Artificial intelligence solutions to reduce information asymmetry for Colombian cocoa small-scale farmers

被引:3
|
作者
De la Pen, Nicolas [1 ]
Granados, Oscar M. [2 ]
机构
[1] Univ Salle, Fac Econ & Social Sci, Carrera 4 59A-44, Bogota, Colombia
[2] Univ Jorge Tadeo Lozano, Dept Econ Finance & Trade, Carrera 4 22-61, Bogota, Colombia
来源
INFORMATION PROCESSING IN AGRICULTURE | 2024年 / 11卷 / 03期
关键词
Cocoa; Information Asymmetry; Artificial Intelligence; Trade Cycles; MARKET-INFORMATION; MOBILE PHONES; IMPACT; WELFARE; PERFORMANCE; PERSISTENCE; LEMONS;
D O I
10.1016/j.inpa.2023.03.001
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The lack of information creates problems for Colombian small-scale farmers, as it impedes them from selling at fair prices and knowing efficient production techniques. Around the world, many technological interventions have proven helpful in reducing information asymmetries. Therefore, we proposed a technological scheme based on a genetic algorithm and a natural language processor (NLP) that enables producers to obtain knowledge through information processing. Also, we ran fieldwork in twenty municipalities and a survey among 500 Colombian cocoa small-scale farmers in different regions in Colombia. This fieldwork helps us determine small-scale farmers' necessities, market conditions, and the relevance of an Artificial Intelligence (AI) tool. The results have shown that AI methodologies could improve the economic conditions of small farmers by providing access to information on prices, weather, and production techniques. The fieldwork evidence that a technological tool is a good option only if there are dynamic trade cycles. AI tools could transmit and process information to become producers' knowledge and help them evolve into collective strategies. The methodology, which combines genetic algorithms, NLP, and fieldwork for cocoa farming, is a novelty that contributes to information asymmetry reduction. We contributed to the literature about adopting AI tools to develop cocoa small-scale farming better. (c) 2023 China Agricultural University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:310 / 324
页数:15
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