THEORY AND METHODOLOGY OF SCIENTIFIC RESEARCH ON INVESTMENT MANAGEMENT OF DISTRIBUTION NETWORKS IN AGRIBUSINESS
農業ビジネスにおける流通ネットワークの投資管理に関する科学研究の理論と方法論 (AI 翻訳)
I. Kravchuk, N. Valinkevych, O. Prysiazhniuk
🤖 gxceed AI 要約
日本語
本論文は、農業ビジネスの流通ネットワーク形成・発展のための投資管理の理論的・応用的基盤を提示する。従来の線形投資モデルに代わり、ポートフォリオ多様化、リアルオプション評価、行動ファイナンス、ESG指標、DeFiを統合し、AIとビッグデータによる階層的デジタル化モデルを提案。国家・地域・地方の3レベルで資本配分を最適化し、金融信用スコアとESGプロファイリングを組み合わせた「二因子バランス発展マトリクス」を導入。グリーントレードファイナンスや気候保険などのリスク軽減手段により、Scope3排出評価の改善を目指す。
English
This paper presents theoretical and applied foundations for investment management in agribusiness distribution networks, integrating portfolio diversification, real options, behavioral finance, ESG metrics, and DeFi. It proposes a hierarchical AI and Big Data-driven digitization model operating at national, regional, and local levels to optimize capital allocation. A 'Two-Factor Balanced Development Matrix' links financial credit scoring with ESG profiling to categorize counterparties. Risk mitigation tools like green trade finance and parametric climate insurance aim to reduce non-performing loans and improve Scope 3 emission ratings.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、SSBJ開示やサプライチェーン排出量算定が進む中、農業・食品産業の流通網におけるESG統合投資モデルは、地域経済や食料安全保障の観点から参考になる。AIを活用した階層的投資管理は、日本の農業法人や食品企業のScope3対応や投資判断に示唆を与える。
In the global GX context
Globally, this paper contributes to the discourse on integrating ESG metrics into investment management for agricultural supply chains, aligning with ISSB and CSRD disclosure trends. The proposed AI-driven hierarchical model and risk mitigation instruments offer a framework for enhancing Scope 3 reporting and green finance in agribusiness, relevant for emerging markets and international development finance.
👥 読者別の含意
🔬研究者:Provides a conceptual framework combining AI, ESG, and investment theory for agricultural supply chains, useful for further empirical testing.
🏢実務担当者:Offers a matrix for categorizing counterparties by ESG and financial risk, aiding in trade credit decisions and Scope 3 management.
🏛政策担当者:Highlights the need for policy support for green trade finance and climate insurance in agribusiness to foster sustainable investment.
📄 Abstract（原文）
This paper substantiates the theoretical and applied foundations of investment management for forming and developing resilient distribution networks in agribusiness. Under global food market transformations, systemic macroeconomic instability, and geopolitical shocks, conventional linear investment models prove ineffective for long-term planning. To bridge this gap, this research adapts advanced economic frameworks directly to agricultural supply chains, shifting the focus from discrete physical asset valuation to ecosystem-wide synergy. This is achieved by combining classic capital planning with portfolio diversification, real options valuation (ROV), behavioral finance, stakeholder-driven ESG metrics, and decentralized financial tools (DeFi). The study proposes a hierarchical digitization model of the investment process powered by artificial intelligence (AI) and Big Data. This system operates at three spatial levels: national (for comprehensive stress-testing against geopolitical shocks), regional (deploying predictive digital twins of logistics clusters to optimize infrastructure placement), and local (facilitating agile capital allocation and behavioral consumer analysis). This structure ensures capital flows efficiently into highperforming channels while minimizing bottlenecks. To address the trade-off between environmental requirements and financial risks, the study introduces the "Two-Factor Balanced Development Matrix." This model links financial credit scoring with multidimensional ESG profiling. Counterparties are categorized into operational quadrants (e.g., Green Leaders, Traditional Pragmatists, Eco-Startups) to determine customized trade credit lines and commercial terms. Finally, the research outlines integrated risk mitigation instruments, including green trade finance (IFC, EBRD), eco-premium forward contracts, and parametric climate insurance. These measures reduce non-performing loans, lower the cost of capital, and improve the Scope 3 emission rating for distributors.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.32782/business-navigator.86-33first seen 2026-08-16 05:27:53
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