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РОЗРОБКА ТОВАРНОЇ СТРАТЕГІЇ ОПТОВОЇ ТОРГІВЛІ АГРОПРОДУКЦІЇ В УМОВАХ НЕВИЗНАЧЕНОСТІ
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The trade of agricultural products plays an essential role in agricultural development. Agricultural trade is more complicated and diversified than other industrial products, influenced by product characteristics for perishable. The Association of Southeast Asian Nations (ASEAN) is one of the most important markets for China’s agricultural exports. This study aimed to analyze the impact of trade facilitation indicators on China’s agricultural exports to ASEAN countries. A gravity model was adopted by taking the volume of Chinese agricultural exports to ASEAN countries from 2006–2020 as the dependent variable. Indicators such as economic freedom (EF), trade across borders (TAB), and infrastructure quality (Infra) were introduced that were representing trade facilitation as the core independent variable. Also, an empirical analysis was carried out using a mixed regression model. The results show that the three proxy indicators of trade facilitation had a significantly positive impact on the scale of China’s agricultural exports to the ASEAN market. The results could play a guiding role in strengthening the cooperation between China and the ASEAN regarding trade facilitation and expansion of the scale of agricultural trade.
With the gradual development of artificial intelligence (AI), the traditional production, marketing, and management methods for agricultural products have undergone dramatic changes, necessitating a greater optimization of these methods. Agricultural product operators have begun incorporating AI technology into product production, marketing, and distribution processes. This article examines the current state of agricultural product management and then investigates the integration of production, marketing, and distribution using artificial intelligence. In addition, given the limitations of conventional methods for classifying agricultural products, this article presents a classification model that combines factor analysis with an enhanced support vector machine (SVM) based on genetic algorithms (GAs). The results of the experiments indicate that the improved method is capable of distinguishing agricultural product quality categories rapidly and precisely, significantly improving the classification accuracy of agricultural product quality, and being broadly applicable to the evaluation of agricultural product quality.
As a leading effort to improve the welfare of smallholder farmers, several governments have led major reforms in improving market access for these farmers through online agricultural platforms. Leveraging collaboration with the state government of Karnataka, India, this paper provides an empirical assessment on the impact of such a reform—implementation of the Unified Market Platform (UMP)—on market prices and farmers’ profitability. UMP was created in 2014 to unify all trades in the agricultural wholesale markets of the state to be carried out within a single platform. By November 2019, 62.8 million metric tons of commodities valued at $21.7 billion (USD) have been traded on UMP. Employing a difference-in-differences method, we demonstrate that the impact of UMP on modal prices varies substantially across commodities. In particular, the implementation of UMP has yielded an average 5.1%, 3.6%, and 3.5% increase in the modal prices of paddy, groundnut, and maize. Furthermore, UMP has generated a greater benefit for farmers who produce higher-quality commodities. Given low profit margins of smallholder farmers (2 to 9%), the range of profit improvement is significant (36 to 159%). In contrast, UMP has no statistically significant impact on the modal prices of cotton, green gram, or tur. Using detailed market data from UMP, we analyze how features related to logistical challenges, bidding efficiency, in-market concentration, and the price discovery process differ between commodities with and without a significant price increase due to UMP. These analyses lead to several policy insights regarding the design of similar agri-platforms in developing countries.
Збірник матеріалів Міжнародної науково-практичної конференції «Економічна аналітика: сучасні реалії та прогностичні можливості» (19 квітня 2019 року). К.: КНЕУ
- Н Шквиря
Шквиря Н. Розробка товарної стратегії підприємства. Збірник
матеріалів Міжнародної науково-практичної конференції «Економічна
аналітика: сучасні реалії та прогностичні можливості» (19 квітня 2019 року).
К.: КНЕУ, 2019. С. 318-321.
How does trade Policy uncertrainty affect agriculture commodity prices? Pacific-Basin Finance
- T Sun
- C Su
- N Mirza
- M Umar
Sun T., Su C., Mirza N., Umar M. How does trade Policy uncertrainty
affect agriculture commodity prices? Pacific-Basin Finance Journal. 2021. Vol. 6.
URL: https://doi.org/10.1016/j.pacfin.2021.101514.
Analysis of the Ukrainian wholesale market
- M S Rahman
- D V Prus
Rahman, M.S. and Prus, D.V. (2020), "Analysis of the Ukrainian
wholesale market", BusinessInform, vol. 7. Pp. 154-160.
Zbirnyk materialiv Mizhnarodnoi naukovo-praktychnoi konferentsii «Ekonomichna analityka: suchasni realii ta prohnostychni mozhlyvosti
- N Shkvirya
Shkvirya, N. (2019), "Development of the company's product strategy",
Zbirnyk materialiv Mizhnarodnoi naukovo-praktychnoi konferentsii «Ekonomichna
analityka: suchasni realii ta prohnostychni mozhlyvosti» [Collection of materials of the
International Scientific and Practical Conference "Economic Analytics: Modern
Realities and Prognostic Possibilities"], Kyiv, Ukraine, pp. 318-321.