Effective Economic Model for Greenhouse Facilities Management and Digitalization

Akmal Durmanov, Tulkin Farmanov, Fotima Nazarova, Bahtiyar Khasanov, Farkhod Karakulov, Nodira Saidaxmedova, Murodjon Mamatkulov, Talantbek Madumarov, Khurshida Kurbanova, Abror Mamasadikov, Zahiriddin Kholmatov


The main objective of this study was to inform evidence-based financial strategies and policy directions for Uzbekistan’s ambitious greenhouse agriculture expansion by quantifying how integration with agricultural data platforms affects key operational metrics like crop productivity, expenditures, profitability, and technical efficiency. The core methodological approach integrated econometric modeling techniques (production, cost, and profit functions) with data envelopment analysis to conduct comprehensive techno-economic assessments across a representative sample of 58 greenhouse facilities using primary data collected on yields, costs, technology deployment levels, and digital platform accessibility. A key finding was that involvement in digital supply chain coordination platforms corresponded to a 36% increase in profitability, coupled with a 19% reduction in expenses, a 29% improvement in crop yields, and a 22% boost in optimized technical efficiency scores relative to conventional practices after controlling for technology adoption and other factors. This novel contribution provides quantifiable evidence on the synergistic productivity, financial sustainability, and climate resilience dividends unlocked by aligning physical infrastructure upgrades with virtual enhancements around data visibility and supply network integration to overcome constraints facing smallholder agricultural operations. The interdisciplinary analysis outlines an integrated roadmap for smart greenhouse expansion through investments in transparency tools, digital ecosystems, and workforce training.


Doi: 10.28991/HEF-2024-05-02-04

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Greenhouse Economics; Agriculture Technology Adoption; Agricultural Policy; Digital Platform Integration; Data Envelopment Analysis.


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DOI: 10.28991/HEF-2024-05-02-04


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