Digitisation has significantly transformed the global economy. It has also sought to reform the Indian agricultural sector, which continually faces challenges in agricultural marketing. One key approach to addressing these challenges is the adoption of the electronic National Agriculture Market (e-NAM). This study aims to analyse the factors influencing the adoption of e-NAM using a logistic regression model. We collected primary data from 482 respondents across 6 districts in West Bengal using simple random sampling and structured questionnaires. Secondary data were also gathered from relevant research papers and government reports. The findings indicate that factors such as age, distance from the mandi and credit acquisition negatively impact the adoption of e-NAM, whereas farming experience, farmers’ education, land ownership and extension services, among others, have a positive influence. The study recommends enhancing digital literacy and awareness campaigns, as well as establishing more e-NAM facility centres, to encourage wider adoption of e-NAM among farmers.
AbateG. T., KasaL., MinotN., RashidS., LemmaS., & WarnerJ. (2015). Maize value chain in Ethiopia. Structure, conduct, and performance. International Food Policy Research Institute (IFPRI), Markets, Trade, and Institutions Division.
2.
AcharyaS. S., & AgarwalN. L. (2007). Agricultural marketing in India (pp. 385–417). African Journal of Science, Technology, Innovation and Development, 12(1), 85–96. https://doi.org/10.1080/20421338.2019.1609783
3.
AcharyaS. S., & AgarwalN. L. (2011). Agricultural marketing in India. Oxford and IBH Publishing Co.
4.
AlampayE. (2006). Analyzing socio-demographic differences in the access and use of ICTs in the Philippines using the capability approach. Electronic Journal of Information Systems in Developing Countries, 27(1), 1–39.
5.
AlavioonS., & AllahyariM. (2013). Socio-cultural characteristics of rice e-marketing users (case of Rasht Township, Iran). Journal of Central European Agriculture, 14(1), 400–406.
6.
AreguL., PuskurR., & Bishop-SambrookC. (2011). The role of gender in crop value chain in Ethiopia. Paper presented at the Gender and Market Oriented Agriculture (AgriGender 2011) Workshop, Addis Ababa, Ethiopia, 31st January–2nd February 2011, Nairobi, Kenya, ILRI.
7.
BandhavyaM., SinghA. K., & LalS. P. (2022). Procedural impediments in e-NAM system faced by stakeholders in Guntur mandi of Andhra Pradesh. Indian Research Journal of Extension Education, 22(4), 106–111.
8.
BarnesA. P., SotoI., EoryV., BeckB., BalafoutisA., SánchezB., VangeyteS., FountasS., Van der WalT., & Gómez-BarberoM. (2019). Exploring the adoption of precision agricultural technologies: A cross-regional study of EU farmers. Land Use Policy, 80, 163–174.
9.
BarrettC. B. (2008). Smallholder market participation. Concepts and evidence from Eastern and Southern Africa. Food Policy, 33(4), 299–317. https://doi.org/10.1016/j.foodpol.2007.10.005
10.
BerryT. (2010). Channel marketing moves goods from producers to consumers. Agricultural Review Paper, 13, 23–24.
11.
BezabihE. (2015). Factors affecting market outlet choice of potato producers in Tern Hararghe Zone, Ethiopia. Journal of Economics and Sustainable Development, 6(15), 2222–2855.
12.
BucciS., SchwannauerM., & BerryN. (2019). The digital revolution and its impact on mental health care. Psychology and Psychotherapy: Theory, Research and Practice, 92(2), 277–297.
13.
ChaudharyJ., & SinghH. P. (2021). Market arrivals and price behaviour of potato: A study of selected markets of Uttar Pradesh. Indian Journal of Economics and Development, 17(3), 487–494.
14.
ChaudharyS., & SuriP. K. (2022). Modelling the enablers of e-trading adoption in agricultural marketing: A TISM-based analysis of eNAM. Vision, 26(1), 65–79.
15.
Directorate of Economics and Statistics, Department of Agriculture and Farmers’ Welfare, Ministry of Agriculture and Farmers’ Welfare, Government of India. (2021). 5.3(b): Area, production, and yield of potato in major potato-producing states. https://desagri.gov.in/document-report/5-3b-area-production-and-yield-of-potato-in-major-potato-producing-states/
16.
