Open Access
Issue
E3S Web Conf.
Volume 235, 2021
2020 International Conference on New Energy Technology and Industrial Development (NETID 2020)
Article Number 01044
Number of page(s) 6
Section Research on New Energy Technology and Energy Consumption Development
DOI https://doi.org/10.1051/e3sconf/202123501044
Published online 03 February 2021
  1. J. K. Huang, H. S. Deng, Z. G. Xu. The service function and its influencing factors of Chinese farmers’ professional cooperative economic organizations [J]. Management World, 2010 (05): 7581. [Google Scholar]
  2. X. S. Zhang. An analysis of the development trend of farmer professional cooperatives [J]. Management World, 2009 (05): 89-96. [Google Scholar]
  3. D. R. Yang. Reason analysis and strategy empirical analysis on the “difficulty in agricultural products selling” of farmers’ professional cooperatives [J]. Agricultural Economy, 2013 (10): 116-118. [Google Scholar]
  4. Z. H. Huang, J. Zhang, K. Chen. Transaction costs and contract selection of farmers—Empirical evidence from the investigation of pear farmers in 30 villages in 15 counties in Zhejiang and Hebei provinces[J]. Management World, 2008 (09): 76-81. [Google Scholar]
  5. J. Yang, H. J. Wang. Analysis of the transaction costs of agricultural products circulation——Theoretical comparison based on e-commerce and non-ecommerce [J]. Rural South, 2014, 30 (08): 41-45. [Google Scholar]
  6. T. Q. Zhao. Promote the construction of informatization and improve the development level of farmers’ professional cooperatives [J]. China Farmers’ Cooperative, 2011 (12): 34-37. [Google Scholar]
  7. X. Z. Kong. Put the wings of e-commerce on the cooperative [J]. China Farmers Cooperative, 2015 (07): 33. [Google Scholar]
  8. M. Qian, Z. H. Li, W. Wang. Comparison and applicability analysis of the “production-sales docking” and “production-consumption docking” models——Based on the investigation of cooperative agricultural product circulation paths [J]. Management Modernization, 2013 (05) : 47-49. [Google Scholar]
  9. N. Zhang, L. Wang, C. Q. Li, et al. Research on the ecommerce model of farmers’ professional cooperatives under the background of “Internet +”[J]. E-commerce, 2017 (02): 28-30. [Google Scholar]
  10. D. S. Chen, D. M. Qiu, H. D. Guo, et al. Comparative analysis of cooperatives’ e-commerce model development [J]. China Farmers Cooperative, 2015 (07): 25-26. [Google Scholar]
  11. L. Xu, Z. C. Si. Analysis of the Agricultural Products E-commerce Model of Farmer Cooperatives [J]. Jiangsu Rural Economy, 2016 (04): 65-66. [Google Scholar]
  12. Y. Chen. Some thoughts on the marketing of farmer cooperatives in the Internet age [J]. China Farmer Cooperatives, 2014 (10): 52-54. [Google Scholar]
  13. R. D. Zhang. Internet + agriculture: new opportunities for cooperative development [J]. China Farmers Cooperative, 2015 (07): 27-29. [Google Scholar]
  14. Z. J. Wu, J. J. Qiu. Challenges, significance and mechanism of agricultural cooperatives operating fresh e-commerce platforms [J]. Science and Technology Management Research, 2015, 35 (19): 197-201. [Google Scholar]
  15. Z. Yao. Empirical study on the differences of ecommerce cognitive behaviors and influencing factors of new agricultural management entities [J]. China Circulation Economy, 2017, 31 (09): 46-52. [Google Scholar]
  16. Y. F. Zhang. E-commerce sales of fresh fruits, farmers’ willingness to participate and cooperatives embedding-survey data from farmers in Yantai big cherry production area [J]. Journal of Nanjing Agricultural University (Social Science Edition), 2016, 16 (01) : 49-58. [Google Scholar]
  17. C. C. Wang, C. P. Xia, Y. Cai, et al. The impact of social trust on farmers’ cooperative participation in ecommerce management [J]. Journal of China Agricultural University, 2019, 24 (03): 198-209. [Google Scholar]
  18. B. Liu, Y. M. Ye, X. L. Kang, et al. Analysis of the choice of farmers’ e-commerce entrepreneurial behavior and its influencing factors——Based on the data of 150 farmers’ e-commerce entrepreneurs in Jiangxi province [J]. Journal of Agricultural and Forestry Economic Management, 2019, 18 (01): 36-42. [Google Scholar]
  19. J. L. Luo, C. X. Qiu, J. Li. Research on cooperative resource base and willingness to participate in ecommerce model——Based on 118 farmer professional cooperatives in Zhejiang Province [J]. Chinese Agricultural Science Bulletin, 2017, 33 (14): 158-164. [Google Scholar]
  20. B. Liu, X. K. Lei, C. Y. Du, et al. Influencing factors of farmers cooperatives participating in agricultural product e-commerce behaviors——Taking Jiangxi Province as an example [J]. Jiangsu Agricultural Sciences, 2017, 45 (14): 284-288. [Google Scholar]
  21. A. C. Dorr. Economic Analysis of Certification in the Brazilian Fruit ¨Chain. Cuvillier Publisher, Gottingen. 2009. [Google Scholar]
  22. X. D. Zhang. Research on the influence of the coupling of agricultural product brand and culture on online sales [J]. Frontier, 2020 (01): 48-56. [Google Scholar]
  23. C. Bacon. Confronting the coffee crisis: Can fair trade, organic, and specialty coffees reduce small-scale farmer vulnerability in Northern Nicaragua? World Develop [J]. 2005, 33(3), 497–511. [Google Scholar]
  24. P. R. Jena, B. B. Chichaibelu, T. Stellmacher, et al. The impact of coffee certification on small-scale producers’ livelihoods: a case study from the Jimma Zone, Ethiopia[J]. Agricultural Economics, 2012, 43(4): 429-440. [Google Scholar]
  25. R. X. Wang. The conditions and feasibility for farmers’ cooperatives to engage in e-commerce [J]. China Farmers’ Cooperative, 2016 (06): 41-42. [Google Scholar]
  26. Y. Y. Dong, Y. Zhu. Discussion on the development of agricultural product e-commerce by farmers professional cooperatives [J]. Zhejiang Agricultural Sciences, 2012 (02): 262-265. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.