Will participating in ECPs improve organic tea farmers’ income in the context of the COVID-19 epidemic?
Tóm tắt
Product commercialization is an integral part of the production chain. Previously, most farming households sold organic tea to traders, supermarkets, and consumers at traditional markets. However, in the context of the complicated development of the COVID-19 epidemic, they have gradually switched to selling online or on e-commerce platforms (ECPs). The benefits of ECPs to the community’s health have been demonstrated in many studies. However, the economic benefits for organic tea farmers have not been specifically considered. This study aims to shed light on whether participating in ECPs improves the income of organic tea farmers in the context of the COVID-19 epidemic. To answer this question, we used the Propensity Score Matching (PSM) method after interviewing 298 organic tea farmers in the mountainous provinces of northern Vietnam. Research results have shown that farming households that use ECPs to sell products have a higher income than those that do not use ECPs. This result implies that supporting and promoting farmers to put organic tea on ECPs is a valuable solution to help them improve their income. Therefore, local authorities and farmers’ associations in the mountainous provinces of northern Vietnam should find practical solutions to support farmers’ participation in ECPs during the current epidemic.
Tài liệu tham khảo
Abokyi E, Strijker D, Asiedu KF, Daams MN (2020) The impact of output price support on smallholder farmers’ income: evidence from maize farmers in Ghana. Heliyon 6(9):e05013. https://doi.org/10.1016/j.heliyon.2020.e05013
Aschemann-Witzel J, Zielke S (2017) Can’t buy me green? A review of consumer perceptions of and behavior toward the price of organic food. J Consum Aff 51(1):211–251. https://doi.org/10.1111/joca.12092
Attipoe SG, Cao J-M, Opoku-Kwanowaa Y, Ohene-Sefa F (2021) Assessing the impact of non-governmental organization’s extension programs on sustainable cocoa production and household income in Ghana. J Integr Agric 20(10):2820–2836. https://doi.org/10.1016/s2095-3119(21)63607-9
Ayuya OI (2018) Organic certified production systems and household income: micro level evidence of heterogeneous treatment effects. Org Agric 9(4):417–433. https://doi.org/10.1007/s13165-018-0236-8
Becerril J, Abdulai A (2010) The impact of improved maize varieties on poverty in Mexico: a propensity score-matching approach. World Dev 38(7):1024–1035. https://doi.org/10.1016/j.worlddev.2009.11.017
Bezabeh A, Beyene F, Haji J, Lemma T, Yildiz F (2020) Impact of contract farming on income of smallholder malt barley farmers in Arsi and West Arsi zones of Oromia region Ethiopia. Cogent Food Agric 6(1):1834662. https://doi.org/10.1080/23311932.2020.1834662
Budhathoki N, Bhatta GD (2016) Adoption of improved rice varieties in Nepal: impact on household wellbeing. Agric Res 5(4):420–432. https://doi.org/10.1007/s40003-016-0220-z
Danso-Abbeam G, Dagunga G, Ehiakpor DS (2020) Rural non-farm income diversification: implications on smallholder farmers’ welfare and agricultural technology adoption in Ghana. Heliyon 6(11):e05393. https://doi.org/10.1016/j.heliyon.2020.e05393
Dhanapal S, Vashu D, Subramaniam T (2015) Perceptions on the challenges of online purchasing: a study from “baby boomers”, generation “X” and generation “Y” point of views. Contaduría y Administración 60:107–132. https://doi.org/10.1016/j.cya.2015.08.003
Doanh N, Thuong N, Heo Y (2018) Impact of conversion to organic tea cultivation on household income in the mountainous areas of Northern Vietnam. Sustainability 10(12):4475. https://doi.org/10.3390/su10124475
