Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior

The use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized i...

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Published inPrecision agriculture Vol. 22; no. 6; pp. 1816 - 1844
Main Authors Mohr, Svenja, Kühl, Rainer
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2021
Springer Nature B.V
Subjects
Agricultural economics
Agriculture
Artificial intelligence
Atmospheric Sciences
Biomedical and Life Sciences
Chemistry and Earth Sciences
Computer Science
equations
Farmers
labor
Life Sciences
Physics
precision agriculture
Property rights
questionnaires
Remote Sensing/Photogrammetry
Soil compaction
Soil Science & Conservation
Statistics for Engineering
Structural equation modeling
Technology Acceptance Model
Technology utilization
Theory of planned behavior
variance
Working hours
Survey
Technology acceptance model
Artificial intelligence
Theory of planned behavior
Structural equation model
Online AccessGet full text
ISSN1385-2256
1573-1618
DOI10.1007/s11119-021-09814-x

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Abstract The use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis ( 1989 ) and the theory of planned behavior (TPB) of Ajzen ( 1991 ) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.
AbstractList The use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis (1989) and the theory of planned behavior (TPB) of Ajzen (1991) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.
The use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis ( 1989 ) and the theory of planned behavior (TPB) of Ajzen ( 1991 ) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.
Author Mohr, Svenja
Kühl, Rainer
Author_xml – sequence: 1
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  orcidid: 0000-0002-8929-1670
  surname: Mohr
  fullname: Mohr, Svenja
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  organization: Institute of Farm and Agribusiness Management, University of Giessen
– sequence: 2
  givenname: Rainer
  surname: Kühl
  fullname: Kühl, Rainer
  organization: Institute of Farm and Agribusiness Management, University of Giessen
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  text: 20211200
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
– name: Dordrecht
PublicationSubtitle An International Journal on Advances in Precision Agriculture
PublicationTitle Precision agriculture
PublicationTitleAbbrev Precision Agric
PublicationYear 2021
Publisher Springer US
Springer Nature B.V
Publisher_xml – name: Springer US
– name: Springer Nature B.V
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Snippet The use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours...
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SubjectTerms Agricultural economics
Agriculture
Artificial intelligence
Atmospheric Sciences
Biomedical and Life Sciences
Chemistry and Earth Sciences
Computer Science
equations
Farmers
labor
Life Sciences
Physics
precision agriculture
Property rights
questionnaires
Remote Sensing/Photogrammetry
Soil compaction
Soil Science & Conservation
Statistics for Engineering
Structural equation modeling
Technology Acceptance Model
Technology utilization
Theory of planned behavior
variance
Working hours
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Title Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior
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