Correlation Between Agricultural Product Purchases and Live-Streaming Economy in the Digital Economy
Downloads
Objectives: This paper aims to explore how agricultural product sales via live streaming affects the purchasing behavior in the context of the digital economy and evaluate the correlation between them. Methods: A questionnaire was designed to collect respondent’ personal information and information on their purchases of agricultural products. The correlation between agricultural product purchases and the live-streaming economy was measured. Findings: Most respondents purchased agricultural products on platforms such as Douyin and Taobao, preferred watching live streaming of internet celebrities and farmers, primarily bought fruits, vegetables, whole grains, and coarse cereals, and expressed high satisfaction with their agricultural product purchases. Correlation analysis indicated that the correlation coefficient between agricultural products and purchases in the live-streaming economy was highest at 0.742. Regression analysis found a significant positive correlation between agricultural products, anchors, live streaming, platforms, and agricultural product purchases. Novelty: The research quantifies the relevant information on agricultural product live streaming and purchases through questionnaire analysis. It also reveals the positive influence of the digital economy on agricultural product purchases, providing some references for the further development of agricultural product live streaming.
Downloads
[1] Chen, Z., Shu, W., Guo, H., & Pan, C. (2021). The spatial characteristics of sustainable development for agricultural products e‐commerce at county‐level: Based on the empirical analysis of China. Sustainability (Switzerland), 13(12), 6557. doi:10.3390/su13126557.
[2] Lin, L. W., & Xuan-Gang. (2023). Survey of Consumer Purchase Intentions of Live Stream in the Digital Economy. Smart Innovation, Systems and Technologies, 312, 67–72. doi:10.1007/978-981-19-3575-6_8.
[3] Wang, X., & Cao, S. (2024). Harnessing the stream: algorithmic imaginary and coping strategies for live-streaming e-commerce entrepreneurs on Douyin. Journal of Chinese Sociology, 11(1), 9. doi:10.1186/s40711-024-00213-z.
[4] Chen, X., Zhang, X. E., & Chen, J. (2024). TAM-Based Study of Farmers’ Live Streaming E-Commerce Adoption Intentions. Agriculture (Switzerland), 14(4), 518. doi:10.3390/agriculture14040518.
[5] Jing, W., & Loang, O. K. (2024). Live Streaming of E-Commerce in China: Evidence from Impulsive Chinese Tea Purchases. Studies in Systems, Decision and Control, 545, 1063–1079. doi:10.1007/978-3-031-65203-5_91.
[6] Xiao, Y., Yu, J., & Zhou, S. X. (2024). Commit on Effort or Sales? Value of Commitment in Live-streaming E-commerce. Production and Operations Management, 33(11), 2241–2258. doi:10.1177/10591478241270119.
[7] Xu, Y., Qi, J., Kong, J., & Zhang, W. (2024). Strategic decision making in live streaming e-commerce through tripartite evolutionary game analysis. PLoS ONE, 19(7 July), 32. doi:10.1371/journal.pone.0305427.
[8] Liu, Y., & Fan, J. (2025). Factors influencing consumers repurchase intention on e-commerce live streaming of agricultural products. International Food and Agribusiness Management Review, 1–18, 1–18. doi:10.22434/ifamr1125.
[9] Han, T., Han, J., Liu, J., & Li, W. (2024). Effect of emotional factors on purchase intention in live streaming marketing of agricultural products: A moderated mediation model. PLoS ONE, 19(4 April), 22. doi:10.1371/journal.pone.0298388.
[10] Chou, C. C., Tsai, S. Te, & Huang, F. (2024). Enhanced Network Media Application in Live-Streaming E-Commerce for Agricultural Products: A Systematic Approach Using Stimulus Organism Response Model. Proceedings of the 2024 IEEE 6th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2024, 353–356. doi:10.1109/ECBIOS61468.2024.10885524.
[11] Zhang, C., & Zhang, Y. (2021). Consumers' Purchase Intention of Geographical Indication Agricultural Products under the Background of Live-streaming Sales: An Exploratory Research Based on Grounded Theory. Asian Agricultural Research, 13(1), 21-31. doi:10.19601/j.cnki.issnl943-9903.2021.01.006.
