The alternative model to predict adoption behavior of agricultural technologies

Appropriate and accurate management of water resources and agricultural irrigation plays an important role in preventing the water and food crisis worldwide especially in arid developing countries. Application of modern irrigation technologies and methods is the main issue in the optimal use of water. This goal would not be happened without considering the adoption process of the end users. Analysis of pressurized irrigation technology adoption models was the main purpose of current study. This research was accomplished based on survey method using questionnaire for data collection. All of the farmers of Abadeh county in Iran was the research population which 418 of them were selected using stratified random sampling as research sample. The face validity and reliability of the questionnaire were confirmed by a panel of specialists as well as doing a pilot study out of the main research (r = 0.74–0.92), respectively. Discriminant analysis was used to determine the predictive power of different adoption models of pressurized irrigation including task-technology fit, communicative-learning and integrative models in grouping of farmers in the two categories of adopters and non-adopters. The findings indicated that integrative model has a higher ability to classify adopters and non-adopters of pressurized irrigation with better accuracy and desirability in comparison with each of the other two models, separately. Task-technology fit and communicative learning models had low power in determining the pressurized irrigation users. Integrative model includes the factors of the two previous models as well as considering the social participation and environmental responsibility in discriminant function which could better classify the adopters and non-adopters of the technology.