Abstract
Farmers’ credit is an important financial tool to promote agricultural development, farmers’ income and rural prosperity. This study utilizes 2018 China Family Panel Studies (CFPS) data. It applies a binary Logit model and a mediation effect model to analyze the impact of digital technology usage on farmers’ credit behavior. The results show that digital technology use can significantly increase farmers’ formal and informal credit availability, and the results still hold after robustness and endogeneity tests. Further analysis reveals that the intensity (duration) and depth (in learning, social interaction, and commercial activities) of digital technology usage can increase farmers’ probability of accessing formal and informal credit. Heterogeneity analysis shows that the use of digital technologies has a more significant promoting effect on formal and informal credit for young and middle-aged farmers, and a more prominent promoting effect on formal credit for farmers with low educational levels and those in central and western regions. Mechanism analysis shows that both bonding social capital and bridging social capital play an intermediary role in the impact of the use of digital technologies on farmers’ formal and informal credit behaviors. Based on the findings, we suggest that the government should improve farmers’ credit availability through measures such as improving information infrastructure, carrying out public welfare-oriented financial knowledge training, and rural cultural and recreational activities.
Similar content being viewed by others
Data availability
The data used in this study were obtained from the China Family Panel Studies (CFPS). Researchers who wish to access CFPS data must submit an application via the official CFPS platform (https://www.isss.pku.edu.cn/cfps/) and comply with the data usage agreement. In accordance with CFPS data protection regulations, the processed relevant data shall not be publicly shared.
References
Akoijam SLS (2012) Rural credit: a source of sustainable livelihood of rural India. Int J Soc Econ 40:83–97. https://doi.org/10.1108/03068291311283454
Baiyegunhi LJS, Fraser GCG, Darroch MaG (2010) Credit constraints and household welfare in the eastern cape province, south africa. Afr J Agric Res 5:2243–2252
Baron RM, Kenny DA (1986) The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51:1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
Cao D, Zhou Z, Liu G et al (2022) Does social capital buffer or exacerbate mental health inequality? Evidence from the China Family Panel Study (CFPS). Int J Equity Health 21:75. https://doi.org/10.1186/s12939-022-01642-3
Chandio AA, Jiang Y (2018) Determinants of credit constraints: evidence from Sindh, Pakistan. Emerg Mark Financ Trade 54:3401–3410. https://doi.org/10.1080/1540496X.2018.1481743
Chuong HN, Chi Hai N (2023) Measuring household social capital in rural Vietnam using MIMIC approach. Cogent Econ Financ 11:2268758. https://doi.org/10.1080/23322039.2023.2268758
Cofré-Bravo G, Klerkx L, Engler A (2019) Combinations of bonding, bridging, and linking social capital for farm innovation: how farmers configure different support networks. J Rural Stud 69:53–64. https://doi.org/10.1016/j.jrurstud.2019.04.004
Cuevas CE, Graham DH (2021) Agricultural lending costs in Honduras. In Undermining Rural Development with Cheap Credit. Routledge, pp. 96–103
Deng X, Xu D, Zeng M, Qi Y (2019) Does Internet use help reduce rural cropland abandonment? Evidence from China. Land Use Policy 89:104243. https://doi.org/10.1016/j.landusepol.2019.104243
Dong X, Yang F (2021) Informal credit constraints and farmers’ health: an empirical study of China. Ciênc Rural 51:e20200437. https://doi.org/10.1590/0103-8478cr20200437
Faton C, Chabossou A (2021) Effet des TIC sur l’inclusion financière au Bénin. Rev Int Econ Numér 3:10–22
Faton CY, Chabossou AF (2024a) Effect of digital financial inclusion on household consumption in ECOWAS countries. SN Soc Sci 4:231. https://doi.org/10.1007/s43545-024-01014-4
Faton CY, Chabossou AF (2024b) Effect of information technologies on employment in ECOWAS countries. SN Bus Econ 4:123. https://doi.org/10.1007/s43546-024-00725-3
Faton CY, Nonvide GMA, Chabossou AF (2025) Digital financial inclusion and the reduction of gender inequalities in Africa. Discov Glob Soc 3:25. https://doi.org/10.1007/s44282-025-00146-z
Guirkinger C, Boucher SR (2008) Credit constraints and productivity in Peruvian agriculture. Agric Econ 39:295–308. https://doi.org/10.1111/j.1574-0862.2008.00334.x