Dong Y, Mu Y, Abler D (2019) Do farmer professional cooperatives improve technical efficiency and income? Evidence from small vegetable farms in China. J Agric Appl Econ 51(04):591–605. https://doi.org/10.1017/aae.2019.22
Dung ND (2018) Psychology, perceptions of ethnic groups in new rural construction in ethnic minority areas and mountains. http://mattran.org.vn/hoi-dong-tu-van/tam-ly-nhan-thuc-cua-cac-toc-nguoi-trong-xay-dung-nong-thon-moi-vung-dan-toc-thieu-so-va-mien-nui-hien-nay-12955.html. Accessed 15/2/2022
Ehiakpor DS, Danso-Abbeam G, Dagunga G, and Ayambila SN (2019) Impact of Zai technology on farmers’ welfare: evidence from northern Ghana. Technol Society 59. https://doi.org/10.1016/j.techsoc.2019.101189
Hanif Y, Lallie HS (2021) Security factors on the intention to use mobile banking applications in the UK older generation (55+). A mixed-method study using modified UTAUT and MTAM – with perceived cyber security, risk, and trust. Technol Society 67:101693. https://doi.org/10.1016/j.techsoc.2021.101693
Hien T (2021) Online business – “lifebuoy” for food and drink during the pandemic. Accessed 1/2/2022 http://www.hanoimoi.com.vn/tin-tuc/Kinh-te/1001586/kinh-doanh-online---phao-cuu-sinh-cho-hang-an-uong-thoi-dich-benh
Kernecker M, Knierim A, Wurbs A, Kraus T, Borges F (2019) Experience versus expectation: farmers’ perceptions of smart farming technologies for cropping systems across Europe. Precision Agric 21(1):34–50. https://doi.org/10.1007/s11119-019-09651-z
Kumar P, Singh SS, Pandey AK, Singh RK, Srivastava PK, Kumar M, ... Drews M (2021) Multi-level impacts of the COVID-19 lockdown on agricultural systems in India: the case of Uttar Pradesh. Agric Syst 187. https://doi.org/10.1016/j.agsy.2020.103027
Lambrecht I, Vanlauwe B, Merckx R, Maertens M (2014) Understanding the process of agricultural technology adoption: mineral fertilizer in Eastern DR Congo. World Dev 59:132–146. https://doi.org/10.1016/j.worlddev.2014.01.024
Landmann D, Lagerkvist C-J, Otter V (2020) Determinants of small-scale farmers’ intention to use smartphones for generating agricultural knowledge in developing countries: evidence from rural India. Eur J Dev Res 33(6):1435–1454. https://doi.org/10.1057/s41287-020-00284-x
Lohr L, Diamond A, Dicken C, and Marquardt D (2011) Mapping competition zones for vendors and customers in U.S. farmers markets (146970). Retrieved from: https://ideas.repec.org/p/ags/uamsrr/146970.html
Malaquias RF, and Silva AF (2020) Understanding the use of mobile banking in rural areas of Brazil. Technol Society 62. https://doi.org/10.1016/j.techsoc.2020.101260
Michels M, Bonke V, Musshoff O (2019) Understanding the adoption of smartphone apps in dairy herd management. J Dairy Sci 102(10):9422–9434. https://doi.org/10.3168/jds.2019-16489
Mkhize S, and Ellis D (2020) Creativity in marketing communication to overcome barriers to organic produce purchases: the case of a developing nation. J Clean Prod 242. https://doi.org/10.1016/j.jclepro.2019.118415
Nafees L, Hyatt EM, Garber LL, Das N, and Boya ÜÖ (2022) Motivations to buy organic food in emerging markets: an exploratory study of urban Indian millennials. Food Qual Prefer 96. https://doi.org/10.1016/j.foodqual.2021.104375
Nguyen HH, Ngo VM, and Tran ANT (2021a) Financial performances, entrepreneurial factors and coping strategy to survive in the COVID-19 pandemic: case of Vietnam. Res Int Bus Finance 56. https://doi.org/10.1016/j.ribaf.2021a.101380
Nguyen MH, Armoogum J, Nguyen Thi B (2021) Factors affecting the growth of e-shopping over the COVID-19 era in Hanoi Vietnam. Sustainability 13(16):9205. https://doi.org/10.3390/su13169205
Olounlade OA, Li G-C, Kokoye SEH, Dossouhoui FV, Akpa KAA, Anshiso D, Biaou G (2020) Impact of participation in contract farming on smallholder farmers’ income and food security in rural Benin: PSM and LATE parameter combined. Sustainability 12(3):901. https://doi.org/10.3390/su12030901
