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Understanding Farmers’ Intentions to Adopt Pest and Disease Green Control Techniques: Comparison and Integration Based on Multiple Models

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  • Pingan Xiang

    (School of Business, Hunan Agricultural University, Changsha 410128, China)

  • Jian Guo

    (School of Business, Hunan Agricultural University, Changsha 410128, China)

Abstract

Green control techniques (GCT) are an important supporting technology to ensure sustainable agricultural development. To advance the adoption of GCT, it is crucial to understand the intention of farmers to adopt GCT and its related determinants. However, current research is mostly limited to using a single theoretical model to explore farmers’ intentions to adopt GCT, which is not conducive to revealing the determinants of farmers’ intentions to adopt GCT. To address this gap, this study integrates the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), the Innovation Diffusion Theory (IDT), and the Motivational Model (MM) based on research data from 362 rice farmers in Heshan District, Yiyang City, Hunan Province, and uses partial least squares structural equation modeling (PLS-SEM) to empirically test and compare the above models. The model comparison results prove that the TPB (R 2 = 0.818, Q 2 = 0.705), TAM (R 2 = 0.649, Q 2 = 0.559), IDT (R 2 = 0.782, Q 2 = 0.674), and MM (R 2 = 0.678, Q 2 = 0.584) models all have explanatory power and predictive validity in the context of green control techniques. However, the integrated model (R 2 = 0.843, Q 2 = 0.725) is found to be superior to these individual theoretical models because it has larger values of R 2 , Q 2 , and smaller values of Asymptotically Efficient, Asymptotically Consistent, and provides a multifaceted understanding for identifying the factors influencing adoption intentions. The results of the path analysis show that attitude, perceived behavioral control, perceived usefulness, subjective norm, and visibility significantly and positively influence adoption intentions in both the single and integrated models and are determinants of farmers’ intentions to adopt GCT.

Suggested Citation

  • Pingan Xiang & Jian Guo, 2023. "Understanding Farmers’ Intentions to Adopt Pest and Disease Green Control Techniques: Comparison and Integration Based on Multiple Models," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:10822-:d:1190734
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    1. Hyland, John J. & Heanue, Kevin & McKillop, Jessica & Micha, Evgenia, 2018. "Factors underlying farmers' intentions to adopt best practices: The case of paddock based grazing systems," Agricultural Systems, Elsevier, vol. 162(C), pages 97-106.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    4. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    5. Elahi, Ehsan & Khalid, Zainab & Tauni, Muhammad Zubair & Zhang, Hongxia & Lirong, Xing, 2022. "Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: A retrospective survey of rural Punjab, Pakistan," Technovation, Elsevier, vol. 117(C).
    6. Siyu Gong & Bo Wang & Zhigang Yu, 2022. "Whether the Use of the Internet Can Assist Farmers in Selecting Biopesticides or Not: A Study Based on Evidence from the Largest Rice-Producing Province in China," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    7. Gary D. Lynne & J. S. Shonkwiler & Leandro R. Rola, 1988. "Attitudes and Farmer Conservation Behavior," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 70(1), pages 12-19.
    8. Mzoughi, Naoufel, 2011. "Farmers adoption of integrated crop protection and organic farming: Do moral and social concerns matter?," Ecological Economics, Elsevier, vol. 70(8), pages 1536-1545, June.
    9. Adnan Abbas & Chengyi Zhao & Waheed Ullah & Riaz Ahmad & Muhammad Waseem & Jianting Zhu, 2021. "Towards Sustainable Farm Production System: A Case Study of Corn Farming," Sustainability, MDPI, vol. 13(16), pages 1-12, August.
    10. Garini, C.S. & Vanwindekens, F. & Scholberg, J.M.S. & Wezel, A. & Groot, J.C.J., 2017. "Drivers of adoption of agroecological practices for winegrowers and influence from policies in the province of Trento, Italy," Land Use Policy, Elsevier, vol. 68(C), pages 200-211.
    11. Valborg Kvakkestad & Åsmund Lægreid Steiro & Arild Vatn, 2021. "Pesticide Policies and Farm Behavior: The Introduction of Regulations for Integrated Pest Management," Agriculture, MDPI, vol. 11(9), pages 1-17, August.
    12. Chepchirchir, Fridah & Muriithi, Beatrice & Langat, Jackson K., 2021. "Knowledge, Attitude, and Practices of Tomato Leaf Miner (Tuta absoluta) and Potential Demand for Integrated Pest Management Among Smallholder Farmers in Kenya and Uganda," 2021 Conference, August 17-31, 2021, Virtual 315892, International Association of Agricultural Economists.
    13. Ye Jin & Qingning Lin & Shiping Mao, 2022. "Tanzanian Farmers’ Intention to Adopt Improved Maize Technology: Analyzing Influencing Factors Using SEM and fsQCA Methods," Agriculture, MDPI, vol. 12(12), pages 1-23, November.
    14. Elahi, Ehsan & Khalid, Zainab & Zhang, Zhixin, 2022. "Understanding farmers’ intention and willingness to install renewable energy technology: A solution to reduce the environmental emissions of agriculture," Applied Energy, Elsevier, vol. 309(C).
    15. Gao, Yang & Niu, Ziheng & Yang, Haoran & Yu, Lili, 2019. "Impact of green control techniques on family farms' welfare," Ecological Economics, Elsevier, vol. 161(C), pages 91-99.
    16. Fridah Chepchirchir & Beatrice W. Muriithi & Jackson Langat & Samira A. Mohamed & Shepard Ndlela & Fathiya M. Khamis, 2021. "Knowledge, Attitude, and Practices on Tomato Leaf Miner, Tuta absoluta on Tomato and Potential Demand for Integrated Pest Management among Smallholder Farmers in Kenya and Uganda," Agriculture, MDPI, vol. 11(12), pages 1-20, December.
    17. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    18. Elahi, Ehsan & Khalid, Zainab, 2022. "Estimating smart energy inputs packages using hybrid optimisation technique to mitigate environmental emissions of commercial fish farms," Applied Energy, Elsevier, vol. 326(C).
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