[12] Zeng, B., Liu, X., Zhang, W., Wu, L., & Xu, D. (2023). Digital Transformation of Agricultural Products Purchasing: From the Perspective of Short Videos Live-Streaming. Sustainability (Switzerland), 15(20), 14948. doi:10.3390/su152014948.
[13] Li, K. (2023). A Review on Strategies and Development of the Live Broadcast for Agricultural Products under COVID-19. SHS Web of Conferences, 155, 02012. doi:10.1051/shsconf/202315502012.
[14] Gu, C., Sun, X., Wei, W., Sun, J., Zeng, Y., & Zhang, L. (2025). How to improve users’ purchase intention of agricultural products through live streaming systems? Acta Psychologica, 254, 104883. doi:10.1016/j.actpsy.2025.104883.
[15] Zhou, Z., & Luo, Z. (2025). Study on the extension path of agricultural products live marketing mode of rural e-commerce platform based on network traffic analysis. Applied Mathematics and Nonlinear Sciences, 10(1). doi:10.2478/amns-2025-0021.
[16] Zhou, J., Lan, H., Zhao, C., & Zhou, J. (2021). Haze pollution levels, spatial spillover influence, and impacts of the digital economy: Empirical evidence from china. Sustainability (Switzerland), 13(16), 1–18. doi:10.3390/su13169076.
[17] Krasnostavskaia, N., Maslova, T., Ruglova, L., & Chigir, M. (2020). Problems of forming marketing competencies in the digital economy. IOP Conference Series: Materials Science and Engineering, 940(1), 1–12. doi:10.1088/1757-899X/940/1/012066.
[18] Li, R., & Huang, W. (2024). Differential Games between a Brand Manufacturer and an Internet Celebrity Regarding Fairness Concerns. Mathematics, 12(19), 3154. doi:10.3390/math12193154.
[19] Unver, S., & Kurdoglu, O. (2024). A Comparative Analysis of Forest Engineers’ Opinions on Forest Road Construction in Türkiye. Applied Ecology and Environmental Research, 22(5), 4259–4275. doi:10.15666/aeer/2205_42594275.
[20] Kuei Lin, Y., Ye, W., Hepworth, E., Matus, A. M., Flatt, A., De Zoysa, N., Shaw, J. A., Rickels, M. R., Amiel, S. A., & Speight, J. (2024). 178-OR: Assessing Hypoglycemia Awareness—Validating HypoA-Q within the T1D Exchange Registry. Diabetes, 73(Supplement_1), 5. doi:10.2337/db24-178-or.
[21] Pina-Camacho, L., Diaz-Caneja, C. M., Fraguas, D., Boada, L., Parellada, M., Winter-van Rossum, I., Kahn, R., & Arango, C. (2020). T117. Prominent and Persistent Autistic Traits Are Associated with Early Non-Remission in First-Episode Schizophrenia. Schizophrenia Bulletin, 46(Supplement_1), S275–S275. doi:10.1093/schbul/sbaa029.677.
[22] Mohammed, M. O. A. (2024). Multivariate Analysis for Characterization of Air Pollution Sources: Part 1 Prior Data Screening and Underlying Assumptions. Polish Journal of Environmental Studies, 33(4), 4257–4271. doi:10.15244/pjoes/179919.
[23] Denis, F., Kane, H., Baumgart, J. G., Rusch, E., Deloyer, J., Fuenzalida, C., Kelemen, G., Gavrila-Ardelean, M., Krzystanek, M., Marazziti, D., Moraitou, M., Reunanen, M., Shyhrete, R., El Hage, W., Thome, J., Verwaest, W., Rude, N., Laruppe, C., & Fond Harmant, L. (2024). Internal consistency of the Mental Health Professional Culture Inventory: A pilot study in Romanian population. Translational Neuroscience, 15(1), 1–17. doi:10.1515/tnsci-2022-0350.
[24] Wang, Y., Fang, L., & Pan, J. (2024). The antecedents of customer satisfaction in the live-streaming commerce of green agricultural products. PLoS ONE, 19(7 July), 20. doi:10.1371/journal.pone.0305527.
- This work (including HTML and PDF Files) is licensed under a Creative Commons Attribution 4.0 International License.
