21186/IPR.2026.11.2.261
Jeong Woo Hwang; Seung In Kim. A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner. Industry Promotion Research. 2026; 11(2) 261-273. doi: 10.21186/IPR.2026.11.2.261
Jeong Woo Hwang, Seung In Kim. A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner. 2026; 11(2), 261-273. Available from: doi:10.21186/IPR.2026.11.2.261
Jeong Woo Hwang and Seung In Kim. "A Study on the Acceptance Process of Generation Z Users Who Perceive Text-Based Generative AI as a Collaborative Partner" Industry Promotion Research 11, no.2 (2026) : 261-273.doi: 10.21186/IPR.2026.11.2.261