Durga PrasadM. V. (2012). A matching game in tomato pricing at Madanapalle tomato market[Working paper]. Institute of Rural Management, IDRC-TTI.
17.
EweoyaI., OkuboyejoS. R., OdetunmibiO. A., & OdusoteB. O. (2021). An empirical investigation of acceptance, adoption and the use of E-agriculture in Nigeria. Heliyon, 7(7), e07588.
18.
FafchampsM., Gabre-MadhinE., & MintenB. (2005). Increasing returns and market efficiency in agricultural trade. Journal of Development Economics, 78(2), 406–442. https://doi.org/10.1016/j.jdeveco.2004.10.001
19.
GargM., & SinghalS. (2022). Digitalization in agricultural marketing: The future of India. ECS Transactions, 107(1), 9793–9803. https://doi.org/10.1149/10701.9793ecst
20.
GautamS., MishraH., GuptaV., KumarP., & ShakyaA. K. (2023). Ascertain the farmers and traders’ willingness to participate in E-National Agriculture Market (eNAM): Binary logistic regression analysis. International Journal of Environment and Climate Change, 13(8), 1961–1968.
21.
GebreG. G., IsodaH., AmekawaY., RahutD. B., NomuraH., & WatanabeT. (2022). Marketing efficiency among gender-based decision-making farm households in southern Ethiopia. Journal of International Food & Agribusiness Marketing, 34(5), 538–563.
22.
Government of India, Ministry of Home Affairs. (2011). Population census 2011: West Bengal. Census of India. https://westbengal.census.gov.in/pca_2011_wb.php
23.
Government of India. (2024). Home page. Press Information Bureau. https://pib.gov.in/indexd.aspx?reg=3&lang=1
24.
Government of West Bengal. (2023). Home page. West Bengal Agricultural Marketing Board. https://wbagrimarketingboard.gov.in/
HandschuchC., & WollniM. (2016). Traditional food crop marketing in Sub-Saharan Africa: Does gender matter?The Journal of Development Studies, 52(3), 343–359. https://doi.org/10.1080/00220388.2015.1068289
27.
HonaryarG. (2019). An economic analysis of production, marketing and value chain of potato in Bamyan Province. International Journal of Research—Granthaalayah, 7(10), 1–25.
28.
KambleS. S., GunasekaranA., & GawankarS. A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. International Journal of Production Economics, 219, 179–194.
29.
KaranjaA. M., ShisanyaC., & MakokhaG. (2014). Analysis of the key challenges facing potato farmers in Oljoro-Orok division, Kenya. Agricultural Sciences, 5(10), Article 48689, 1–5.
30.
KausarA. K. M. G., & AlamJ. M. (2016). Marketing efficiency of maize in Bangladesh. Asian Journal of Agricultural Extension, Economics & Sociology, 11(2), 1–12. https://doi.org/10.9734/AJAEES/2016/26170
31.
KiizaB., & PedersonG. (2012). ICT-based market information and adoption of agricultural seed technologies: Insights from Uganda. Telecommunications Policy, 36(4), 253–259.
32.
KumarS. (2014). Marketing efficiency analysis: A case of broiler marketing in Anand district of Gujarat. International Journal of Commerce and Business Management, 7(1), 186–190.
33.
KumarR., JhajhariaA. K., KumarR., KumarS., & Shubham. (2023). Attitude of registered farmers and traders toward e-NAM. Indian Research Journal of Extension Education, 23(1), 1–6.
34.
LalzaiF., JamaliA., MutalebA., & ShakirM. (2023). Potatoes storage, price spread through various channels and marketing efficiency in Parwan Province, Afghanistan. Journal for Research in Applied Sciences and Biotechnology, 2(4), 19–24.
35.
MangoN., MapembaL., TchaleH., MakateC., DunjanaN., & LundyM. (2018). Maize value chain analysis: A case of smallholder maize production and marketing in selected areas of Malawi and Mozambique. Cogent Business & Management, 5(1), 1503220. https://doi.org/10.1080/23311975.2018.1503220
36.
ManognaR. L. (2025). Determinants of small farmers access to agricultural markets: Evidence from South India. Discover Sustainability, 6(1), 962.
37.
