Human–generative AI cooperation and knowledge collaboration in online knowledge communities: an analysis based on adaptive structuration theory for individuals

Purpose Human-generative artificial intelligence (AI) cooperation (HGAIC) offers new opportunities for knowledge collaboration in online knowledge communities (OKCs). However, existing studies neglect to explore how different HGAIC strategies (exploitative and explorative) affect knowledge collaboration (knowledge acquisition and contribution) under the influence of GAI capabilities (generativity, autonomy and interactivity) and OKC factors (question variety and platform involvement). This means there is a lack of sufficient theoretical and practical guidelines on promoting flexible HGAIC to enhance knowledge collaboration in OKC. Design/methodology/approach The partial least squares structural equation modeling method was employed to analyze data from 355 OKC users, and the vignette experiment method was used to analyze data from 345 OKC users. Findings The findings indicate that both exploitative and explorative cooperation positively affect knowledge acquisition and contribution. GAI generativity, GAI autonomy, GAI interactivity and platform involvement positively affect both exploitative and explorative cooperation. In contrast, question variety only significantly enhances exploitative cooperation. Furthermore, the structured antecedents can enhance knowledge acquisition and contribution by facilitating exploitative and explorative cooperation. In addition, creative time pressure weakens the positive relationship between exploitative cooperation and knowledge contribution while enhancing the positive relationship between explorative cooperation and knowledge contribution. Originality/value First, this study classifies HGAIC into exploitative and explorative cooperation and reveals their crucial roles in knowledge collaboration in OKC. Second, this study supplements and examines the ASTI framework, identifying the antecedents and outcomes of exploitative and explorative cooperation. Finally, this study emphasizes the bidirectional moderating role of creative time pressure in the impact of exploitative and explorative cooperation on knowledge contribution.

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Publication Details

Journal
Information Technology and People
Published
2026-01-05
DOI
https://doi.org/10.1108/itp-09-2024-1184
Citations
1
Primary Topic
Knowledge Management and Sharing
Type
article
Field-Weighted Citation Impact
0.00
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article

Human–generative AI cooperation and knowledge collaboration in online knowledge communities: an analysis based on adaptive structuration theory for individuals

Peng Yu, Hongyu Cui
1 citations
Information Technology and People
Knowledge Management and Sharing
article

Human–generative AI cooperation and knowledge collaboration in online knowledge communities: an analysis based on adaptive structuration theory for individuals

Peng Yu, Hongyu Cui
article en
1 citations

Abstract

Purpose Human-generative artificial intelligence (AI) cooperation (HGAIC) offers new opportunities for knowledge collaboration in online knowledge communities (OKCs). However, existing studies neglect to explore how different HGAIC strategies (exploitative and explorative) affect knowledge collaboration (knowledge acquisition and contribution) under the influence of GAI capabilities (generativity, autonomy and interactivity) and OKC factors (question variety and platform involvement). This means there is a lack of sufficient theoretical and practical guidelines on promoting flexible HGAIC to enhance knowledge collaboration in OKC. Design/methodology/approach The partial least squares structural equation modeling method was employed to analyze data from 355 OKC users, and the vignette experiment method was used to analyze data from 345 OKC users. Findings The findings indicate that both exploitative and explorative cooperation positively affect knowledge acquisition and contribution. GAI generativity, GAI autonomy, GAI interactivity and platform involvement positively affect both exploitative and explorative cooperation. In contrast, question variety only significantly enhances exploitative cooperation. Furthermore, the structured antecedents can enhance knowledge acquisition and contribution by facilitating exploitative and explorative cooperation. In addition, creative time pressure weakens the positive relationship between exploitative cooperation and knowledge contribution while enhancing the positive relationship between explorative cooperation and knowledge contribution. Originality/value First, this study classifies HGAIC into exploitative and explorative cooperation and reveals their crucial roles in knowledge collaboration in OKC. Second, this study supplements and examines the ASTI framework, identifying the antecedents and outcomes of exploitative and explorative cooperation. Finally, this study emphasizes the bidirectional moderating role of creative time pressure in the impact of exploitative and explorative cooperation on knowledge contribution.

Information Technology and People
Shandong University of Finance and Economics (CN)
Partnerships for the goals
Openalex Percentile: Top 96%
Knowledge Management and Sharing
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