Ranking the Effective Factors in the Technology Acceptance Model for the Actual Use of Agricultural Automation (Case study: Ardebil)

IntroductionIn Iran, due to population growth and rising costs in the coming years and supply of food needs, there should be solutions for more production, with less waste, so the presence of robots can be justified for more production, reducing waste and reducing current costs. The present study investigates the factors affecting the adoption of automation in agriculture in Ardabil within the framework of the constructive factors of "Technology Acceptance Model" and examining the applicability of this model in the research community.Materials and MethodsIn the present study, the conceptual model factors include perceived usefulness, perceived ease of use, attitude toward use, and the intention to use, that affect the dependent variable of automation. Six of the first hypotheses of this study are based on the study of the significant relationships between each pair of variables in the framework of the "Technology Acceptance Model", and the applicability of the "Technology Acceptance Model" in the research community is defined in the seventh hypothesis. The method of this research is surveyed and data collection tool is a questionnaire designed based on technology acceptance model (TAM). In this research, the population of 27670 people were investigated that include university staffs-farmers and managers of ministry of agriculture in Ardabil. Using Cochran formula, 380 of them were selected in the form of stratified random sampling as sample size. Validity was confirmed by experts in agricultural management and mechanization, using Cronbach's alpha (0.958). Also, descriptive and inferential statistics were used and data analysis was performed using SPSS20 software.Results and DiscussionThe findings of this study showed that the technology acceptance model with a final determination coefficient of 635.0 was used in the studied population, which means that the applicability of the model (TAM) was very suitable for agricultural study in Ardabil. The priorities for the effects of the variables of the technology acceptance model for the actual use of automation were perceived ease of use (1.284), perceived usefulness (1.280), intention to use (0.954) and attitude (0.478) respectively.Using the results of modeling, it was also found that the correlation coefficient between individual factors and the perceived usefulness of the application of automation has a strong relationship. The correlation coefficient between the two variables is negative and indicates that with increasing individual factors, the level of perceived usefulness of the use of automation also decreases, and vice versa. However, experience, self-confidence and financial situations, level of education, land area, number of family workforce, have not greatly increased productivity and reduced production costs and helped agricultural activities (understanding the usefulness of technology).The relationship can be considered as the most important factor in holding weak and undesirable classes in creating knowledge, experience and poor self-confidence of the respondents towards accurate agricultural technology. In these classes, the content should be presented in a more specialized and practical way to make them understand the usefulness of precision agricultural technology.According to the results of this study, the organization of workshops and periodic training courses, as well as the introduction of this technology in journals and publications and social media is recommended.ConclusionsConsidering the confirmation of the hypotheses of this research and the priorities obtained for the effects of the structures of the technology acceptance model, it can be concluded that as it is known, the two main constituents of this model, perceived ease of use and perceived usefulness have had a significant impact on the amount of technology used, or, in other words, technology acceptance. The perceived usefulness is the most effective factor in the actual use of automation. In following, perceived ease of use, intention to use, and the attitude was ranked respectively.