Classification and evaluation of uncertain influence factors for farm machinery service

• Published in: International journal of agricultural and biological engineering Vol. 10; no. 6; pp. 164 - 174
• Main Authors: Caicong, Wu, Yaping, Cai, Bingbing, Hu, Jie, Wang
• Format: Journal Article
• Language: English
• Published: Beijing International Journal of Agricultural and Biological Engineering (IJABE) 01.11.2017
• Subjects: Agricultural equipment; Agriculture; Biomass; Classification; Cooperatives; Customer services; Electronics; Engineering; Evaluation; Family farms; Farm machinery; Farm management; Farms; Machinery and equipment; Management information systems; Questionnaires; Risk management; Scheduling; Social services; Uncertainty; Working groups; China
• ISSN: 1934-6344; 1934-6352
• DOI: 10.25165/j.ijabe.20171006.3045

Uncertainty extremely interferes with the execution of farm machinery operation. Treating uncertainties is especially important for machinery cooperatives providing social service since they face more uncertain influence factors (UIFs) than family farms. Under social service circumstance, uncertainties may arise from participants and environments. Classification and evaluation of UIFs were studied in this research. According to the production system, 32 UIFs are defined and classified into six categories, which include supply, demand, interactivity, nature, society and others. Uncertainty composite index (UCI) is defined to evaluate the importance of UIFs, which is the square root of the product of occurrence frequency (OF) and impact degree (ID) calculated from the well-designed questionnaire responded by farm machinery operators. UCI is divided into five ranks based on normalization distribution test to illustrate the level of importance. Results from questionnaire showed that natural UIFs have an extreme impact on farm operation, UIFs of the demand and the supply have a serious influence on farm operation, UIFs of interactivity cannot be ignored, and social UIFs have a weak impact on farm operations. This study discovered the uncertainty problems under the specific circumstance of farm machinery service, which may provide a theoretical basis and potential methods for risk management of machinery cooperatives.