<![CDATA[The livestock sector plays a crucial role in food security and rural economic resilience; however, goat farming management in developing economies remains largely traditional and weakly integrated with structured environmental accounting systems. This study develops and validates a Material Flow Cost Accounting (MFCA)-Driven Smart Goat Livestock Management System, which integrates environmental management accounting, Internet of Things (IoT) monitoring, emission estimation, and artificial intelligence (AI)-based decision support within a unified digital platform. Using a design science research approach combined with field validation, the system was implemented in a medium-scale goat farm over a two-month period. The MFCA model quantified material inputs and outputs in both physical and monetary terms, including feed conversion, waste generation, and methane (CH₄) and nitrous oxide (N₂O) emissions based on IPCC Tier 1 guidelines. The results demonstrate improvements in feed efficiency (from 74% to 84%), mortality reduction (from 8% to 4%), increased data accuracy (from 60% to 92%), and a 22% improvement in eco-efficiency ratios. The AI module achieved 87% accuracy in estrus detection and 84% accuracy in early disease classification. The study extends MFCA application from manufacturing to biological production systems and introduces the concept of accounting-driven smart farming, where environmental accounting is embedded within digital infrastructure. The findings contribute to the advancement of Digital Environmental Management Accounting (Digital EMA) and provide a scalable model for sustainable livestock transformation in emerging economies.]]>
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