The role of social networks in promoting technology adoption in rice production: evidence from panel data

Authors

DOI:

https://doi.org/10.51599/are.2025.11.03.12

Keywords:

social networks, technology adoption, rice production, fertilisers, Vietnam.

Abstract

Purpose. This research aims to determine the impact of social networks, including the number of household groups involved, on the adoption of technologies such as improved rice varieties, chemical fertilisers, and organic fertilisers in the rice production sector in Vietnam.

Methodology / approach. This study used panel data from the Vietnam Access to Resources Household Survey (VARHS) from 2012 to 2018. After merging several files of data, the study received the panel data with 684 households for each period. This study involves establishing an internal instrumental variable to mitigate the problem of the endogeneity of social networks and measure its impact on technology adoption. In addition, several estimations, such as Instrumental Variables (IV), Fixed Effects (FE), Correlated Random Effects (CRE), and Random Effects (RE), were used to show the relationship between social networks and technology adoption in rice production.

Results. The study’s results suggest that using social networks tends to increase the likelihood of using organic fertiliser in rice production. Across all model specifications, including Random Effects, Correlated Random Effects, and Fixed Effects, household participation in social groups has a statistically significant positive effect on organic fertiliser adoption. However, the difference in those models about the coefficients suggests that these standard panel estimators may underestimate the true impact of social networks. This potential downward bias highlights the importance of addressing endogeneity, reinforcing the need for Instrumental Variable (IV) approaches in such analyses. On the other hand, the research does not discover any connection between social networks and the adoption of technologies like chemical fertilisers and improved seeds.

Originality / scientific novelty. This is the first study that rigorously investigates the relationship between social networks and technology adoption in rice production in Vietnam, using long panel data and an internal instrumental variable approach. While prior research in other developing countries (e.g., China, Ethiopia) has explored similar themes, our study contributes by providing country-specific evidence from Vietnam’s rice sector, a globally significant producer.

Practical value / implications. In light of the findings, policymakers can leverage the positive influence of social relations to encourage more environmentally responsible farming methods in the production of rice. By prioritising the promotion of social networks, policymakers can encourage the use of organic fertilisers.

References

Abdulai, A. (2023). Information acquisition and the adoption of improved crop varieties. American Journal of Agricultural Economics, 105(4), 1049–1062. https://doi.org/10.1111/ajae.12419

Ambong, R. M. A. (2022). Methods of rice technology adoption studies in the Philippines and other Asian countries: a systematic review. Research on World Agricultural Economy, 3(2), 15–24. https://doi.org/10.36956/rwae.v3i2.513

Asfaw, A., & Admassie, A. (2004). The role of education on the adoption of chemical fertiliser under different socioeconomic environments in Ethiopia. Agricultural Economics, 30(3), 215–228. https://doi.org/10.1016/j.agecon.2002.12.002

Baum, C. F., & Lewbel, A. (2019). Advice on using heteroskedasticity-based identification. The Stata Journal: Promoting Communications on Statistics and Stata, 19(4), 757–767. https://doi.org/10.1177/1536867X19893614

Belay, M., & Mengiste, M. (2023). The ex‐post impact of agricultural technology adoption on poverty: evidence from north Shewa zone of Amhara region, Ethiopia. International Journal of Finance & Economics, 28(2), 1327–1337. https://doi.org/10.1002/ijfe.2479

Belayneh, M. (2023). Factors affecting the adoption and effectiveness of soil and water conservation measures among small-holder rural farmers: the case of Gumara watershed. Resources, Conservation and Recycling Advances, 18, 200159. https://doi.org/10.1016/j.rcradv.2023.200159

BenYishay, A., & Mobarak, A. M. (2019). Social learning and incentives for experimentation and communication. The Review of Economic Studies, 86(3), 976–1009. https://doi.org/10.1093/restud/rdy039

Bojorquez-Chapela, I., Manrique-Espinoza, B. S., Mejía-Arango, S., Solís, M. M. T.-R., & Salinas-Rodríguez, A. (2012). Effect of social capital and personal autonomy on the incidence of depressive symptoms in the elderly: evidence from a longitudinal study in Mexico. Aging & Mental Health, 16(4), 462–471. https://doi.org/10.1080/13607863.2011.651432

Bosworth, G., Annibal, I., Carroll, T., Price, L., Sellick, J., & Shepherd, J. (2016). Empowering local action through neo-endogenous development; the case of LEADER in England. Sociologia Ruralis, 56(3), 427–449. https://doi.org/10.1111/soru.12089

