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The study's goal was to determine the variables that were linked to university students' intentions to pursue agricultural-related employment. Quantitative data was gathered from 323 students who were enrolled in various agricultural-based university programs in Bangladesh. Structural equation modeling (SEM) and artificial neural networks (ANN) were employed to examine the data. The results revealed that students' intentions to enter agricultural-related careers were predicted by their attitudes toward agriculture, agricultural knowledge, perceived behavioral control, facilities and resource conditions, innovativeness and creativity, career planning, perception of sustainable agriculture methods, perception of organizational support, and technological competency. Perceived behavioral control is the strongest predictor. Subjective norms, perceived value, and entrepreneurial capabilities were found the insignificant predictors. The results shed light on the parameters agricultural undergraduates take into account when selecting whether to pursue jobs in the field of agriculture. This can assist academic specialists in retaining and attracting students by meeting their demands for motivation. By including nine extra components, the study broadens the theory of planned behavior's application for predicting intention in the agricultural sector. The study first time examined the linear and nonlinear correlations among variables. The areas where programming efforts are most likely to be successful can be more clearly identified by having a deeper grasp of the variables that influence students' decisions regarding their future professions in agriculture. |
