Factors Affecting Adoption of Artificial Insemination in Dairy Farms of Ardabil Province (A Comparison of Models)

Artificial insemination (AI) is an important technique for breeding that has been extensively used in dairy farming worldwide. However, it has not been fully adopted in Iran's dairy farms, especially in Ardabil province. The main objective of this research was to study factors affecting adoption of AI in dairy farms of Ardabil province. In order to predict the adoption of AI, technology adoption models were compared for their ability to explain the variations. Survey research design was used in this study. To collect data, a randomly selected sample of 95 dairy farmers was studied using a questionnaire. The instrument was validated by a panel of experts. A pilot study was carried out in collaboration with 30 farmers and accordingly appropriate changes were made in the construction and sequence of interview schedule. Moreover, Cronbach's alpha was computed to measure the reliability of the instrument (?=0.89). To examine the objective of the study, respondents were divided into two categories of adopters and non-adopters. Discriminant analysis was used to find the impacts of selected variables of diffusion model (DM), farm structure model (FSM), technology acceptance model (TAM) and multiplicity model (MM) on adoption of AI. Results revealed that DM and FSM explained 51.55% and 15.29% of variances of discriminant function, respectively. The TAM with two key components could explain only 38.69% of variance. However, TAM and FSM jointly explained 45.43% of variance indicating that TAM could be a supplement of FSM. Finally, MM consisting of all variables of mentioned models with a set of suitable factors explained 58.06% of variance. So, key factors affecting adoption of AI were dairy farmers' innovativeness (farmers' objectives), extension-administration and common factors (information sources) from DM, agro-pasture landholding size from FSM and PU from TAM models.