Information generated by precision farming technologies is of particular importance to producers. Precision farming technologies implies the ability to improve the management of production factors using site-specific information. This study examines factors influencing cotton farmers’ perceptions about the importance of crop consultants, farm input dealerships, Extension, other farmers, trade shows, the Internet and printed news/media for making precision farming decisions using a rank ordered logit model (ROLM). Results suggest that age, land tenure, income, percentage of income from farming, and location may affect farmers’ perceptions about the importance of different information sources when making decisions about precision farming technologies. Results suggest that regardless of farmer/farm business characteristics other farmers (OF) is one of the most important information sources when making precision farming decisions. Findings suggest that high income producers are more likely to prefer crop consultants, University/Extension, trade shows, and the Internet over OF as a source of information when making decisions about precision farming technologies. Findings also suggest that researchers need to be very careful when designing questions that ask respondents to rank alternatives so that they guarantee that individuals with different skills are able to precisely understand what is being asked. Decreasing the number of alternatives respondents must consider may be one strategy to reduce the complexity of ranking questions to minimize the probability of the respondents leaving alternatives unranked or ranking them randomly.

精细农业技术产生的信息对生产者特别重要。精细农业技术意味着有能力利用特定地点的信息改进生产要素的管理。本研究利用一种排序logit模型(ROLM)，调查了影响棉农对作物顾问、农场投入经销商、推广、其他农民、贸易展览、互联网和印刷新闻/媒体在精密农业决策中的重要性的影响因素。研究结果显示，年龄、土地保有权、收入、农耕收入百分比及地理位置等因素，可能会影响农民对不同资讯来源在精密农耕技术决策中的重要性认知。结果显示，无论农户/农户业务特征如何，其他农户(of)是进行精准农业决策时最重要的信息来源之一。研究结果表明，高收入生产者更倾向于选择作物咨询师、大学/推广、贸易展览和互联网作为信息来源，而不是在做关于精细农业技术的决策时。研究结果还表明，研究人员在设计问题时需要非常谨慎，要求受访者对备选方案进行排序，以确保拥有不同技能的个人能够准确理解所问的问题。减少受访者必须考虑的备选方案的数量可能是降低排序问题复杂性的一种策略，以最小化受访者留下备选方案未排序或随机排序的概率。