Competitive and Knowledge Intelligence
Open access
Peer reviewed
Abstract
Abstract
Purpose: This study investigates whether competitive intelligence (CI) driven agricultural digitalization enhances Agricultural Green Total Factor Productivity (AGTFP) across China's 30 provinces. Three research questions guide the inquiry: (1) does digitalization significantly improve AGTFP? (2) through which institutional mechanisms digital financial inclusion and land transfer—does this impact operate? and (3) do the effects exhibit regional heterogeneity and nonlinear dynamics that generate paradoxical outcomes under certain conditions? Methodology/approach: A composite agricultural digitalization index is constructed via the entropy-weighting method. AGTFP is measured using an input-oriented Slack-Based Measure (SBM) model with undesirable outputs. Within a two-way fixed-effects panel framework, this study applies mediation analysis, moderation and threshold tests, quantile regression, and regional subgroup regressions. Originality/Relevance: By integrating competitive intelligence theory with green productivity analysis, this paper develops a unified 'mechanism–context' framework to explain how identical digital investments produce divergent efficiency outcomes across regions. The study extends digital agriculture theory beyond technology adoption narratives toward ecosystem-level structural transformation. Key findings: Digitalization exerts a significant positive effect on AGTFP (β = 0.495, p < 0.05) under the preferred two-way fixed-effects specification. Digital financial inclusion mediates this relationship more effectively (indirect effect = 0.051) than land transfer (indirect effect = 0.002). Moderate fiscal support amplifies digitalization effectiveness while excessive intervention weakens it. Regional analysis reveals strong positive effects in eastern China but adverse outcomes in the central region, suggesting transitional inefficiency. Quantile regression confirms that the productivity-enhancing effect is strongest among lower-performing provinces. Theoretical/methodological contributions: The study contributes a multidimensional digitalization index, an SBM-based green productivity measure, a staged nonlinear modernization trajectory, and a conditioned policy-effectiveness framework to digital agriculture and green productivity literature.
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@article{Wang2026Competitive,
title = {Competitive Intelligence–Driven Agricultural Digitalization and Green Productivity Transformation: Evidence from China's Provincial AGTFP Dynamics},
author = {Miao Wang and Adul Supanut and Suppanunta Romprasert and Jianxu Liu},
journal = {Journal of Sustainable Competitive Intelligence},
year = {2026},
doi = {10.37497/eaglesustainable.v16i.693},
url = {https://doi.org/10.37497/eaglesustainable.v16i.693}
}FAQ
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