Business Intelligence Adoption in Local Agribusiness Critical Success Factors and Performance Metrics
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Abstract
Business intelligence (BI) is essential for decision-making and competitiveness in many industries, including agribusiness, in the digital age. This study examines the key elements impacting BI adoption in North Sulawesi agricultural businesses. The mixed-methods study uses quantitative data from 276 agribusiness firms (response rate: 78.86%) and qualitative insights from 12 important stakeholders through semi-structured interviews. Technology infrastructure readiness (TIR), organizational readiness and support (ORS), human capital capability (HCC), and external environmental factors (EEF) are the four dimensions of the conceptual framework. Organizational readiness support is the strongest predictor of BI adoption, with a path coefficient of 0.603 and a substantial impact size (f² = 0.782). Additionally, the model indicates a direct relationship between Organizational readiness and support and Agricultural Process Innovation Performance (APIP) (β = 0.333). Research indicates that technology infrastructure readiness positively impacts BI adoption (β = 0.168), emphasizing the significance of strong IT systems. While human capital capability has a minor impact on BI adoption (β = 0.151), it needs significant organizational support to improve its impact on APIP. External environmental factors have a minor but significant impact (β = 0.119), indicating market dynamics and regulatory pressures influence BI adoption. The model predicts 77.2% of APIP and 68.2% of BI adoption. These findings add agribusiness-specific features to technology adoption models. The report offers policymakers, technology suppliers, and agricultural managers practical advice on BI deployment to improve sector efficiency and sustainability in emerging nations.
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