This study analyzed the probability that experiment stations, agricultural technology and extension centers, provincial agricultural research and extension services, central government organs, or civilian and other related organs will be the first choice of the compositional subjects of local innovation networks. While gender effect was statistically insignificant, educational level, income, main acquired information, sources of necessary information, and frequency of information acquisition sessions were significant, and the preference ranking model was highly relevant. According to the analysis, highly academic and business-related information was most likely to be acquired from the civilian sector; agricultural technology such as technology, crops/plants, storage, and circulation was most likely to be acquired from experiment stations and provincial agricultural research and extension services; and information on agricultural production was most likely to be acquired from agricultural technology centers.