Factors Influencing Farmers’ Decisions in Farm Machineries Usage: The Case of Vegetable Farmers in Quezon Province, Philippines

Purpose – The study assessed the influence of some variables relevant to vegetable farmers’ decisions in farm machinery usage. The decision of farmers in using farm machineries is determined by a number of social, technical, environmental and economic factors. Design/Methodology/Approach – The binary logit model was employed to determine the relationship of the predetermined factors on farmers’ use of a single-specific farm machine. Furthermore, the study utilized negative binomial regression to assess the factors influencing the decisions of farmers in using various farm machineries in their farming operations. Findings – Results showed that majority of the farmers still follow traditional farming methods using very limited farm technologies. Farmers face the challenge of optimizing their land use, and this includes their decision whether or not to use farm machineries in their farming operations in order to boost production. Various factors are considered, more than just the cost of technology. Thus, a combination of household-specific, economic, technology, institutional and moderating factors influences the technology adoption decisions of vegetable farmers. Moreover, it was revealed that formal education, household size, household income, cash availability, farm size, access to extension workers, attendance in seminars, trainings and workshops, and on-farm demo participation are all positively related to the probability of farmers’ usage of identified farming machines. Conversely, farming experience, cost of technology, technology triability, credit access, and farm distance to market are all found to be negatively related to the probability of farmers’ usage of farm machineries. Research Implications – Various recommendations were offered to address challenges encountered by farmers in terms of farm machinery usage including changing the farmers’ mindset from a traditional perspective to a market-oriented one via the R.E.S.E.T. model.