How do generative AI applications impact employees’ exploitative innovation behavior? An explanation based on the technology-organization-environment framework

Purpose We aim to adopt a technology-organization-environment framework to explain how Generative Artificial Intelligence (GenAI) applications influence exploitative innovation behavior among employees. Design/methodology/approach Based on the technology-organization-environment framework, we take perceived task-technology fit as the mediator to explore the mechanism of GenAI application on employees’ exploitative innovation behavior from technology, organization, and environmental aspects, and verifies the structural equation model with data from 374 questionnaires. Findings The personalization, information quality, organizational readiness, digital leadership, and competitive pressure significantly affect perceived task-technology fit, which in turn affects employees’ exploitative innovation behavior. Furthermore, AI awareness moderates the relationship between perceived task-technology fit and exploitative innovation behavior. Specifically, the higher the AI awareness, the stronger the positive influence of perceived task-technology fit on attitude, and the stronger the mediating effect of user attitude on the relationship between perceived task-technology fit and exploitative innovation behavior. Originality/value We identified the underlying mechanisms linking GenAI adoption to exploitative innovation behavior, thus offering the theoretical guidance for enterprises to apply GenAI further and improve the practice of employee innovation management.

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Publication Details

Journal
Journal of Systems and Information Technology
Published
2026-03-14
DOI
https://doi.org/10.1108/jsit-05-2025-0221
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

How do generative AI applications impact employees’ exploitative innovation behavior? An explanation based on the technology-organization-environment framework

Zhangxiang Zhu, Yaqin Gan, Jing Wang
Journal of Systems and Information Technology
Ethics and Social Impacts of AI
article

How do generative AI applications impact employees’ exploitative innovation behavior? An explanation based on the technology-organization-environment framework

Zhangxiang Zhu, Yaqin Gan, Jing Wang
article en

Abstract

Purpose We aim to adopt a technology-organization-environment framework to explain how Generative Artificial Intelligence (GenAI) applications influence exploitative innovation behavior among employees. Design/methodology/approach Based on the technology-organization-environment framework, we take perceived task-technology fit as the mediator to explore the mechanism of GenAI application on employees’ exploitative innovation behavior from technology, organization, and environmental aspects, and verifies the structural equation model with data from 374 questionnaires. Findings The personalization, information quality, organizational readiness, digital leadership, and competitive pressure significantly affect perceived task-technology fit, which in turn affects employees’ exploitative innovation behavior. Furthermore, AI awareness moderates the relationship between perceived task-technology fit and exploitative innovation behavior. Specifically, the higher the AI awareness, the stronger the positive influence of perceived task-technology fit on attitude, and the stronger the mediating effect of user attitude on the relationship between perceived task-technology fit and exploitative innovation behavior. Originality/value We identified the underlying mechanisms linking GenAI adoption to exploitative innovation behavior, thus offering the theoretical guidance for enterprises to apply GenAI further and improve the practice of employee innovation management.

Journal of Systems and Information Technology
Hunan Normal University (CN), Changsha Normal University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 24%
Ethics and Social Impacts of AI
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