• 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 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.

• Korean Journal of Organic Agriculture
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• v.28 no.3
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• pp.315-334
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• 2020

This study was conducted to analyze factors affecting acceptance of smart farm technology. Smart farm technology is rapidly being introduced to agriculture in accordance with the progress of the 4th Industrial Revolution, but research on this is still little. Therefore, in this study, based on the unified theory of acceptance and use of technology (UTAUT), a research model reflecting the characteristics of smart farm technology was constructed. To test this, empirical analysis was performed. A survey was conducted for students in smart farm technology education and adult male and female farmers who are currently planning to operate smart farms. Valid 204 sample were used for analysis. The hypothesis test was based on multiple regression analysis using SPSS 24 statistical package. For the mediating effect and moderating effect, Process Macro 3.4 based on the regression equation was used. The results of testing the hypothesis are as follows. First, in the causal hypothesis test, it was shown that performance expectancy, social influence and price value have a significant positive effect on the intention to use smart farm technology. On the other hand, effort expectancy, facilitating conditions were not tested for a significant influence on the use of smart farm technology. As a result of analyzing the mediating effect of trust, it was found that trust plays a mediating role between performance expectancy, effort expectancy, social influence, facilitating conditions, price value and intention to use smart farm technology. In particular, the effort expectancy has not been tested for a direct significant effect on intention to use smart farm technology, but it has been shown to have an impact through trust. Trust was found to be a full mediating between the effort expectancy and the intention to use the smart farm technology. The current IT level of prospective users has been shown to play a moderating role between performance expectancy, facilitating conditions and intention to use smart farm technology. In particular, the IT level was found to strengthen the relationship between performance expectancy and intention to use smart farm technology. Based on the results of these studies, academic and practical implications were suggested.

• 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.

• Korean Journal of Organic Agriculture
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• v.28 no.2
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• pp.119-138
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• 2020

The purpose of this study was to examine the intention of consumer acceptance of technology in agricultural production by applying the unified theory of acceptance and use of technology (UTAUT) to smart farm. In particular, this study analyzed the intention to accept the technology of agricultural students, farmers, start-up farmers, returning farmers, and returnees in the general manufacturing industry and high-tech industries, and in agricultural sectors corresponding to primary industries. The results showed that performance expectancy, social influence, facilitating conditions, IT development level, and reliability had a significant influence on the intention to use smart farm technology. However, effort expectancy and price value were rejected because no significant impact on use intention was tested. In addition, the influences of the variables showing their influence were reliability (β=.569) > IT development level (β=.252) > social influence (β=.235) > performance expectancy (β=.182) > facilitating conditions (β=.134).