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作 者:Nicolas De la Pena Oscar M.Granados
机构地区:[1]Faculty of Economics and Social Sciences,Universidad de La Salle,Carrera 4#59A-44,Bogota,Colombia [2]Department of Economics,Finance&Trade,Universidad Jorge Tadeo Lozano,Carrera 4#22-61,Bogota,Colombia
出 处:《Information Processing in Agriculture》2024年第3期310-324,共15页农业信息处理(英文)
基 金:supported by the Administrative Department of Science,Technology,and Innovation(former COLCIENCIAS)Grant Number 44842-372-2017;the Universidad de Bogota Jorge Tadeo Lozano(Grant Number 12399070).
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.
关 键 词:Cocoa Information Asymmetry Artificial Intelligence Trade Cycles
分 类 号:S571[农业科学—作物学] TP18[自动化与计算机技术—控制理论与控制工程]
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