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Provedor de dados:  AgEcon
País:  United States
Título:  Factors Influencing Cotton Farmers’ Perceptions about the Importance of Information Sources in Precision Farming Decisions
Autores:  Velandia, Margarita M.
Lambert, Dayton M.
Mendieta, Maria P.
Roberts, Roland K.
Larson, James A.
English, Burton C.
Rejesus, Roderick M.
Mishra, Ashok K.
Data:  2011-05-03
Ano:  2011
Palavras-chave:  Information-source preferences
Rank Ordered Logit Model
Precision Farming
Production Economics
Research Methods/ Statistical Methods
Q16
C25
Resumo:  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.
Tipo:  Conference Paper or Presentation
Idioma:  Inglês
Identificador:  http://purl.umn.edu/103752
Relação:  Agricultural and Applied Economics Association>2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania
Selected Paper
13452
Formato:  37
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