Peng L, Lu G, Pang K, and Yao Q (2021) Optimal farmer’s income from farm products sales on live streaming with random rewards: case from China’s rural revitalisation strategy. Comput Electron Agric 189. https://doi.org/10.1016/j.compag.2021.106403
Pufahl A, and Weiss CR (2008) Evaluating the effects of farm programs: results from propensity score matching. Paper presented at the 12th Congress of the European Association of Agricultural Economists, Ghent, Belgium. http://purl.umn.edu/44149. Accessed 10/2/2022
Robina-Ramírez R, Chamorro-Mera A, and Moreno-Luna L (2020) Organic and online attributes for buying and selling agricultural products in the e-marketplace in Spain. Electron Comm Res App 42. https://doi.org/10.1016/j.elerap.2020.100992
Rose DC, Sutherland WJ, Parker C, Lobley M, Winter M, Morris C, ... Dicks LV (2016) Decision support tools for agriculture: towards effective design and delivery. Agric Syst 149:165-174. https://doi.org/10.1016/j.agsy.2016.09.009
Shaltoni AM (2016) E-marketing education in transition: an analysis of international courses and programs. Int J Manag Educ 14(2):212–218. https://doi.org/10.1016/j.ijme.2016.04.004
Thanh M (2020) It's not easy to deal with people who are “booming” online. http://www.baodongnai.com.vn/bandoc/202010/khong-de-xu-ly-nhung-nguoi-bung-hang-online-3027072/. Accessed 1/3/2022
The World Bank (2016) World Development Report 2016: Digital Dividends. Retrieved from https://www.worldbank.org/en/publication/wdr2016. Accessed 1/3/2022
Tran GTH, Nanseki T, Chomei Y, and Nguyen LT (2021) The impact of cooperative participation on income: the case of vegetable production in Vietnam. J Agribus Dev Emerg Econom ahead-of-print(ahead-of-print). https://doi.org/10.1108/jadee-05-2021-0108
Van VH, Quynh NN, and Doanh NK (2022) Factors affecting farmers’ intention to use ECEs in Covid-19 pandemic: combining the technology acceptance model (TAM) and barrier factors. J Agribus Dev Emerg Econ. https://doi.org/10.1108/jadee-01-2022-0008
Vietnam e-commerce and digital economy agency (2021) Vietnam e-trade in 2021. Vietnam: Ministry of industry and trade
Vuong QD, Tran VTT, Dang QV, and Mai VN (2021) The impact of access to cooperatives on households’ income: an empirical study in Vietnam. J Asian Fin Econ Bus 8(12). https://doi.org/10.13106/jafeb.2021
Wang YS, Wang YM, Lin HH, Tang TI (2003) Determinants of user acceptance of Internet banking: an empirical study. Int J Serv Ind Manag 14(5):501–519. https://doi.org/10.1108/09564230310500192
Wordofa M, Sassi M (2017) Impact of farmers’ training centres on household income: evidence from propensity score matching in Eastern Ethiopia. Social Sci 7(2):4. https://doi.org/10.3390/socsci7010004
Wordofa MG, Hassen JY, Endris GS, Aweke CS, Moges DK, and Rorisa DT (2021a) Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia. Agric Food Secur 10(1). https://doi.org/10.1186/s40066-020-00278-2
Wordofa MG, Hassen JY, Endris GS, Aweke CS, Moges DK, Rorisa DT (2021b) Impact of improved agricultural technology use on household income in Eastern Ethiopia: empirical evidence from a propensity score matching estimation. J Land Rural Studies 9(2):276–290. https://doi.org/10.1177/23210249211007676
Wu H, Ding S, Pandey S, Tao D (2010) Assessing the impact of agricultural technology adoption on farmers’ well-being using propensity-score matching analysis in rural China. Asian Econ J 24(2):141–160. https://doi.org/10.1111/j.1467-8381.2010.02033.x
Zheng Q (2009) Introduction to E-commerce, 1st edn. Springer, Berlin, Heidelberg
Zhu Z, Bai Y, Dai W, Liu D, and Hu Y (2021) Quality of e-commerce agricultural products and the safety of the ecological environment of the origin based on 5G Internet of Things technology. Environ Technol Innov 22. https://doi.org/10.1016/j.eti.2021.101462