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TAM-Based Study of Farmers’ Live Streaming E-Commerce Adoption Intentions

Author

Listed:
  • Xinqiang Chen

    (School of Economic and Management, Xiamen University of Technology, Xiamen 361024, China)

  • Xiu-e Zhang

    (School of Business and Management, Jilin University, Changchun 130012, China)

  • Jiangjie Chen

    (School of Design, Jiangnan University, Wuxi 214122, China)

Abstract

Amidst the digital economy surge, live streaming e-commerce of agricultural products has significantly boosted agricultural prosperity. Investigating farmers’ behavioral intentions toward adopting live streaming e-commerce holds critical importance for fostering agricultural healthy and swift growth. Utilizing the Technology Acceptance Model (TAM) as a foundation, this study incorporates three additional variables—government support, platform support, and social learning—to devise a theoretical model. It takes the agriculture-related live streaming e-commerce platform as an example, with 424 Chinese farmers as the sample, to quantitatively assess the factors that impact the intentions to adopt live streaming e-commerce behaviors. The findings indicate that, firstly, the TAM is applicable to the assessment of farmers’ intentions to adopt live streaming e-commerce. Secondly, government support positively impacts perceived usefulness, social learning enhances perceived ease of use, and platform support positively impacts both perceived ease of use and usefulness. Lastly, the technology acceptance extension model applicability varies among farmer groups: government support influence on perceived ease of use is more significant among traditional farmers, social learning impact on perceived ease of use is higher in farmers with higher education levels, and platform support effect on perceived usefulness is stronger among farmers experienced in e-commerce. Therefore, differentiated promotion strategies by the government are necessary, and e-commerce platforms should leverage their technology to offer efficient services and encourage farmer education. A multi-party collaboration model involving the government, platforms, and farmers is essential to collectively foster the healthy development of rural live streaming e-commerce.

Suggested Citation

  • Xinqiang Chen & Xiu-e Zhang & Jiangjie Chen, 2024. "TAM-Based Study of Farmers’ Live Streaming E-Commerce Adoption Intentions," Agriculture, MDPI, vol. 14(4), pages 1-22, March.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:4:p:518-:d:1362997
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    References listed on IDEAS

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    1. Timothy Conley & Udry Christopher, 2001. "Social Learning Through Networks: The Adoption of New Agricultural Technologies in Ghana," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 668-673.
    2. 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.
    3. 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.
    4. Andrew Crane-Droesch, 2018. "Technology Diffusion, Outcome Variability, and Social Learning: Evidence from a Field Experiment in Kenya," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(3), pages 955-974.
    5. Chen, Rui & Meng, Qiang & Yu, Jiayi Joey, 2023. "Optimal government incentives to improve the new technology adoption: Subsidizing infrastructure investment or usage?," Omega, Elsevier, vol. 114(C).
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