Burlig, F., & Stevens, A. W. (2024). Social networks and technology adoption: Evidence from church mergers in the U.S. Midwest. American Journal of Agricultural Economics, 106(3), 1141–1166. https://doi.org/10.1111/ajae.12429

Chang, S. E., & Kuo, M.-Y. (2021). A place-based pedagogical action study to enrich rural sustainability: knowledge ties of National Taiwan University’s 10-year partnership with Pinglin. Sustainability, 13(5), 2916. https://doi.org/10.3390/su13052916

Chen, X., & Li, T. (2022). Diffusion of agricultural technology innovation: research progress of innovation diffusion in Chinese agricultural science and technology parks. Sustainability, 14(22), 15008. https://doi.org/10.3390/su142215008

Dadzie, S. K. N., Ndebugri, J., Inkoom, E. W., & Akuamoah-Boateng, S. (2022). Social networking and risk attitudes nexus: implication for technology adoption among smallholder cassava farmers in Ghana. Agriculture and Food Security, 11(1), 41. https://doi.org/10.1186/s40066-022-00376-3

Esther, W. (2018). Innovation development and transfer by agricultural development agencies: a case study of cowpea IPM in northern Ghana. Agro-Science, 17(1), 7–19. https://doi.org/10.4314/as.v17i1.2

Farooq, M. S., Riaz, S., Abid, A., Abid, K., & Naeem, M. A. (2019). A survey on the role of IoT in agriculture for the implementation of smart farming. IEEE Access, 7, 156237–156271. https://doi.org/10.1109/ACCESS.2019.2949703

Gebremariam, G., & Tesfaye, W. (2018). The heterogeneous effect of shocks on agricultural innovations adoption: microeconometric evidence from rural Ethiopia. Food Policy, 74, 154–161. https://doi.org/10.1016/j.foodpol.2017.12.010

Genius, M., Koundouri, P., Nauges, C., & Tzouvelekas, V. (2014). Information transmission in irrigation technology adoption and diffusion: social learning, extension services, and spatial effects. American Journal of Agricultural Economics, 96(1), 328–344. https://doi.org/10.1093/ajae/aat054

Grootaert, C., Narayan, D., Jones, V. N., & Woolcock, M. (2004). Measuring social capital: an integrated questionnaire. The International Bank for Reconstruction and Development / The World Bank. Available at: https://documents1.worldbank.org/curated/en/515261468740392133/pdf/281100PAPER0Measuring0social0capital.pdf

Guntukogula Pattabhi, S., Prashanth, P., Sreenivasulu, M., & Madavilata, A. (2023). Effectiveness of social media agricultural information on farmer’s knowledge. Environment Conservation Journal, 24(1), 123–129. https://doi.org/10.36953/ECJ.11432297

Holden, S. T., & Quiggin, J. (2017). Climate risk and state-contingent technology adoption: shocks, drought tolerance and preferences. European Review of Agricultural Economics, 44(2), 285–308. https://doi.org/10.1093/erae/jbw016

Hossain, M., Bose, M. L., & Mustafi, B. A. A. (2006). Adoption and Productivity Impact of Modern Rice Varieties in Bangladesh. The Developing Economies, 44(2), 149–166. https://doi.org/10.1111/j.1746-1049.2006.00011.x

Huang, X., Lu, Q., Wang, L., Cui, M., & Yang, F. (2020). Does aging and off-farm employment hinder farmers’ adoption behavior of soil and water conservation technology in the Loess Plateau? International Journal of Climate Change Strategies and Management, 12(1), 92–107. https://doi.org/10.1108/IJCCSM-04-2019-0021

Khonje, M. G., Nyondo, C., Chilora, L., Mangisoni, J. H., Ricker‐Gilbert, J., & Burke, W. J. (2022). Exploring adoption effects of subsidies and soil fertility management in Malawi. Journal of Agricultural Economics, 73(3), 874–892. https://doi.org/10.1111/1477-9552.12486

Kumar, A., Takeshima, H., Thapa, G., Adhikari, N., Saroj, S., Karkee, M., & Joshi, P. K. (2020). Adoption and diffusion of improved technologies and production practices in agriculture: insights from a donor-led intervention in Nepal. Land Use Policy, 95, 104621. https://doi.org/10.1016/j.landusepol.2020.104621

