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Dissertation 4.5

Explainable AI Adoption in Agritech Startups: Data Quality And Bias — 2024–2028 Trends

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Abstract

This dissertation investigates “Explainable AI Adoption in Agritech Startups: Data Quality And Bias — 2024–2028 Trends” using a panel regression with fixed effects. Through a behavioral lens, the analysis integrates multi-source data to derive an actionable roadmap for researchers and practitioners.

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Explainable AI Adoption in Agritech Startups: Data Quality And Bias — 2024–2028 Trends

ABSTRACT
Explainable AI Adoption in Agritech Startups: Data Quality And Bias — 2024–2028 Trends is unpacked across themes: governance, benefits, KPIs, and interoperability. Limitations and future research paths are noted.
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