MansoM. C., CerqueiraR. M., FernandesC., & CorreiaM. (2010). Logistic multivariate regression analysis as a tool to predict fibrosis in light-drinking chronic hepatitis C patients. Biometrical Letters, 47(1), 33–44.
38.
MdodaL., ObiA., TamakoN., NaidooD., & BaloyiR. (2023). Resource use efficiency of potato production among smallholder irrigated farmers in the Eastern Cape Province of South Africa. Sustainability, 15(19), 14457.
39.
MekonnenT. (2017). Impact of agricultural technology adoption on market participation in the rural social network system. Maastricht Economic and Social Research Institute on Innovation and Technology, 43.
40.
MgaleY. J., & YunxianY. (2020). Marketing efficiency and determinants of marketing channel choice by rice farmers in rural Tanzania: Evidence from Mbeya region, Tanzania. Australian Journal of Agricultural and Resource Economics, 64(4), 1239–1259.
41.
Ministry of Agriculture and Farmers’ Welfare, Government of India. (2024). eNAM stakeholder data. eNAM. https://enam.gov.in/web/dashboard/stakeholder-data
42.
MittalS., & MeharM. (2016). Socio-economic factors affecting adoption of modern information and communication technology by farmers in India: Analysis using multivariate probit model. Journal of Agricultural Education and Extension, 22(2), 199–212.
43.
MkundaJ. J., LassenJ., ChachageB., KusilukaL. J. M., & PasapeL. (2019). Analysis of marketing efficiency of processed sardine products of Lake Victoria: Case of Tanzania. African Journal of Science, Technology, Innovation and Development, 12(1), 85–96. https://doi.org/10.1080/20421338.2019.1609783
44.
ModekurtiD. P. V. (2016). Automation of modified marketing procedural system to maximize transparency: A case study of vegetables in Madanapalle market. Journal of Agribusiness in Developing and Emerging Economies, 6(1), 72–88.
45.
MosheI., TerhorstY., Opoku AsareK., SanderL. B., FerreiraD., BaumeisterH., MohrD. C., & Pulkki-RåbackL. (2021). Predicting symptoms of depression and anxiety using smartphone and wearable data. Frontiers in Psychiatry, 12, 625247.
46.
MuradiA. J., & RahmaniZ. (2020). Marketing channel efficiency of almond products: Evidence from Samangan and Balkh-Afghanistan. Asian Journal of Agricultural Extension, Economics & Sociology, 38(1), 169–179.
47.
MusaraJ. P., MusemwaL., MutenjeM., MushunjeA., & PfukwaC. (2018). Market participation and marketing channel preferences by small scale sorghum farmers in semiarid Zimbabwe. Agrekon, 57(1), 64–77. https://doi.org/10.1080/03031853.2018.1454334
48.
MushiG. E., BurgiP. Y., & Di Marzo SerugendoG. (2024). State of agricultural E-government services to farmers in Tanzania: Toward the participatory design of a farmers digital information system (FDIS). Agriculture, 14(3), 475.
49.
MuthiniD. N. (2015). An assessment of mango farmers’ choice of marketing channels in Makueni, Kenya[Master’s thesis, University of Nairobi].
50.
NyagangoA. I., SifeA. S., & KazunguI. (2023). Factors influencing the use of mobile phone for accessing agricultural marketing information by grape smallholder farmers in Tanzania. Cogent Business & Management, 10(3).
51.
OkelloJ. J., KatengezaS. P., & MensahE. R. (2011). Factors influencing awareness and use of electronic-based market information services for farming business in Malawi. International Journal of Economic Research, 2(4), 43–58.
52.
OmarM. I., & HoqM. S. (2014). Analysis of growth rate, marketing efficiency and seasonal price variation of potato in selected areas of Bangladesh. Journal of Natural Sciences Research, 4(5), 43–54.
53.
OmitiJ. M., OtienoD. J., NyanambaT. O., & McCulloughE. B. (2009). Factors influencing the intensity of market participation by smallholder farmers: A case study of rural and peri-urban areas of Kenya. African Journal of Agricultural and Resource Economics, 3(1), 57–82.
54.
PandaR. K., & SreekumarR. (2012). Marketing channel choice and marketing efficiency assessment in agribusiness. Journal of International Food & Agribusiness Marketing, 24(3), 213–230. https://doi.org/10.1080/08974438.2012.691812
55.
