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Queue Modeling and Cooperative Credit Access in Benin City: A Study of Rural Husbandmen Cooperative Credit and Relief Programme
Subject area: Management and Commerce · Area of research: Cooperative Credit Access Modeling
DOI: https://doi.org/10.64388/IREV9I12-1718968
Abstract
Credit access remains a critical constraint for smallholder farmers in Nigeria despite policy interventions. This study applied queueing theory to analyze the efficiency of loan processing at the Rural Husbandmen Cooperative Credit and Relief Programme (RH-CRRP) in Benin City, Edo State, between 2011 and 2015. Using cooperative records and survey data from 60 respondents, the study found an 88.2% loan approval rate with a traffic intensity of 1.132, indicating system overload. Key constraints included inadequate finance (M=2.66), loan repayment issues (M=2.64), and embezzlement (M=2.52). Findings suggest that cooperative credit systems require improved financial management, digital processing, and financial literacy training to reduce queuing delays and enhance farmer productivity.
Keywords
Queueing Theory, Cooperative Credit, Agricultural Finance, RH-CRRP, Benin City, Nigeria
How to cite this paper
@article{1718968,
author = {Iyekekpolor M. N., Ogbochie V. E., Iyasele R. O.},
title = {Queue Modeling and Cooperative Credit Access in Benin City: A Study of Rural Husbandmen Cooperative Credit and Relief Programme},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {12},
pages = {3685-3688},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1718968.pdf},
abstract = {Credit access remains a critical constraint for smallholder farmers in Nigeria despite policy interventions. This study applied queueing theory to analyze the efficiency of loan processing at the Rural Husbandmen Cooperative Credit and Relief Programme (RH-CRRP) in Benin City, Edo State, between 2011 and 2015. Using cooperative records and survey data from 60 respondents, the study found an 88.2% loan approval rate with a traffic intensity of 1.132, indicating system overload. Key constraints included inadequate finance (M=2.66), loan repayment issues (M=2.64), and embezzlement (M=2.52). Findings suggest that cooperative credit systems require improved financial management, digital processing, and financial literacy training to reduce queuing delays and enhance farmer productivity.},
keywords = {Queueing Theory, Cooperative Credit, Agricultural Finance, RH-CRRP, Benin City, Nigeria},
month = {June},
doi = {https://doi.org/10.64388/IREV9I12-1718968}
}