Guo Y, Liu C, Liu H et al (2023) Financial literacy, borrowing behavior and rural households’ income: evidence from the collective forest area, China. Sustainability 15:1153. https://doi.org/10.3390/su15021153
Hampton K, Wellman B (2001) Long distance community in the network society: contact and support beyond netville. Am Behav Sci 45:476–495. https://doi.org/10.1177/00027640121957303
Harraka M (2002) Bowling alone: the collapse and revival of American community, by Robert D. Putnam. J Cathol Educ 6:. https://doi.org/10.15365/joce.0602122013
Haryanto T, Wardana WW, Jamil IR et al (2023) Impact of credit access on farm performance: does source of credit matter?. Heliyon 9:e19720. https://doi.org/10.1016/j.heliyon.2023.e19720
Hyndman K, Serio G (2010) Competition and inter-firm credit: theory and evidence from firm-level data in Indonesia. J Dev Econ 93:88–108. https://doi.org/10.1016/j.jdeveco.2009.04.004
Khadjavi M, Sipangule K, Thiele R (2020) Social capital and large-scale agricultural investments: an experimental investigation. https://doi.org/10.1093/ej/ueaa050
Kim M, Duvendack M (2024) Digital credit for all? An empirical analysis of mobile loans for financial inclusion in Kenya. Inf Technol Dev 0:1–18. https://doi.org/10.1080/02681102.2024.2402996
Kiros S, Meshesha GB (2022) Factors affecting farmers’ access to formal financial credit in Basona Worana District, North Showa Zone, Amhara Regional State, Ethiopia. Cogent Econ Financ 10(1):2035043
Kumar A, Mishra AK, Sonkar VK, Saroj S (2020) Access to credit and economic well-being of rural households: evidence from eastern India. J Agric Resour Econ 45:145–160
Ladman JR, Afcha G (1990) Group lending; why it failed in Bolivia/Groupe emprunteur: Pourquoi N’a pas eu du succes dans la Bolivie. Sav Dev 14:353–369
Li F, Zang D, Chandio AA et al (2023) Farmers’ adoption of digital technology and agricultural entrepreneurial willingness: evidence from China. Technol Soc 73:102253. https://doi.org/10.1016/j.techsoc.2023.102253
Li X, Xiong H, Hao J, Li G (2024) Impacts of internet access and use on grain productivity: evidence from central China. Humanit Soc Sci Commun 11:1–9. https://doi.org/10.1057/s41599-023-02546-5
Liang X, Xiao H, Hou F et al (2024) Breaking the chains of poverty: examining the influence of smartphone usage on multidimensional poverty in rural settings. Humanit Soc Sci Commun 11:1–17. https://doi.org/10.1057/s41599-024-02645-x
Lin L, Wang W, Gan C et al (2019) Rural credit constraint and informal rural credit accessibility in China. Sustainability 11:1935. https://doi.org/10.3390/su11071935
Liu J, Zhang G, Zhang J, Li C (2020) Human capital, social capital, and farmers’ credit availability in china: based on the analysis of the ordered probit and PSM models. Sustainability 12:1583. https://doi.org/10.3390/su12041583
Luan DX, Bauer S (2016) Does credit access affect household income homogeneously across different groups of credit recipients? Evidence from rural Vietnam. J Rural Stud 47:186–203. https://doi.org/10.1016/j.jrurstud.2016.08.001
Ma W, Nie P, Zhang P, Renwick A (2020) Impact of Internet use on economic well-being of rural households: evidence from China. Rev Dev Econ 24:503–523. https://doi.org/10.1111/rode.12645
Ma W, Qiu H, Rahut DB (2023) Rural development in the digital age: does information and communication technology adoption contribute to credit access and income growth in rural China?. Rev Dev Econ 27:1421–1444. https://doi.org/10.1111/rode.12943
Moahid M, Maharjan KL (2020) Factors affecting farmers’ access to formal and informal credit: evidence from rural Afghanistan. Sustainability 12:1268. https://doi.org/10.3390/su12031268
Neves BB, Fonseca JRS (2015) Latent class models in action: bridging social capital & Internet usage. Soc Sci Res 50:15–30. https://doi.org/10.1016/j.ssresearch.2014.11.002
Nie P, Ma W, Sousa-Poza A (2021) The relationship between smartphone use and subjective well-being in rural China. Electron Commer Res 21:983–1009. https://doi.org/10.1007/s10660-020-09397-1
Nonvide GMA, Faton CY, Togodo Azon MSS (2025) Inclusion financière digitale et croissance economique dans L’espace UEMOA: rôle de la qualité des institutions. Afr Dev Rev 37:e70004. https://doi.org/10.1111/1467-8268.70004
Patulny RV, Lind Haase Svendsen G (2007) Exploring the social capital grid: bonding, bridging, qualitative, quantitative. Int J Socio Soc Policy 27:32–51. https://doi.org/10.1108/01443330710722742
