Methodology for analyzing the business development environment to establish strategic priorities for agribusinessin the bani world context

Viktoriia Kyfyak
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Viktoriia Kyfyak: Yurii Fedkovych Chernivtsi National University

Economic Synergy, 2025, issue 3, 97-114

Abstract: The study develops a methodology for analyzing the agribusiness development environment in the BANI world (Brittle, Anxious, Nonlinear, Incomprehensible) to establish strategic priorities. A transdisciplinary approach integrates institutional economics, systems analysis, and scenario forecasting. The objective of the article is to develop and validate a methodology for analyzing the environment for agribusiness development within the context of the BANI world (brittle, anxious, nonlinear, incomprehensible), aimed at identifying strategic priorities that ensure the sustainability and competitiveness of agricultural enterprises. An adapted APESTEL analysis, incorporating agroecological and logistical factors, is proposed alongside the AgriStrat-AI algorithm, leveraging artificial intelligence (AI), Big Data, IoT, and blockchain to process data from World Bank, FAO, OECD, IFAD, and WBA research. The methodology comprises five stages: data integration, contextual analysis, predictive modeling, priority setting, and adaptive monitoring. It employs natural language processing, K-means clustering, deep learning, Monte Carlo simulations, and reinforcement learning to forecast market trends, assess climate risks, and optimize supply chains. The approach enhances strategic planning accuracy, enabling agribusinesses to adapt to uncertainty driven by geopolitical, climatic, and technological challenges. Key findings include improved demand forecasting for sustainable products, enhanced supply chain transparency via blockchain, and identification of climate-resilient strategies. Applicable to agribusinesses of varying scales, the methodology supports compliance with global sustainability goals, such as the European Green Deal. Implementation requires significant investment in AI infrastructure and workforce training, posing challenges for small enterprises. Future research should focus on reducing costs and enhancing technology accessibility to promote sustainable agribusiness development in dynamic global conditions.

Keywords: BANI world; agribusiness; APESTEL analysis; artificial intelligence; Big Data; IoT; blockchain; scenario forecasting; climate risks; sustainability (search for similar items in EconPapers)
JEL-codes: B41 D81 M10 O13 Q13 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bja:isteus:y:2025:i:3:p:97-114

DOI: 10.53920/ES-2025-3-8

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