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Technology Acceptance, Adoption and Workforce on Australian Cotton Farms

Author

Listed:
  • Nicole McDonald

    (Institute for Future Farming Systems, School of Health, Medical and Applied Sciences, CQUniversity, Rockhampton, QLD 4701, Australia)

  • Eloise S. Fogarty

    (Institute for Future Farming Systems, School of Health, Medical and Applied Sciences, CQUniversity, Rockhampton, QLD 4701, Australia)

  • Amy Cosby

    (Institute for Future Farming Systems, School of Health, Medical and Applied Sciences, CQUniversity, Rockhampton, QLD 4701, Australia)

  • Peter McIlveen

    (School of Education, University of Southern Queensland, Toowoomba, QLD 4350, Australia)

Abstract

The future of work is influenced by the digital transformation of industries, including agriculture. The current study aimed to understand the social drivers of automated technology acceptance and adoption in Australian cotton farms. The study employed a mixed-methods approach to compare those who were (a) currently using automated technology, (b) not currently using automated technology but considering adoption, and (c) not currently using automated technology and no intention to adopt. The research found that social factors and workforce considerations influence growers’ motivation to adopt automated technology on farms. Furthermore, differences on appraisals of perceived usefulness were observed when comparing growers with no intention to adopt automated technology with those considering adoption or who have adopted automated technology. Both perceived usefulness and ease of use barriers are challenges for those considering adoption of automated technology. Support that improves ease of use for those who have adopted automated technology is important for continued appraisals of perceived usefulness of automated technology. Further research to understand antecedents to appraisals of perceived usefulness and ease of use, and how these interact to influence acceptance and automated technology, is required to inform strategic workforce interventions that support the digital transformation of cotton farms.

Suggested Citation

  • Nicole McDonald & Eloise S. Fogarty & Amy Cosby & Peter McIlveen, 2022. "Technology Acceptance, Adoption and Workforce on Australian Cotton Farms," Agriculture, MDPI, vol. 12(8), pages 1-16, August.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:8:p:1180-:d:883220
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    References listed on IDEAS

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    1. Oksana Hrynevych & Miguel Blanco Canto & Mercedes Jiménez García, 2022. "Tendencies of Precision Agriculture in Ukraine: Disruptive Smart Farming Tools as Cooperation Drivers," Agriculture, MDPI, vol. 12(5), pages 1-15, May.
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    Cited by:

    1. Matthew Champness & Leigh Vial & Carlos Ballester & John Hornbuckle, 2023. "Evaluating the Performance and Opportunity Cost of a Smart-Sensed Automated Irrigation System for Water-Saving Rice Cultivation in Temperate Australia," Agriculture, MDPI, vol. 13(4), pages 1-16, April.
    2. Gonçalo C. Rodrigues, 2022. "Precision Agriculture: Strategies and Technology Adoption," Agriculture, MDPI, vol. 12(9), pages 1-4, September.

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