IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i4p518-d1362997.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/4/518/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/4/518/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
    4. 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.
    5. 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.
    6. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhammad Ali & Syed Ali Raza & Chin-Hong Puah & Mohd Zaini Abd Karim, 2017. "Islamic home financing in Pakistan: a SEM-based approach using modified TPB model," Housing Studies, Taylor & Francis Journals, vol. 32(8), pages 1156-1177, November.
    2. Enid M. Katungi & Catherine Larochelle & Josephat R. Mugabo & Robin Buruchara, 2018. "The effect of climbing bean adoption on the welfare of smallholder common bean growers in Rwanda," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(1), pages 61-79, February.
    3. Alam, Syed Shah & Nik Hashim, Nik Hazrul & Rashid, Mamunur & Omar, Nor Asiah & Ahsan, Nilufar & Ismail, Md Daud, 2014. "Small-scale households renewable energy usage intention: Theoretical development and empirical settings," Renewable Energy, Elsevier, vol. 68(C), pages 255-263.
    4. 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.
    5. Wen-Jye Shyr & Wei-Sho Ho & Jie-Ru Chen & Li-Ya Chang & I-Min Chen, 2022. "Effectiveness of Social Participation Courses Applied in the Disaster Prevention for Taiwanese K-12 Education," Sustainability, MDPI, vol. 14(13), pages 1-19, July.
    6. Wasapon Thanabodypath & Achara Chandrachai & Sudkate Chaiyo & Orawon Chailapakul, 2021. "Industrial Buyer Innovation Adoption Model: A Focus on a Smartphone-Based Electrochemical Analytical Device for Toxic Heavy Metal Detection," Sustainability, MDPI, vol. 13(21), pages 1-21, October.
    7. Hsing-Chun Hung & Yuh-Wen Chen, 2023. "Striving to Achieve United Nations Sustainable Development Goals of Taiwanese SMEs by Adopting Industry 4.0," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    8. Muhammad Hamza & Rai Waqas Azfar & Khwaja Mateen Mazher & Basel Sultan & Ahsen Maqsoom & Shabir Hussain Khahro & Zubair Ahmed Memon, 2023. "Exploring Perceptions of the Adoption of Prefabricated Construction Technology in Pakistan Using the Technology Acceptance Model," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    9. Nadia A. Streletskaya & Samuel D. Bell & Maik Kecinski & Tongzhe Li & Simanti Banerjee & Leah H. Palm‐Forster & David Pannell, 2020. "Agricultural Adoption and Behavioral Economics: Bridging the Gap," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 54-66, March.
    10. Fellnhofer, Katharina, 2022. "Entrepreneurial alertness toward responsible research and innovation: Digital technology makes the psychological heart of entrepreneurship pound," Technovation, Elsevier, vol. 118(C).
    11. Night, Sadress & Bananuka, Juma, 2020. "The mediating role of adoption of an electronic tax system in the relationship between attitude towards electronic tax system and tax compliance," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 25(49), pages 73-88.
    12. Alsajjan, Bander & Dennis, Charles, 2010. "Internet banking acceptance model: Cross-market examination," Journal of Business Research, Elsevier, vol. 63(9-10), pages 957-963, September.
    13. Islam, Asadul & Ushchev, Philip & Zenou, Yves & Zhang, Xin, 2019. "The Value of Information in Technology Adoption," IZA Discussion Papers 12672, Institute of Labor Economics (IZA).
    14. Shagun Tyagi & Ashulekha Gupta & Nabila Ansari, 2024. "Adoption and perception of banking customers towards green mode of banking: a demonstration of structural equation modelling," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(3), pages 826-842, September.
    15. Jahanmir, Sara F. & Cavadas, Joana, 2018. "Factors affecting late adoption of digital innovations," Journal of Business Research, Elsevier, vol. 88(C), pages 337-343.
    16. Gbêtondji Melaine Armel Nonvide, 2021. "Adoption of agricultural technologies among rice farmers in Benin," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 2372-2390, November.
    17. Kazushi Takahashi & Rie Muraoka & Keijiro Otsuka, 2020. "Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 31-45, January.
    18. 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.
    19. Konietzny, Jirka & Caruana, Albert & Cassar, Mario L., 2018. "Fun and fair, and I don’t care: The role of enjoyment, fairness and subjective norms on online gambling intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 91-99.
    20. Xiaolong Feng & Mingyue Liu & Xuexi Huo & Wanglin Ma, 2017. "What Motivates Farmers’ Adaptation to Climate Change? The Case of Apple Farmers of Shaanxi in China," Sustainability, MDPI, vol. 9(4), pages 1-15, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:14:y:2024:i:4:p:518-:d:1362997. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.