Lan, N. T. P., & Van Kien, N. (2021). Back to Nature-based agriculture: green livelihoods are taking root in the Mekong river delta. Journal of People, Plants, and Environment, 24(6), 551–561. https://doi.org/10.11628/ksppe.2021.24.6.551

Lewbel, A. (2012). Using heteroscedasticity to identify and estimate mismeasured and endogenous regressor models. Journal of Business and Economic Statistics, 30(1), 67–80. https://doi.org/10.1080/07350015.2012.643126

Li, L., Gao, Y., & Wang, X. (2023). Impact of economic policy uncertainty on agribusiness technology innovation: evidence from 231 listed firms in China. Sustainability, 15(13), 10037. https://doi.org/10.3390/su151310037

Liu, Y., Liu, Z., Liu, J., Qiu, L., Wang, Y., & Fu, X. (2022). Research on the impact of members’ social capital within agricultural cooperatives on their adoption of IPM in China. International Journal of Environmental Research and Public Health, 19(18), 11538. https://doi.org/10.3390/ijerph191811538

Ma, R., & Yang, S. (2023). The effect of social network on controlled-release fertilizer use: evidence from rice large-scale farmers in Jiangsu province, China. Sustainability, 15(4), 2982. https://doi.org/10.3390/su15042982

Maertens, A., & Barrett, C. B. (2013). Measuring social networks’ effects on agricultural technology adoption. American Journal of Agricultural Economics, 95(2), 353–359. https://doi.org/10.1093/ajae/aas049

Magnan, N., Spielman, D. J., Lybbert, T. J., & Gulati, K. (2015). Leveling with friends: social networks and Indian farmers’ demand for a technology with heterogeneous benefits. Journal of Development Economics, 116, 223–251. https://doi.org/10.1016/j.jdeveco.2015.05.003

Mehar, M., Mittal, S., & Prasad, N. (2016). Farmers coping strategies for climate shock: Is it differentiated by gender? Journal of Rural Studies, 44, 123–131. https://doi.org/10.1016/j.jrurstud.2016.01.001

Moore, C. (2024). Renewable energy adoption and its effect on rural development in United States. Journal of Developing Country Studies, 8(2), 15–31. https://doi.org/10.47604/jdcs.2674

Nakano, Y., Tsusaka, T. W., Aida, T., & Pede, V. O. (2018). Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania. World Development, 105, 336–351. https://doi.org/10.1016/j.worlddev.2017.12.013

National Statistics Office (NSO) (2022). Vietnam Statiscal Yearbook 2022. Hanoi. Available at: https://www.nso.gov.vn/en/data-and-statistics/2023/06/statistical-yearbook-of-2022

Nazreen Hassan, S., Swarna Priya, R., Kavitha, K., Selvarani, A., Latha, R., & Suresh, S. (2023). Utilization pattern of TNAU banana expert system among Nendren banana growers in Kanyakumari district. Asian Journal of Agricultural Extension, Economics & Sociology, 41(7), 23–28. https://doi.org/10.9734/ajaees/2023/v41i71938

Nguyen Duc, K., Ancev, T., & Randall, A. (2021). Farmers’ choices of climate-resilient strategies: evidence from Vietnam. Journal of Cleaner Production, 317(317), 128399. https://doi.org/10.1016/j.jclepro.2021.128399

Nguyen Duc, K., Nguyen Thai, P., Nguyen, C. D., Dinh, T. K. O., Nguyen, T. M. P., & Truong, Q. D. (2024). Regional heterogeneity in livelihood strategies and its implications for household welfare: a panel data analysis of rural Vietnam. Agris On-Line Papers in Economics and Informatics, 16(3), 75–91. https://doi.org/10.7160/aol.2024.160306

Nguyen, L. (2020). Land rights and technology adoption: improved rice varieties in Vietnam. The Journal of Development Studies, 56(8), 1489–1507. https://doi.org/10.1080/00220388.2019.1677889

Nnodim, A. U., & Raji, W. I. (2020). Assessment of agricultural technology adoption behaviour among crop farmers in Ikwerre local government rivers state. Asian Research Journal of Agriculture, 12(2), 16–26. https://doi.org/10.9734/arja/2020/v12i230079