Pénard T, Poussing N (2010) Internet use and social capital: the strength of virtual ties. J Econ Issues 44:569–595. https://doi.org/10.2753/JEI0021-3624440301
Peng Y, Ren Y, Li H (2021) Do credit constraints affect households’ economic vulnerability? Empirical evidence from rural China. J Integr Agric 20:2552–2568. https://doi.org/10.1016/S2095-3119(20)63557-2
Phan C, Filomeni S, Kok SK (2024) The impact of technology on access to credit: a review of loan approval and terms in rural Vietnam and Thailand. Res Int Bus Financ 72:102504. https://doi.org/10.1016/j.ribaf.2024.102504
Phua J, Jin SV, Kim J(Jay) (2017) Uses and gratifications of social networking sites for bridging and bonding social capital: a comparison of Facebook, Twitter, Instagram, and Snapchat. Comput Hum Behav 72:115–122. https://doi.org/10.1016/j.chb.2017.02.041
Ping L, Xiaosong S, Jinzhao L (2022) Research on farmers’ households credit behavior and social capital acquisition. Front Psychol 13:961862. https://doi.org/10.3389/fpsyg.2022.961862
Rodgers J, Valuev AV, Hswen Y, Subramanian SV (2019) Social capital and physical health: an updated review of the literature for 2007–2018. Soc Sci Med 236:112360. https://doi.org/10.1016/j.socscimed.2019.112360
Sarfo Y, Musshoff O, Weber R (2023) Farmers’ awareness of digital credit: does financial literacy matter?. J Int Dev 35:2299–2317. https://doi.org/10.1002/jid.3774
Sekyi S, Abu BM, Nkegbe PK (2020) Effects of farm credit access on agricultural commercialization in Ghana: empirical evidence from the northern Savannah ecological zone. Afr Dev Rev 32:150–162. https://doi.org/10.1111/1467-8268.12424
Shoji M, Aoyagi K, Kasahara R et al (2012) Social capital formation and credit access: evidence from Sri Lanka. World Dev 40:2522–2536. https://doi.org/10.1016/j.worlddev.2012.08.003
Slijper T, Urquhart J, Poortvliet PM et al (2022) Exploring how social capital and learning are related to the resilience of Dutch arable farmers. Agric Syst 198:103385. https://doi.org/10.1016/j.agsy.2022.103385
Snyder SM, Li W, O’Brien JE, Howard MO (2015) The effect of U.S. university students’ problematic internet use on family relationships: a mixed-methods investigation. PLoS ONE 10:e0144005. https://doi.org/10.1371/journal.pone.0144005
Stiglitz JE, Weiss A (1981) Credit rationing in markets with imperfect information. Am Econ Rev 71:393–410
Storm BC, Stone SM, Benjamin AS (2017) Using the internet to access information inflates future use of the internet to access other information. Memory 25(6):717–723
Sun H, Hartarska V, Zhang L, Nadolnyak D (2018) The influence of social capital on farm household’s borrowing behavior in rural China. Sustainability 10:4361. https://doi.org/10.3390/su10124361
Tampil Y, Komaliq H, Langi Y (2017) Analisis regresi logistik untuk menentukan faktor-faktor yang mempengaruhi indeks prestasi kumulatif (IPK) mahasiswa FMIPA Universitas Sam Ratulangi Manado. d’Cartes 6:56–62. https://doi.org/10.35799/dc.6.2.2017.17023
Tasheva S, Hillman AJ (2019) Integrating diversity at different levels: multilevel human capital, social capital, and demographic diversity and their implications for team effectiveness. Acad Manag Rev 44:746–765. https://doi.org/10.5465/amr.2015.0396
Tilore FG, Shano BK, Shirko AT, Hawitibo AL (2024) Effect of credit constraint on yield: the case of ginger producers in southern and central Ethiopia. Front Sustain Food Syst 8: 1334799. https://doi.org/10.3389/fsufs.2024.1334799
Tiwari S, Lane M, Alam K (2019) Do social networking sites build and maintain social capital online in rural communities?. J Rural Stud 66:1–10. https://doi.org/10.1016/j.jrurstud.2019.01.029
Ullah A, Verner V, Madaki MY et al (2024) Factors Influencing informal credit access and utilization among smallholder farmers: insights from mountainous regions of Pakistan. Agriculture 14:1764. https://doi.org/10.3390/agriculture14101764
Wang W, Zhong Y (2025) Can agricultural insurance play a protective role? Evidence from China’s agriculture. Humanit Soc Sci Commun 12:951. https://doi.org/10.1057/s41599-025-05340-7
Wellman B, Haase AQ, Witte J, Hampton K (2001) Does the internet increase, decrease, or supplement social capital?: social networks, participation, and community commitment. Am Behav Sci 45:436–455. https://doi.org/10.1177/00027640121957286
Wen C, Yang J, Gan L, Pan Y (2021) Big data driven Internet of Things for credit evaluation and early warning in finance. Future Gener Comput Syst 124:295–307. https://doi.org/10.1016/j.future.2021.06.003
