• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.3
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• pp.19-32
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• 2020

This study analyzed the effects of ICT technical characteristics of agricultural industry on smart farm entrepreneurial intention by using smart farm effort expectation and smart farm acceptance intention as mediators for smart farm pre-founders. Sub-variables of the technical characteristics of agricultural industry ICT were classified into availability, economics, data convergence and scalability. 349 questionnaires collected from pre-founders living in the country were used for empirical analysis. SPSS v22.0 and Process macro v3.4 were used to analyze the data based on serial multiple mediation model. First, economics and scalability had a positive (+) effect on start-up intention. Second, availability, economics and scalability had a significant effect on effort expectation. Third, effort expectation had a significant positive effect on acceptance intention. Fourth, acceptance intention had a significant positive effect on start-up intention. Fifth, the indirect effects of economics on start-up intention were all significant through effort expectation, through acceptance intention and through both effort expectation and acceptance intention. Sixth, the indirect effect of data convergence on start-up intention was significant through acceptance intention. Seventh, the indirect effect of scalability on start-up intention was significant through effort expectation and through both effort expectation and acceptance intention. As a follow-up study, it is necessary to study for the mediating variables other than mediators introduced in the study or the moderated mediation analysis through the conditional process model in which the moderating variable is introduced.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.145-157
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• 2019

This study is to look at the influential factors associated with the acceptance intention of smart farm and suggest a proposal for spreading adoption of smart farms. The research questionnaire distributed to the farmers were used for the research analysis by statistical program SPSS v22.0 and Process macro v3.0. The technical characteristics of smart farm, which are availability, reliability and economic efficiency were selected as independent variables to analyze the influential factors on acceptance intention of smart farm and the mediating effect of effort expectation was observed. As a result, availability and economic efficiency have a positive(+) influence on acceptance intention and reliability have no influence on acceptance intention. And availability, reliability and economic efficiency have a positive(+) influence on effort expectation. Effort expectation mediates the relationship between the technical characteristics of smart farm and acceptance intention. The results of the study are expected to be utilized at the seeking direction of policy for potential adopters of smart farm, the training and consulting in actual field of smart farm.

• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.115-126
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• 2020

This study designed an extended technology acceptance model incorporating and combining TPB, TAM, UTAUT, and IDT, which are known to be useful in explaining technology acceptance intention, to analyze antecedents affecting smart farm acceptance intention from the perspective of policy handlers. In the model of this study, nine independent variables were set, including subjective norm, perceived behavioral control, attitude, perceived usefulness, performance expectation, effort expectation, social impact, promotion condition, and fitness. The effect of these variables on farm acceptance intention was analyzed. The study found that four factors, including perceived behavioral control, perceived usefulness, social impact, and fitness, had positive effects on the acceptance intention of smart farms. Of these, perceived usefulness had the highest impact. In conclusion, all the TPB, TAM, UTAUT, and IDT applied to the research hypothesis to explain the smart farm acceptance intention included on or more variables with significant effects. In other words, these theories were evaluated as useful to explain the acceptance intention of smart farms.