assessment of scenario-based policy adoption of crop change among farmers of Kurdistan province: integration of structural equation models, Bayesian power networks and factor-based modeling

Abstract

The purpose of this study was to provide an integrated framework for evaluating the acceptance of policy change in the context of uncertainty. The study was conducted with a mixed exploratory approach. In the qualitative stage, the data obtained from semi-structured interviews with 20 farmers and experts in the field of agriculture were analyzed using the subject analysis method. In the first step, the data collected from 300 farmers of four cities of Kurdistan province were analyzed by partial least squares structural equation modeling method. In the following, the structures and connections were verified in the form of a network of Bayesian modeling and, in addition to the final situation, six political scenarios were evaluated. Then, the possible outputs of the network were transferred to the factor-based model to simulate the rate of acceptance of crop change at the level of farmers' factors. Qualitative findings also identified seven main articles including economy and market, risk and decision, collective influence and trust, politics and institutional support, technical and promotional capacity, environment and health, economy and the pace of change. The results of the structural model showed economic advantage, market security, institutional trust, collective influence and technical ability, proportional to the model's directions, and have a positive effect on attitude, intention or speed of change; In contrast, perceived cost and risk and environmental and health consequences play a deterrent role. The coefficient of determination of attitude was equal to 0.644 and the coefficient of determination of intention and speed was equal to 0.716, and the amount of standardized fit index reached 0.049. The results of the trust network showed that the probability of the intention to change increased from 25.87 percent in the final situation to 54.23 percent in the desirable scenario, while this probability decreased to 11.01 percent in the undesirable scenario. Also, the factor-based model showed that the rate of change acceptance increased from 53 percent in the final situation to 74 percent in the desirable scenario and decreased to 31.67 percent in the undesirable scenario. The results of the findings show that the success of policy change depends on the design and implementation of a coordinated package of economic benefits, market security, risk reduction, institutional support, practical training and trust building.