Digital orientation enables disruptive technological innovation in agricultural technology enterprises
Year: 2026
Type: article
Abstract: Agricultural technology enterprises face growing pressure to achieve technological breakthroughs in response to the challenges of food security, climate change and digital transformation. However, how these enterprises can strategically drive disruptive technological innovation remains underexplored. Drawing on dynamic capabilities theory, this study addresses this research gap by examining how digital orientation shapes disruptive technological innovation outcomes at the technological paradigm level through the mediating mechanisms of sensing, seizing and reconfiguring capabilities, and how these relationships are conditioned by organizational unlearning and resource orchestration. Based on survey data from 422 agricultural technology enterprises in China, structural equation modeling and bootstrap testing were employed to empirically validate the proposed framework. The results demonstrate that digital orientation significantly enhances disruptive technological innovation both directly and indirectly via dynamic capabilities. Furthermore, organizational unlearning strengthens the effect of digital orientation on dynamic capabilities, while resource orchestration amplifies the impact of dynamic capabilities on innovation outcomes. By clarifying the internal mechanisms and boundary conditions of digital orientation in agriculture, this study extends the application of dynamic capabilities theory to a sector characterized by long innovation cycles and high resource uncertainty. The findings also provide actionable insights for managers and policymakers aiming to foster technological self-reliance and high-impact innovation in agriculture.
Source: Scientific Reports
Authors: Yunqi Chen, Liqing Zhou, Yichu Wang
Institution: Shanxi University of Finance and Economics
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,690
Award: G5083782308
OpenAlex ID: W7166456667
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