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Willingness of Tea Farmers to Adopt Ecological Agriculture Techniques Based on the UTAUT Extended Model

Author

Listed:
  • Kexiao Xie

    (Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou 362406, China)

  • Yuerui Zhu

    (College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Yongqiang Ma

    (Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou 362406, China)

  • Youcheng Chen

    (Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou 362406, China
    Fujian Anxi Tieguanyin Tea Science and Technology Backyard, Quanzhou 362406, China)

  • Shuiji Chen

    (Anxi Agricultural and Rural Bureau, Quanzhou 362400, China)

  • Zhidan Chen

    (Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou 362406, China
    Fujian Anxi Tieguanyin Tea Science and Technology Backyard, Quanzhou 362406, China
    Engineering Technology and Research Center of Fujian Tea Industry, Fuzhou 350002, China)

Abstract

Ecological agricultural technology is the key method for making the transition from traditional agriculture to ecological agriculture, and is also the basic measure for promoting the transformation and upgrading of the tea industry and sustainable development. This study explores the influencing factors and mechanisms of tea farmers’ adoption of ecological agricultural technology by using the extended model of the unified theory of technology adoption and use (UTAUT) based on perceived value. The analysis results, using the partial least squares structural equation model (PLS-SEM), show that: the positive impact of perceived value on willingness to use not only makes the explanatory power of the extended model greater than that of the original model but also expands the UTAUT model into a full mediating model, in which performance expectation has the greatest impact on behavioral intention through the implemented value. Effect expectation, social influence and factoring factors following, then the four intermediary paths have significant positive effects on behavioral intention. This study improves on the limitations of the UTAUT theoretical model through the theory of perceived value, and provides a reference for research on the same topic. At the same time, the government should provide tea farmers with enhanced subsidies, skills training and communication platforms.

Suggested Citation

  • Kexiao Xie & Yuerui Zhu & Yongqiang Ma & Youcheng Chen & Shuiji Chen & Zhidan Chen, 2022. "Willingness of Tea Farmers to Adopt Ecological Agriculture Techniques Based on the UTAUT Extended Model," IJERPH, MDPI, vol. 19(22), pages 1-14, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:15351-:d:978796
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    References listed on IDEAS

    as
    1. Chatzimichael, Konstantinos & Genius, Margarita & Tzouvelekas, Vangelis, 2014. "Informational cascades and technology adoption: Evidence from Greek and German organic growers," Food Policy, Elsevier, vol. 49(P1), pages 186-195.
    2. Nick Bontis & Mary M. Crossan & John Hulland, 2002. "Managing An Organizational Learning System By Aligning Stocks and Flows," Journal of Management Studies, Wiley Blackwell, vol. 39(4), pages 437-469, June.
    3. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    4. Ronaghi, Mohammad Hossein & Forouharfar, Amir, 2020. "A contextualized study of the usage of the Internet of things (IoTs) in smart farming in a typical Middle Eastern country within the context of Unified Theory of Acceptance and Use of Technology model," Technology in Society, Elsevier, vol. 63(C).
    5. He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2020. "Households’ willingness to pay for energy utilization of crop straw in rural China：Based on an improved UTAUT model," Energy Policy, Elsevier, vol. 140(C).
    6. Theodore W. Schultz, 1966. "Transforming Traditional Agriculture: Reply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 48(4_Part_I), pages 1015-1018.
    7. Namara, Regassa E. & Upadhyay, Bhawana & Nagar, Rashmi K., 2005. "Adoption and impacts of microirrigation technologies: Empirical results from selected localities of Maharashtra and Gujarat states of India," IWMI Research Reports 44543, International Water Management Institute.
    8. Hai Hu & Andi Cao & Si Chen & Houjian Li, 2022. "Effects of Risk Perception of Pests and Diseases on Tea Famers’ Green Control Techniques Adoption," IJERPH, MDPI, vol. 19(14), pages 1-15, July.
    9. Kelvin Mashisia Shikuku & Janneke Pieters & Erwin Bulte & Peter Läderach, 2019. "Incentives and the Diffusion of Agricultural Knowledge: Experimental Evidence from Northern Uganda," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(4), pages 1164-1180.
    10. Namara, Regassa & Upadhyay, Bhawana & Nagar, R. K., 2005. "Adoption and impacts of microirrigation technologies: empirical results from selected localities of Maharashtra and Gujarat states of India," IWMI Research Reports H037307, International Water Management Institute.
    11. Soe Paing Oo & Koichi Usami, 2020. "Farmers’ Perception of Good Agricultural Practices in Rice Production in Myanmar: A Case Study of Myaungmya District, Ayeyarwady Region," Agriculture, MDPI, vol. 10(7), pages 1-20, June.
    12. Margarita Genius & Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2014. "Information Transmission in Irrigation Technology Adoption and Diffusion: Social Learning, Extension Services, and Spatial Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 328-344.
    13. Friedrich Rübcke von Veltheim & Heinke Heise, 2021. "German Farmers’ Attitudes on Adopting Autonomous Field Robots: An Empirical Survey," Agriculture, MDPI, vol. 11(3), pages 1-19, March.
    14. Castillo, Gracia Maria Lanza & Engler, Alejandra & Wollni, Meike, 2021. "Planned behavior and social capital: Understanding farmers’ behavior toward pressurized irrigation technologies," Agricultural Water Management, Elsevier, vol. 243(C).
    15. He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2018. "Rural households' willingness to accept compensation for energy utilization of crop straw in China," Energy, Elsevier, vol. 165(PA), pages 562-571.
    16. Yaying Zhu & Juan Chen, 2022. "Small-Scale Farmers’ Preference Heterogeneity for Green Agriculture Policy Incentives Identified by Choice Experiment," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
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