Weng F, Liu X, Huo X (2023) Impact of internet use on farmers’ organic fertilizer investment: a new perspective of access to credit. Agriculture 13:219. https://doi.org/10.3390/agriculture13010219
Williams JR (2019) The use of online social networking sites to nurture and cultivate bonding social capital: a systematic review of the literature from 1997 to 2018. N Media Soc 21:2710–2729. https://doi.org/10.1177/1461444819858749
Williamson OE (1988) Technology and transaction cost economics: a reply. J Econ Behav Organ 10:355–363. https://doi.org/10.1016/0167-2681(88)90055-8
Wyckhuys KAG, Bentley JW, Lie R et al (2018) Maximizing farm-level uptake and diffusion of biological control innovations in today’s digital era. BioControl 63:133–148. https://doi.org/10.1007/s10526-017-9820-1
Xia M (2011) Social capital and rural grassroots governance in China. J Curr Chin Aff 40:135–163. https://doi.org/10.1177/186810261104000206
Xiong F, Zhu S, Xiao H et al (2021) Does social capital benefit the improvement of rural households’ sustainable livelihood ability? Based on the survey data of Jiangxi Province, China. Sustainability 13:10995. https://doi.org/10.3390/su131910995
Xu Y, Peng Z, Sun Z et al (2022) Does digital finance lessen credit rationing?—evidence from Chinese farmers. Res Int Bus Financ 62:101712. https://doi.org/10.1016/j.ribaf.2022.101712
Yang Y, Zeng D, Yang F (2022) Internet use and subjective well-being of the elderly: an analysis of the mediating effect based on social capital. Int J Environ Res Public Health 19:12087. https://doi.org/10.3390/ijerph191912087
Yu G, Xiang H (2021) Rural E-commerce development and farmers’ digital credit behavior: evidence from China family panel studies. PLoS ONE 16:e0258162. https://doi.org/10.1371/journal.pone.0258162
Yu L, Nilsson J, Zhan F, Cheng S (2023) Social capital in cooperative memberships and farmers’ access to bank credit–evidence from Fujian, China. Agriculture 13:418. https://doi.org/10.3390/agriculture13020418
Yuan Y, Xu L (2015) Are poor able to access the informal credit market? Evidence from rural households in China. China Econ Rev 33:232–246. https://doi.org/10.1016/j.chieco.2015.01.003
Zhang W, Wang J (2022) Analysis of rural households’ borrowing behavior and its influencing factors in Western China. Procedia Comput Sci 199:1074–1081. https://doi.org/10.1016/j.procs.2022.01.136
Zheng Y, Zhu T, Jia W (2022) Does Internet use promote the adoption of agricultural technology? Evidence from 1 449 farm households in 14 Chinese provinces. J Integr Agric 21:282–292. https://doi.org/10.1016/S2095-3119(21)63750-4
Zhou Z, Li Z, Chen G et al (2024) Digital literacy level and formal credit constraints: probit analysis of farm households’ borrowing behavior in China. Agriculture 14:832. https://doi.org/10.3390/agriculture14060832
Zou B, Mishra AK (2022) How internet use affects the farmland rental market: an empirical study from rural China. Comput Electron Agric 198:107075. https://doi.org/10.1016/j.compag.2022.107075
Acknowledgements
This research was funded by the Regional Program of the National Natural Science Foundation of China (No. 72263017), the Key Base Project of Humanities and Social Sciences for Universities in Jiangxi Province (JD25035), the Science and Technology Research Project of the Department of Education of Jiangxi Province (GJJ2500309), and the Interdisciplinary Integration Project of Jiangxi Agricultural University (JXAU-02-2025-01).
Author information
Authors and Affiliations
Contributions
Conceptualization, CC and RP; methodology, CC; software, RP; validation, CC and XL; formal analysis, RP; investigation, CC; resources, XL and FY; data curation, XL and FY; writing—original draft preparation, CC; writing—review and editing, XL and FY; visualization, RP; supervision, XL and FY; project administration, CC; funding acquisition, CC. All authors have read and agreed to the published version of the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Ethical approval
This article does not contain any studies with human participants performed by any of the authors.
Informed consent
Not applicable.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Pubisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Chen, C., Peng, R., Li, X. et al. The impact of digital technology use on farmers’ credit behavior: empirical evidence from China. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-07014-4
Received:
Accepted:
Published:
DOI: https://doi.org/10.1057/s41599-026-07014-4

