Research on World Agricultural Economy

The Role of Agricultural Cooperatives in Enhancing Credit Access, Market Information, and Smart Farming Among Rural Farmers

Shaymaa Hussein Nowfal

Department of Medical Physics, College of Science, University of Warith Al‑Anbiyaa, Karbala 56001, Iraq; Department of Medical Physics, College of Applied Medical Sciences, University of Kerbala, Karbala 56001, Iraq

Sireesha Nanduri

Faculty of Management Studies, CMS Business School, JAIN (Deemed‑to‑Be University), Bengaluru 560009, Karnataka, India

Gracy Theresa W

Department of Artificial Intelligence and Data Science, Panimalar Engineering College, Chennai 600029, Tamil Nadu, India

Keerthi Samhitha B

Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram 522502, Andhra Pradesh, India

R. Vinoth

Department of Computer Science and Engineering, RMK College of Engineering and Technology, Chennai 601206, Tamil Nadu, India

Ashokkumar Veerapandi

Department of Information Technology, V.S.B College of Engineering Technical Campus, Coimbatore 642109, Tamil Nadu, India

Ravi Kumar Bommisetti

Maris Stella College

DOI: https://doi.org/10.36956/rwae.v6i1.1536

Received: 28 November 2024; Published: 10 March 2025

Abstract

This study examines the role of agricultural cooperatives in enhancing Credit Access (CA), Market Information (MI), and Smart Farming (SF) among rural farmers in Kerala. Agricultural cooperatives serve as vital organizations that address key challenges smallholder farmers face, including limited CA, MI, and SF. Using a quantitative research design, structured surveys collected data from 421 cooperative and non-member farmers. The study aims to identify the effects of cooperative membership in CA services, MI and SF among rural farmers. Analysis of key findings shows that cooperative members loan from multiple financial sectors, are provided with more frequent MI, and have higher adoption of SF practices, thus featuring the importance of cooperatives in financial development, MI, and environmental organization. The analysis employs t-tests, Chi-square tests, Pearson correlations, and regression models to compare the impact of cooperative membership on CA, MI, and SF. The results reveal that cooperative members are significantly more likely to secure loans, receive more significant loan amounts, and report higher satisfaction with loan terms than non-members. Cooperative members also receive more frequent and reliable MI, which enables them to adjust their sales approaches and access better market opportunities. In addition, cooperative members exhibit higher adoption rates of SF and perceive more significant economic benefits. The study confirms that agricultural organizations are critical in promoting financial inclusion, market participation, and environmental sustainability among rural farmers. These findings underscore the importance of cooperatives as a key tool for rural development and SF growth.

Keywords: Smart Farming; Chi‑Square Tests; Pearson Correlations; Rural Farmers; Machine Learning

References