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The leading role of perception: the FACOPA model to comprehend innovation adoption

Author

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  • Yari Vecchio

    (University of Bologna)

  • Marcello De Rosa

    (University of Cassino and Southern Lazio)

  • Gregorio Pauselli

    (University of Bologna)

  • Margherita Masi

    (University of Bologna)

  • Felice Adinolfi

    (University of Bologna)

Abstract

In this work, we explore the link between the perception of complexity and the possibility of adopting precision agricultural tools (PATs). Many studies have analysed the role of perception, mostly considering it a determinant of adoption on the same level as other contextual factors. In contrast, this study contributes by assuming that farmers' perceived complexity is the main factor influencing their propensity to innovate and should be analysed on a different level. Starting from this assumption, a new theoretical model is proposed with the aim of studying the “factors–perception of complexity–adoption” (FACOPA) process. To test the validity of our hypothesis, a survey is conducted based on a purposive sample of 285 farmers. First, a linear regression model permits us to identify determinants of the perception of complexity. Then, a multinomial logistic model is used to determine which aspects of perceived complexity may affect the choice to adopt precision farming tools made by three different types of agricultural entrepreneurs: adopters, non-adopters, and planners. First, the linear regression results show that socio-structural variables have a logical relationship with perceived complexity, with age, farm size, the intensity of information and the intensity of work being significant. Then, the multinomial logistic model highlights that non-adopters perceive almost all aspects of complexity as barriers to adoption. Planners show a lower perception of complexity than non-adopters, with complexity being determined by financial and network aspects. The results provide interesting suggestions for policy-makers. Indeed, the FACOPA model offers insights into an intervention framework in which policy measures can be diversified to disseminate PATs based on farmer categories. Non-adopters require a broader set of policy instruments, while planners should be encouraged to become adopters through financial support and the activation of innovation networks.

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  • Yari Vecchio & Marcello De Rosa & Gregorio Pauselli & Margherita Masi & Felice Adinolfi, 2022. "The leading role of perception: the FACOPA model to comprehend innovation adoption," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-19, December.
    • Handle: RePEc:spr:agfoec:v:10:y:2022:i:1:d:10.1186_s40100-022-00211-0
    DOI: 10.1186/s40100-022-00211-0
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    Cited by:

    1. Margherita Masi & Marcello Rosa & Yari Vecchio & Luca Bartoli & Felice Adinolfi, 2022. "The long way to innovation adoption: insights from precision agriculture," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-17, December.
    2. Wang, Tong & Jin, Hailong & Sieverding, Heidi L. & Rao, Xudong & Miao, Yuxin & Kumar, Sandeep & Redfearn, Daren & Nafchi, Ali, 2022. "Understanding farmer perceptions of precision agriculture profitability in the U.S. Midwest," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322502, Agricultural and Applied Economics Association.
    3. Alexandros Theodoridis & Sotiria Vouraki & Emmanuel Morin & Georgia Koutouzidou & Georgios Arsenos, 2022. "Efficiency Analysis and Identification of Best Practices and Innovations in Dairy Sheep Farming," Sustainability, MDPI, vol. 14(21), pages 1-12, October.
    4. Marilena Gemtou & Konstantina Kakkavou & Evangelos Anastasiou & Spyros Fountas & Soren Marcus Pedersen & Gohar Isakhanyan & Kassa Tarekegn Erekalo & Serafin Pazos-Vidal, 2024. "Farmers’ Transition to Climate-Smart Agriculture: A Systematic Review of the Decision-Making Factors Affecting Adoption," Sustainability, MDPI, vol. 16(7), pages 1-34, March.
    5. Osrof, Hazem Yusuf & Tan, Cheng Ling & Angappa, Gunasekaran & Yeo, Sook Fern & Tan, Kim Hua, 2023. "Adoption of smart farming technologies in field operations: A systematic review and future research agenda," Technology in Society, Elsevier, vol. 75(C).
    6. Wang, Tong & Jin, Hailong & Sieverding, Heidi & Kumar, Sandeep & Miao, Yuxin & Rao, Xudong & Obembe, Oladipo & Mirzakhani Nafchi, Ali & Redfearn, Daren & Cheye, Stephen, 2023. "Understanding farmer views of precision agriculture profitability in the U.S. Midwest," Ecological Economics, Elsevier, vol. 213(C).

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