Features of the development of the agricultural marketing system using information technologies

O. Stepanyuk, Y. Senyk, I. Ivanyk, A. Senyk
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Abstract

Forecasting prices for agricultural products is a complex, end-to-end and dynamic task of agricultural marketing. With constant development and changes in data sources, data types, data quality, data processing methods, model building methods, and model evaluation methods, agricultural price forecasting methods will also be updated and improved. An overview of the use of digital technologies is proposed, leading to profound changes in the functioning of economic factors, including in the agro-industrial complex. The article shows that the digital transformation (digitalization) of the agro-industrial market will lead to a change in the sectoral structure of the agro-industrial complex due to the replacement of traditional industries with new ones based on forecasts obtained using artificial intelligence systems. The paper provides an overview of specialized applied software products that are available on the Internet and are used to analyze financial data. An overview of modern information technologies, which allow convenient processing, systematization and visualization of data, as well as forecasting the movement of asset prices, was carried out. Scientific abstraction, analysis and synthesis methods, quantitative and qualitative assessment methods, which were used to determine the content of marketing concepts and its features in the activities of agro-industrial enterprises, as well as the method of source analysis served as the scientific and theoretical basis for deepening the research. When selecting sources for analysis, a search was made in open databases available in the global information network Internet, on the basis of which neural network training was carried out. The main functionalities of the created system are described, including a visual comparison of historical data, price movement forecasting using machine learning, and recommendations on the optimal content of the investment portfolio. The results obtained in the work substantiate the following basic propositions: - digitalization leads not only to technological, but also to organizational transformations in the agro-industrial complex; - the result of digital transformation will be a profound change in the model of the organization of the agro-industrial complex and its role in the national economy; - agribusiness needs to take measures to support the digital transformation of the agro-industrial market and the adaptation of the agro-industrial complex to the new digital system.
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利用信息技术发展农业营销系统的特点
农产品价格预测是农产品营销中一项复杂的、点对点的动态工作。随着数据来源、数据类型、数据质量、数据处理方法、模型建立方法和模型评估方法的不断发展和变化,农产品价格预测方法也将不断更新和完善。文章概述了数字技术的使用情况,数字技术的使用将导致包括农工综合体在内的经济要素的运作发生深刻变化。文章指出,农工市场的数字化转型(数字化)将导致农工综合体的部门结构发生变化,原因是在利用人工智能系统进行预测的基础上,新产业将取代传统产业。本文概述了互联网上可用于分析金融数据的专业应用软件产品。本文对现代信息技术进行了概述,这些技术可以对数据进行便捷的处理、系统化和可视化,并预测资产价格的走势。科学的抽象、分析和综合方法,定量和定性评估方法,用于确定营销概念的内容及其在农工企业活动中的特点,以及来源分析方法,是深化研究的科学和理论基础。在选择分析来源时,对全球信息网络因特网上的开放式数据库进行了搜索,并在此基础上进行了神经网络训练。文中介绍了所创建系统的主要功能,包括历史数据的可视化比较、利用机器学习预测价格走势,以及就投资组合的最佳内容提出建议。工作中获得的结果证实了以下基本命题:- 数字化不仅会导致农工综合体的技术转型,也会导致其组织转型; - 数字化转型的结果将是农工综合体组织模式及其在国民经济中作用的深刻变化; - 农业企业需要采取措施支持农工市场的数字化转型以及农工综合体对新数字化系统的适应。
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