Ogada, M. J., Mwabu, G., & Muchai, D. (2014). Farm technology adoption in Kenya: a simultaneous estimation of inorganic fertilizer and improved maize variety adoption decisions. Agricultural and Food Economics, 2(1), 12. https://doi.org/10.1186/s40100-014-0012-3

Ojo, T. O., Baiyegunhi, L. J. S., Adetoro, A. A., & Ogundeji, A. A. (2021). Adoption of soil and water conservation technology and its effect on the productivity of smallholder rice farmers in Southwest Nigeria. Heliyon, 7(3), e06433. https://doi.org/10.1016/j.heliyon.2021.e06433

Patil, D. S., Chavan, M. V. G., & Patil, D. P. (2019). Social innovation through precision farming: an IoT based precision farming system for examining and improving soil fertility and soil health. International Journal of Innovative Technology and Exploring Engineering, 8(11), 2877–2881. https://doi.org/10.35940/ijitee.K2421.0981119

Phan Nguyen, T., Nguyen, D. K., & Truong, Q. D. (2025). How does climate shock affect technology adoption in rice production? Agricultural Economics – Czech, 71(1), 14–26. https://doi.org/10.17221/296/2024-AGRICECON

Phan, N. T. (2025). Improving household food diversity via non-farming livelihoods in Vietnam. SAGE Open, 15(3), 1–15. https://doi.org/10.1177/21582440251365808

Phan, N. T., Lee, J., & Kien, N. D. (2022a). The impact of land fragmentation in rice production on household food insecurity in Vietnam. Sustainability, 14(18), 11162. https://doi.org/10.3390/su141811162

Phan, N. T., Pabuayon, I. M., Kien, N. D., Dung, T. Q., An, L. T., & Dinh, N. C. (2022b). Factors driving the adoption of coping strategies to market risks of shrimp farmers: a case study in a Coastal province of Vietnam. Asian Journal of Agriculture and Rural Development, 12(2), 65–74. https://doi.org/10.55493/5005.v12i2.4444

Ruan, H., Chen, J., Wang, C., Xu, W., & Tang, J. (2022). Social network, sense of responsibility, and resident participation in China’s rural environmental governance. International Journal of Environmental Research and Public Health, 19(11), 6371. https://doi.org/10.3390/ijerph19116371

Sayuti, R. H., Taqiuddin, M., Evendi, A., Hidayati, S. A., & Muttaqin, M. Z. (2023). Impact of COVID-19 pandemic on the existence of social solidarity: evidence from rural-urban communities in Lombok island, Indonesia. Frontiers in Sociology, 8, 1164837. https://doi.org/10.3389/fsoc.2023.1164837

Shakya, P. B., & Flinn, J. C. (1985). Adoption of modern varieties and fertilizer use on rice in the Eastern Tarai of Nepal. Journal of Agricultural Economics, 36(3), 409–419. https://doi.org/10.1111/j.1477-9552.1985.tb00188.x

Shikuku, K. M. (2019). Information exchange links, knowledge exposure, and adoption of agricultural technologies in northern Uganda. World Development, 115, 94–106. https://doi.org/10.1016/j.worlddev.2018.11.012

Skaalsveen, K., Ingram, J., & Urquhart, J. (2020). The role of farmers’ social networks in the implementation of no-till farming practices. Agricultural Systems, 181, 102824. https://doi.org/10.1016/j.agsy.2020.102824

Sulaeman, Cyio, M. B., & Rauf, R. A. (2020). Factors affecting production in the intensification of lowland rice farming in Parigi Moutong regency, Indonesia. International Journal of Agriculture, Environment and Bioresearch, 05(01), 36–50. https://doi.org/10.35410/IJAEB.2020.5458

Takahashi, R., Todo, Y., & Degefa, T. (2015). The effects of a participatory approach on the adoption of agricultural technology: focusing on the social network structure in rural Ethiopia. Studies in Agricultural Economics, 117(1), 50–56. https://doi.org/10.7896/j.1504

Tesfay, M. G. (2021). Impact of irrigated agriculture on welfare of farm households in northern Ethiopia: panel data evidence. Irrigation and Drainage, 70(2), 306–320. https://doi.org/10.1002/ird.2545

Thai, P. N., Diem, M. N. H., Nguyen Thi Thuy, H., Le Thanh, A., Nguyen Cong, D., & Nguyen Duc, K. (2025). The impact of social networks on water security in rice production in central Vietnam. Discover Sustainability, 6(1), 1036. https://doi.org/10.1007/s43621-025-01714-8