PatilC., KumariA., MahtoR. K., & GoraiP. K. (2024). Factors influencing farmers decision to participate in e-auction: A case of Electronic National Agriculture Market (e-NAM) in Punjab, India. Journal of Farm Sciences, 37(3), 264–272.
56.
PhularaB., AcharyaB., AdhikariS., OjhaB., & SigdelU. P. (2021). Production economics and marketing of potatoes in Okhaldhunga, Nepal. Innovare Journal of Agricultural Sciences, 9(5), 5–10.
57.
PoushterJ. (2016). Smartphone ownership and internet usage continues to climb in emerging economies. Pew Research Center.
58.
PraneethM., MeeraS. N., & AwasthiH. K. (2024). Factors influencing the perception of farmers about the use of e-NAM and digital marketing applications. Indian Research Journal of Extension Education, 24(3), 45–56.
59.
RahmanM. S., TakedaJ., & MohiuddinM. (2006). Rise farmers’ marketing efficiency in southwestern part of Bangladesh. Journal of Applied Sciences, 6(9), 2043–2050. https://doi.org/10.3923/jas.2006.2043.2050
60.
RajuM. S., DevyM. R., & GopalP. S. (2022). Knowledge of farmers on functioning of e-NAM. Indian Journal of Extension Education, 58(2), 26–29.
61.
RanjanA., & ZechariahJ. (2018). An economic analysis of postharvest losses and marketing of potato in Nawada district, Bihar. The Pharma Innovation Journal, 7(12), 391–394.
62.
ReddyA. A. (2018). Electronic national agricultural markets: The way forward. Current Science, 115(5), 826–837. https://ssrn.com/abstract=3242075
63.
SamantarayS. K., KumarD., FarhanM., & KumarS. (2023). Assessment of e-training in developing resilience to adopt e-NAM technology: A case study of farmers’ development in Odisha, India. Resmilitaris, 13(3), 137–157.
64.
SánchezM., BeriainM. J., & CarrT. R. (2012). Socio-economic factors affecting consumer behaviour for United States and Spanish beef under different information scenarios. Food Quality and Preference, 24(1), 30–39.
65.
SapkotaS. C., RajP. R., AcharyaH., & UpretyS. (2019). An economic analysis of potato production in Achham District of Nepal. International Journal of Horticulture & Agriculture, 4(2), 1–9.
66.
ShepherdA. W. (1993). A guide to marketing costs and how to calculate them. Food and Agriculture Organization of the United Nations.
67.
ShiferawB., ObareG., & MurichoG. (2008). Rural market imperfections and the role of institutions in collective action to improve markets for the poor. Natural Resources Forum, 32(1), 25–38. https://doi.org/10.1111/j.1477-8947.2008.00167.x
68.
TankodaraK. D., & GohilG. R. (2020). Level of adoption of chickpea growers about chickpea production technology. Indian Research Journal of Extension Education, 20(4), 85–88.
69.
TyngkanH., PathakH., GuptaA. K., & LyngkhoiD. R. (2021). Post-integration effect of e-NAM in Nawapara APMC, Chhattisgarh. Economic Affairs, 66(3), 509–513. https://doi.org/10.46852/0424-2513.3.2021.22
70.
World Bank. (2018). Cereal market performance in Ethiopia: Policy implications for improving investments in maize and wheat value chains. World Food Program and Central Statistical Agency (CSA) of Ethiopia. (2019). Comprehensive food security and vulnerability analysis (CFSVA) of Ethiopia 2019.
71.
XabaB. G., & MicahB. M. (2012). Factors affecting the choice of marketing channel by vegetable farmers in Swaziland. Sustainable Agriculture Research, 2(1), 1441.
72.
YadavJ., MisraM., & GoundarS. (2020). Autonomous agriculture marketing information system through blockchain: A case study of e-NAM adoption in India. In Blockchain technologies, applications and cryptocurrencies: Current practice and future trends (pp. 115–138). World Scientific Publishing Co. Pte. Ltd. https://doi.org/10.1142/9789811205279_0005
73.
YamaneT. (1967). Statistics: An introductory analysis (2nd ed.). Harper and Row.