Tian, M., Liu, R., Wang, J., Liang, J., Nian, Y., & Ma, H. (2023). Impact of environmental values and information awareness on the adoption of soil testing and formula fertilization technology by farmers – a case study considering social networks. Agriculture, 13(10), 2008. https://doi.org/10.3390/agriculture13102008

Tshikovhi, N., More, K., & Cele, Z. (2023). Driving sustainable growth for small and medium enterprises in emerging urban-rural economies. Sustainability, 15(21), 15337. https://doi.org/10.3390/su152115337

Usman, M., Hameed, G., Saboor, A., Almas, L. K., & Hanif, M. (2021). R&D innovation adoption, climatic sensitivity, and absorptive ability contribution for agriculture TFP growth in Pakistan. Agriculture, 11(12), 1206. https://doi.org/10.3390/agriculture11121206

Uzoagu, I. F., & Oriji, A. (2022). Education & developmental initiatives: examining the role of adult education in rural community development in Nigeria. European Journal of Training and Development Studies, 9(2), 11–26. https://doi.org/10.37745/ejtds.2014/vol9n21126

Volpi, F., & Clark, J. A. (2019). Activism in the Middle East and North Africa in times of upheaval: social networks’ actions and interactions. Social Movement Studies, 18(1), 1–16. https://doi.org/10.1080/14742837.2018.1538876

Wang, G., Lu, Q., & Capareda, S. C. (2020). Social network and extension service in farmers’ agricultural technology adoption efficiency. PLoS ONE, 15(7), e0235927. https://doi.org/10.1371/journal.pone.0235927

Wang, H., Pandey, S., Hu, F., Xu, P., Zhou, J., Li, J., Deng, X., … & Tao, D. (2010). Farmers’ adoption of improved upland rice technologies for sustainable mountain development in Southern Yunnan. Mountain Research and Development, 30(4), 373–380. https://doi.org/10.1659/MRD-JOURNAL-D-09-00012.1

Wang, Z., Liu, J., Li, T., Chao, J., & Gao, X. (2021). Factors affecting new agricultural business entities’ adoption of sustainable intensification practices in China: evidence from the main apple-producing areas in the loess plateau. Agronomy, 11(12), 2435. https://doi.org/10.3390/agronomy11122435

Wossen, T., Berger, T., Mequaninte, T., & Alamirew, B. (2013). Social network effects on the adoption of sustainable natural resource management practices in Ethiopia. International Journal of Sustainable Development & World Ecology, 20(6), 477–483. https://doi.org/10.1080/13504509.2013.856048

Xu, J., Cui, Z., Wang, T., Wang, J., Yu, Z., & Li, C. (2023). Influence of agricultural technology extension and social networks on Chinese farmers’ adoption of conservation tillage technology. Land, 12(6), 1215. https://doi.org/10.3390/land12061215

Xu, P., Ye, P., Jahanger, A., Huang, S., & Zhao, F. (2023). Can green credit policy reduce corporate carbon emission intensity: evidence from China’s listed firms. Corporate Social Responsibility and Environmental Management, 30(5), 2623–2638. https://doi.org/10.1002/csr.2506

Yang, Q., Zhu, Y., & Wang, F. (2021a). Exploring mediating factors between agricultural training and farmers’ adoption of drip fertigation system: evidence from banana farmers in China. Water, 13(10), 1364. https://doi.org/10.3390/w13101364

Yang, Q., Zhu, Y., & Wang, F. (2021b). Social media participation, low-carbon agricultural practices, and economic performance of banana farmers in Southern China. Frontiers in Psychology, 12, 790808. https://doi.org/10.3389/fpsyg.2021.790808

Zheng, H., Ma, J., Yao, Z., & Hu, F. (2022). How does social embeddedness affect farmers’ adoption behavior of low-carbon agricultural technology? Evidence from Jiangsu province, China. Frontiers in Environmental Science, 10, 909803. https://doi.org/10.3389/fenvs.2022.909803

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2025-09-20

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Nguyen Thai, P., Nguyen Cong, D., Le Thanh, A., Nguyen Duc, K., & Nguyen Tran Thuy, A. (2025). The role of social networks in promoting technology adoption in rice production: evidence from panel data. Agricultural and Resource Economics: International Scientific E-Journal, 11(3), 342–367. https://doi.org/10.51599/are.2025.11.03.12

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